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Alewel DI, Kodavanti UP. Neuroendocrine contribution to sex-related variations in adverse air pollution health effects. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2024:1-28. [PMID: 39075643 DOI: 10.1080/10937404.2024.2383637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/31/2024]
Abstract
Air pollution exposure is ranked as a leading environmental risk factor for not only cardiopulmonary diseases but also for systemic health ailments including diabetes, reproductive abnormalities, and neuropsychiatric disorders, likely mediated by central neural stress mechanisms. Current experimental evidence links many air pollution health outcomes with activation of neuroendocrine sympathetic-adrenal-medullary and hypothalamic-pituitary-adrenal (HPA) stress axes associated with resultant increases in adrenal-derived hormone levels acting as circulating mediators of multi-organ stress reactions. Epidemiological and experimental investigations also demonstrated sex-specific responses to air pollutant inhalation, which may be attributed to hormonal interactions within the stress and reproductive axes. Sex hormones (androgens and estrogens) interact with neuroendocrine functions to influence hypothalamic responses, subsequently augmenting stress-mediated metabolic and immune changes. These neurohormonal interactions may contribute to innate sex-specific responses to inhaled irritants, inducing differing individual susceptibility. The aim of this review was to: (1) examine neuroendocrine co-regulation of the HPA axis by gonadal hormones, (2) provide experimental evidence demonstrating sex-specific respiratory and systemic effects attributed to air pollutant inhalation exposure, and (3) postulate proposed mechanisms of stress and sex hormone interactions during air pollution-related stress.
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Affiliation(s)
- Devin I Alewel
- Oak Ridge Institute for Science and Education Research Participation Program, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Urmila P Kodavanti
- Public Health and Integrated Toxicology Division, Center for Public Health and Environmental Assessment, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
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Xu J, Chen Y, Lu F, Chen L, Dong Z. The Association between Short-Term Exposure to PM 1 and Daily Hospital Admission and Related Expenditures in Beijing. TOXICS 2024; 12:393. [PMID: 38922073 PMCID: PMC11209456 DOI: 10.3390/toxics12060393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 05/16/2024] [Accepted: 05/18/2024] [Indexed: 06/27/2024]
Abstract
Ambient particulate matter (PM) pollution is a leading environmental health threat worldwide. PM with an aerodynamic diameter ≤ 1.0 μm, also known as PM1, has been implicated in the morbidity and mortality of several cardiorespiratory and cerebrovascular diseases. However, previous studies have mostly focused on analyzing fine PM (PM2.5) associated with disease metrics, such as emergency department visits and mortality, rather than ultrafine PM, including PM1. This study aimed to evaluate the association between short-term PM1 exposure and hospital admissions (HAs) for all-cause diseases, chronic obstructive pulmonary disease (COPD), and respiratory infections (RIs), as well as the associated expenditures, using Beijing as a case study. Here, based on air pollution and hospital admission data in Beijing from 2015 to 2017, we performed a time-series analysis and meta-analysis. It was found that a 10 μg/m3 increase in the PM1 concentration significantly increased all-cause disease HAs by 0.07% (95% Confidence Interval (CI): [0, 0.14%]) in Beijing between 2015 and 2017, while the COPD and RI-related HAs were not significantly associated with short-term PM1 exposure. Meanwhile, we estimated the attributable number of HAs and hospital expenditures related to all-cause diseases. This study revealed that an average of 6644 (95% CI: [351, 12,917]) cases of HAs were attributable to ambient PM1, which was estimated to be associated with a 106 million CNY increase in hospital expenditure annually (95% CI: [5.6, 207]), accounting for 0.32% (95% CI: [0.02, 0.62%]) of the annual total expenses. The findings reported here highlight the underlying impact of ambient PM pollution on health risks and economic burden to society and indicate the need for further policy actions on public health.
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Affiliation(s)
- Jingwen Xu
- School of Cancer and Pharmaceutical Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 1UL, UK
| | - Yan Chen
- Ganzhou People’s Hospital, Ganzhou 341000, China
| | - Feng Lu
- Beijing Municipal Health Big Data and Policy Research Center, Beijing 100034, China
| | - Lili Chen
- School of Public Health, Southeast University, Nanjing 210009, China
| | - Zhaomin Dong
- School of Materials Science and Engineering, Beihang University, Beijing 100191, China
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Zhang Y, Hu M, Xiang B, Yu H, Wang Q. Urban-rural disparities in the association of nitrogen dioxide exposure with cardiovascular disease risk in China: effect size and economic burden. Int J Equity Health 2024; 23:22. [PMID: 38321458 PMCID: PMC10845777 DOI: 10.1186/s12939-024-02117-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 01/23/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Together with rapid urbanization, ambient nitrogen dioxide (NO2) exposure has become a growing health threat. However, little is known about the urban-rural disparities in the health implications of short-term NO2 exposure. This study aimed to compare the association between short-term NO2 exposure and hospitalization for cardiovascular disease (CVD) among urban and rural residents in Shandong Province, China. Then, this study further explored the urban-rural disparities in the economic burden attributed to NO2 and the explanation for the disparities. METHODS Daily hospitalization data were obtained from an electronic medical records dataset covering a population of 5 million. In total, 303,217 hospital admissions for CVD were analyzed. A three-stage time-series analytic approach was used to estimate the county-level association and the attributed economic burden. RESULTS For every 10-μg/m3 increase in NO2 concentrations, this study observed a significant percentage increase in hospital admissions on the day of exposure of 1.42% (95% CI 0.92 to 1.92%) for CVD. The effect size was slightly higher in urban areas, while the urban-rural difference was not significant. However, a more pronounced displacement phenomenon was found in rural areas, and the economic burden attributed to NO2 was significantly higher in urban areas. At an annual average NO2 concentration of 10 μg/m3, total hospital days and expenses in urban areas were reduced by 81,801 (44,831 to 118,191) days and 60,121 (33,002 to 86,729) thousand CNY, respectively, almost twice as much as in rural areas. Due to disadvantages in socioeconomic status and medical resources, despite similar air pollution levels in the urban and rural areas of our sample sites, the rural population tended to spend less on hospitalization services. CONCLUSIONS Short-term exposure to ambient NO2 could lead to considerable health impacts in either urban or rural areas of Shandong Province, China. Moreover, urban-rural differences in socioeconomic status and medical resources contributed to the urban-rural disparities in the economic burden attributed to NO2 exposure. The health implications of NO2 exposure are a social problem in addition to an environmental problem. Thus, this study suggests a coordinated intervention system that targets environmental and social inequality factors simultaneously.
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Affiliation(s)
- Yike Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Mengxiao Hu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Bowen Xiang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Haiyang Yu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Qing Wang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
- National Institute of Health Data Science of China, Shandong University, Jinan, China.
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Yu LJ, Li XL, Wang YH, Zhang HY, Ruan SM, Jiang BG, Xu Q, Sun YS, Wang LP, Liu W, Yang Y, Fang LQ. Short-Term Exposure to Ambient Air Pollution and Influenza: A Multicity Study in China. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:127010. [PMID: 38078423 PMCID: PMC10711743 DOI: 10.1289/ehp12146] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/02/2023] [Accepted: 10/27/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND Air pollution is a major risk factor for planetary health and has long been suspected of predisposing humans to respiratory diseases induced by pathogens like influenza viruses. However, epidemiological evidence remains elusive due to lack of longitudinal data from large cohorts. OBJECTIVE Our aim is to quantify the short-term association of influenza incidence with exposure to ambient air pollutants in Chinese cities. METHODS Based on air pollutant data and influenza surveillance data from 82 cities in China over a period of 5 years, we applied a two-stage time series analysis to assess the association of daily incidence of reported influenza cases with six common air pollutants [particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ), particulate matter with aerodynamic diameter ≤ 10 μ m (PM 10 ), NO 2 , SO 2 , CO, and O 3 ], while adjusting for potential confounders including temperature, relative humidity, seasonality, and holiday effects. We built a distributed lag Poisson model for one or multiple pollutants in each individual city in the first stage and conducted a meta-analysis to pool city-specific estimates in the second stage. RESULTS A total of 3,735,934 influenza cases were reported in 82 cities from 2015 to 2019, accounting for 72.71% of the overall case number reported in the mainland of China. The time series models for each pollutant alone showed that the daily incidence of reported influenza cases was positively associated with almost all air pollutants except for ozone. The most prominent short-term associations were found for SO 2 and NO 2 with cumulative risk ratios of 1.094 [95% confidence interval (CI): 1.054, 1.136] and 1.093 (95% CI: 1.067, 1.119), respectively, for each 10 μ g / m 3 increase in the concentration at each of the lags of 1-7 d. Only NO 2 showed a significant association with the daily incidence of influenza cases in the multipollutant model that adjusts all six air pollutants together. The impact of air pollutants on influenza was generally found to be greater in children, in subtropical cities, and during cold months. DISCUSSION Increased exposure to ambient air pollutants, particularly NO 2 , is associated with a higher risk of influenza-associated illness. Policies on reducing air pollution levels may help alleviate the disease burden due to influenza infection. https://doi.org/10.1289/EHP12146.
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Affiliation(s)
- Lin-Jie Yu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Xin-Lou Li
- Department of Medical Research, Key Laboratory of Environmental Sense Organ Stress and Health of the Ministry of Environmental Protection, PLA Strategic Support Force Medical Center, Beijing, P. R. China
| | - Yan-He Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Hai-Yang Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Shi-Man Ruan
- Jinan Center for Disease Control and Prevention, Jinan, P. R. China
| | - Bao-Gui Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Qiang Xu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Yan-Song Sun
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Li-Ping Wang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, P. R. China
| | - Wei Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Yang Yang
- Department of Statistics, Franklin College of Arts and Science, University of Georgia, Athens, Georgia, USA
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
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Dong TF, Zha ZQ, Sun L, Liu LL, Li XY, Wang Y, Meng XL, Li HB, Wang HL, Nie HH, Yang LS. Ambient nitrogen dioxide and cardiovascular diseases in rural regions: a time-series analyses using data from the new rural cooperative medical scheme in Fuyang, East China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:51412-51421. [PMID: 36809617 DOI: 10.1007/s11356-023-25922-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 02/09/2023] [Indexed: 06/18/2023]
Abstract
Most of studies relating ambient nitrogen dioxide (NO2) exposure to hospital admissions for cardiovascular diseases (CVDs) were conducted among urban population. Whether and to what extent these results could be generalizable to rural population remains unknown. We addressed this question using data from the New Rural Cooperative Medical Scheme (NRCMS) in Fuyang, Anhui, China. Daily hospital admissions for total CVDs, ischaemic heart disease, heart failure, heart rhythm disturbances, ischaemic stroke, and haemorrhagic stroke in rural regions of Fuyang, China, were extracted from NRCMS between January 2015 and June 2017. A two-stage time-series analysis method was used to assess the associations between NO2 and CVD hospital admissions and the disease burden fractions attributable to NO2. In our study period, the average number (standard deviation) of hospital admissions per day were 488.2 (117.1) for total CVDs, 179.8 (45.6) for ischaemic heart disease, 7.0 (3.3) for heart rhythm disturbances, 13.2 (7.2) for heart failure, 267.9 (67.7) for ischaemic stroke, and 20.2 (6.4) for haemorrhagic stroke. The 10-μg/m3 increase of NO2 was related to an elevated risk of 1.9% (RR: 1.019, 95% CI: 1.005 to 1.032) for hospital admissions of total CVDs at lag0-2 days, 2.1% (1.021, 1.006 to 1.036) for ischaemic heart disease, and 2.1% (1.021, 1.006 to 1.035) for ischaemic stroke, respectively, while no significant association was observed between NO2 and hospital admissions for heart rhythm disturbances, heart failure, and haemorrhagic stroke. The attributable fractions of total CVDs, ischaemic heart disease, and ischaemic stroke to NO2 were 6.52% (1.87 to 10.94%), 7.31% (2.19 to 12.17%), and 7.12% (2.14 to 11.85%), respectively. Our findings suggest that CVD burdens in rural population are also partly attributed to short-term exposure to NO2. More studies across rural regions are required to replicate our findings.
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Affiliation(s)
- Teng-Fei Dong
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Zhen-Qiu Zha
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
- Anhui Provincial Center for Disease Control and Prevention, Hefei, 230601, Anhui, China
| | - Liang Sun
- Fuyang Center for Disease Control and Prevention, Fuyang, 236069, Anhui, China
| | - Ling-Li Liu
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Xing-Yang Li
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Yuan Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Xiang-Long Meng
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Huai-Biao Li
- Fuyang Center for Disease Control and Prevention, Fuyang, 236069, Anhui, China
| | - Hong-Li Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Huan-Huan Nie
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Lin-Sheng Yang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China.
