1
|
Poniedziałek B, Rzymski P, Zarębska-Michaluk D, Flisiak R. Viral respiratory infections and air pollution: A review focused on research in Poland. CHEMOSPHERE 2024; 359:142256. [PMID: 38723686 DOI: 10.1016/j.chemosphere.2024.142256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 05/02/2024] [Accepted: 05/04/2024] [Indexed: 05/14/2024]
Abstract
The COVID-19 pandemic has reinforced an interest in the relationship between air pollution and respiratory viral infections, indicating that their burden can be increased under poor air quality. This paper reviews the pathways through which air pollutants can enhance susceptibility to such infections and aggravate their clinical course and outcome. It also summarizes the research exploring the links between various viral infections and exposure to solid and gaseous pollution in Poland, a region characterized by poor air quality, especially during a heating season. The majority of studies focused on concentrations of particulate matter (PM; 86.7%); the other pollutants, i.e., BaP, benzene, CO, NOx, O3, and SO2, were studied less often and sometimes only in the context of a particular infection type. Most research concerned COVID-19, showing that elevated levels of PM and NO2 correlated with higher morbidity and mortality, while increased PM2.5 and benzo[a]pyrene levels were related to worse clinical course and outcome in hospitalized, regardless of age and dominant SARS-CoV-2 variant. PM10 and PM2.5 levels were also associated with the incidence of influenza-like illness and, along with NO2 concentrations, with a higher rate of children's hospitalizations due to lower respiratory tract RSV infections. Higher levels of air pollutants also increased hospitalization due to bronchitis (PM, NOx, and O3) and emergency department admission due to viral croup (PM10, PM2.5, NOx, CO, and benzene). Although the conducted studies imply only correlations and have other limitations, as discussed in the present paper, it appears that improving air quality through reducing combustion processes in energy production in Poland should be perceived as a part of multilayered protection measures against respiratory viral infections, decreasing the healthcare costs of COVID-19, lower tract RSV infections, influenza, and other respiratory viral diseases prevalent between autumn and early spring, in addition to other health and climate benefits.
Collapse
Affiliation(s)
- Barbara Poniedziałek
- Department of Environmental Medicine, Poznan University of Medical Sciences, Poznań, Poland.
| | - Piotr Rzymski
- Department of Environmental Medicine, Poznan University of Medical Sciences, Poznań, Poland.
| | | | - Robert Flisiak
- Department of Infectious Diseases and Hepatology, Medical University of Białystok, Białystok, Poland.
| |
Collapse
|
2
|
Zhang Y, Li J, Wu C, Xiao Y, Wang X, Wang Y, Chen L, Ren L, Wang J. Impacts of environmental factors on the aetiological diagnosis and disease severity of community-acquired pneumonia in China: a multicentre, hospital-based, observational study. Epidemiol Infect 2024; 152:e80. [PMID: 38721832 PMCID: PMC11131030 DOI: 10.1017/s0950268824000700] [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: 01/03/2024] [Revised: 04/15/2024] [Accepted: 04/23/2024] [Indexed: 05/25/2024] Open
Abstract
Environmental exposures are known to be associated with pathogen transmission and immune impairment, but the association of exposures with aetiology and severity of community-acquired pneumonia (CAP) are unclear. A retrospective observational study was conducted at nine hospitals in eight provinces in China from 2014 to 2019. CAP patients were recruited according to inclusion criteria, and respiratory samples were screened for 33 respiratory pathogens using molecular test methods. Sociodemographic, environmental and clinical factors were used to analyze the association with pathogen detection and disease severity by logistic regression models combined with distributed lag nonlinear models. A total of 3323 CAP patients were included, with 709 (21.3%) having severe illness. 2064 (62.1%) patients were positive for at least one pathogen. More severe patients were found in positive group. After adjusting for confounders, particulate matter (PM) 2.5 and 8-h ozone (O3-8h) were significant association at specific lag periods with detection of influenza viruses and Klebsiella pneumoniae respectively. PM10 and carbon monoxide (CO) showed cumulative effect with severe CAP. Pollutants exposures, especially PM, O3-8h, and CO should be considered in pathogen detection and severity of CAP to improve the clinical aetiological and disease severity diagnosis.
Collapse
Affiliation(s)
- Yichunzi Zhang
- National Health Commission Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiang Li
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chao Wu
- National Health Commission Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yan Xiao
- National Health Commission Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xinming Wang
- National Health Commission Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ying Wang
- National Health Commission Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lan Chen
- National Health Commission Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lili Ren
- National Health Commission Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Key Laboratory of Pathogen Infection Prevention and Control (Ministry of Education), State Key Laboratory of Respiratory Health and Multimorbidity, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianwei Wang
- National Health Commission Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, National Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| |
Collapse
|
3
|
Hong JY, Bang T, Kim SB, Hong M, Jung J. Atmosphere particulate matter and respiratory diseases during COVID-19 in Korea. Sci Rep 2024; 14:10074. [PMID: 38698010 PMCID: PMC11066041 DOI: 10.1038/s41598-024-59643-x] [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: 11/06/2023] [Accepted: 04/12/2024] [Indexed: 05/05/2024] Open
Abstract
We aimed to examine the impact of COVID-19 non-pharmaceutical interventions (NPIs) on the relationship between air pollutants and hospital admissions for respiratory and non-respiratory diseases in six metropolitan cities in South Korea. This study compared the associations between particulate matter (PM10 and PM2.5) and hospital admission for respiratory and non-respiratory diseases before (2016-2019) and during (2020) the implementation of COVID-19 NPIs by using distributed lag non-linear models. In the Pre-COVID-19 period, the association between PM10 and admission risk for asthma and COPD showed an inverted U-shaped pattern. For PM2.5, S-shaped and inverted U-shaped changes were observed in asthma and COPD, respectively. Extremely high and low levels of PM10 and extremely low levels of PM2.5 significantly decreased the risk of admission for asthma and COPD. In the Post-COVID-19 outbreak period, the overall cumulative relationship between PM10 and PM2.5 and respiratory diseases and the effects of extreme levels of PM10 and PM2.5 on respiratory diseases were completely changed. For non-respiratory diseases, PM10 and PM2.5 were statistically insignificant for admission risk during both periods. Our study may provide evidence that implementing NPIs and reducing PM10 and PM2.5 exposure during the COVID-19 pandemic has contributed to reducing hospital admissions for environment-based respiratory diseases.
