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Lin W, Pan J, Li J, Zhou X, Liu X. Short-Term Exposure to Air Pollution and the Incidence and Mortality of Stroke: A Meta-Analysis. Neurologist 2024; 29:179-187. [PMID: 38048541 DOI: 10.1097/nrl.0000000000000544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/06/2023]
Abstract
BACKGROUND The relationship between short-term exposure to various air pollutants [particulate matter <10 μm (PM 10 ), particulate matter <2.5 μm (PM 2.5 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), carbon monoxide, and ozone (O 3 )] and the incidence and mortality of stroke remain unclear. REVIEW SUMMARY We conducted a comprehensive search across databases, including PubMed, Web of Science, and others. A random-effects model was employed to estimate the odds ratios (OR) and their 95% CIs. Short-term exposure to PM 10 , PM 2.5 , NO 2 , SO 2 , and O 3 was associated with increased stroke incidence [per 10 μg/m 3 increase in PM 2.5 : OR = 1.005 (95% CI: 1.004-1.007), per 10 μg/m 3 increase in PM 10 : OR = 1.006 (95% CI: 1.004-1.009), per 10 μg/m 3 increase in SO 2 : OR = 1.034 (95% CI: 1.020-1.048), per 10 μg/m 3 increase in NO 2 : OR = 1.029 (95% CI: 1.015-1.043), and O 3 for per 10 μg/m 3 increase: OR: 1.006 (95% CI: 1.004-1.007)]. In addition, short-term exposure to PM 2.5 , PM 10 , SO 2, and NO 2 was correlated with increased mortality from stroke [per 10 μg/m 3 increase in PM 2.5 : OR = 1.010 (95% CI: 1.006-1.013), per 10 μg/m 3 increase in PM 10 : OR = 1.004 (95% CI: 1.003-1.006), per 10 μg/m 3 increase in SO 2 : OR = 1.013 (95% CI: 1.007-1.019) and per 10 μg/m 3 increase in NO 2 : OR = 1.012 (95% CI: 1.008-1.015)]. CONCLUSION Reducing outdoor air pollutant levels may yield a favorable outcome in reducing the incidence and mortality associated with strokes.
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Affiliation(s)
- Wenjian Lin
- Department of Neurology, Shanghai Tenth People's Hospital, Tongji University School of Medicine
- Tongji University School of Medicine, Shanghai, China
| | - Jie Pan
- Department of Neurology, Shanghai Tenth People's Hospital, Tongji University School of Medicine
| | - Jiahe Li
- Tongji University School of Medicine, Shanghai, China
| | - Xiaoyu Zhou
- Department of Neurology, Shanghai Tenth People's Hospital, Tongji University School of Medicine
| | - Xueyuan Liu
- Department of Neurology, Shanghai Tenth People's Hospital, Tongji University School of Medicine
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Shen W, Li X, Fang Q, Li G, Xiao W, Wu Y, Liu J, Hu W, Lu H, Huang F. The impact of ambient air pollutants on childhood respiratory system disease and the resulting disease burden: a time-series study. Int Arch Occup Environ Health 2023; 96:1087-1100. [PMID: 37338586 DOI: 10.1007/s00420-023-01991-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 06/13/2023] [Indexed: 06/21/2023]
Abstract
PURPOSE The effects of air pollution on human health have long been a hot topic of research. For respiratory diseases, a large number of studies have proved that air pollution is one of the main causes. The purpose of this study was to investigate the risk of hospitalization of children with respiratory system diseases (CRSD) caused by six pollutants (PM2.5, PM10, NO2, SO2, CO, and O3) in Hefei City, and further calculate the disease burden. METHOD In the first stage, the generalized additive models were combined with the distributed lag non-linear models to evaluate the impact of air pollution on the inpatients for CRSD in Hefei. In the second stage, this study used the cost-of-illness approach to calculate the attributable number of hospitalizations and the extra disease burden. RESULT Overall, all the six kinds of pollutants had the strongest effects on CRSD inpatients within lag10 days. SO2 and CO caused the highest and lowest harm, respectively, and the RR values were SO2 (lag0-5): 1.1 20 (1.053, 1.191), and CO (lag0-6): 1.002 (1.001, 1.003). During the study period (January 1, 2014 to December 30, 2020), the 7-year cumulative burden of disease was 36.19 million CNY under the WHO air pollution standards. CONCLUSION In general, we found that six air pollutants were risk factors for CRSD in Hefei City, and create a huge burden of disease.