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Chen Y, Tan J, Liu Y, Dong GH, Yang BY, Li N, Wang L, Chen G, Li S, Guo Y. Long-term exposure to outdoor light at night and mild cognitive impairment: A nationwide study in Chinese veterans. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 847:157441. [PMID: 35863567 DOI: 10.1016/j.scitotenv.2022.157441] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 07/01/2022] [Accepted: 07/13/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Evidence is limited for the association between outdoor light at night (LAN) and mild cognitive impairment (MCI), a transitional stage between normal aging and dementia and Alzheimer's disease in the elderly. In this study, the association between outdoor LAN and MCI was examined based on a multi-city study among veterans in China. METHODS A total of 5496 participants from 18 cities across China were investigated during 2009-2011, selected using a multi-stage random sampling method. Participants' cognitive function was firstly assessed using the Mini Mental State Examination and the Montreal Cognitive Assessment in the Chinese version, and then was further confirmed by clinical examination. Participants' exposure to outdoor LAN was estimated using the Global Radiance Calibrated Nighttime Lights Product at a spatial resolution of around 1 km. The mixed-effects logistic regression model was used to examine the association between outdoor LAN and MCI. RESULTS After controlling for covariates, odds ratio (OR) and 95 % confidence intervals (95%CI) of MCI was 1.44 (95%CI: 1.36, 1.52) associated with per interquartile range (IQR = 21.17 nW/cm2/sr) increase in exposure to outdoor LAN during the 3 years before the investigation, and for categorical variable of LAN, the highest OR was observed for the highest against the lowest quartile of LAN with a monotonically increasing trend (p values for trend <0.001). Furthermore, higher ORs were observed for females, veterans who had less educational attainment, and had no regular social activities. CONCLUSIONS Our study revealed that exposure to excessive outdoor LAN was associated with higher risk of MCI. Effective measures should be taken to reduce LAN exposure, which may help to prevent MCI.
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Affiliation(s)
- Yan Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Jiping Tan
- Geriatric Neurology Department of the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yuewei Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Guang-Hui Dong
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Bo-Yi Yang
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Nan Li
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, China
| | - Luning Wang
- Geriatric Neurology Department of the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China.
| | - Gongbo Chen
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
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Xu H, Wang X, Tian Y, Tian J, Zeng Y, Guo Y, Song F, Xu X, Ni X, Feng G. Short-term exposure to gaseous air pollutants and daily hospitalizations for acute upper and lower respiratory infections among children from 25 cities in China. ENVIRONMENTAL RESEARCH 2022; 212:113493. [PMID: 35618009 DOI: 10.1016/j.envres.2022.113493] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/29/2022] [Accepted: 05/14/2022] [Indexed: 06/15/2023]
Abstract
To examine the short-term association between gaseous air pollutants (CO, NO2, SO2, and O3) and all-cause respiratory disease, acute upper respiratory infections (AURIs) as well as acute lower respiratory infections (ALRIs) among children, we conducted the study from 25 major cities in China. Hospitalization records of children aged 0-18 years due to all-cause respiratory diseases (889,926), AURIs (97,858), and ALRIs (642,154) from 2016 to 2019 were extracted. Concentrations of CO, NO2, SO2, and O3 were averaged across monitoring stations. Generalized additive models were used to estimate the associations between gaseous air pollutants and daily hospitalizations for all-cause respiratory disease, AURIs, and ALRIs. The meta-analysis was used to combine the city-specific estimates. A 10 mg/m3 increase in CO at lag01, and a 10 μg/m3 increase in NO2, SO2, and O3 at lag01 were associated with 1.65% (95%CI, 0.41-2.91), 0.54% (95%CI, 0.30-0.79), 0.60% (95%CI, 0.22-0.99), and 0.23% (95%CI, 0.06-0.39) increase of hospitalizations due to all-cause respiratory disease, respectively. For the disease subtype, O3 only had adverse effects on AURIs, CO and SO2 mainly on ALRIs, and NO2 on both AURIs and ALRIs. Children aged 4-6years were more vulnerable to the effects of CO and NO2, but those aged <1year were more susceptible to SO2 and O3. Besides, the O3 effect was stronger in the warm season than in the cold season. The study indicated that short-term exposure to CO, NO2, SO2, and O3 was associated with increased hospitalization for pediatric respiratory disease, and the association may vary by position of the respiratory tract, age, and season.
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Affiliation(s)
- Hui Xu
- Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Xinyu Wang
- Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yaohua Tian
- Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jian Tian
- Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yueping Zeng
- Medical Record Management Office, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yongli Guo
- Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Fei Song
- Medical Record Management Office, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Xin Xu
- Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Xin Ni
- Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, China; Department of Otolaryngology Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
| | - Guoshuang Feng
- Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, China.
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He M, Zhong Y, Chen Y, Zhong N, Lai K. Association of short-term exposure to air pollution with emergency visits for respiratory diseases in children. iScience 2022; 25:104879. [PMID: 36065191 PMCID: PMC9440288 DOI: 10.1016/j.isci.2022.104879] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 06/07/2022] [Accepted: 08/02/2022] [Indexed: 11/16/2022] Open
Abstract
Ambient air pollutants are health hazards to children. This study comprised 773,504 emergency department visits (EDVs) at 0–14 years of age with respiratory diseases in southern China. All air pollutants were positively associated with EDVs of total respiratory diseases, especially pneumonia. NO2, PM10, and PM2.5 had intraday effects and cumulative effects on asthma EDVs. The effect of SO2, PM10, and PM2.5 on pneumonia EDVs was stronger in girls than in boys. The effect of NO2 on acute upper respiratory tract infection EDVs was greater in children aged 0–5 years old; however, the effect of PM10 on acute upper respiratory tract infection EDVs was greater in the 6–14 years group. In a two-pollutant model, NO2 was associated with bronchitis and pneumonia, and PM10 was associated with acute upper respiratory tract infection. In this time-series study, NO2 and PM10 were risk indicators for respiratory diseases in children. Air pollution associates with children emergency visits for respiratory diseases NO2 and PM10 are risk indicators for respiratory diseases in children Young children are more sensitive to gaseous pollutants School-age children are more sensitive to PM10
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Ugalde-Resano R, Riojas-Rodríguez H, Texcalac-Sangrador JL, Cruz JC, Hurtado-Díaz M. Short term exposure to ambient air pollutants and cardiovascular emergency department visits in Mexico city. ENVIRONMENTAL RESEARCH 2022; 207:112600. [PMID: 34990608 DOI: 10.1016/j.envres.2021.112600] [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: 10/16/2021] [Revised: 12/09/2021] [Accepted: 12/17/2021] [Indexed: 06/14/2023]
Abstract
Available data on the acute cardiovascular effect of ambient air pollution (AAP) in Latin America is limited considering that over 80% of its 1 billion inhabitants live in urban settlements with poor air quality. The study aim was to evaluate the association between Cardiovascular Emergency Department Visits (CEDVs) and AAP in Mexico City from 2016 to 2019 using generalized additive models with distributed lags to examine the percentage change of CEDVs and a backward approach of time-series model to calculate attributable fractions. A total of 48,891 CEDVs were recorded in a period of 1019 days. We estimated a significant percentage increase for each 10 μg/m3 of PM10 at Lag0-5 (2.8%, 95%CI 0.6-5.0), PM2.5 at Lag0-6 (3.7%, 95%CI 0.1-7.6), O3 at Lag0-5 (1.1%, 95%CI 0.2-2.0), NO2 at Lag0-4 (2.5%, 95%CI 0.3-4.7) and for each 1 mg/m3 of CO at Lag0 (6.6%, 95%CI 0.3-13.2). Overall, 10.3% of CEDVs in Mexico City may be related to PM10 exposure, 9.5% to PM2.5, 10.3% to O3, 11% to NO2 and 5.7% to CO. AAP significantly increase cardiovascular morbidity impacting on emergency medical services.
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Affiliation(s)
- Rodrigo Ugalde-Resano
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, 655 Avenida Universidad, Santa María Ahuacatitlan, Cuernavaca, Morelos, 62100, Mexico
| | - Horacio Riojas-Rodríguez
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, 655 Avenida Universidad, Santa María Ahuacatitlan, Cuernavaca, Morelos, 62100, Mexico
| | - José Luis Texcalac-Sangrador
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, 655 Avenida Universidad, Santa María Ahuacatitlan, Cuernavaca, Morelos, 62100, Mexico
| | - Julio C Cruz
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, 655 Avenida Universidad, Santa María Ahuacatitlan, Cuernavaca, Morelos, 62100, Mexico
| | - Magali Hurtado-Díaz
- Department of Environmental Health, Center for Population Health Research, National Institute of Public Health, 655 Avenida Universidad, Santa María Ahuacatitlan, Cuernavaca, Morelos, 62100, Mexico.
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Association between Ambient Air Pollutants and Pneumonia in Wuhan, China, 2014–2017. ATMOSPHERE 2022. [DOI: 10.3390/atmos13040578] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Objectives: To assess associations between short-time air pollution exposure and outpatient visits for pneumonia by the distributed lag nonlinear model (DLNM). Methods: Daily outpatient visits for pneumonia and air pollutant data were collected from Wuhan Basic Medical Insurance Database in China and 10 national air quality monitoring stations in Wuhan from 2014 to 2017, respectively. Taking the first percentile of the concentration as the reference, DLNM was used to estimate the impact of moderate (50th) and high levels (99th) of pollutants on pneumonia. Results: A total of 133,882 outpatient visits were identified during the period of the study. Moderate-level (P50) fine particulate matter (PM2.5) or sulfur dioxide (SO2) and high-level nitrogen dioxide (NO2) (P99) can increase the risk of pneumonia. The maximum RR was 1.198 (95% CI: 1.094–1.311) at lag0-11, 1.304 (95% CI: 1.166–1.458) at lag0-13, and 1.286 (95% CI: 1.060–1.561) at lag0-14, respectively. Females and children had greater risks. Conclusions: Short-time PM2.5, SO2, and NO2 exposure were associated with outpatient visits for pneumonia in Wuhan, China.
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Qiu H, Wang L, Luo L, Shen M. Gaseous air pollutants and hospitalizations for mental disorders in 17 Chinese cities: Association, morbidity burden and economic costs. ENVIRONMENTAL RESEARCH 2022; 204:111928. [PMID: 34437848 DOI: 10.1016/j.envres.2021.111928] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 08/06/2021] [Accepted: 08/19/2021] [Indexed: 06/13/2023]
Abstract
The short-term morbidity effects of gaseous air pollutants on mental disorders (MDs), and the corresponding morbidity and economic burdens have not been well studied. We aimed to explore the associations of ambient sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3) and carbon monoxide (CO) with MDs hospitalizations in 17 Chinese cities during 2015-2018, and estimate the attributable risk and economic costs of MDs hospitalizations associated with gaseous pollutants. City-specific relationships between gaseous pollutants and MDs hospitalizations were evaluated using over-dispersed generalized additive models, then combined to obtain the pooled effect. Concentration-response (C-R) curves of gaseous pollutants with MDs from each city were pooled to allow regional estimates to be derived. The morbidity and economic burdens of MDs hospitalizations attributable to gaseous pollutants were further assessed. A total of 171,939 MDs hospitalizations were included. We observed insignificant association of O3 with MDs. An interquartile range increase in SO2 at lag0 (9.1 μg/m³), NO2 at lag0 (16.7 μg/m³) and CO at lag2 (0.4 mg/m³) corresponded to a 3.02% (95%CI: 0.72%, 5.38%), 5.03% (95%CI: 1.84%, 8.32%) and 2.18% (95%CI: 0.40%, 4.00%) increase in daily MDs hospitalizations, respectively. These effects were modified by sex, season and cause-specific MDs. The C-R curves of SO2 and NO2 with MDs indicated nonlinearity and the slops were steeper at lower concentrations. Overall, using current standards as reference concentrations, 0.27% (95%CI: 0.07%, 0.48%) and 0.06% (95%CI: 0.02%, 0.10%) of MDs hospitalizations could be attributable to extra SO2 and NO2 exposures, and the corresponding economic costs accounted for 0.34% (95%CI: 0.08%, 0.60%) and 0.07% (95%CI: 0.03%, 0.11%) of hospitalization expenses, respectively. Moreover, using threshold values detected from C-R curves as reference concentrations, the above mentioned morbidity and economic burdens increased a lot. These findings suggest more strict emission control regulations are needed to protect mental health from gaseous pollutants.