Collapse
Affiliation(s)
- Ji Young Hong
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Chuncheon Sacred Heart Hospital, Hallym University Medical Center, Chuncheon-si, Gangwon-do, 24253, Republic of Korea
| | - Taemo Bang
- AI Product Team, Gmarket, Seoul, Republic of Korea
| | - Sun Bean Kim
- Department of Internal Medicine, Division of Infectious Diseases, Korea University College of Medicine, Seoul, Republic of Korea
| | - Minwoo Hong
- Department of Preventive Medicine, Gachon University College of Medicine, 38-13, Dokjeom-ro 3beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea
| | - Jaehun Jung
- Department of Preventive Medicine, Gachon University College of Medicine, 38-13, Dokjeom-ro 3beon-gil, Namdong-gu, Incheon, 21565, Republic of Korea.
- Artificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea.
| |
Collapse
|
4
|
Roudreo B, Puangthongthub S. Alleviation of PM2.5-associated Risk of Daily Influenza Hospitalization by COVID-19 Lockdown Measures: A Time-series Study in Northeastern Thailand. J Prev Med Public Health 2024; 57:108-119. [PMID: 38374709 PMCID: PMC10999304 DOI: 10.3961/jpmph.23.349] [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: 08/04/2023] [Revised: 11/29/2023] [Accepted: 12/13/2023] [Indexed: 02/21/2024] Open
Abstract
OBJECTIVES Abrupt changes in air pollution levels associated with the coronavirus disease 2019 (COVID-19) outbreak present a unique opportunity to evaluate the effects of air pollution on influenza risk, at a time when emission sources were less active and personal hygiene practices were more rigorous. METHODS This time-series study examined the relationship between influenza cases (n=22 874) and air pollutant concentrations from 2018 to 2021, comparing the timeframes before and during the COVID-19 pandemic in and around Thailand's Khon Kaen province. Poisson generalized additive modeling was employed to estimate the relative risk of hospitalization for influenza associated with air pollutant levels. RESULTS Before the COVID-19 outbreak, both the average daily number of influenza hospitalizations and particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) concentration exceeded those later observed during the pandemic (p<0.001). In single-pollutant models, a 10 μg/m3 increase in PM2.5 before COVID-19 was significantly associated with increased influenza risk upon exposure to cumulative-day lags, specifically lags 0-5 and 0-6 (p<0.01). After adjustment for co-pollutants, PM2.5 demonstrated the strongest effects at lags 0 and 4, with elevated risk found across all cumulative-day lags (0-1, 0-2, 0-3, 0-4, 0-5, and 0-6) and significantly greater risk in the winter and summer at lag 0-5 (p<0.01). However, the PM2.5 level was not significantly associated with influenza risk during the COVID-19 outbreak. CONCLUSIONS Lockdown measures implemented during the COVID-19 pandemic could mitigate the risk of PM2.5-induced influenza. Effective regulatory actions in the context of COVID-19 may decrease PM2.5 emissions and improve hygiene practices, thereby reducing influenza hospitalizations.
Collapse
Affiliation(s)
- Benjawan Roudreo
- Industrial Toxicology and Risk Assessment Graduate Program, Department of Environmental Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailand
- Department of Disease Control, Ministry of Public Health, Nonthaburi, Thailand
| | - Sitthichok Puangthongthub
- Industrial Toxicology and Risk Assessment Graduate Program, Department of Environmental Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailand
| |
Collapse
|
5
|
Sun R, Tao J, Tang N, Chen Z, Guo X, Zou L, Zhou J. Air Pollution and Influenza: A Systematic Review and Meta-Analysis. IRANIAN JOURNAL OF PUBLIC HEALTH 2024; 53:1-11. [PMID: 38694869 PMCID: PMC11058381 DOI: 10.18502/ijph.v53i1.14678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 10/04/2023] [Indexed: 05/04/2024]
Abstract
Background Influenza is the first infectious disease that implements global monitoring and is one of the major public health issues in the world. Air pollutants have become an important global public health issue, in recent years, and much epidemiological and clinical evidence has shown that air pollutants are associated with respiratory diseases. Methods We comprehensively searched articles published up to 15 November 2022 in PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Database of Chinese sci-tech periodicals, and Wanfang Database. The search strategies were based on keyword combinations related to influenza and air pollutants. The air pollutants included particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3). Meta-analysis was performed using the R programming language (R4.2.1). Results A total of 2926 records were identified and 1220 duplicates were excluded. Finally, 19 studies were included in the meta-analysis according to inclusion and exclusion criteria. We observed a significant association between partial air pollutants (PM2.5, NO2, PM10 and SO2) and the incidence risk of influenza. The RRs were 1.0221 (95% CI: 1.0093~1.0352), 1.0395 (95% CI: 1.0131~1.0666), 1.007 (95% CI: 1.0009~1.0132), and 1.0352 (95% CI. 1.0076~1.0635), respectively. However, there was no significant relationship between CO and O3 exposure and influenza, and the RRs were 1.2272 (95% CI: 0.9253~1.6275) and 1.0045 (95% CI: 0.9930~1.0160), respectively. Conclusion Exposure to PM2.5, NO2, PM10, and SO2 was significantly associated with influenza, which may be risk factors for influenza. The association of CO and O3 with influenza needs further investigation.
Collapse
Affiliation(s)
- Rui Sun
- Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, 410013, Hunan, China
| | - Juan Tao
- Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, 410013, Hunan, China
| | - Na Tang
- Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, 410013, Hunan, China
| | - Zhijun Chen
- Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, 410013, Hunan, China
| | - Xiaowei Guo
- Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, 410013, Hunan, China
| | - Lianhong Zou
- Hunan Provincial People’s Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, Hunan 410013, P.R. China
| | - Junhua Zhou
- Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, Changsha, 410013, Hunan, China
| |
Collapse
|
6
|
Zhang R, Lai KY, Liu W, Liu Y, Ma X, Webster C, Luo L, Sarkar C. Associations between Short-Term Exposure to Ambient Air Pollution and Influenza: An Individual-Level Case-Crossover Study in Guangzhou, China. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:127009. [PMID: 38078424 PMCID: PMC10711742 DOI: 10.1289/ehp12145] [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: 10/12/2023] [Accepted: 10/27/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND Influenza imposes a heavy burden on public health. Little is known, however, of the associations between detailed measures of exposure to ambient air pollution and influenza at an individual level. OBJECTIVE We examined individual-level associations between six criteria air pollutants and influenza using case-crossover design. METHODS In this individual-level time-stratified case-crossover study, we linked influenza cases collected by the Guangzhou Center for Disease Control and Prevention from 1 January 2013 to 31 December 2019 with individual residence-level exposure to particulate matter (PM 2.5 and PM 10 ), sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), ozone (O 3 ) and carbon monoxide (CO). The exposures were estimated for the day of onset of influenza symptoms (lag 0), 1-7 d before the onset (lags 1-7), as well as an 8-d moving average (lag07), using a random forest model and linked to study participants' home addresses. Conditional logistic regression was developed to investigate the associations between short-term exposure to air pollution and influenza, adjusting for mean temperature, relative humidity, public holidays, population mobility, and community influenza susceptibility. RESULTS N = 108,479 eligible cases were identified in our study. Every 10 - μ g / m 3 increase in exposure to PM 2.5 , PM 10 , NO 2 , and CO and every 5 - μ g / m 3 increase in SO 2 over 8-d moving average (lag07) was associated with higher risk of influenza with a relative risk (RR) of 1.028 (95% CI: 1.018, 1.038), 1.041 (95% CI: 1.032, 1.049), 1.169 (95% CI: 1.151, 1.188), 1.004 (95% CI: 1.003, 1.006), and 1.134 (95% CI: 1.107, 1.163), respectively. There was a negative association between O 3 and influenza with a RR of 0.878 (95% CI: 0.866, 0.890). CONCLUSIONS Our findings suggest that short-term exposure to air pollution, except for O 3 , is associated with greater risk for influenza. Further studies are necessary to decipher underlying mechanisms and design preventive interventions and policies. https://doi.org/10.1289/EHP12145.