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Affiliation(s)
- Wenbin Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Xue Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Qingfeng Fang
- Department of Infectious Diseases, Anhui Provincial Children's Hospital, Hefei, Anhui, China
| | - Guoao Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Wei Xiao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Yueyang Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Jianjun Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Wenlei Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Huanhuan Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Fen Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China.
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Alhussaini AR, Aljabri MR, Al-Harbi ZT, Abdulrahman Almohammadi G, Al-Harbi TM, Bashir S. Air Pollution and Its Adverse Effects on the Central Nervous System. Cureus 2023; 15:e38927. [PMID: 37313075 PMCID: PMC10259194 DOI: 10.7759/cureus.38927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/11/2023] [Indexed: 06/15/2023] Open
Abstract
Air pollution is recognized as a significant public health problem and is associated with illnesses of the central nervous system (CNS) as well as neuroinflammation and neuropathology. Air pollution may cause chronic brain inflammation, white matter abnormalities, and microglia activation, which increases the risk of autism spectrum disorders, neurodegenerative disorders, stroke, and multiple sclerosis (MS). Methods: A literature review was done on "PubMed, EMBASE and Web of Science" on the relationship of air pollution with MS and stroke, using the keywords "air pollution" OR "pollution"; "ambient air pollution," "particulate matter, ozone, black carbon" AND "stroke" OR "cerebrovascular diseases," "multiple sclerosis," "neuroinflammation," or "neurodegeneration." Results: We first identified 128 articles and their related websites, of which 44 articles were further selected for analysis mainly based on study relevance, study quality and reliability, and date of publication. Further studies on air pollution and its adverse effects on the CNS are needed. The findings of such studies will support the development of appropriate preventive measures in the future.
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Affiliation(s)
| | | | - Zeyad T Al-Harbi
- College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam, SAU
| | | | | | - Shahid Bashir
- Neuroscience, Neuroscience Center, King Fahad Specialist Hospital, Dammam, SAU
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Huang QS, Zhou LX, Yang LL, Jiang YX, Xiao H, Li DW, Zhou YM, Hu YG, Li N, Li YF, Ji AL, Luo P, Cai TJ. Association between ambient carbon monoxide levels and hospitalization costs of patients with myocardial infarction: Potential effect modification by ABO blood group. ENVIRONMENTAL RESEARCH 2023; 216:114516. [PMID: 36220442 DOI: 10.1016/j.envres.2022.114516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 09/29/2022] [Accepted: 10/04/2022] [Indexed: 06/16/2023]
Abstract
Previous researches have reported the association between air pollution and various diseases. However, few researches have investigated whether air pollutants are associated with the economic loss resulting from patients' hospitalization, especially the economic loss of hospitalization due to acute cardiovascular events. The purpose of our research was to explore the association between the levels of carbon monoxide (CO), taken as an index of pollution, and the hospitalization costs of myocardial infarction (MI), and the potential effect modification by the ABO blood group. A total of 3237 MI inpatients were included in this study. A multiple linear regression model was used to evaluate the association between ambient CO levels and hospitalization costs of MI patients. Moreover, we performed stratified analyses by age, gender, body mass index (BMI), season, hypertension, and ABO blood types. There was a positive association between the levels of CO in the air and the costs of hospitalization caused by MI. Furthermore, such association was stronger in males, BMI ≥25, <65 years, with hypertension, and non-O blood group. Interestingly, we found the association was particularly significant in patients with blood group B. Overall, our study first found that ambient CO levels could have an impact on the hospitalization costs for MI patients, and those with blood group B can be more sensitive.
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Affiliation(s)
- Qing-Song Huang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 550025, China; Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Lai-Xin Zhou
- Medical Department, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Li-Li Yang
- Department of Information, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, China
| | - Yue-Xu Jiang
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 550025, China; Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Hua Xiao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Da-Wei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yu-Meng Zhou
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yue-Gu Hu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Na Li
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 550025, China; Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ai-Ling Ji
- Department of Preventive Medicine, Chongqing Medical and Pharmaceutical College, Chongqing, 401331, China
| | - Peng Luo
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 550025, China.