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Affiliation(s)
- Hang Qiu
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
| | - Liya Wang
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Luo
- Business School, Sichuan University, Chengdu, China
| | - Minghui Shen
- Health Information Center of Sichuan Province, Chengdu, China
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Short-Term Ambient Particulate Air Pollution and Hospitalization Expenditures of Cause-Specific Cardiorespiratory Diseases in China: A Multicity Analysis. LANCET REGIONAL HEALTH-WESTERN PACIFIC 2021; 15:100232. [PMID: 34528013 PMCID: PMC8342975 DOI: 10.1016/j.lanwpc.2021.100232] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/01/2021] [Accepted: 07/12/2021] [Indexed: 01/23/2023]
Abstract
Background Ambient air pollution is leading risk factor for health burden in China. Few studies in China have investigated the economic loss related to short-term exposure to ambient PM2.5, which could trigger acute onset of cardiorespiratory diseases within a few days. Methods Daily ambient air pollutants data are obtained for each city from the National Air Quality Monitoring System and daily hospitalization data are obtained from the urban employee-based basic medical insurance scheme database in 74 Chinese cities with an average coverage of 88.5 million urban employees during 2016-2017. A three-stage time-series analytic approach is used in this study to investigate the impact of short-term exposure to ambient fine particulate (PM2.5) air pollution on hospital admissions, expenses and hospital stays of three cause-specific cardiorespiratory diseases, including lower respiratory infections (LRI), coronary heart disease (CHD) and stroke in the included cities. Findings Based on the time-series analysis using daily hospitalization data, 28,560 LRI cases, 54,600 CHD cases, and 23,989 stroke cases are attributable to ambient PM2.5 in the 74 cities during the study period, and the related attributable expenses are 220 million CNY (US$ 32.9 million) for LRI, 458 million CNY (US$ 68.5 million) for CHD, and 410 million CNY (US$ 65.8 million) for stroke, respectively. These attributable numbers account for 1.45% to 2.05% of total hospital admissions and 1.10% to 1.51% of total expenses for the three diseases during 2016-2017, respectively. The attributable numbers for the three cause-specific cardiorespiratory diseases would increase to 362,007 hospital admission cases and 3.68 billion CNY expenses ($US550 million) in the entire urban employee population (299 million) in China during 2016-2017, and the related direct economic loss of absence from work would be 798 million CNY (US$ 119.3 million). Interpretation Our results support that short-term exposure to ambient PM2.5 pollution could lead to significant health and economic impacts in China. Reducing levels of ambient PM2.5 can avoid substantial health damage and expenditures, and generate appreciable economic benefits from decreasing absence from work. Funding Natural Science Foundation of China (82073509, 71903010, 71903011), and the National Key Research and Development Program of China (2017YFC0211600, 2017YFC0211601).
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Yadav R, Nagori A, Mukherjee A, Singh V, Lodha R, Kabra SK, Yadav G, Saini JK, Singhal KK, Jat KR, Madan K, George MP, Mani K, Mrigpuri P, Kumar R, Guleria R, Pandey RM, Sarin R, Dhaliwal RS. Effects of ambient air pollution on emergency room visits of children for acute respiratory symptoms in Delhi, India. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:45853-45866. [PMID: 33881691 DOI: 10.1007/s11356-021-13600-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 03/17/2021] [Indexed: 06/12/2023]
Abstract
The present study explored the association between daily ambient air pollution and daily emergency room (ER) visits due to acute respiratory symptoms in children of Delhi. The daily counts of ER visits (ERV) of children (≤15 years) having acute respiratory symptoms were obtained from two hospitals of Delhi for 21 months. Simultaneously, data on daily concentrations of particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) and weather variables were provided by the Delhi Pollution Control Committee. K-means clustering with time-series approach and multi-pollutant generalized additive models with Poisson link function was used to estimate the 0-6-day lagged change in daily ER visits with the change in multiple pollutants levels. Out of 1,32,029 children screened, 19,120 eligible children having acute respiratory symptoms for ≤2 weeks and residing in Delhi for the past 4 weeks were enrolled. There was a 29% and 21% increase in ERVs among children on high and moderate level pollution cluster days, respectively, compared to low pollution cluster days on the same day and previous 1-6 days of exposure to air pollutants. There was percentage increase (95% CI) 1.50% (0.76, 2.25) in ERVs for acute respiratory symptoms for 10 μg/m3 increase of NO2 on previous day 1, 46.78% (21.01, 78.05) for 10 μg/m3 of CO on previous day 3, and 13.15% (9.95, 16.45) for 10 μg/m3 of SO2 on same day of exposure. An increase in the daily ER visits of children for acute respiratory symptoms was observed after increase in daily ambient air pollution levels in Delhi.
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Affiliation(s)
- Rashmi Yadav
- Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, 110029, India
| | - Aditya Nagori
- CSIR-Institute of Genomics and Integrative Biology, New Delhi, 110007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India
| | - Aparna Mukherjee
- Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, 110029, India
| | - Varinder Singh
- Kalawati Saran Children Hospital and Lady Harding Medical College, New Delhi, ,110001, India
| | - Rakesh Lodha
- Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, 110029, India.
| | - Sushil Kumar Kabra
- Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, 110029, India.
| | - Geetika Yadav
- Indian Council of Medical Research, New Delhi, 110029, India
| | - Jitendra Kumar Saini
- National Institute of Tuberculosis and Respiratory Diseases, New Delhi, 110030, India
| | - Kamal Kumar Singhal
- Kalawati Saran Children Hospital and Lady Harding Medical College, New Delhi, ,110001, India
| | - Kana Ram Jat
- Department of Pediatrics, All India Institute of Medical Sciences, New Delhi, 110029, India
| | - Karan Madan
- Pulmonology, Critical Care and Sleep Disorders, All India Institute of Medical Sciences, New Delhi, 10029, India
| | - Mohan P George
- Delhi Pollution Control Committee, Kashmere Gate, New Delhi, 110006, India
| | - Kalaivani Mani
- Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, 110029, India
| | - Parul Mrigpuri
- Vallabhbhai Patel Chest Institute, New Delhi, 110007, India
| | - Raj Kumar
- Vallabhbhai Patel Chest Institute, New Delhi, 110007, India
| | - Randeep Guleria
- Pulmonology, Critical Care and Sleep Disorders, All India Institute of Medical Sciences, New Delhi, 10029, India
| | - Ravindra Mohan Pandey
- Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, 110029, India
| | - Rohit Sarin
- National Institute of Tuberculosis and Respiratory Diseases, New Delhi, 110030, India
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14
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Chen G, Guo Y, Yue X, Tong S, Gasparrini A, Bell ML, Armstrong B, Schwartz J, Jaakkola JJK, Zanobetti A, Lavigne E, Nascimento Saldiva PH, Kan H, Royé D, Milojevic A, Overcenco A, Urban A, Schneider A, Entezari A, Vicedo-Cabrera AM, Zeka A, Tobias A, Nunes B, Alahmad B, Forsberg B, Pan SC, Íñiguez C, Ameling C, De la Cruz Valencia C, Åström C, Houthuijs D, Van Dung D, Samoli E, Mayvaneh F, Sera F, Carrasco-Escobar G, Lei Y, Orru H, Kim H, Holobaca IH, Kyselý J, Teixeira JP, Madureira J, Katsouyanni K, Hurtado-Díaz M, Maasikmets M, Ragettli MS, Hashizume M, Stafoggia M, Pascal M, Scortichini M, de Sousa Zanotti Stagliorio Coêlho M, Valdés Ortega N, Ryti NRI, Scovronick N, Matus P, Goodman P, Garland RM, Abrutzky R, Garcia SO, Rao S, Fratianni S, Dang TN, Colistro V, Huber V, Lee W, Seposo X, Honda Y, Guo YL, Ye T, Yu W, Abramson MJ, Samet JM, Li S. Mortality risk attributable to wildfire-related PM 2·5 pollution: a global time series study in 749 locations. Lancet Planet Health 2021; 5:e579-e587. [PMID: 34508679 DOI: 10.1016/s2542-5196(21)00200-x] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 07/22/2021] [Accepted: 07/22/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM2·5 and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM2·5 and mortality across various regions of the world. METHODS For this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000-16. Daily concentrations of wildfire-related PM2·5 were estimated using the three-dimensional chemical transport model GEOS-Chem at a 0·25° × 0·25° resolution. The association between wildfire-related PM2·5 exposure and mortality was examined using a quasi-Poisson time series model in each city considering both the current-day and lag effects, and the effect estimates were then pooled using a random-effects meta-analysis. Based on these pooled effect estimates, the population attributable fraction and relative risk (RR) of annual mortality due to acute wildfire-related PM2·5 exposure was calculated. FINDINGS 65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 μg/m3 increase in the 3-day moving average (lag 0-2 days) of wildfire-related PM2·5 exposure were 1·019 (95% CI 1·016-1·022) for all-cause mortality, 1·017 (1·012-1·021) for cardiovascular mortality, and 1·019 (1·013-1·025) for respiratory mortality. Overall, 0·62% (95% CI 0·48-0·75) of all-cause deaths, 0·55% (0·43-0·67) of cardiovascular deaths, and 0·64% (0·50-0·78) of respiratory deaths were annually attributable to the acute impacts of wildfire-related PM2·5 exposure during the study period. INTERPRETATION Short-term exposure to wildfire-related PM2·5 was associated with increased risk of mortality. Urgent action is needed to reduce health risks from the increasing wildfires. FUNDING Australian Research Council, Australian National Health & Medical Research Council.
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Affiliation(s)
- Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
| | - Xu Yue
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, China
| | - Shilu Tong
- Shanghai Children's Medical Center, Shanghai Jiao-Tong University School of Medicine, Shanghai, China; School of Public Health, Institute of Environment and Human Health, Anhui Medical University, Hefei, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia
| | - Antonio Gasparrini
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change & Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Ben Armstrong
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Joel Schwartz
- Department of Environmental Health, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Jouni J K Jaakkola
- Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Eric Lavigne
- School of Epidemiology & Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Air Health Science Division, Health Canada, Ottawa, ON, Canada
| | | | - Haidong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China
| | - Dominic Royé
- Department of Geography, University of Santiago de Compostela, CIBER of Epidemiology and Public Health (CIBERESP), Spain
| | - Ai Milojevic
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Ala Overcenco
- National Agency for Public Health of the Ministry of Health, Chisinau, Moldova
| | - Aleš Urban
- Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Alireza Entezari
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Khorasan Razavi, Iran
| | - Ana Maria Vicedo-Cabrera
- Institute of Social and Preventive Medicine and Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
| | - Ariana Zeka
- Institute of Environment, Health and Societies, Brunel University London, London, UK
| | - Aurelio Tobias
- Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, Spain; School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Baltazar Nunes
- Department of Epidemiology, Instituto Nacional de Saúde Dr Ricardo Jorge, Lisbon, Portugal
| | - Barrak Alahmad
- Department of Environmental Health, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Bertil Forsberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Shih-Chun Pan
- National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan
| | - Carmen Íñiguez
- Department of Statistics and Computational Research. Universitat de València, Valencia, CIBERESP, Spain
| | - Caroline Ameling
- National Institute for Public Health and the Environment (RIVM), Centre for Sustainability and Environmental Health, Bilthoven, Netherlands
| | - César De la Cruz Valencia
- Department of Environmental Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Christofer Åström
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Danny Houthuijs
- National Institute for Public Health and the Environment (RIVM), Centre for Sustainability and Environmental Health, Bilthoven, Netherlands
| | - Do Van Dung
- Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece
| | - Fatemeh Mayvaneh
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Khorasan Razavi, Iran
| | - Francesco Sera
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Department of Statistics, Computer Science and Applications "G Parenti", University of Florence, Florence, Italy
| | - Gabriel Carrasco-Escobar
- Institute of Tropical Medicine "Alexander von Humboldt", Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Yadong Lei
- Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Hans Orru
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Ho Kim
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, South Korea
| | | | - Jan Kyselý
- Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic; Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic
| | - João Paulo Teixeira
- Department of Environmental Health, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal
| | - Joana Madureira
- Department of Environmental Health, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal; EPIUnit-Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece
| | - Magali Hurtado-Díaz
- Department of Environmental Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | | | - Martina S Ragettli
- Swiss Tropical and Public Health Institute, Basel, Switzerland; Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland
| | - Masahiro Hashizume
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Mathilde Pascal
- Santé Publique France, Department of Environmental and occupational Health, French National Public Health Agency, Saint Maurice, France
| | | | | | | | - Niilo R I Ryti
- Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Patricia Matus
- Department of Public Health, Universidad de los Andes, Santiago, Chile
| | | | - Rebecca M Garland
- Council for Scientific and Industrial Research, Pretoria, South Africa; Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa; Unit for Environmental Sciences and Management, North West University, South Africa
| | - Rosana Abrutzky
- Instituto de Investigaciones Gino Germani, Facultad de Ciencias Sociales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | | | - Shilpa Rao
- Norwegian institute of Public Health, Oslo, Norway
| | - Simona Fratianni
- Department of Earth Sciences, University of Torino, Turin, Italy
| | - Tran Ngoc Dang
- Department of Environmental Health, Faculty of Public Health, University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Valentina Colistro
- Department of Quantitative Methods, School of Medicine, University of the Republic, Montevideo, Uruguay
| | - Veronika Huber
- Potsdam Institute for Climate Impact Research, Potsdam, Germany; Department of Physical, Chemical and Natural Systems, Universidad Pablo de Olavide, Seville, Spain
| | - Whanhee Lee
- School of Environment, Yale University, New Haven, CT, USA
| | - Xerxes Seposo
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Yasushi Honda
- Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Yue Leon Guo
- National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan; Environmental and Occupational Medicine, and Institute of Environmental and Occupational Health Sciences, National Taiwan University and National Taiwan University Hospital, Taipei, Taiwan
| | - Tingting Ye
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Wenhua Yu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Michael J Abramson
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Jonathan M Samet
- The Colorado School of Public Health, University of Colorado, Aurora
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
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15
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Lin X, Du Z, Liu Y, Hao Y. The short-term association of ambient fine particulate air pollution with hypertension clinic visits: A multi-community study in Guangzhou, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 774:145707. [PMID: 33611009 DOI: 10.1016/j.scitotenv.2021.145707] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 01/31/2021] [Accepted: 02/03/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND The association of ambient fine particulate pollution with daily outpatient clinic visits (OCV) for hypertension in China remains to be investigated. OBJECTIVES This study aimed to examine short-term impacts of exposure to fine particulate matter of aerodynamic diameter < 2.5μm (PM2.5) on daily OCV for hypertension, using a large-scale multi-center community database in Guangzhou, one of the most densely-populated cities in Southern China. METHODS We collected a total of 28,548 individual records of OCV from 22 community healthcare facilities in Guangzhou from January 1st to May 7th 2020. Hourly data on air pollutants and daily information on meteorological factors were obtained. According to the World Health Organization air-quality guidelines, daily excessive concentration hours (DECH) was calculated. PM2.5 daily mean, hourly-peak concentration and DECH were used as the exposure variables. Based on a case-time-control design, the Cox regression model was applied to evaluate the short-term relative risks (RR) of daily OCV for hypertension. Sensitivity analyses were conducted, with nitrogen dioxide, sulfur dioxide, carbon monoxide, and ozone being adjusted. RESULTS Daily mean and hourly-peak of PM2.5 were significantly associated with daily OCV for hypertension, while weaker associations were observed for DECH. The estimated RRs at lag day 0 were 1.039 (95% confidence interval [CI]: 1.037, 1.040), 1.851 (95%CI: 1.814, 1.888), and 1.287 (95%CI: 1.276, 1.298), respectively, in association with a 1-unit increase in DECH, daily mean, and hourly-peak concentration of PM2.5. For the lagged effect, lag4 models estimated the greatest RRs for PM2.5 DECH and hourly-peak, whereas a lag2 model produced the highest for PM2.5 daily mean. DISCUSSION This study consolidates the evidence for a positive correlation between ambient PM2.5 exposure and risks of hypertensive OCV. It also provides profound insight regarding planning for health services needs and establishing early environmental responses to the worsening air pollution in the communities.