Collapse
Affiliation(s)
- Rong Zhang
- Healthy High Density Cities Lab, HKUrbanLab, University of Hong Kong (HKU), Hong Kong, China
- Department of Urban Planning and Design, HKU, Hong Kong, China
| | - Ka Yan Lai
- Healthy High Density Cities Lab, HKUrbanLab, University of Hong Kong (HKU), Hong Kong, China
- Department of Urban Planning and Design, HKU, Hong Kong, China
| | - Wenhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yanhui Liu
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Xiaowei Ma
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Chris Webster
- Healthy High Density Cities Lab, HKUrbanLab, University of Hong Kong (HKU), Hong Kong, China
- Department of Urban Planning and Design, HKU, Hong Kong, China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Chinmoy Sarkar
- Healthy High Density Cities Lab, HKUrbanLab, University of Hong Kong (HKU), Hong Kong, China
- Department of Urban Planning and Design, HKU, Hong Kong, China
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| |
Collapse
|
7
|
Zhang R, Li Y, Bi P, Wu S, Peng Z, Meng Y, Wang Y, Wang S, Huang Y, Liang J, Wu J. Seasonal associations between air pollutants and influenza in 10 cities of southern China. Int J Hyg Environ Health 2023; 252:114200. [PMID: 37329817 DOI: 10.1016/j.ijheh.2023.114200] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 05/20/2023] [Accepted: 06/05/2023] [Indexed: 06/19/2023]
Abstract
Few studies have explored the associations between air pollutants and influenza across seasons, especially at large scales. This study aimed to evaluate seasons' modifying effects on associations between air pollutants and influenza from 10 cities of southern China. Through scientific evidence, it provides mitigation and adaptation strategies with practical guidelines to local health authorities and environmental protection agencies. Daily influenza incidence, meteorological, and air pollutants data from 2016 to 2019 were collected. Quasi-Poisson regression with a distributed lag nonlinear model was used to evaluate city-specific air pollutants and influenza associations. Meta-analysis was used to pool site-specific estimates. Attributable fractions (AFs) of influenza incidence due to pollutants were calculated. Stratified analyses were conducted by season, sex, and age. Overall, the cumulative relative risk (CRR) of influenza incidence for a 10-unit increase in PM2.5, PM10, SO2, NO2, and CO was 1.45 (95% CI: 1.25, 1.68), 1.53 (95% CI: 1.29, 1.81), 1.87 (95% CI: 1.40, 2.48), 1.74 (95% CI: 1.49, 2.03), and 1.19 (95% CI: 1.04, 1.36), respectively. Children aged 0-17 were more sensitive to air pollutants in spring and winter. PM10 had greater effect on influenza than PM2.5 in autumn, winter, and overall, lesser in spring. The overall AF due to PM2.5, PM10, SO2, NO2, and CO was 4.46% (95% eCI: 2.43%, 6.43%), 5.03% (95% eCI: 2.33%, 7.56%), 5.36% (95% eCI: 3.12%, 7.58%), 24.88% (95% eCI: 18.02%, 31.67%), and 23.22% (95% eCI: 17.56%, 28.61%), respectively. AF due to O3 was 10.00% (95% eCI: 4.76%, 14.95%) and 3.65% (95% eCI: 0.50%, 6.59%) in spring and summer, respectively. The seasonal variations in the associations between air pollutants and influenza in southern China would provide evidence to service providers for tailored intervention, especially for vulnerable populations.
Collapse
Affiliation(s)
- Rui Zhang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yonghong Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Bi
- School of Public Health, The University of Adelaide, South Australia, Australia
| | - Siyuan Wu
- Sprott School of Business, Carleton University, Ottawa Ontario, Canada
| | - Zhibin Peng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yujie Meng
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yu Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Songwang Wang
- Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yushu Huang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Juan Liang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jing Wu
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; Chinese Center for Disease Control and Prevention, Beijing, China.
| |
Collapse
|
8
|
Lei J, Chen R, Liu C, Zhu Y, Xue X, Jiang Y, Shi S, Gao Y, Kan H, Xuan J. Fine and coarse particulate air pollution and hospital admissions for a wide range of respiratory diseases: a nationwide case-crossover study. Int J Epidemiol 2023; 52:715-726. [PMID: 37159523 DOI: 10.1093/ije/dyad056] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 04/20/2023] [Indexed: 05/11/2023] Open
Abstract
BACKGROUND The associations between fine and coarse particulate matter (PM2.5 and PM2.5-10) air pollution and hospital admissions for full-spectrum respiratory diseases were rarely investigated, especially for age-specific associations. We aim to estimate the age-specific associations of short-term exposures to PM2.5 and PM2.5-10 with hospital admissions for full-spectrum respiratory diseases in China. METHODS We conducted an individual-level case-crossover study based on a nationwide hospital-based registry including 153 hospitals across 20 provincial regions in China in 2013-20. We applied conditional logistic regression models and distributed lag models to estimate the exposure- and lag-response associations. RESULTS A total of 1 399 955 hospital admission records for various respiratory diseases were identified. The associations of PM2.5 and PM2.5-10 with total respiratory hospitalizations lasted for 4 days, and an interquartile range increase in PM2.5 (34.5 μg/m3) and PM2.5-10 (26.0 μg/m3) was associated with 1.73% [95% confidence interval (95% CI): 1.34%, 2.12%)] and 1.70% (95% CI: 1.31%, 2.10%) increases, respectively, in total respiratory hospitalizations over lag 0-4 days. Acute respiratory infections (i.e. pneumonia, bronchitis and bronchiolitis) were consistently associated with PM2.5 or PM2.5-10 exposure across different age groups. We found the disease spectrum varied by age, including rarely reported findings (i.e. acute laryngitis and tracheitis, and influenza) among children and well-established associations (i.e. chronic obstructive pulmonary disease, asthma, acute bronchitis and emphysema) among older populations. Besides, the associations were stronger in females, children and older populations. CONCLUSIONS This nationwide case-crossover study provides robust evidence that short-term exposure to both PM2.5 and PM2.5-10 was associated with increased hospital admissions for a wide range of respiratory diseases, and the spectra of respiratory diseases varied by age. Females, children and older populations were more susceptible.