| | - Tong-Jian Cai
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, 550025, China; Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
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Cui M, Zhan C, Wu W, Guo D, Song Y. Acute Gaseous Air Pollution Exposure and Hospitalizations for Acute Ischemic Stroke: A Time-Series Analysis in Tianjin, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph192013344. [PMID: 36293925 PMCID: PMC9603069 DOI: 10.3390/ijerph192013344] [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: 08/02/2022] [Revised: 10/10/2022] [Accepted: 10/12/2022] [Indexed: 05/13/2023]
Abstract
BACKGROUND Stroke has always been an important problem troubling human health. Short-term exposure to air pollutants is associated with increased hospital admissions. The rise of pollutants such as O3 has caused a huge social and economic burden. This study aims to explore the relationship between short-term exposure to ambient gaseous pollutants and daily hospitalizations for ischemic stroke, utilizing a four-year time-series study in Tianjin. METHODS Collecting the data of gaseous pollutants (NO2, SO2, CO, O3), meteorological data (including daily average temperature and relative humidity) and the number of hospitalizations due to ischemic stroke in Tianjin Medical University General Hospital from 2013 to 2016. Poisson regression generalized additive model with single-day and multi-day moving average lag structure was used to estimate adverse effects of gaseous pollutants on daily hospitalizations. Subgroup analysis was performed to detect modification effect by gender and age. RESULTS In total, there were 9081 ischemic stroke hospitalizations. After controlling for the meteorological factors in the same period, no significant findings were found with the increase of NO2, SO2, CO and O3 concentrations at most of the time in the single-pollutant model. Similarly, in the stratified analysis, no associations between gaseous pollutants and ischemic stroke were observed in this study. CONCLUSIONS Short-term exposure to NO2, SO2, CO and O3 was not distinctly associated with daily hospitalizations for ischemic stroke in Tianjin. Multicenter studies in the future are warranted to explore the associations between gaseous pollution exposure and ischemic stroke.
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Affiliation(s)
- Mingrui Cui
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Changqing Zhan
- Department of Neurology, Wuhu No.2 People’s Hospital, Wuhu 241001, China
| | - Wenjuan Wu
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Dandan Guo
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yijun Song
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin 300052, China
- Correspondence: ; Tel.: +86-13012270022
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Yang D, Yan Y, Pu K. The Association Between Air Pollutants and Daily Outpatient Visits for Allergic Rhinitis: A Time-Series Analysis Based on Distribution Lag Nonlinear Model in Chongqing, China. Healthc Policy 2022; 15:1501-1515. [PMID: 35966499 PMCID: PMC9374097 DOI: 10.2147/rmhp.s373085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 07/25/2022] [Indexed: 11/23/2022] Open
Abstract
Background Allergic rhinitis (AR) is a severe and the most common chronic allergic disease, affecting 10-40% of the world population. The effect of air pollutants on AR has been confirmed in clinical experiments. Purpose This study aimed to quantify the association between air pollutants and daily outpatient visits for AR in Chongqing, China. Methods Based on the data of AR outpatients in the primary urban area of Chongqing from 2016 to 2017, along with the atmospheric pollutants and meteorological data in the same period, the distributed lag nonlinear model (DLNM) and generalized additive model (GAM) were used to analyze the time-series. We examined the effects of the single and double pollutant models with a maximum lag day of 30 days. Effect estimates were described as relative risk (RR) and 95% confidence intervals (CIs) in daily outpatient visits for AR per 10 μg/m3 increases in PM2.5, PM10, SO2, NO2, O3, and per 1 mg/m3 increase in CO. Results A single pollutant's O3 level had an immediate positive effect on AR within two days, the relative risks (RR, 95% CI) were 1.066 (1.008-1.127), 1.057 (1.005-1.112) and 1.048 (1.002-1.097). PM2.5 had a lag effect within 11-18 days, the max relative risks (RR, 95% CI) were 1.083 (1.010-1.160). Moreover, O3, PM2.5, PM10, SO2 and NO2 had significant effects on AR in the two-pollutant model. The RR cumulative effect of PM2.5 became more pronounced as the concentration increased. The cumulative effect of NO2 was lesser than PM2.5. Conclusion Air pollutants were associated with the daily outpatient visits for AR, which may have considerable implications for developing tailored health policies and services to prevent AR in Chongqing and even all over the world.