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Affiliation(s)
- Xiao Lin
- Department of Medical Statistics and Epidemiology & Health Information Research Center & Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
| | - Zhicheng Du
- Department of Medical Statistics and Epidemiology & Health Information Research Center & Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
| | - Yu Liu
- Department of Medical Statistics and Epidemiology & Health Information Research Center & Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China
| | - Yuantao Hao
- Department of Medical Statistics and Epidemiology & Health Information Research Center & Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, Guangdong, China; Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, Guangdong, China.
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16
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The Influence of Air Pollutants and Meteorological Conditions on the Hospitalization for Respiratory Diseases in Shenzhen City, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18105120. [PMID: 34065982 PMCID: PMC8151817 DOI: 10.3390/ijerph18105120] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 04/27/2021] [Accepted: 05/07/2021] [Indexed: 12/29/2022]
Abstract
Air pollutants have significant direct and indirect adverse effects on public health. To explore the relationship between air pollutants and meteorological conditions on the hospitalization for respiratory diseases, we collected a whole year of daily major air pollutants’ concentrations from Shenzhen city in 2013, including Particulate Matter (PM10, PM2.5), Nitrogen dioxide (NO2), Ozone (O3), Sulphur dioxide (SO2), and Carbon monoxide (CO). Meanwhile, we also gained meteorological data. This study collected 109,927 patients cases with diseases of the respiratory system from 98 hospitals. We investigated the influence of meteorological factors on air pollution by Spearman correlation analysis. Then, we tested the short-term correlation between significant air pollutants and respiratory diseases’ hospitalization by Distributed Lag Non-linear Model (DLNM). There was a significant negative correlation between the north wind and NO2 and a significant negative correlation between the south wind and six pollutants. Except for CO, other air pollutants were significantly correlated with the number of hospitalized patients during the lag period. Most of the pollutants reached maximum Relative Risk (RR) with a lag of five days. When the time lag was five days, the annual average of PM10, PM2.5, SO2, NO2, and O3 increased by 10%, and the risk of hospitalization for the respiratory system increased by 0.29%, 0.23%, 0.22%, 0.25%, and 0.22%, respectively. All the pollutants except CO impact the respiratory system’s hospitalization in a short period, and PM10 has the most significant impact. The results are helpful for pollution control from a public health perspective.
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Shin HH, Parajuli RP, Gogna P, Maquiling A, Dehghani P. Pollutant-sex specific differences in respiratory hospitalization and mortality risk attributable to short-term exposure to ambient air pollution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 755:143135. [PMID: 33168238 DOI: 10.1016/j.scitotenv.2020.143135] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 09/11/2020] [Accepted: 10/13/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Many studies have reported associations of individual pollutants with respiratory hospitalization and mortality based on different populations, which makes it difficult to directly compare adverse health effects among multiple air pollutants. OBJECTIVES The study goal is to compare acute respiratory-related hospitalization and mortality associated with short-term exposure to three ambient air pollutants and analyze differences in health risks by season, age and sex. METHODS Hourly measurements of air pollutants (ozone, NO2, PM2.5) and temperature were collected from ground-monitors for 24 cities along with daily hospitalization (1996-2012) and mortality (1984-2012) data. National associations between air pollutant and health outcome were estimated for season (warm, cold vs. year-round), age (base ≥ 1, seniors > 65), and sex (females ≥ 1 and males ≥ 1) using Bayesian hierarchical models. RESULTS Overall, the three air pollutants were significantly associated with acute respiratory health outcomes at different lag-days. For respiratory hospitalization, the increased risks in percent changes with 95% posterior intervals for a 10-unit increase in each pollutant were: ozone (lag1, 0.7% (0.4, 0.9)), NO2 (lag0, 0.7% (0.1, 1.4)), and PM2.5 (lag1, 1.3% (0.7, 1.9)). For respiratory mortality: ozone (lag2, 1.2% (0.4, 1.9)), NO2 (lag1, 2.1% (0.6, 3.5)), and PM2.5 (lag1, 0.6% (-1.0, 2.2)). While some differences in risk were observed by season and age group, sex-specific differences were more pronounced. Compared with males, females had a higher respiratory mortality risk (1.8% (0.6, 2.9) vs 0.5% (-0.3, 1.3)) from ozone, a higher respiratory hospitalization risk (0.9% (0.0, 1.8) vs 0.6% (-0.3, 1.4)) but lower mortality risk (1.4% (-1.0, 3.7) vs 2.2% (0.4, 4.0)) from NO2, and a lower hospitalization risk (0.7% (-0.2, 1.7) vs 1.8% (1.0, 2.6)) from PM2.5. CONCLUSION This study reports significant health effects of short-term exposure to three ambient air pollutants on respiratory hospitalization (ozone≈NO2 < PM2.5 per-10 unit; ozone>NO2 ≈ PM2.5 per-IQR) and mortality (ozone≈NO2 > PM2.5) in Canada. Pollutant-sex-specific differences were found, but inconclusive due to limited biological and physiological explanations. Further studies are warranted to understand the pollutant-sex specific differences.
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Affiliation(s)
- Hwashin Hyun Shin
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada; Department of Mathematics and Statistics, Queen's University, Kingston, ON, Canada.
| | | | - Priyanka Gogna
- Department of Public Health Sciences, Queen's University, Kingston, ON, Canada.
| | - Aubrey Maquiling
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada.
| | - Parvin Dehghani
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada.
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Pu X, Wang L, Chen L, Pan J, Tang L, Wen J, Qiu H. Differential effects of size-specific particulate matter on lower respiratory infections in children: A multi-city time-series analysis in Sichuan, China. ENVIRONMENTAL RESEARCH 2021; 193:110581. [PMID: 33309823 DOI: 10.1016/j.envres.2020.110581] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 11/23/2020] [Accepted: 12/01/2020] [Indexed: 05/08/2023]
Abstract
Evidence on the short-term effects of size-specific particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10), and their difference (PMC) on children's Lower Respiratory Infections (LRI) is scare. This study aimed to estimate the differential effects of three size-specific PM on hospitalizations of children aged <18 years for pneumonia and bronchitis in 18 cities of southwestern China. The city-specific association was firstly estimated using the over-dispersed generalized additive model and then combined to obtain the regional average association. Further, to evaluate the robustness of the key findings, subgroup analyses and co-pollutant models were constructed. PM-related risks of LRI differed by PM fractions and cause-specific LRI. A 10 μg/m3 increment in PM2.5_lag03, PM10_lag06, and PMC_lag06 was associated with a 0.79% (95% CI: 0.29%, 1.29%), 0.77% (95% CI: 0.13%, 1.41%), and 2.33% (95% CI: 1.23%, 3.44%) increase in children's LRI hospitalizations, respectively. After adjustment for gaseous pollutants, adverse effects of the three types of size-specific PM on pneumonia hospitalizations were stable, ranging from 0.29% (95% CI: 0.05%, 0.54%) for PM2.5-2.50% (95% CI: 1.38%, 3.64%) for PMC. Additionally, PMC-related risk of bronchitis hospitalizations remained stable after adjustment for gaseous pollutants. Associations of pneumonia with PMC and PM10 in infants, bronchitis with PM2.5 in children aged 6-17 years, pneumonia and bronchitis with PM2.5, PMC, and PM10 in children aged 1-5 years were all statistical significant. Specifically, the effects of PM2.5 on LRI hospitalizations increased by age, with the highest effect of 1.72% (95%CI: 1.01%, 2.43%) in children aged 6-17 years. Our study provided evidence for short-term effects of different PM fractions on children LRI hospitalizations in Southwestern China, which will be useful for making and promoting policies on air quality standards in order to protect children's health.
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Affiliation(s)
- Xiaorong Pu
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Liya Wang
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Lina Chen
- West China Second University Hospital, Sichuan University, Chengdu, China
| | - Jingping Pan
- Health Information Center of Sichuan Province, Chengdu, China
| | - Lei Tang
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Jing Wen
- Glasgow College, University of Electronic Science and Technology of China, Chengdu, China
| | - Hang Qiu
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
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Li M, Tang J, Yang H, Zhao L, Liu Y, Xu H, Fan Y, Hong J, Long Z, Li X, Zhang J, Guo W, Liu M, Yang L, Lai X, Zhang X. Short-term exposure to ambient particulate matter and outpatient visits for respiratory diseases among children: A time-series study in five Chinese cities. CHEMOSPHERE 2021; 263:128214. [PMID: 33297172 DOI: 10.1016/j.chemosphere.2020.128214] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 08/25/2020] [Accepted: 08/29/2020] [Indexed: 06/12/2023]
Abstract
There was limited evidence regarding the association between short-term exposure to ambient particulate matter (PM) and respiratory outpatient visits among children at a multicity level. In this study, a time-series study was conducted among children aged 0-14 years in five Chinese cities from 2013 to 2018. City-specific effects of fine particles (PM2.5), inhalable particles (PM10) and coarse particles (PM10-2.5) were estimated for time lags of zero up to seven previous days using the overdispersed generalized additive models after adjusting for time trends, meteorological variables, day of the week and holidays. Meta-analyses were applied to pool the overall effects, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. The overall effects of PM were significantly associated with total and cause-specific respiratory outpatients among children, even at PM2.5 and PM10 levels below the current Chinese Ambient Air Quality Standards (CAAQS) Grade II. Each 10 μg/m3 increment in PM2.5, PM10 and PM10-2.5 at lag 07 was associated with a 1.39% (95% CI: 0.38%, 2.40%), 1.10% (95% CI: 0.38%, 1.83%) and 2.93% (95% CI: 1.05%, 4.84%) increase in total respiratory outpatients, respectively. An E-R relationship was observed except for PM2.5 in Beijing and PM10 and PM10-2.5 in Shanghai. The effects of PM were stronger in cold season in 3 southern cities, while it was stronger in transition season in 2 northern cities. In conclusion, short-term PM exposures were dose-responsive associated with increased respiratory outpatient visits among children, even for PM2.5 and PM10 levels below current CAAQS II in certain cities.
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Affiliation(s)
- Meng Li
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Jie Tang
- Department of Preventive Medicine, School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Huihua Yang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Lei Zhao
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Ya Liu
- Department of Medical Record, Beijing Hospital, Beijing, China
| | - Haoli Xu
- Department of Healthcare, Guangdong Women and Children Hospital, Guangzhou, China
| | - Yali Fan
- Qinghai Provincial Women and Children's Hospital, Xining, China
| | - Jun Hong
- Qinghai Provincial Women and Children's Hospital, Xining, China
| | - Zhen Long
- Department of Pediatric respiratory Medicine, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, HUST, Wuhan, China
| | - Xiaojuan Li
- Department of Medical Record and Statistics, Emergency General Hospital, Beijing, China
| | - Jianduan Zhang
- Department of Woman and Child's Care and Adolescence Health, School of Public Health, Tongji Medical College, HUST, Wuhan, China
| | - Wenting Guo
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Miao Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Liangle Yang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Xuefeng Lai
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, China.