Collapse
Affiliation(s)
- Jian Lei
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Renjie Chen
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Cong Liu
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yixiang Zhu
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Xiaowei Xue
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yixuan Jiang
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Su Shi
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Ya Gao
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Haidong Kan
- Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
- National Center for Children's Health, Children's Hospital of Fudan University, Shanghai, China
| | - Jianwei Xuan
- Health Economic Research Institute, School of Pharmacy, Sun Yat-Shen University, Guangzhou, China
| |
Collapse
|
9
|
Ma P, Zhou N, Wang X, Zhang Y, Tang X, Yang Y, Ma X, Wang S. Stronger susceptibilities to air pollutants of influenza A than B were identified in subtropical Shenzhen, China. ENVIRONMENTAL RESEARCH 2023; 219:115100. [PMID: 36565842 DOI: 10.1016/j.envres.2022.115100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/10/2022] [Accepted: 12/17/2022] [Indexed: 06/17/2023]
Abstract
Air pollution was indicated to be a key factor contributing to the aggressive spread of influenza viruses, whereas uncertainty still exists regarding to whether distinctions exist between influenza subtypes. Our study quantified the impact of five air pollutants on influenza subtype outbreaks in Shenzhen, China, a densely populated and highly urbanized megacity. Daily influenza outbreak data of laboratory-confirmed positive cases were obtained from the Shenzhen CDC, from May 1, 2013 to Dec 31, 2015. Concentrations of nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matters ≤2.5 μm (PM2.5), particulate matters ≤10 μm (PM10), and ozone (O3), were retrieved from the 18 national monitoring stations. The generalized additive model (GAM) and distributed lag non-linear model (DLNM) were used to calculate the concentration-response relationships between environmental inducers and outbreak epidemics, respectively for influenza A (Flu-A) and B (Flu-B). There were 1687 positive specimens were confirmed during the study period. The cold season was restricted from Nov. 4th to Apr. 20th, covering all seasons other than the long-lasting summer. Relatively heavy fine particle matter (PM2.5) and NO2 pollution was observed in cold months, with mean concentrations of 46.06 μg/m3 and 40.03 μg/m3, respectively. Time-series analysis indicated that high concentrations of NO2, PM2.5, PM10, and O3 were associated with more influenza outbreaks at short lag periods (0-5 d). Although more Flu-B (679 cases) epidemics occurred than Flu-A (382 cases) in the cold season, Flu-A generally showed higher susceptibility to air pollutants. A 10 μg/m3 increment in concentrations of PM2.5, PM10, and O3 at lag 04, was associated with a 2.103 (95%CI: 1.528-2.893), 1.618 (95%CI: 1.311-1.996), and 1.569 (95%CI: 1.214-2.028) of the relative risk (RR) of Flu-A, respectively. A 5 μg/m3 increase in NO2 was associated with higher risk of Flu-A at lag 03 (RR = 1.646, 95%CI: 1.295-2.092) and of Flu-B at lag 04 (RR = 1.319, 95%CI: 1.095-1.588). Nevertheless, barely significant effect of particulate matters (PM2.5, PM10) on Flu-B and SO2 on both subtypes was detected. Further, the effect estimates of NO2 increased for both subtypes when coexisting with other pollutants. This study provides evidence that declining concentrations of main pollutants including NO2, O3, and particulate matters, could substantially decrease influenza risk in subtropical Shenzhen, especially for influenza A.
Collapse
Affiliation(s)
- Pan Ma
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China; Chengdu Plain Urban Meteorology and Environment Scientific Observation and Research Station of Sichuan Province, Chengdu, 610225, Sichuan, China.
| | - Ning Zhou
- The First People's Hospital of Lanzhou, Lanzhou, 730050, Gansu, China.
| | - Xinzi Wang
- Meteorological Bureau of Jinnan District, Tianjin, 300350, China.
| | - Ying Zhang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China; Chengdu Plain Urban Meteorology and Environment Scientific Observation and Research Station of Sichuan Province, Chengdu, 610225, Sichuan, China.
| | - Xiaoxin Tang
- Shenzhen National Climate Observatory, Shenzhen, 518000, China.
| | - Yang Yang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China.
| | - Xiaolu Ma
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China.
| | - Shigong Wang
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, 610225, Sichuan, China.
| |
Collapse
|
10
|
Lian XY, Xi L, Zhang ZS, Yang LL, Du J, Cui Y, Li HJ, Zhang WX, Wang C, Liu B, Yang YN, Cui F, Lu QB. Impact of air pollutants on influenza-like illness outpatient visits under COVID-19 pandemic in the subcenter of Beijing, China. J Med Virol 2023; 95:e28514. [PMID: 36661040 DOI: 10.1002/jmv.28514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/13/2023] [Accepted: 01/16/2023] [Indexed: 01/21/2023]
Abstract
This study aimed to explore the association between air pollutants and outpatient visits for influenza-like illnesses (ILI) under the coronavirus disease 2019 (COVID-19) stage in the subcenter of Beijing. The data on ILI in the subcenter of Beijing from January 1, 2018 to December 31, 2020 were obtained from the Beijing Influenza Surveillance Network. A generalized additive Poisson model was applied to examine the associations between the concentrations of air pollutants and daily outpatient visits for ILI when controlling meteorological factors and temporal trend. A total of 171 943 ILI patients were included. In the pre-coronavirus disease 2019 (COVID-19) stage, an increased risk of ILI outpatient visits was associated to a high air quality index (AQI) and the high concentrations of particulate matter less than 2.5 (PM2.5 ), particulate matter 10 (PM10 ), sulphur dioxide (SO2 ), nitrogen dioxide (NO2 ), and carbon monoxide (CO), and a low concentration of ozone (O3 ) on lag0 day and lag1 day, while a higher increased risk of ILI outpatient visits was observed by the air pollutants in the COVID-19 stage on lag0 day. Except for PM10 , the concentrations of other air pollutants on lag1 day were not significantly associated with an increased risk of ILI outpatient visits during the COVID-19 stage. The findings that air pollutants had enhanced immediate effects and diminished lag-effects on the risk of ILI outpatient visits during the COVID-19 pandemic, which is important for the development of public health and environmental governance strategies.