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Affiliation(s)
- Dan Yang
- School of Medical Information, Chongqing Medical University, Chongqing, People's Republic of China
| | - Yongjie Yan
- School of Medical Information, Chongqing Medical University, Chongqing, People's Republic of China
| | - Kexue Pu
- School of Medical Information, Chongqing Medical University, Chongqing, People's Republic of China.,Medical Data Research Institute of Chongqing Medical University, Chongqing, People's Republic of China
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Ji Y, Liu B, Song J, Pan R, Cheng J, Wang H, Su H. Short-term effects and economic burden assessment of ambient air pollution on hospitalizations for schizophrenia. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:45449-45460. [PMID: 35149942 DOI: 10.1007/s11356-022-19026-z] [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: 10/20/2021] [Accepted: 01/29/2022] [Indexed: 06/14/2023]
Abstract
The evidence on the health and economic impacts of air pollution with schizophrenia is scarce, especially in developing countries. In this study, we aimed to systemically examine the short-term effects of PM2.5 (particulate matter ≤ 2.5 μm in diameter), PM10 (≤ 10 μm in diameter), NO2 (nitrogen dioxide), SO2 (sulfur dioxide), CO (carbon monoxide), and O3 (ozone) on hospital admissions for schizophrenia in a Chinese coastal city (Qingdao) and to further assess the corresponding attributable risk and economic burden. A generalized additive model (GAM) was applied to model the impact of air pollution on schizophrenia, and the corresponding economic burden including the direct costs (medical expenses) and indirect costs (productivity loss). Stratified analyses were also performed by age, gender, and season (warm or cold). Our results showed that for a 10 μg/m3 increase in the concentrations of PM2.5, PM10, SO2, and CO at lag5, the corresponding relative risks (RRs) were 1.0160 (95% CI: 1.0038-1.0282), 1.0097 (1.0018-1.0177), 1.0738 (1.0222-1.01280), and 1.0013 (1.0001-1.0026), respectively. However, no significant effect of NO2 or O3 on schizophrenia admissions was found. The stratified analysis indicated that females and younger individuals (< 45 years old) appeared to be more vulnerable, but no significant difference was found between seasons. Furthermore, 12.41% of schizophrenia hospitalizations were attributable to exposure to air pollution exceeding the World Health Organization (WHO) air quality standard, with a total economic burden of 89.67 million RMB during the study period. At the individual level, excessive air pollution exposure resulted in an economic burden of 8232.08 RMB per hospitalization. Our study found that short-term exposure to air pollutants increased the risk of hospital admissions for schizophrenia and resulted in a substantial economic burden. Considerable health benefits can be achieved by further reducing air pollution.
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Affiliation(s)
- Yanhu Ji
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Bin Liu
- Qingdao Mental Health Center, 299 Nanjing Road, Qingdao, Shandong, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Heng Wang
- Department of Hospital Management, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China.
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China.
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Zhao Z, Guo M, An J, Zhang L, Tan P, Tian X, Zhao Y, Liu L, Wang X, Liu X, Guo X, Luo Y. Acute effect of air pollutants' peak-hour concentrations on ischemic stroke hospital admissions among hypertension patients in Beijing, China, from 2014 to 2018. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:41617-41627. [PMID: 35094263 DOI: 10.1007/s11356-021-18208-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 12/14/2021] [Indexed: 06/14/2023]
Abstract
Air pollutants' effect on ischemic stroke (IS) has been widely reported. But the effect of high-level concentrations during people's outdoor periods among hypertension patients was unknown. Peak-hour concentrations were defined considering air pollutants' high concentrations as well as people's outdoor periods. We conducted a time-series study and used the generalized additive model to analyze peak-hour concentrations' acute effect. A total of 315,499 IS patients comorbid with hypertension were admitted to secondary and above hospitals in Beijing from 2014 to 2018. A 10 µg/m3 (CO: 1 mg/m3) increase of the peak-hour concentrations was positively associated with IS hospital admissions among hypertension patients. The maximum effect sizes were as follows: for PM2.5, 0.17% (95% confidence interval [CI]: 0.10-0.24%) at Lag0 and 0.22% (95% CI: 0.12-0.33%) at Lag0-5; for PM10, 0.09% (95% CI: 0.05-0.13%) at Lag5 and 0.17% (95% CI: 0.09-0.26%) at Lag0-5; for SO2, 0.87% (95% CI: 0.46-1.29%) at Lag5; for NO2, 0.83% (95% CI: 0.62-1.04%) at Lag0 and 0.86% (95% CI: 0.59-1.13%) at Lag0-1; for CO 1.23% (95% CI: 0.66-1.80%) at Lag0 and 1.33% (95% CI: 0.33-2.35%) at Lag0-5; for O3 0.23% (95% CI: 0.12-0.35%) at Lag0 and 0.20% (95% CI: 0.05-0.34%) at Lag0-1. The effect sizes of PM2.5, NO2, and O3 remained significant after adjusting daily mean. Larger effect sizes were observed for PM2.5 and PM10 in cool season and for O3 in warm season. As significant exposure indicators of air pollution, peak-hour concentrations exposure increased the risk of IS hospital admissions among hypertension patients and it is worthy of consideration in relative environmental standard. It is suggested for hypertension patients to avoid outdoor activity during peak hours. More relevant searches are required to further illustrate air pollutant's effect on chronic disease population.