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20
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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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Cochard M, Ledoux F, Landkocz Y. Atmospheric fine particulate matter and epithelial mesenchymal transition in pulmonary cells: state of the art and critical review of the in vitro studies. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2020; 23:293-318. [PMID: 32921295 DOI: 10.1080/10937404.2020.1816238] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Exposure to fine particulate matter (PM2.5) has been associated with several diseases including asthma, chronic obstructive pulmonary disease (COPD) and lung cancer. Mechanisms such as oxidative stress and inflammation are well-documented and are considered as the starting point of some of the pathological responses. However, a number of studies also focused on epithelial-mesenchymal transition (EMT), which is a biological process involved in fibrotic diseases and cancer progression notably via metastasis induction. Up until now, EMT was widely reported in vivo and in vitro in various cell types but investigations dealing with in vitro studies of PM2.5 induced EMT in pulmonary cells are limited. Further, few investigations combined the necessary endpoints for validation of the EMT state in cells: such as expression of several surface, cytoskeleton or extracellular matrix biomarkers and activation of transcription markers and epigenetic factors. Studies explored various cell types, cultured under differing conditions and exposed for various durations to different doses. Such unharmonized protocols (1) might introduce bias, (2) make difficult comparison of results and (3) preclude reaching a definitive conclusion regarding the ability of airborne PM2.5 to induce EMT in pulmonary cells. Some questions remain, in particular the specific PM2.5 components responsible for EMT triggering. The aim of this review is to examine the available PM2.5 induced EMT in vitro studies on pulmonary cells with special emphasis on the critical parameters considered to carry out future research in this field. This clarification appears necessary for production of reliable and comparable results.
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Affiliation(s)
- Margaux Cochard
- Unité de Chimie Environnementale et Interactions sur le Vivant, UCEIV UR4492, SFR Condorcet FR-CNRS-3417, Univ. Littoral Côte d'Opale (ULCO) , Dunkerque, France
| | - Frédéric Ledoux
- Unité de Chimie Environnementale et Interactions sur le Vivant, UCEIV UR4492, SFR Condorcet FR-CNRS-3417, Univ. Littoral Côte d'Opale (ULCO) , Dunkerque, France
| | - Yann Landkocz
- Unité de Chimie Environnementale et Interactions sur le Vivant, UCEIV UR4492, SFR Condorcet FR-CNRS-3417, Univ. Littoral Côte d'Opale (ULCO) , Dunkerque, France
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Chen L, Zhang Y, Zhang W, Chen G, Lu P, Guo Y, Li S. Short-term effect of PM 1 on hospital admission for ischemic stroke: A multi-city case-crossover study in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 260:113776. [PMID: 31962264 DOI: 10.1016/j.envpol.2019.113776] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 11/12/2019] [Accepted: 12/08/2019] [Indexed: 06/10/2023]
Abstract
This study aims to examine the association between short-term exposures to PM1, PM2.5 and PM10 (particulate matter with aerodynamic diameters ≤1 μm, ≤2.5 μm and ≤10 μm, respectively) and hospital admission for ischemic stroke in China. Daily counts of hospital admission for ischemic stroke were collected in 5 hospitals in China during November 2013 to October 2015. Daily concentrations of PM1, PM2.5 and PM10 were collected in 5 cities where the hospitals were located. A time-stratified case-crossover design was used to examine the hospital-specific PM-ischemic stroke association after controlling for potential confounders. Then the effect estimates were pooled using a random-effect meta-analysis. A total of 68,122 hospital admissions for ischemic stroke were identified from 5 hospitals during the study period. The pooled results showed that exposures to PM1, PM2.5 and PM10 were significantly associated with increased hospital admission for ischemic stroke on the current day and previous 1 day. The RRs (relative risk associated with per 10 μg/m3 increase in each pollutant) and 95%CIs (confidence intervals) for the cumulative effects of PM1, PM2.5 and PM10 on ischemic stroke during lag 0-1 days were 1.014 (1.005, 1.0023), 1.007 (1.000, 1.014) and 1.005 (1.001, 1.009), respectively. In total, 3.5%, 3.6% and 4.1% of hospital admissions for ischemic stroke could be attributable to PM1, PM2.5 and PM10, respectively. Exposures to ambient PM1, PM2.5 and PM10 pollution showed acute adverse effects on hospital admission for ischemic stroke. The health effects of PM1 should be considered by policy-makers.
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Affiliation(s)
- Lijun Chen
- Information Engineering College, Hubei University of Chinese Medicine, Wuhan, Hubei, China
| | - Yongming Zhang
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Beijing, China.
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, Hubei, China
| | - Peng Lu
- Department of Epidemiology, School of Public Health and Management, Binzhou Medical University, Yantai, Shandong, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
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Qiu H, Luo L, Su Z, Zhou L, Wang L, Chen Y. Machine learning approaches to predict peak demand days of cardiovascular admissions considering environmental exposure. BMC Med Inform Decis Mak 2020; 20:83. [PMID: 32357880 PMCID: PMC7195717 DOI: 10.1186/s12911-020-1101-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 04/23/2020] [Indexed: 02/05/2023] Open
Abstract
Background Accumulating evidence has linked environmental exposure, such as ambient air pollution and meteorological factors, to the development and severity of cardiovascular diseases (CVDs), resulting in increased healthcare demand. Effective prediction of demand for healthcare services, particularly those associated with peak events of CVDs, can be useful in optimizing the allocation of medical resources. However, few studies have attempted to adopt machine learning approaches with excellent predictive abilities to forecast the healthcare demand for CVDs. This study aims to develop and compare several machine learning models in predicting the peak demand days of CVDs admissions using the hospital admissions data, air quality data and meteorological data in Chengdu, China from 2015 to 2017. Methods Six machine learning algorithms, including logistic regression (LR), support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) were applied to build the predictive models with a unique feature set. The area under a receiver operating characteristic curve (AUC), logarithmic loss function, accuracy, sensitivity, specificity, precision, and F1 score were used to evaluate the predictive performances of the six models. Results The LightGBM model exhibited the highest AUC (0.940, 95% CI: 0.900–0.980), which was significantly higher than that of LR (0.842, 95% CI: 0.783–0.901), SVM (0.834, 95% CI: 0.774–0.894) and ANN (0.890, 95% CI: 0.836–0.944), but did not differ significantly from that of RF (0.926, 95% CI: 0.879–0.974) and XGBoost (0.930, 95% CI: 0.878–0.982). In addition, the LightGBM has the optimal logarithmic loss function (0.218), accuracy (91.3%), specificity (94.1%), precision (0.695), and F1 score (0.725). Feature importance identification indicated that the contribution rate of meteorological conditions and air pollutants for the prediction was 32 and 43%, respectively. Conclusion This study suggests that ensemble learning models, especially the LightGBM model, can be used to effectively predict the peak events of CVDs admissions, and therefore could be a very useful decision-making tool for medical resource management.
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Affiliation(s)
- Hang Qiu
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, No.2006, Xiyuan Ave, West Hi-Tech Zone, 611731, Chengdu, Sichuan, P.R. China. .,Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
| | - Lin Luo
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Ziqi Su
- Department of Statistics, Faculty of Science, University of British Columbia, Vancouver, Canada
| | - Li Zhou
- Health Information Center of Sichuan Province, Chengdu, China
| | - Liya Wang
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Yucheng Chen
- Cardiology Division, West China Hospital, Sichuan University, Chengdu, China.,West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
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Tian Y, Liu H, Liang T, Xiang X, Li M, Juan J, Song J, Cao Y, Wang X, Chen L, Wei C, Gao P, Hu Y. Fine particulate air pollution and adult hospital admissions in 200 Chinese cities: a time-series analysis. Int J Epidemiol 2020; 48:1142-1151. [PMID: 31157384 DOI: 10.1093/ije/dyz106] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/10/2019] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND The association between short-term exposure to ambient fine particulate matter (PM2.5) and morbidity risk in developing countries is not fully understood. We conducted a nationwide time-series study to estimate the short-term effect of PM2.5 on hospital admissions in Chinese adults. METHODS Daily counts of hospital admissions for 2014-16 were obtained from the National Urban Employee Basic Medical Insurance database. We identified more than 58 million hospitalizations from 0.28 billion insured persons in 200 Chinese cities for subjects aged 18 years or older. Generalized additive models with quasi-Poisson regression were applied to examine city-specific associations of PM2.5 concentrations with hospital admissions. National-average estimates of the association were obtained from a random-effects meta-analysis. We also investigated potential effect modifiers, such as age, sex, temperature and relative humidity. RESULTS An increase of 10 μg/m3 in same-day PM2.5 concentrations was positively associated with a 0.19% (95% confidence interval: 0.07-0.30) increase in the daily number of hospital admissions at the national level. PM2.5 exposure remained positively associated with hospital admissions on days when the daily concentrations met the current Chinese Ambient Air Quality Standards (75 μg/m3). Estimates of admission varied across cities and increased in cities with lower PM2.5 concentrations (p = 0.044) or higher temperatures (p = 0.002) and relative humidity (p = 0.003). The elderly were more sensitive to PM2.5 exposure (p < 0.001). CONCLUSIONS Short-term exposure to PM2.5 was positively associated with adult hospital admissions in China, even at levels below current Chinese Ambient Air Quality Standards.
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Affiliation(s)
- Yaohua Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Hui Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.,Medical Informatics Center, Peking University, Beijing, China
| | | | - Xiao Xiang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Man Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Juan Juan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jing Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yaying Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Xiaowen Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Libo Chen
- HealthCom Data Technology Co. Ltd, Beijing, China
| | - Chen Wei
- HealthCom Data Technology Co. Ltd, Beijing, China
| | - Pei Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.,Key Laboratory of Molecular Cardiovascular (Peking University), Ministry of Education, Beijing, China
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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Chen D, Mayvaneh F, Baaghideh M, Entezari A, Ho HC, Xiang Q, Jiao A, Zhang F, Hu K, Chen G, Zhao Q, Sun S, Zhang Y. Utilizing daily excessive concentration hours to estimate cardiovascular mortality and years of life lost attributable to fine particulate matter in Tehran, Iran. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 703:134909. [PMID: 31757557 DOI: 10.1016/j.scitotenv.2019.134909] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 09/22/2019] [Accepted: 10/08/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Evidence for associations between fine particulate matter (PM2.5) and cardiovascular diseases (CVDs) in Iran is scarce. Given large within-day variations of PM2.5 concentration, using the daily mean of PM2.5 (PM2.5mean) as exposure metric might bias the health-related assessment. This study applied a novel indicator, daily excessive concentration hours (DECH), to evaluate the effect of ambient PM2.5 on CVD mortality and years of life lost (YLL) in Tehran, the capital city of Iran. METHODS Hourly concentration data for PM2.5, daily information for meteorology and records of registered cardiovascular deaths from 2012 to 2016 were obtained from Tehran, Iran. Daily excessive concentration hours of PM2.5 (PM2.5DECH) was defined as daily total concentration-hours exceeding 35 μg/m3. Using a time-series design, we applied generalized linear models to assess the attributable effects of PM2.5DECH and PM2.5mean on CVD mortality and YLL. RESULTS For an interquartile range (IQR) rise in PM2.5DECH, total CVD mortality at lag 0-10 days and YLL at lag 0-8 days increased 2.26% (95% confidence interval (CI): 0.85-3.69%) and 23.24 (6.07-40.42) person years, respectively. Corresponding increases were 3.45% (1.44-5.49%) and 35.21 (10.85-59.58) person years for an IQR rise in PM2.5mean. Significant associations between PM2.5 pollution (i.e., PM2.5mean and PM2.5DECH) and cause-specific cardiovascular health (i.e., mortality and YLL) were only identified in stroke. Subgroup analyses showed that male and people aged 0-64 years suffered more from PM2.5 pollution. Furthermore, we attributed a greater CVD burden to PM2.5DECH (1.67% for mortality and 2.67% for YLL) than PM2.5mean (0.63% for mortality and 0.70% for YLL) during the study period. CONCLUSIONS This study strengthened the evidence for the aggravated CVD mortality burden associated with short-term exposure to PM2.5. Our findings also suggested that PM2.5DECH might be a potential alternative indicator of exposure assessment in PM2.5-related health investigations.
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Affiliation(s)
- Dieyi Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Fatemeh Mayvaneh
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar 9617916487, Khorasan Razavi, Iran
| | - Mohammad Baaghideh
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar 9617916487, Khorasan Razavi, Iran
| | - Alireza Entezari
- Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar 9617916487, Khorasan Razavi, Iran
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China
| | - Qianqian Xiang
- Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - Anqi Jiao
- Department of Preventive Medicine, School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Faxue Zhang
- Department of Preventive Medicine, School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Kejia Hu
- Department of Precision Health and Data Science, School of Public Health, Zhejiang University, Hangzhou 310003, China
| | - Gongbo Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Qi Zhao
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
| | - Shengzhi Sun
- Department of Epidemiology, Brown University School of Public Health, Providence, RI 02912, USA
| | - Yunquan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, China; Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan 430065, China.