Collapse
Affiliation(s)
- Xin Yao Lian
- Department of Laboratorial Science and Technology, Vaccine Research Center, School of Public Health, Peking University, Beijing, People's Republic of China
| | - Lu Xi
- Beijing Tongzhou Center for Diseases Prevention and Control, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Zhong Song Zhang
- Department of Laboratorial Science and Technology, Vaccine Research Center, School of Public Health, Peking University, Beijing, People's Republic of China
| | - Li Li Yang
- Beijing Tongzhou Center for Diseases Prevention and Control, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Juan Du
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Yan Cui
- Beijing Tongzhou Center for Diseases Prevention and Control, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Hong Jun Li
- Beijing Tongzhou Center for Diseases Prevention and Control, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Wan Xue Zhang
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Chao Wang
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Bei Liu
- Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Yan Na Yang
- Center for Disease Control and Prevention of Beijing Economic and Technological Development Area, Institute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing, People's Republic of China
| | - Fuqiang Cui
- Department of Laboratorial Science and Technology, Vaccine Research Center, School of Public Health, Peking University, Beijing, People's Republic of China.,Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| | - Qing Bin Lu
- Department of Laboratorial Science and Technology, Vaccine Research Center, School of Public Health, Peking University, Beijing, People's Republic of China.,Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, Beijing, People's Republic of China
| |
Collapse
|
11
|
Yin J, Liu T, Tang F, Chen D, Sun L, Song S, Zhang S, Wu J, Li Z, Xing W, Wang X, Ding G. Effects of ambient temperature on influenza-like illness: A multicity analysis in Shandong Province, China, 2014-2017. Front Public Health 2023; 10:1095436. [PMID: 36699880 PMCID: PMC9868675 DOI: 10.3389/fpubh.2022.1095436] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 12/12/2022] [Indexed: 01/11/2023] Open
Abstract
Background The associations between ambient temperature and influenza-like illness (ILI) have been investigated in previous studies. However, they have inconsistent results. The purpose of this study was to estimate the effect of ambient temperature on ILI in Shandong Province, China. Methods Weekly ILI surveillance and meteorological data over 2014-2017 of the Shandong Province were collected from the Shandong Center for Disease Control and Prevention and the China Meteorological Data Service Center, respectively. A distributed lag non-linear model was adopted to estimate the city-specific temperature-ILI relationships, which were used to pool the regional-level and provincial-level estimates through a multivariate meta-analysis. Results There were 911,743 ILI cases reported in the study area between 2014 and 2017. The risk of ILI increased with decreasing weekly ambient temperature at the provincial level, and the effect was statistically significant when the temperature was <-1.5°C (RR = 1.24, 95% CI: 1.00-1.54). We found that the relationship between temperature and ILI showed an L-shaped curve at the regional level, except for Southern Shandong (S-shaped). The risk of ILI was influenced by cold, with significant lags from 2.5 to 3 weeks, and no significant effect of heat on ILI was found. Conclusion Our findings confirm that low temperatures significantly increased the risk of ILI in the study area. In addition, the cold effect of ambient temperature may cause more risk of ILI than the hot effect. The findings have significant implications for developing strategies to control ILI and respond to climate change.
Collapse
Affiliation(s)
- Jia Yin
- Department of Epidemiology, School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China,Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Ti Liu
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Fang Tang
- Center for Big Data Research in Health and Medicine, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Dongzhen Chen
- Institute of Viral Disease Control and Prevention, Liaocheng Center for Disease Control and Prevention, Liaocheng, Shandong, China
| | - Lin Sun
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Shaoxia Song
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Shengyang Zhang
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Julong Wu
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Zhong Li
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Weijia Xing
- Department of Epidemiology, School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China,Weijia Xing ✉
| | - Xianjun Wang
- Institute for Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, Shandong, China,Xianjun Wang ✉
| | - Guoyong Ding
- Department of Epidemiology, School of Public Health, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China,*Correspondence: Guoyong Ding ✉
| |
Collapse
|
12
|
Wang X, Cai J, Liu X, Wang B, Yan L, Liu R, Nie Y, Wang Y, Zhang X, Zhang X. Impact of PM 2.5 and ozone on incidence of influenza in Shijiazhuang, China: a time-series study. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:10426-10443. [PMID: 36076137 PMCID: PMC9458314 DOI: 10.1007/s11356-022-22814-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 08/27/2022] [Indexed: 05/03/2023]
Abstract
Most of the studies are focused on influenza and meteorological factors for influenza. There are still few studies focused on the relationship between pollution factors and influenza, and the results are not consistent. This study conducted distributed lag nonlinear model and attributable risk on the relationship between influenza and pollution factors, aiming to quantify the association and provide a basis for the prevention of influenza and the formulation of relevant policies. Environmental data in Shijiazhuang from 2014 to 2019, as well as the data on hospital-confirmed influenza, were collected. When the concentration of PM2.5 was the highest (621 μg/m3), the relative risk was the highest (RR: 2.39, 95% CI: 1.10-5.17). For extremely high concentration PM2.5 (348 μg/m3), analysis of cumulative lag effect showed statistical significance from cumulative lag0-1 to lag0-6 day, and the minimum cumulative lag effect appeared in lag0-2 (RR: 0.760, 95% CI: 0.655-0.882). In terms of ozone, the RR value was 2.28(1.19,4.38), when O3 concentration was 310 μg/m3, and the RR was 1.65(1.26,2.15), when O3 concentration was 0 μg/m3. The RR of this lag effect increased with the increase of lag days, and reached the maximum at lag0-7 days, RR and 95% CI of slightly low concentration and extremely high concentration were 1.217(1.108,1.337) and 1.440(1.012,2.047), respectively. Stratified analysis showed that there was little difference in gender, but in different age groups, the cumulative lag effect of these two pollutants on influenza was significantly different. Our study found a non-linear relationship between two pollutants and influenza; slightly low concentrations were more associated with contaminant-related influenza. Health workers should encourage patients to get the influenza vaccine and wear masks when going out during flu seasons.