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Affiliation(s)
- Zemeng Zhao
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Moning Guo
- Beijing Municipal Commission of Health and Family Planning Information Center, Beijing, 100034, China
| | - Ji An
- Department of Medical Engineering, Peking University Third Hospital, Beijing, 100191, China
| | - Licheng Zhang
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
- Beijing Cancer Hospital, Beijing, 100142, China
| | - Peng Tan
- Beijing Municipal Commission of Health and Family Planning Information Center, Beijing, 100034, China
| | - Xue Tian
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Yuhan Zhao
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Lulu Liu
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Xiaonan Wang
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Xiangtong Liu
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Xiuhua Guo
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China
| | - Yanxia Luo
- School of Public Health, Capital Medical University, No.10 Xitoutiao, You'anmen Wai, Fengtai District, Beijing, 100069, China.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, 100069, China.
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Lin H, Long Y, Su Y, Song K, Li C, Ding N. Air pollution and hospital admissions for critical illness in emergency department: a tertiary-center research in Changsha, China, 2016-2020. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:21440-21450. [PMID: 34761317 DOI: 10.1007/s11356-021-17295-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 10/27/2021] [Indexed: 06/13/2023]
Abstract
We aimed to comprehensively investigate the associations of air pollutants with hospital admissions for critical illness in ED. Patients with critical illness including level 1 and level 2 of the Emergency Severity Index admitted in ED of Changsha Central Hospital from January 2016 to December 2020 were enrolled. Meteorological and air pollutants data source were collected from the National Meteorological Science Data Center. A Poisson generalized linear regression combined with a polynomial distributed lag model (PDLM) was utilized to explore the effect of air pollution on hospital admissions for critical illness in ED. Benchmarks as references (25th) were conducted for comparisons with high levels of pollutant concentrations (75th). At first, lagged effects of all different air pollutants were analyzed. Then, based on the most significant factor, analyses in subgroups were performed by gender (male and female), age (< 45, 45-65, and > 65), disorders (cardiovascular, neurological, respiratory), and seasons (spring, summer, autumn, and winter). A total of 47,290 patients with critical illness admitted in ED were included. The effects of air pollutants (PM2.5, PM10, SO2, NO2, O3 and CO) on critical illness ED visits were statistically significant. Strong collinearity between PM2.5 and PM10 (r = 0.862) was found. Both single-day lag and cumulative-day lag day models showed that PM2.5 had the strongest effects (lag 0, RR = 1.025, 95% CI 1.008-1.043, and lag 0-14, RR = 1.067, 95% CI 1.017-1.120, respectively). In both PM2.5 and PM10, the risks of critical illness in male, > 65 ages, respiratory diseases, and winter increased the most significant. Air pollutants, especially PM2.5 and PM10 exposure, could increase the risk of critical illness admission.
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Affiliation(s)
- Hang Lin
- Department of Emergency Medicine, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, NO. 161 Shaoshan South Road, Changsha, Hunan, 410004, China
| | - Yong Long
- Department of Emergency Medicine, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, NO. 161 Shaoshan South Road, Changsha, Hunan, 410004, China
| | - Yingjie Su
- Department of Emergency Medicine, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, NO. 161 Shaoshan South Road, Changsha, Hunan, 410004, China
| | - Kun Song
- Department of Emergency Medicine, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, NO. 161 Shaoshan South Road, Changsha, Hunan, 410004, China
| | - Changluo Li
- Department of Emergency Medicine, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, NO. 161 Shaoshan South Road, Changsha, Hunan, 410004, China
| | - Ning Ding
- Department of Emergency Medicine, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, NO. 161 Shaoshan South Road, Changsha, Hunan, 410004, China.