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Jiao A, Xiang Q, Ding Z, Cao J, Ho HC, Chen D, Cheng J, Yang Z, Zhang F, Yu Y, Zhang Y. Short-term impacts of ambient fine particulate matter on emergency department visits: Comparative analysis of three exposure metrics. CHEMOSPHERE 2020; 241:125012. [PMID: 31606575 DOI: 10.1016/j.chemosphere.2019.125012] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 09/15/2019] [Accepted: 09/29/2019] [Indexed: 05/29/2023]
Abstract
BACKGROUND Research argued that daily excessive concentration hours (DECH) could be more informative through accounting for within-day variations, when assessing population-level exposure to ambient fine particle (PM2.5). However, few studies have comparatively investigated PM2.5-associated risks using DECH and two common metrics of daily mean and hourly peak concentration. METHODS We collected daily records of all-cause emergency department visits (EDVs) and hourly data on air pollutants and meteorological factors from Shenzhen, China, 2015-2018. According to guidelines proposed by the World Health Organization, DECH was calculated by summing up daily concentrations exceeding 25 μg/m3. Based on time-stratified case-crossover design, we adopted conditional logistic regression models to assess short-term attributable risks of EDVs associated with PM2.5 using three exposure metrics. RESULTS DECH and daily average of PM2.5 strongly elevated risks of EDVs, while less evident associations were observed using hourly peak metric. Estimated excess relative risks at lag 0 day were 0.56% (95% confidence interval [CI]: 0.21 to 0.91), 0.69% (95% CI: 0.25 to 1.13) and 0.37% (95% CI: 0.02 to 0.76), respectively, associated with an interquartile range increase in DECH (420.2 μg/m3), 24-h average (24.9 μg/m3) and hourly peak concentration (38 μg/m3). More emergency visits could be attributed to DECH than daily mean PM2.5, with attributable fractions of 2.02% (95% CI: 1.42 to 2.61) and 1.09% (95% CI: 0.69 to 1.49), respectively. CONCLUSIONS This study added evidence for increased risk of EDVs associated with exposure to ambient PM2.5. DECH was a potential alternative exposure metric for PM2.5 assessment, which may have implications for future revision of air quality standards.
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Affiliation(s)
- Anqi Jiao
- Department of Preventive Medicine, School of Health Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China; Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada
| | - Qianqian Xiang
- Hubei Provincial Center for Disease Control and Prevention, Wuhan, 430079, China
| | - Zan Ding
- The Institute of Metabolic Diseases, Baoan Central Hospital of Shenzhen, The Fifth Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, 518102, China
| | - Jiguo Cao
- Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC, V5A 1S6, Canada
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China
| | - Dieyi Chen
- Department of Global Health, School of Health Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Jian Cheng
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, 4059, Australia
| | - Zhiming Yang
- Donlinks School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China
| | - Faxue Zhang
- Department of Preventive Medicine, School of Health Sciences, Wuhan University, 185 Donghu Road, Wuhan, 430071, China
| | - Yong Yu
- School of Public Health and Management, Hubei University of Medicine, Shiyan, 442000, China.
| | - Yunquan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan, 430065, China; Hubei Province Key Laboratory of Occupational Hazard Identification and Control, Wuhan University of Science and Technology, Wuhan, 430065, China.
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Chen C, Liu X, Wang X, Qu W, Li W, Dong L. Effect of air pollution on hospitalization for acute exacerbation of chronic obstructive pulmonary disease, stroke, and myocardial infarction. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2020; 27:3384-3400. [PMID: 31845265 DOI: 10.1007/s11356-019-07236-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Accepted: 12/02/2019] [Indexed: 05/03/2023]
Abstract
This study aims to analyze the acute effects of PM2.5, PM10, SO2, NO2, and O3 on hospitalizations for acute exacerbation of chronic obstructive pulmonary disease (AECOPD), stroke, and myocardial infarction (MI) from 2014 to 2017 in Shenyang, China. Hospitalization records for AECOPD (17,655), stroke (276,736) and MI (26,235) and air pollutions concentration data (PM2.5, PM10, SO2, NO2, and O3) were collected. A generalized additive model (GAM) was utilized to determine the impact of air pollutants on the relative risk (RR) of hospitalization for AECOPD, stroke, and MI. Stratified analysis for AECOPD was based on gender and age. It was based on gender, age, hypertension, and diabetes for stroke, and for MI it was based on gender, age, and coronary atherosclerosis. The lag effect for AECOPD in terms of gender analysis occurred at lag3-lag5. The hospitalization risk for stroke with hypertension due to SO2 and NO2 was greater than that of stroke without hypertension. The risk of hospitalization for stroke with hypertension as a comorbidity due to O3 was lower than without hypertension. The risk of hospitalization for MI combined with coronary atherosclerosis due to PM2.5, PM10, or NO2 was higher than that of hospitalizations for MI without coronary atherosclerosis. Air pollution increased the rate of hospitalization for AECOPD. SO2 and O3 appeared protective for stroke patients with coronary atherosclerosis. PM2.5, PM10, and NO2 had no influence on total hospitalization for myocardial infarction.
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Affiliation(s)
- Cai Chen
- Biomedical Engineering Institute, School of Control Science and Engineering, Shandong University, Jinan, 250061, China
| | - Xuejian Liu
- The First General Internal Medicine, Shengjing Hospital, China Medical University, No.16 Puhe Road, Shenbei New District, Shenyang City, 110000, Liaoning Province, China
| | - Xianfeng Wang
- PFLMET Experimental Center, Shandong University, Jinan, People's Republic of China
| | - Wenxiu Qu
- The First General Internal Medicine, Shengjing Hospital, China Medical University, No.16 Puhe Road, Shenbei New District, Shenyang City, 110000, Liaoning Province, China.
| | - Wei Li
- Biomedical Engineering Institute, School of Control Science and Engineering, Shandong University, Jinan, 250061, China.
| | - Leilei Dong
- Biomedical Engineering Institute, School of Control Science and Engineering, Shandong University, Jinan, 250061, China
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Zhu X, Qiu H, Wang L, Duan Z, Yu H, Deng R, Zhang Y, Zhou L. Risks of hospital admissions from a spectrum of causes associated with particulate matter pollution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 656:90-100. [PMID: 30502738 DOI: 10.1016/j.scitotenv.2018.11.240] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 11/16/2018] [Accepted: 11/16/2018] [Indexed: 05/04/2023]
Abstract
Ambient particulate matter (PM) pollution has been linked to elevated hospital admissions (HAs), especially from respiratory and cardiovascular diseases. However, few studies have estimated the associations between PM pollution and HAs for a wider range of broad disease categories. This study aimed to evaluate the effects of PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) and ≤10 μm (PM10) on a range of broad and specific causes of HAs in Chengdu, China during 2015-2016, using a generalized additive model (GAM). Age-, gender- and season-specific analyses were also performed on the broad categories. We further calculated the corresponding morbidity burden due to PM exposure. During the study period, the daily mean level for PM2.5 and PM10 was 57.3 μg/m3 and 94.7 μg/m3, respectively. For broad disease categories, each 10 μg/m3 increase in PM10 at lag06 was associated with increments of 0.65% (95% CI: 0.32%-0.99%) in HAs from respiratory, 0.49% (95% CI: 0.04%-0.95%) from circulatory and 0.91% (95% CI: 0.15%-1.69%) from skin and subcutaneous tissue diseases. By contrast, only respiratory HAs showed a significant positive association with elevated PM2.5 at lag06 (1.03% increase per 10 μg/m3, 95% CI: 0.50%-1.56%, p < 0.001). Increased HAs risks for several more refined specific causes within respiratory, circulatory, skin and subcutaneous tissue, nervous and genitourinary diseases were also observed. Subgroup analyses indicated that effect estimates were modified by age, gender and season. Overall, the largest morbidity burden was observed in myocardial infarction, about 11.27% (95% CI: 3.45%-18.07%) and 11.11% (95% CI: 4.07%-17.27%) of HAs for myocardial infarction could be attributable to PM2.5 and PM10 levels exceeding the WHO's air quality guidelines (24-h mean: 25 μg/m3 for PM2.5 and 50 μg/m3 for PM10). Our study suggests that both PM2.5 and PM10 increase risks of morbidity from broad range of causes of HAs in Chengdu, and result in substantial morbidity burden.
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Affiliation(s)
- Xiaojuan Zhu
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; Center for Artificial Intelligence and Smart Health, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Hang Qiu
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; Center for Artificial Intelligence and Smart Health, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.
| | - Liya Wang
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhanqi Duan
- Health and Family Planning Information Center of Sichuan Province, Chengdu, China
| | - Haiyan Yu
- School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, China; Department of Statistics, The Pennsylvania State University, University Park, PA, USA
| | - Ren Deng
- Health and Family Planning Information Center of Sichuan Province, Chengdu, China
| | - Yanlong Zhang
- Chengdu Shulianyikang Technology Co., Ltd, Chengdu, China
| | - Li Zhou
- Health and Family Planning Information Center of Sichuan Province, Chengdu, China.
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Qiu H, Zhu X, Wang L, Pan J, Pu X, Zeng X, Zhang L, Peng Z, Zhou L. Attributable risk of hospital admissions for overall and specific mental disorders due to particulate matter pollution: A time-series study in Chengdu, China. ENVIRONMENTAL RESEARCH 2019; 170:230-237. [PMID: 30594694 DOI: 10.1016/j.envres.2018.12.019] [Citation(s) in RCA: 77] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 11/27/2018] [Accepted: 12/10/2018] [Indexed: 05/23/2023]
Abstract
The associations of particulate matter (PM) pollution with the morbidity of overall and subtypes of mental disorders (MDs), as well as the corresponding morbidity burden, remain understudied, especially in developing countries. This study aimed to evaluate the short-term effects of PM2.5 (diameters ≤ 2.5 µm), PM10 (diameters ≤ 10 µm) and PMC (diameters between 2.5 and 10 µm) on hospital admissions (HAs) for MDs in Chengdu, China, during 2015-2016, and calculate corresponding attributable risks. A generalized additive model (GAM) with controlling for time trend, meteorological conditions, holidays and day of the week was used to estimate the associations. Stratified analyses were also performed by age, gender and season. We further estimated the burden of HAs for MDs attributable to PM exposure. During the study period, a total of 10,947 HAs for MDs were collected. PM2.5, PM10 and PMC were significantly associated with elevated risks of MDs hospitalizations. Each 10 μg/m3 increase in PM2.5, PM10 and PMC at lag06 corresponded to an increase of 2.89% (95% CI: 0.75-5.08%), 1.91% (95% CI: 0.57-3.28%) and 3.95% (95% CI: 0.84-7.15%) in daily HAs for MDs, respectively. The risk estimates of PM on MDs hospitalizations were generally robust after adjustment for gaseous pollutants in two-pollutant models. We found stronger associations between PM pollution and MDs in males and in cool seasons than in females and in warm seasons. For specific subtypes of MDs, significant associations of PM pollution with dementia,schizophrenia and depression were observed. Using WHO's air quality guidelines as the reference concentrations, 9.53% (95% CI: 2.67-15.58%), 9.17% (95% CI: 2.91-14.70%) and 6.10% (95% CI: 1.40-10.32%) of HAs for MDs could be attributable to PM2.5, PM10 and PMC, respectively. Our results suggested that PM exposure might be an important trigger of hospitalizations for MDs in Chengdu, China, and account for substantial morbidity burden.
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Affiliation(s)
- Hang Qiu
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.
| | - Xiaojuan Zhu
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Liya Wang
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Jingping Pan
- Health and Family Planning Information Center of Sichuan Province, Chengdu 610041, Sichuan, China
| | - Xiaorong Pu
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoxi Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Li Zhang
- Sichuan Provincial Center for Disease Control and Prevention, Chengdu, China
| | - Zhao Peng
- Chengdu Wukang Medical Technology Co., Ltd, Chengdu, China
| | - Li Zhou
- Health and Family Planning Information Center of Sichuan Province, Chengdu 610041, Sichuan, China.
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Yang BY, Guo Y, Markevych I, Qian Z(M, Bloom MS, Heinrich J, Dharmage SC, Rolling CA, Jordan SS, Komppula M, Leskinen A, Bowatte G, Li S, Chen G, Liu KK, Zeng XW, Hu LW, Dong GH. Association of Long-term Exposure to Ambient Air Pollutants With Risk Factors for Cardiovascular Disease in China. JAMA Netw Open 2019; 2:e190318. [PMID: 30848806 PMCID: PMC6484675 DOI: 10.1001/jamanetworkopen.2019.0318] [Citation(s) in RCA: 141] [Impact Index Per Article: 28.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
IMPORTANCE Which cardiometabolic risk factors (eg, hypertension, type 2 diabetes, overweight or obesity, and dyslipidemia) are more sensitive to long-term exposure to ambient air pollution and whether participants with these conditions are more susceptible to the cardiovascular effects of air pollution remain unclear. OBJECTIVES To evaluate the associations among long-term exposure to air pollutants, cardiometabolic risk factors, and cardiovascular disease (CVD) prevalence. DESIGN, SETTING, AND PARTICIPANTS This population-based cross-sectional study was conducted from April 1 through December 31, 2009, in 3 cities in Northeastern China. Participants were adults aged 18 to 74 years who had lived in study area for 5 years or longer. Data analysis was performed from May 1 through December 31, 2018. EXPOSURES Long-term (2006-2008) exposure to air pollutants was measured using a spatiotemporal statistical model (particulate matter with an aerodynamic diameter of ≤2.5 μm [PM2.5] and ≤1.0 μm [PM1.0]) and data from air monitoring stations (particulate matter with an aerodynamic diameter of ≤10.0 μm [PM10.0], sulfur dioxide [SO2], nitrogen dioxide [NO2], and ozone [O3]). MAIN OUTCOMES AND MEASURES Cardiovascular disease was determined by self-report of physician-diagnosed CVD. Blood pressure, body mass index, and levels of triglycerides and low-density lipoprotein cholesterol were measured using standard methods. RESULTS Participants included 15 477 adults (47.3% women) with a mean (SD) age of 45.0 (13.5) years. The prevalence of CVD was 4.8%, and the prevalence of cardiometabolic risk factors ranged from 8.6% (hyperbetalipoproteinemia) to 40.5% (overweight or obesity). Mean (SD) air pollutant concentrations ranged from 35.3 (5.5) μg/m3 (for NO2) to 123.1 (14.6) μg/m3 (for PM10.0). Associations with air pollutants were identified for individuals with hyperbetalipoproteinemia (eg, odds ratio [OR], 1.36 [95% CI, 1.03-1.78] for a 10-μg/m3 increase in PM1.0) and the weakest association for those with for overweight or obesity (eg, OR, 1.06 [95% CI, 1.02-1.09] for a 10-μg/m3 increase in PM1.0). Cardiometabolic risk factors only partially mediated associations between air pollution and CVD. However, they modified the associations such that greater associations were found in participants with these cardiometabolic conditions (eg, ORs for CVD and per 10-μg/m3 increase in PM1.0, 1.22 [95% CI, 1.12-1.33] in participants with hyperbetalipoproteinemia and 1.07 [95% CI, 0.98-1.16] in participants without hyperbetalipoproteinemia). CONCLUSIONS AND RELEVANCE In this population-based study of Chinese adults with CVD, long-term exposure to air pollution was associated with a higher prevalence of cardiometabolic risk factors, and the strongest associations were observed for hyperbetalipoproteinemia. In addition, participants with cardiometabolic risk factors may have been more vulnerable to the effects of air pollution on CVD.