Collapse
Affiliation(s)
- Xue Wang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Jianning Cai
- The Department of Epidemic Treating and Preventing, Center for Disease Prevention and Control of Shijiazhuang City, Shijiazhuang, China
| | - Xuehui Liu
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Binhao Wang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Lina Yan
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Ran Liu
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Yaxiong Nie
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Yameng Wang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Xinzhu Zhang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China
| | - Xiaolin Zhang
- Department of Epidemiology and Statistics, School of Public Health, Hebei Medical University, Hebei Province Key Laboratory of Environment and Human Health, 361 Zhongshan East Road, Shijiazhuang, 050017, China.
| |
Collapse
|
13
|
Lu J, Wu K, Ma X, Wei J, Yuan Z, Huang Z, Fan W, Zhong Q, Huang Y, Wu X. Short-term effects of ambient particulate matter (PM 1, PM 2.5 and PM 10) on influenza-like illness in Guangzhou, China. Int J Hyg Environ Health 2023; 247:114074. [PMID: 36436470 DOI: 10.1016/j.ijheh.2022.114074] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 11/09/2022] [Accepted: 11/11/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Particulate matter (PM) has been linked to respiratory infections in a growing body of evidence. Studies on the relationship between ILI (influenza-like illness) and PM1 (particulate matter with aerodynamic diameter ≤1 μm) are, however, scarce. The purpose of this study was to investigate the effects of PM on ILI in Guangzhou, China. METHODS Daily ILI cases, air pollution records (PM1, PM2.5, PM10 and gaseous pollutants), and metrological data between 2014 and 2019 were gathered from Guangzhou, China. To estimate the risk of ILI linked with exposure to PM pollutants, a quasi-Poisson regression was used. Additionally, subgroup analyses stratified by gender, age and season were carried out. RESULTS For each 10 μg/m3 increase of PM1 and PM2.5 over the past two days (lag01), and PM10 over the past three days (lag02), the relative risks (RR) of ILI were 1.079 (95% confidence interval [CI]: 1.050, 1.109), 1.044 (95% CI: 1.027, 1.062) and 1.046 (95% CI: 1.032, 1.059), respectively. The estimated risks for men and women were substantially similar. The effects of PM pollutants between male and female were basically equivalent. People aged 15-24 years old were more susceptive to PM pollutants. CONCLUSIONS It implies that PM1, PM2.5 and PM10 are all risk factors for ILI, the health impacts of PM pollutants vary by particle size. Reducing the concentration of PM1 needs to be considered when generating a strategy to prevent ILI.
Collapse
Affiliation(s)
- Jianyun Lu
- Guangzhou Baiyun Center for Disease Control and Prevention, China
| | - Keyi Wu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Nos.1023-1063, Shatai South Road, Baiyun District, 510515, Guangzhou, China
| | - Xiaowei Ma
- Guangzhou Center for Disease Control and Prevention, Guangzhou City, 510440, Guangdong, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, 20740, USA
| | - Zelin Yuan
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Nos.1023-1063, Shatai South Road, Baiyun District, 510515, Guangzhou, China
| | - Zhiwei Huang
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Nos.1023-1063, Shatai South Road, Baiyun District, 510515, Guangzhou, China
| | - Weidong Fan
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Nos.1023-1063, Shatai South Road, Baiyun District, 510515, Guangzhou, China
| | - Qi Zhong
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Nos.1023-1063, Shatai South Road, Baiyun District, 510515, Guangzhou, China
| | - Yining Huang
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Nos.1023-1063, Shatai South Road, Baiyun District, 510515, Guangzhou, China
| | - Xianbo Wu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Nos.1023-1063, Shatai South Road, Baiyun District, 510515, Guangzhou, China.
| |
Collapse
|
14
|
Zhang Y, Wang S, Feng Z, Song Y. Influenza incidence and air pollution: Findings from a four-year surveillance study of prefecture-level cities in China. Front Public Health 2022; 10:1071229. [PMID: 36530677 PMCID: PMC9755172 DOI: 10.3389/fpubh.2022.1071229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 11/14/2022] [Indexed: 12/04/2022] Open
Abstract
Background Influenza is a serious public health problem, and its prevalence and spread show significant spatiotemporal characteristics. Previous studies have found that air pollutants are linked to an increased risk of influenza. However, the mechanism of influence and the degree of their association have not been determined. This study aimed to determine the influence of the air environment on the spatiotemporal distribution of influenza. Methods The kernel density estimation and Getis-Ord Gi * statistic were used to analyze the spatial distribution of the influenza incidence and air pollutants in China. A simple analysis of the correlation between influenza and air pollutants was performed using Spearman's correlation coefficients. A linear regression analysis was performed to examine changes in the influenza incidence in response to air pollutants. The sensitivity of the influenza incidence to changes in air pollutants was evaluated by performing a gray correlation analysis. Lastly, the entropy weight method was used to calculate the weight coefficient of each method and thus the comprehensive sensitivity of influenza incidence to six pollution elements. Results The results of the sensitivity analysis using Spearman's correlation coefficients showed the following ranking of the contributions of the air pollutants to the influenza incidence in descending order: SO2 >NO2 >CO> PM2.5 >O3 >PM10. The sensitivity results obtained from the linear regression analysis revealed the following ranking: CO>NO2 >SO2 >O3 >PM2.5 >PM10. Lastly, the sensitivity results obtained from the gray correlation analysis showed the following ranking: NO2 >CO>PM10 >PM2.5 >SO2 >O3. According to the sensitivity score, the study area can be divided into hypersensitive, medium-sensitive, and low-sensitive areas. Conclusion The influenza incidence showed a strong spatial correlation and associated sensitivity to changes in concentrations of air pollutants. Hypersensitive areas were mainly located in the southeastern part of northeastern China, the coastal areas of the Yellow River Basin, the Beijing-Tianjin-Hebei region and surrounding areas, and the Yangtze River Delta. The influenza incidence was most sensitive to CO, NO2, and SO2, with the occurrence of influenza being most likely in areas with elevated concentrations of these three pollutants. Therefore, the formulation of targeted influenza prevention and control strategies tailored for hypersensitive, medium-sensitive, low-sensitive, and insensitive areas are urgently needed.