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Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China. Int J Hypertens 2022; 2022:7413115. [PMID: 35223092 PMCID: PMC8872648 DOI: 10.1155/2022/7413115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 12/14/2021] [Accepted: 01/10/2022] [Indexed: 11/17/2022] Open
Abstract
Fine particulate matter (PM2.5) and respirable particulate matter (PM10) are two major air pollutants with toxic effects on the cardiovascular system. Hypertension, as a chronic noncommunicable cardiovascular disease, is also a risk factor for several diseases. We applied generalized linear models with a quasi-Poisson link to assess the effect of air pollution exposure on the number of daily admissions for patients with hypertension. In addition, we established a two-pollutant model to evaluate PM2.5 and PM10 hazard effect stability by adjusting the other gaseous pollutants. Results showed that during the study period, 24 h mean concentrations of ambient PM2.5 and PM10 at 38.17 and 59.84 μg/m3, respectively, and a total of 2,611 hypertension hospital admissions were recorded. Air pollution concentrations significantly affected the number of hospitalizations for hypertension approximately 2 months after exposure. For each 10 μg/m3 increase in PM2.5 and PM10 in single-pollutant models, the number of hospitalizations for hypertension increased by 7.92% (95% CI: 5.48% to 10.42%) and 4.46% (95% CI: 2.86% to 5.65%), respectively, at the lag day with the strongest effect. NO2, O3, CO, and SO2 had different significant effects on the number of hospitalizations over the same time period, and PM2.5 and PM10 still showed robust significant effects after adjustment of gas pollutants through a two-pollutant model. These findings may contribute to a better understanding of the health effects of ambient particulate matter.
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Chen H, Cheng Z, Li M, Luo P, Duan Y, Fan J, Xu Y, Pu K, Zhou L. Ambient Air Pollution and Hospitalizations for Ischemic Stroke: A Time Series Analysis Using a Distributed Lag Nonlinear Model in Chongqing, China. Front Public Health 2022; 9:762597. [PMID: 35118040 PMCID: PMC8804166 DOI: 10.3389/fpubh.2021.762597] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 12/02/2021] [Indexed: 01/11/2023] Open
Abstract
Short-term exposure to air pollution has been associated with ischemic stroke (IS) hospitalizations, but the evidence of its effects on IS in low- and middle-income countries is limited and inconsistent. We aimed to quantitatively estimate the association between air pollution and hospitalizations for IS in Chongqing, China. This time series study included 2,299 inpatients with IS from three hospitals in Chongqing from January 2015 to December 2016. Generalized linear regression models combined with a distributed lag nonlinear model (DLNM) were used to investigate the impact of air pollution on IS hospitalizations. Stratification analysis was further implemented by sex, age, and season. The maximum lag-specific and cumulative percentage changes of IS were 1.2% (95% CI: 0.4–2.1%, lag 3 day) and 3.6% (95% CI: 0.5–6.7%, lag 05 day) for each 10 μg/m3 increase in PM2.5; 1.0% (95% CI: 0.3–1.7%, lag 3 day) and 2.9% (95% CI: 0.6–5.2%, lag 05 day) for each 10 μg/m3 increase in PM10; 4.8% (95% CI: 0.1–9.7%, lag 4 day) for each 10 μg/m3 increase in SO2; 2.5% (95% CI: 0.3–4.7%, lag 3 day) and 8.2% (95% CI: 0.9–16.0%, lag 05 day) for each 10 μg/m3 increase in NO2; 0.7% (95% CI: 0.0–1.5%, lag 6 day) for each 10 μg/m3 increase in O3. No effect modifications were detected for sex, age, and season. Our findings suggest that short-term exposure to PM2.5, PM10, SO2, NO2, and O3 contributes to more IS hospitalizations, which warrant the government to take effective actions in addressing air pollution issues.
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Affiliation(s)
- Hao Chen
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Zheng Cheng
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Mengmeng Li
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Pan Luo
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Yong Duan
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Jie Fan
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Ying Xu
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Kexue Pu
- College of Medical Informatics, Chongqing Medical University, Chongqing, China
| | - Li Zhou
- Department of Epidemiology, School of Public Health and Management, Chongqing Medical University, Chongqing, China
- *Correspondence: Li Zhou
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