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Affiliation(s)
- Bo-Yi Yang
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Iana Markevych
- Institute of Epidemiology, Helmholtz Zentrum München–German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig Maximilian University of Munich, Munich, Germany
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital of Munich, Munich, Germany
| | - Zhengmin (Min) Qian
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St Louis, Missouri
| | - Michael S. Bloom
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, New York
- Department of Epidemiology and Biostatics, University at Albany, State University of New York, Rensselaer, New York
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital of Munich, Munich, Germany
- Comprehensive Pneumology Center Munich, German Center for Lung Research, Munich, Germany
| | - Shyamali C. Dharmage
- Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
- Murdoch Children Research Institute, Melbourne, Australia
| | - Craig A. Rolling
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St Louis, Missouri
| | - Savannah S. Jordan
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, St Louis, Missouri
| | | | - Ari Leskinen
- Finnish Meteorological Institute, Kuopio, Finland
| | - Gayan Bowatte
- The National Institute of Fundamental Studies, Kandy, Sri Lanka
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Gongbo Chen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Kang-Kang Liu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Xiao-Wen Zeng
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Li-Wen Hu
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
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Kang M, Ren L, Ren H, Zhao Y, Kawamura K, Zhang H, Wei L, Sun Y, Wang Z, Fu P. Primary biogenic and anthropogenic sources of organic aerosols in Beijing, China: Insights from saccharides and n-alkanes. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2018; 243:1579-1587. [PMID: 30293040 DOI: 10.1016/j.envpol.2018.09.118] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 09/10/2018] [Accepted: 09/23/2018] [Indexed: 06/08/2023]
Abstract
Sugars and n-alkanes are important organic constituents of atmospheric fine particulate matter (PM2.5). For better understanding their sources and seasonal variations in urban atmosphere, sugar compounds (anhydrosugars, sugars and sugar alcohols) and homologue n-alkanes (C18-C37) were studied in PM2.5 samples collected from September 2013 to July 2014 in Beijing, China. In general, all measured compounds showed the lowest levels in summer. Higher concentrations of sugar compounds and n-alkanes were observed in winter, probably due to elevated combustion emissions (e.g., coal, biofuel and agricultural residue burning) and stable meteorological conditions during heating season. Levoglucosan was the major sugar species in all seasons particularly in autumn and winter, highlighting the significant contribution of biomass burning to fine organic aerosols throughout the whole year especially in cold seasons. Plant waxes contributed to n-alkanes the most in late spring (54.5%) and the least in winter (11.6%); while fossil fuel combustion had the largest contribution in winter (385 ng m-3). The weak odd-carbon predominance of n-alkanes in wintertime aerosols also suggests fossil fuel combustion as the important source of organic aerosols in the heating season. Soil resuspension, fossil fuel combustion and biomass burning, and secondary sources are the main sources of OC in PM2.5 at Beijing. The seasonal variation in source contributions indicates that meteorological condition is a key factor in controlling PM2.5 levels. Furthermore, dust storms in spring can strongly enhance the atmospheric level of fine organic matter in Beijing.
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Affiliation(s)
- Mingjie Kang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
| | - Lujie Ren
- Institute of Surface-Earth System Science, Tianjin University, Tianjin, 300072, China
| | - Hong Ren
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Ye Zhao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China.
| | - Kimitaka Kawamura
- Chubu Institute for Advanced Studies, Chubu University, Kasugai, 487-8501, Japan
| | - Hongliang Zhang
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Lianfang Wei
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Pingqing Fu
- Institute of Surface-Earth System Science, Tianjin University, Tianjin, 300072, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China.
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Qiu H, Yu H, Wang L, Zhu X, Chen M, Zhou L, Deng R, Zhang Y, Pu X, Pan J. The burden of overall and cause-specific respiratory morbidity due to ambient air pollution in Sichuan Basin, China: A multi-city time-series analysis. ENVIRONMENTAL RESEARCH 2018; 167:428-436. [PMID: 30121467 DOI: 10.1016/j.envres.2018.08.011] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 06/29/2018] [Accepted: 08/06/2018] [Indexed: 05/25/2023]
Abstract
Few studies have investigated the respiratory morbidity burden due to ambient air pollution in China, especially in a multi-city setting. This study aimed to estimate the short-term effects of ambient air pollutants (PM10, PM2.5, NO2 and SO2) on hospital admissions (HAs) for overall and cause-specific respiratory diseases, as well as the associated burden in 17 cities of Sichuan Basin, China during 2015-2016. Firstly, city-specific effect estimates for each pollutant on respiratory HAs were obtained using generalized additive model with quasi-Poisson link, and then random- or fixed-effects meta-analysis was applied to pool the effect estimates at the regional level. Subgroup analyses by sex, age, season and region were also performed. A total of 757,712 respiratory HAs were collected from all the tertiary and secondary hospitals located in the 17 cities. Risks of HAs for overall and cause-specific respiratory diseases were elevated following increased PM10, PM2.5, NO2 and SO2 exposure. An increase of 10 μg/m3 in PM10 at lag01, PM2.5 at lag01, NO2 at lag0 and SO2 at lag02 was associated with a 0.43% (95% CI: 0.33%, 0.53%), 0.53% (95% CI: 0.39%, 0.68%), 2.36% (95% CI: 1.75%, 2.98%) and 2.54% (95% CI: 1.51%, 3.59%) increases in total respiratory HAs, respectively. Children (≤ 14 years) and elderly (≥ 65 years) appeared to be more vulnerable to the effects of ambient air pollutants. Comparing to the WHO's air quality guidelines, we estimated that 1.84% (95%CI: 1.42%, 2.25%), 1.73% (95%CI: 1.27%, 2.19%) and 0.34% (95%CI: 0.21%, 0.48%) of respiratory HAs were due to PM10, PM2.5 and SO2 exposure, respectively. This study suggests that air pollution might be an important trigger of respiratory admissions, and result in substantial burden of HAs for respiratory diseases in Sichuan Basin.
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Affiliation(s)
- Hang Qiu
- Health Big Data Research Institute, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Haiyan Yu
- School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, China; Department of Statistics, The Pennsylvania State University, University Park, PA, USA
| | - Liya Wang
- Health Big Data Research Institute, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
| | - Xiaojuan Zhu
- Health Big Data Research Institute, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Mengdie Chen
- Health Big Data Research Institute, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Zhou
- Health and Family Planning Information Center of Sichuan Province, Chengdu, China
| | - Ren Deng
- Health and Family Planning Information Center of Sichuan Province, Chengdu, China; Sichuan Health Information Association, Chengdu, Sichuan, China
| | - Yanlong Zhang
- Chengdu Shulianyikang Technology Co., Ltd, Chengdu, China
| | - Xiaorong Pu
- Health Big Data Research Institute, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Jingping Pan
- Health and Family Planning Information Center of Sichuan Province, Chengdu, China; Sichuan Health Information Association, Chengdu, Sichuan, China.
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Cheng J, Zhang Y, Zhang W, Xu Z, Bambrick H, Hu W, Tong S. Assessment of heat- and cold-related emergency department visits in cities of China and Australia: Population vulnerability and attributable burden. ENVIRONMENTAL RESEARCH 2018; 166:610-619. [PMID: 29982149 DOI: 10.1016/j.envres.2018.06.026] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 06/12/2018] [Accepted: 06/12/2018] [Indexed: 05/22/2023]
Abstract
BACKGROUND Non-optimal ambient temperature has detrimental impacts on mortality worldwide, but little is known about the difference in population vulnerability to non-optimal temperature and temperature-related morbidity burden between developing and developed countries. OBJECTIVES We estimated and compared the associations of emergency department visits (EDV) with non-optimal temperature in terms of risk trigger temperature, the average slope of exposure-risk function and attributable risk in 12 cities from China and Australia. METHODS We modelled the associations of EDV with heat during warm season and with cold during cold season, separately, using generalized additive model. Population vulnerability within a given region was quantified with multiple risk trigger points including minimum risk temperature, increasing risk temperature and excessive risk temperature, and average coefficient of exposure-risk function. Fraction of EDV attributable to heat and cold was also calculated. RESULTS We found large between- and within-country contrasts in the identified multiple risk trigger temperatures, with higher heat and cold trigger points, except excessive risk temperature, observed in Australia than in China. Heat was associated with a relative risk (RR) of 1.009 [95% confidence interval (CI):1.007, 1.011] in China, which accounted for 5.9% of EDV. Higher RR of heat was observed in Australia (1.014, 95% CI: 1.010, 1.018), responsible for 4.0% of EDV. For cold effects, the RR was similar between two countries, but the attributable fraction was higher in China (9.6%) than in Australia (1.5%). CONCLUSIONS Exposure to heat and cold had adverse but divergent impacts on EDV in China and Australia. Further mitigation policy efforts incorporating region-specific population vulnerability to temperature impacts are necessary in both countries.
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Affiliation(s)
- Jian Cheng
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Yongming Zhang
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital; National Clinical Research Center for Respiratory Diseases, Beijing, China
| | - Wenyi Zhang
- Center for Disease Surveillance of PLA, Institute of Disease Control and Prevention of PLA, Beijing, China
| | - Zhiwei Xu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia.
| | - Shilu Tong
- Shanghai Children's Medical Centre, Shanghai Jiao-Tong University, Shanghai, China; School of Public Health, Institute of Environment and Human Health, Anhui Medical University, Hefei, China; School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia.
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Health Impacts of Exposure to Gaseous Pollutants and Particulate Matter in Beijing-A Non-Linear Analysis Based on the New Evidence. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15091969. [PMID: 30201896 PMCID: PMC6165060 DOI: 10.3390/ijerph15091969] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 08/31/2018] [Accepted: 09/05/2018] [Indexed: 11/16/2022]
Abstract
This paper aimed to estimate health risks focusing on respiratory diseases from exposure to gaseous multi-pollutants based on new data and revealed new evidence after the most stringent air pollution control plan in Beijing which was carried out in 2013. It used daily respiratory diseases outpatient data from a hospital located in Beijing with daily meteorological data and monitor data of air pollutants from local authorities. All data were collected from 2014 to 2016. Distributed lag non-linear model was employed. Results indicated that NO2 and CO had positive association with outpatients number on the day of the exposure (1.045 (95% confidence interval (CI): 1.003, 1.089) for CO and 1.022 (95% CI: 1.008, 1.036) for NO2) (and on the day after the exposure (1.026 (95% CI: 1.005, 1.048) for CO and 1.013 (95% CI: 1.005, 1.021) for NO2). Relative risk (RR) generally declines with the number of lags; ozone produces significant effects on the first day (RR = 0.993 (95% CI: 0.989, 0.998)) as well as second day (RR = 0.995 (95% CI: 0.991, 0.999)) after the exposure, while particulate pollutants did not produce significant effects. Effects from the short-term exposure to gaseous pollutants were robust after controlling for particulate matters. Our results contribute to a comprehensive understanding of the dependencies between the change of air pollutants concentration and their health effects in Beijing after the implementation of promising air regulations in 2013. Results of the study can be used to develop relevant measures minimizing the adverse health consequences of air pollutants and supporting sustainable development of Beijing as well as other rapidly growing Asian cities.