Collapse
Affiliation(s)
- Yu Zhang
- School of Geographical Sciences, Northeast Normal University, Changchun, China
| | - Shijun Wang
- School of Geographical Sciences, Northeast Normal University, Changchun, China
- Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun, China
| | - Zhangxian Feng
- School of Geographical Sciences, Northeast Normal University, Changchun, China
- Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun, China
| | - Yang Song
- School of Geographical Sciences, Northeast Normal University, Changchun, China
- Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun, China
| |
Collapse
|
15
|
Álvaro-Meca A, Sepúlveda-Crespo D, Resino R, Ryan P, Martínez I, Resino S. Neighborhood environmental factors linked to hospitalizations of older people for viral lower respiratory tract infections in Spain: a case-crossover study. Environ Health 2022; 21:107. [PMID: 36348411 PMCID: PMC9640778 DOI: 10.1186/s12940-022-00928-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Lower respiratory tract viral infection (LRTI) is a significant cause of morbidity-mortality in older people worldwide. We analyzed the association between short-term exposure to environmental factors (climatic factors and outdoor air pollution) and hospital admissions with a viral LRTI diagnosis in older adults. METHODS We conducted a bidirectional case-crossover study in 6367 patients over 65 years of age with viral LRTI and residential zip code in the Spanish Minimum Basic Data Set. Spain's State Meteorological Agency was the source of environmental data. Associations were assessed using conditional logistic regression. P-values were corrected for false discovery rate (q-values). RESULTS Almost all were hospital emergency admissions (98.13%), 18.64% were admitted to the intensive care unit (ICU), and 7.44% died. The most frequent clinical discharge diagnosis was influenza (90.25%). LRTI hospital admissions were more frequent when there were lower values of temperature and O3 and higher values of relative humidity and NO2. The regression analysis adjusted by temperatures and relative humidity showed higher concentrations at the hospital admission for NO2 [compared to the lag time of 1-week (q-value< 0.001) and 2-weeks (q-value< 0.001)] and O3 [compared to the lag time of 3-days (q-value< 0.001), 1-week (q-value< 0.001), and 2-weeks (q-value< 0.001)] were related to a higher odds of hospital admissions due to viral LRTI. Moreover, higher concentrations of PM10 at the lag time of 1-week (q-value = 0.023) and 2-weeks (q-value = 0.002), and CO at the lag time of 3-days (q-value = 0.023), 1-week (q-value< 0.001) and 2-weeks (q-value< 0.001)], compared to the day of hospitalization, were related to a higher chances of hospital admissions with viral LRTI. CONCLUSION Unfavorable environmental factors (low temperatures, high relative humidity, and high concentrations of NO2, O3, PM10, and CO) increased the odds of hospital admissions with viral LRTI among older people, indicating they are potentially vulnerable to these environmental factors.
Collapse
Affiliation(s)
- Alejandro Álvaro-Meca
- Departamento de Medicina Preventiva y Salud Pública, Facultad de Ciencias de la Salud, Universidad Rey Juan Carlos, Alcorcón, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
| | - Daniel Sepúlveda-Crespo
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
- Unidad de Infección Viral e Inmunidad, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Majadahonda, Madrid, Spain
| | - Rosa Resino
- Departamento de Geografía, Facultad de Geografía e Historia, Universidad Complutense de Madrid, Madrid, Spain
| | - Pablo Ryan
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
- Hospital Universitario Infanta Leonor, Madrid, Spain
- Universidad Complutense de Madrid (UCM), Madrid, Spain
- Instituto de Investigaciones Sanitarias Gregorio Marañón (IiSGM), Madrid, Spain
| | - Isidoro Martínez
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
- Unidad de Infección Viral e Inmunidad, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Majadahonda, Madrid, Spain
| | - Salvador Resino
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.
- Unidad de Infección Viral e Inmunidad, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Majadahonda, Madrid, Spain.
| |
Collapse
|
16
|
Tateo F, Fiorino S, Peruzzo L, Zippi M, De Biase D, Lari F, Melucci D. Effects of environmental parameters and their interactions on the spreading of SARS-CoV-2 in North Italy under different social restrictions. A new approach based on multivariate analysis. ENVIRONMENTAL RESEARCH 2022; 210:112921. [PMID: 35150709 PMCID: PMC8828377 DOI: 10.1016/j.envres.2022.112921] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/13/2022] [Accepted: 02/06/2022] [Indexed: 02/07/2023]
Abstract
In 2020 North Italy suffered the SARS-CoV-2-related pandemic with a high number of deaths and hospitalization. The effect of atmospheric parameters on the amount of hospital admissions (temperature, solar radiation, particulate matter, relative humidity and wind speed) is studied through about 8 months (May-December). Two periods are considered depending on different conditions: a) low incidence of COVID-19 and very few regulations concerning personal mobility and protection ("free/summer period"); b) increasing incidence of disease, social restrictions and use of personal protections ("confined/autumn period"). The "hospitalized people in medical area wards/100000 residents" was used as a reliable measure of COVID-19 spreading and load on the sanitary system. We developed a chemometric approach (multiple linear regression analysis) using the daily incidence of hospitalizations as a function of the single independent variables and of their products (interactions). Eight administrative domains were considered (altogether 26 million inhabitants) to account for relatively homogeneous territorial and social conditions. The obtained models very significantly match the daily variation of hospitalizations, during the two periods. Under the confined/autumn period, the effect of non-pharmacologic measures (social distances, personal protection, etc.) possibly attenuates the virus diffusion despite environmental factors. On the contrary, in the free/summer conditions the effects of atmospheric parameters are very significant through all the areas. Particulate matter matches the growth of hospitalizations in areas with low chronic particulate pollution. Fewer hospitalizations strongly correspond to higher temperature and solar radiation. Relative humidity plays the same role, but with a lesser extent. The interaction between solar radiation and high temperature is also highly significant and represents surprising evidence. The solar radiation alone and combined with high temperature exert an anti-SARS-CoV-2 effect, via both the direct inactivation of virions and the stimulation of vitamin D synthesis, improving immune system function.
Collapse
Affiliation(s)
- Fabio Tateo
- Institute of Geosciences and Earth Resources (IGG), National Research Council of Italy (CNR), Via G. Gradenigo, 6, 35131, Padova, Italy
| | - Sirio Fiorino
- Internal Medicine Unit, Budrio Hospital, Azienda USL, Via Benni, 44, 40054, Bologna, Italy
| | - Luca Peruzzo
- Institute of Geosciences and Earth Resources (IGG), National Research Council of Italy (CNR), Via G. Gradenigo, 6, 35131, Padova, Italy.