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Ambient Particulate Matter Concentrations and Hospital Admissions in 26 of China’s Largest Cities. Epidemiology 2018; 29:649-657. [DOI: 10.1097/ede.0000000000000869] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Risk Reduction Behaviors Regarding PM 2.5 Exposure among Outdoor Exercisers in the Nanjing Metropolitan Area, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15081728. [PMID: 30103552 PMCID: PMC6121644 DOI: 10.3390/ijerph15081728] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 07/20/2018] [Accepted: 08/07/2018] [Indexed: 01/12/2023]
Abstract
Aims: This study aimed to describe risk reduction behaviors regarding ambient particulate matter with a diameter of 2.5 μm or less (PM2.5) among outdoor exercisers and to explore potential factors influencing those behaviors in the urban area of Nanjing, China. Method: A cross-sectional convenience sample survey was conducted among 302 outdoor exercisers in May 2015. Descriptive analysis was used to describe demographics, outdoor physical activity patterns, knowledge of PM2.5 and risk reduction behaviors. Multivariate logistic regression analysis was then used to explore factors that influence the adoption of risk reduction behaviors. Results: The most common behavior to reduce PM2.5 exposure was minimizing the times for opening windows on hazy days (75.5%), and the least common one was using air purifiers (19.3%). Two thirds of respondents indicated that they wore face masks when going outside in the haze (59.5%), but only 13.6% of them would wear professional antismog face masks. Participants adopting risk reduction behaviors regarding PM2.5 exposure tended to be females, 50–60 year-olds, those with higher levels of knowledge about PM2.5 and those who had children. Conclusions: These findings indicate the importance of improving knowledge about PM2.5 among outdoor exercisers. Educational interventions should also be necessary to guide the public to take appropriate precautionary measures when undertaking outdoor exercise in high PM2.5 pollution areas.
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Short-Term Effects of Air Pollution on Respiratory and Circulatory Morbidity in Colombia 2011⁻2014: A Multi-City, Time-Series Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15081610. [PMID: 30061515 PMCID: PMC6121387 DOI: 10.3390/ijerph15081610] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 07/15/2018] [Accepted: 07/17/2018] [Indexed: 11/16/2022]
Abstract
Few studies have been conducted on the effect of air pollution on morbidity in Latin America. This study analyzed the effects of air pollution on respiratory and circulatory morbidity in four major cities in Colombia. An ecological time-series analysis was conducted with pollution data from air quality monitoring networks and information on emergency department visits between 2011 and 2014. Daily 24-h averages were calculated for NO₂, PM10, PM2.5, and SO₂ as well as 8-h averages for CO and O₃. Separate time-series were constructed by disease group and pollutant. Conditional negative binomial regression models were used with average population effects. Effects were calculated for the same day and were adjusted for weather conditions, age groups, and their interactions. The results showed that effects of some of the pollutants differed among the cities. For NO₂, PM10, and PM2.5, the multi-city models showed greater and statistically significant percentage increases in emergency department visits for respiratory diseases, particularly for the 5 to 9-year-old age group. These same pollutants also significantly affected the rate of emergency department visits for circulatory diseases, especially for the group of persons over 60 years of age.
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Chen G, Guo Y, Abramson MJ, Williams G, Li S. Exposure to low concentrations of air pollutants and adverse birth outcomes in Brisbane, Australia, 2003-2013. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 622-623:721-726. [PMID: 29223898 DOI: 10.1016/j.scitotenv.2017.12.050] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 12/04/2017] [Accepted: 12/04/2017] [Indexed: 06/07/2023]
Abstract
BACKGROUND It's unclear whether exposures to low-level air pollution have adverse effects on birth outcomes, and which trimester-specific pregnant exposure is sensitive. OBJECTIVES To investigate the effects of maternal exposure during each trimester and the whole pregnancy to particles with aerodynamic diameter<2.5μm (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) on preterm birth (PTB) and low birth weight (LBW). METHODS Daily data on birth records, air quality, and weather conditions were collected in Brisbane, Australia during 2003-2013. Mean concentrations of air pollutants were calculated for each trimester of pregnancy. Cox proportional hazards models were used to examine the associations between air pollution and birth outcomes. Multi-pollutant models and stratified analyses by ambient temperature were performed. RESULTS Exposures to PM2.5, SO2, NO2, and O3 during the whole pregnancy were associated with increased risk of PTB [IQR HRs (hazard ratios with an interquartile range increase in air pollutants) and 95% confidence intervals (CIs): 1.05 (1.02, 1.08), 1.12 (1.09, 1.16), 1.07 (1.01, 1.13), and 1.13 (1.10, 1.16), respectively] and LBW [IQR HRs and 95% CIs: 1.06 (1.02, 1.10), 1.12 (1.08, 1.16), 1.11 (1.03, 1.18), and 1.13 (1.09, 1.17), respectively]. Highest HRs were observed during trimester 3, and lowest in trimester 1. For each air pollutant, stronger effects on PTB and LBW were present for exposure to low and moderate temperatures than exposure to high ambient temperature. CONCLUSIONS Exposures to low-level air pollutants are related to adverse birth outcomes. More effective policies for air quality control could contribute to improving neonatal health.
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Affiliation(s)
- Gongbo Chen
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Michael J Abramson
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Gail Williams
- School of Public Health, The University of Queensland, Brisbane, Queensland, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; School of Public Health, The University of Queensland, Brisbane, Queensland, Australia.
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Eguchi R, Onozuka D, Ikeda K, Kuroda K, Ieiri I, Hagihara A. The relationship between fine particulate matter (PM 2.5) and schizophrenia severity. Int Arch Occup Environ Health 2018; 91:613-622. [PMID: 29682692 DOI: 10.1007/s00420-018-1311-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2017] [Accepted: 04/18/2018] [Indexed: 12/20/2022]
Abstract
PURPOSE Although particulate matter (PM) is reported to affect the rate of emergency admissions for schizophrenia, no study has examined the relationship between particulate matter less than 2.5 μm in diameter (PM2.5) and the severity of schizophrenia. METHODS We obtained data on patients with schizophrenia at a psychiatric hospital, and on air pollution in Sakai, Japan between Feb 1, 2013 and April 30, 2016. Multivariate logistic regression analyses were used to estimate the relationship between PM2.5 concentrations and scores on the Brief Psychiatric Rating Scale (BPRS) of schizophrenia patients at admission, with a lag of up to 7 days. RESULTS During the study period, there were 1193 schizophrenia cases. The odds ratio (OR) for a BPRS score ≥ 50 at admission was 1.05 [95% confidence interval 1.00-1.10] and the effect of PM2.5 concentration was significant for lag period of 2 days. The ORs associated with PM2.5 concentration increased substantially for patients over 65 years of age. CONCLUSIONS Ambient PM2.5 concentration was associated with exacerbation of schizophrenia. Our results suggest that protection for several days should be considered for controlling PM2.5-related schizophrenia, especially among elderly patients.
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Affiliation(s)
- Rika Eguchi
- Department of Health Services Management and Policy, Kyushu University Graduate School of Medicine, Higashi-ku, Fukuoka, 812-8582, Japan.,Department of Clinical Pharmacokinetics, Kyushu University Graduate School of Pharmaceutical Science, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Daisuke Onozuka
- Department of Health Services Management and Policy, Kyushu University Graduate School of Medicine, Higashi-ku, Fukuoka, 812-8582, Japan.
| | - Kouji Ikeda
- Hannan Hospital, 277 Handaminamino-cho, Naka-ku, Sakai, Osaka, 599-8263, Japan
| | - Kenji Kuroda
- Hannan Hospital, 277 Handaminamino-cho, Naka-ku, Sakai, Osaka, 599-8263, Japan
| | - Ichiro Ieiri
- Department of Clinical Pharmacokinetics, Kyushu University Graduate School of Pharmaceutical Science, Higashi-ku, Fukuoka, 812-8582, Japan.
| | - Akihito Hagihara
- Department of Health Services Management and Policy, Kyushu University Graduate School of Medicine, Higashi-ku, Fukuoka, 812-8582, Japan.
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Qiu H, Tan K, Long F, Wang L, Yu H, Deng R, Long H, Zhang Y, Pan J. The Burden of COPD Morbidity Attributable to the Interaction between Ambient Air Pollution and Temperature in Chengdu, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018. [PMID: 29534476 PMCID: PMC5877037 DOI: 10.3390/ijerph15030492] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Evidence on the burden of chronic obstructive pulmonary disease (COPD) morbidity attributable to the interaction between ambient air pollution and temperature has been limited. This study aimed to examine the modification effect of temperature on the association of ambient air pollutants (including particulate matter (PM) with aerodynamic diameter <10 μm (PM10) and <2.5 μm (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3)) with risk of hospital admissions (HAs) for COPD, as well as the associated morbidity burden in urban areas of Chengdu, China, from 2015 to 2016. Based on the generalized additive model (GAM) with quasi-Poisson link, bivariate response surface model and stratification parametric model were developed to investigate the potential interactions between ambient air pollution and temperature on COPD HAs. We found consistent interactions between ambient air pollutants (PM2.5, PM10 and SO2) and low temperature on COPD HAs, demonstrated by the stronger associations between ambient air pollutants and COPD HAs at low temperatures than at moderate temperatures. Subgroup analyses showed that the elderly (≥80 years) and males were more vulnerable to this interaction. The joint effect of PM and low temperature had the greatest impact on COPD morbidity burden. Using WHO air quality guidelines as reference concentration, about 17.30% (95% CI: 12.39%, 22.19%) and 14.72% (95% CI: 10.38%, 19.06%) of COPD HAs were attributable to PM2.5 and PM10 exposures on low temperature days, respectively. Our findings suggested that low temperature significantly enhanced the effects of PM and SO2 on COPD HAs in urban Chengdu, resulting in increased morbidity burden. This evidence has important implications for developing interventions to reduce the risk effect of COPD morbidity.
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Affiliation(s)
- Hang Qiu
- Health Big Data Research Institute, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Kun Tan
- Health and Family Planning Information Center of Sichuan Province, Chengdu 610041, China.
- Sichuan Health Information Association, Chengdu 610041, China.
| | - Feiyu Long
- School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China.
| | - Liya Wang
- Health Big Data Research Institute, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Haiyan Yu
- Health Big Data Research Institute, Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China.
- School of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
- Department of Statistics, The Pennsylvania State University, University Park, PA 16802-2111, USA.
| | - Ren Deng
- Health and Family Planning Information Center of Sichuan Province, Chengdu 610041, China.
- Sichuan Health Information Association, Chengdu 610041, China.
| | - Hu Long
- Health and Family Planning Information Center of Sichuan Province, Chengdu 610041, China.
- Sichuan Health Information Association, Chengdu 610041, China.
| | - Yanlong Zhang
- Chengdu Shulianyikang Technology Co., Ltd., Chengdu 610041, China.
| | - Jingping Pan
- Health and Family Planning Information Center of Sichuan Province, Chengdu 610041, China.
- Sichuan Health Information Association, Chengdu 610041, China.
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Bliss B, Tran KI, Sioutas C, Campbell A. Ambient ultrafine particles activate human monocytes: Effect of dose, differentiation state and age of donors. ENVIRONMENTAL RESEARCH 2018; 161:314-320. [PMID: 29178980 PMCID: PMC5748008 DOI: 10.1016/j.envres.2017.11.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Revised: 11/14/2017] [Accepted: 11/15/2017] [Indexed: 05/22/2023]
Abstract
Exposure to ambient particulate matter (PM) has been linked to adverse pulmonary and cardiovascular health effects. Activation of both inflammatory and oxidative stress pathways has been observed and may be a probable cause of these outcomes. We tested the hypothesis that in human monocytes, PM-induced oxidative and inflammatory responses are interrelated. A human monocytic cell line (THP-1) was used to determine if dose and differentiation state plays a role in the cellular response after a 24hr exposure to particles. Primary human monocytes derived from eight female, non-smoker donors (aged: 21, 24, 27, 28, 48, 49, 54 & 60yo) were used to determine if the age of donors modulates the response. Cells were treated with aqueous suspensions of ambient ultrafine particles (UFP, defined as smaller than 0.2µm in size) or a media control for 24hr. After exposure, reactive oxygen species (ROS) formation was increased irrespective of dose or differentiation state of THP-1 cells. In the primary human monocytes, ROS formation was not significantly changed. The release of the proinflammatory cytokine, tumor necrosis factor alpha (TNF-α), was dose-dependent and greatest in differentiated compared to undifferentiated THP-1 cells exposed to UFP. In the Primary human monocytes, TNF-α secretion was increased irrespective of the age of the donor. Our results suggest that after a 24hr exposure to particles, general reactive oxygen species formation was nonspecific and uncorrelated to cytokine secretion which was consistently enhanced. Cytokines play an important role in orchestrating many immune responses and thus the ability of ambient particles to enhance robust secretion of a proinflammatory cytokine from primary human monocytes, and how this may influence the response to pathogens and alter disease states, needs to be further evaluated.
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Affiliation(s)
- Bishop Bliss
- Department of Pharmaceutical Sciences, Western University of Health Sciences, Pomona, CA, USA
| | - Kevin Ivan Tran
- Department of Pharmaceutical Sciences, Western University of Health Sciences, Pomona, CA, USA
| | - Constantinos Sioutas
- Department of Civil & Environmental Engineering, University of Southern California, Los Angeles, CA, USA
| | - Arezoo Campbell
- Department of Pharmaceutical Sciences, Western University of Health Sciences, Pomona, CA, USA.
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Environmental Health: Lessons from the Past and Looking to the Future. Ann Am Thorac Soc 2017; 14:1378-1382. [PMID: 28820615 DOI: 10.1513/annalsats.201706-455ps] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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