| | - Maddalena Zippi
- Unit of Gastroenterology and Digestive Endoscopy, Sandro Pertini Hospital, Via dei Monti Tiburtini 385, 00157, Rome, Italy
| | - Dario De Biase
- Department of Pharmacy and Biotechnology, University of Bologna, Via Belmeloro 6, 40126, Bologna, Italy
| | - Federico Lari
- Internal Medicine Unit, Budrio Hospital, Azienda USL, Via Benni, 44, 40054, Bologna, Italy
| | - Dora Melucci
- Department of Chemistry Ciamician, University of Bologna, Via Selmi, 2, 40126, Bologna, Italy
| |
Collapse
|
17
|
Ren FR, Abodurezhake Y, Cui Z, Zhang M, Wang YY, Zhang XR, Lu YQ. Effects of Meteorological Factors and Atmospheric Pollution on Hand, Foot, and Mouth Disease in Urumqi Region. Front Public Health 2022; 10:913169. [PMID: 35812470 PMCID: PMC9257078 DOI: 10.3389/fpubh.2022.913169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 05/16/2022] [Indexed: 11/13/2022] Open
Abstract
Background Hand, foot, and mouth disease (HFMD) is a febrile rash infection caused by enteroviruses, spreading mainly via the respiratory tract and close contact. In the past two decades, HFMD has been prevalent mainly in Asia, including China and South Korea, causing a huge disease burden and putting the lives and health of children at risk. Therefore, a further study of the factors influencing HFMD incidences has far-reaching implications. In existing studies, the environmental factors affecting such incidences are mainly divided into two categories: meteorological and air. Among these studies, the former are the majority of studies on HFMD. Some scholars have studied both factors at the same, but the number is not large and the findings are quite different. Methods We collect monthly cases of HFMD in children, meteorological factors and atmospheric pollution in Urumqi from 2014 to 2020. Trend plots are used to understand the approximate trends between meteorological factors, atmospheric pollution and the number of HFMD cases. The association between meteorological factors, atmospheric pollution and the incidence of HFMD in the Urumqi region of northwest China is then investigated using multiple regression models. Results A total of 16,168 cases in children are included in this study. According to trend plots, the incidence of HFMD shows a clear seasonal pattern, with O3 (ug/m3) and temperature (°C) showing approximately the same trend as the number of HFMD cases, while AQI, PM2.5 (ug/m3), PM10 (ug/m3) and NO2 (ug/m3) all show approximately opposite trends to the number of HFMD cases. Based on multiple regression results, O3 (P = 0.001) and average station pressure (P = 0.037) are significantly and negatively associated with HFMD incidences, while SO2 (P = 0.102), average dew point temperature (P = 0.072), hail (P = 0.077), and thunder (P = 0.14) have weak significant relationships with them.
Collapse
Affiliation(s)
- Fang-rong Ren
- College of Economics and Management, Nanjing Forestry University, Nanjing, China
| | | | - Zhe Cui
- Economics and Management School, Nantong University, Nantong, China
| | - Miao Zhang
- Economics and Management School, Nantong University, Nantong, China
| | - Yu-yu Wang
- Economics and Management School, Nantong University, Nantong, China
| | - Xue-rong Zhang
- Economics and Management School, Nantong University, Nantong, China
| | - Yao-qin Lu
- Department of Infectious Disease Control, Urumqi Center for Disease Control and Prevention, Ürümqi, China
| |
Collapse
|
18
|
Ishmatov A. "SARS-CoV-2 is transmitted by particulate air pollution": Misinterpretations of statistical data, skewed citation practices, and misuse of specific terminology spreading the misconception. ENVIRONMENTAL RESEARCH 2022; 204:112116. [PMID: 34562486 PMCID: PMC8489301 DOI: 10.1016/j.envres.2021.112116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/14/2021] [Accepted: 09/21/2021] [Indexed: 05/03/2023]
Abstract
In epidemiology, there are still outdated myths associated with the spread of respiratory infections. Recently, we have witnessed the origination of a new misconception, to the effect that SARS-CoV-2 is transmitted in the open air by way of particulate air pollution (atmospheric particulate matter (PM)). There is no evidence to support the idea behind this misconception. Nevertheless, more and more people are involved in animated debate and the number of studies concerning atmospheric PM as a carrier of SARS-CoV-2 is growing rapidly. In this work, the origin of the misconception was investigated, and the published papers which have contributed to the spread of this myth were analyzed. The results show that the following factors lie behind the origin and spread of the misconception: a) The specific terminology is not always clearly defined or consistently used by scientists. In particular, the terms 'particulate matter', 'atmospheric aerosol particles', 'air pollutants', and 'atmospheric aerosols' need to be clarified, and besides they are often equated to 'infectious aerosols', 'virus-bearing aerosols', 'bio-aerosols', 'virus-laden particles', 'respiratory aerosol/droplets', and 'droplet nuclei'. b) Authors misinterpret statistical data and information from other sources. Interpretation of the correlation between PM levels and the increasing incidence and severity of COVID-19 infection, is often changed from "PM may reflect the indirect action of certain atmospheric conditions that maintain infectious nuclei suspended for prolonged periods, parameters that also act on atmospheric pollutants" to "PM could cause an increase in infectious droplets/aerosols containing SARS-CoV-2." This is a dramatic change to the meaning. Moreover, it is often not taken into account that PM may reflect activities in areas with high population density and this population density at the same time contributes to the spread COVID-19. c) Skewed citation practices. Many authors cite a hypothetical conclusion from an original study, then other authors cite the papers of these authors as primary sources. This practice leads to the effect that there are many witnesses to a 'phenomenon' that did not ever occur. Thus, the terminology used in interdisciplinary communications should be more nuanced and defined precisely. Authors should be more careful when citing unconfirmed data (and hypotheses) as well as in interpreting statistical data so as to avoid confusion and spreading false information. This is especially important now in the era of the COVID-19 pandemic.
Collapse
Affiliation(s)
- Alexander Ishmatov
- Research Institute of Experimental and Clinical Medicine, Timakova St., Bild. 2., Novosibirsk, 630117, Russian Federation; Kazan Federal University, Kremlyovskaya St. 18, Kazan, 420008, Russian Federation; Togliatti State University, Belorusskaya St. 14, Togliatti, 445020, Russian Federation.
| |
Collapse
|
19
|
Nazar W, Niedoszytko M. Air Pollution in Poland: A 2022 Narrative Review with Focus on Respiratory Diseases. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19020895. [PMID: 35055718 PMCID: PMC8775633 DOI: 10.3390/ijerph19020895] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 01/11/2022] [Accepted: 01/13/2022] [Indexed: 01/23/2023]
Abstract
According to the World Bank Group, 36 of the 50 most polluted cities in the European Union are in Poland. Thus, ambient air pollution and its detrimental health effects are a matter of immense importance in Poland. This narrative review aims to analyse current findings on air pollution and health in Poland, with a focus on respiratory diseases, including COVID-19, as well as the Poles’ awareness of air pollution. PubMed, Scopus and Google Scholar databases were searched. In total, results from 71 research papers were summarized qualitatively. In Poland, increased air pollution levels are linked to increased general and respiratory disease mortality rates, higher prevalence of respiratory diseases, including asthma, lung cancer and COVID-19 infections, reduced forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). The proximity of high traffic areas exacerbates respiratory health problems. People living in more polluted regions (south of Poland) and in the winter season have a higher level of air pollution awareness. There is an urgent need to reduce air pollution levels and increase public awareness of this threat. A larger number of multi-city studies are needed in Poland to consistently track the burden of diseases attributable to air pollution.
Collapse
Affiliation(s)
- Wojciech Nazar
- Faculty of Medicine, Medical University of Gdańsk, Marii Skłodowskiej-Curie 3a, 80-210 Gdańsk, Poland
- Correspondence: ; Tel.: +48-530-087-968
| | - Marek Niedoszytko
- Department of Allergology, Medical University of Gdańsk, Smoluchowskiego 17, 80-214 Gdańsk, Poland;
| |
Collapse
|