1
|
Lin Y, Meng H, He Y, Liang W, Niu Y, Liu Z, Wang Z, Tian Y, Chang S. Short-term effects of air pollution on the infectious disease spectrum in Shanghai, China: a time-series analysis from 2013 to 2019. Front Public Health 2025; 13:1454809. [PMID: 39957988 PMCID: PMC11825447 DOI: 10.3389/fpubh.2025.1454809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Accepted: 01/14/2025] [Indexed: 02/18/2025] Open
Abstract
Background Epidemiological evidence on the effects of air pollution on infectious diseases remains inconsistent, highlighting the need for further research and analysis. We aimed to investigate the relationship between exposure to fine particulate matter (PM2.5) and ozone (O3) and the risk of national notifiable infectious diseases in Shanghai, a megacity in China. Methods A double-pollutant model was used for each air pollutant, utilizing time-series analysis to separately apply single and distributed lag models (DLMs) to assess the exposure-lag-response relationship for 43 national notifiable infectious diseases (NNIDs) from 2013 to 2019. The model was adjusted for seasonality, long-term trends, mean temperature, relative humidity, and other air pollutants. Analysis was further conducted for seven NNID categories (vaccine-preventable; bacterial; gastrointestinal and enterovirus; sexually transmitted and bloodborne; vector-borne; zoonotic; and quarantinable diseases) as well as specific diseases. Results The study included 661,267 NNID cases and found that PM2.5 and O3 exposures were associated with increased NNID risks, although not within the same categories. A 10 μg/m3 increase in O3 was associated with a higher risk of total NNIDs (relative risk [RR] at lag 1 month: 1.29, 95% confidence interval [CI]: 1.02-1.65), vaccine-preventable diseases (RR at lag 1 month: 1.75, 95% CI: 1.02-3.01), and sexually transmitted and bloodborne diseases (RR at lag 2 month: 1.12, 95% CI: 1.00-1.26). However, the association with PM2.5 remained inconclusive. Conclusion These findings suggest a potential link between ambient air pollution exposure and the risk of infectious diseases, highlighting the urgent need for a comprehensive understanding of the relationship between air pollution and notifiable infectious diseases, as well as an in-depth evaluation of disparities across the disease spectrum.
Collapse
Affiliation(s)
- Yihan Lin
- Department of Histology and Embryology, College of Basic Medical, Hebei Medical University, Shijiazhuang, China
| | - Hao Meng
- Department of Pathogenic Biology, College of Basic Medicine, Hebei Medical University, Shijiazhuang, China
| | - Yong He
- Department of Pathogenic Biology, College of Basic Medicine, Hebei Medical University, Shijiazhuang, China
| | - Wenzhuo Liang
- Department of Histology and Embryology, College of Basic Medical, Hebei Medical University, Shijiazhuang, China
| | - Yiran Niu
- Department of Histology and Embryology, College of Basic Medical, Hebei Medical University, Shijiazhuang, China
| | - Zhenliang Liu
- Department of Histology and Embryology, College of Basic Medical, Hebei Medical University, Shijiazhuang, China
| | - Ziying Wang
- Department of Pathogenic Biology, College of Basic Medicine, Hebei Medical University, Shijiazhuang, China
| | - Yangyang Tian
- Department of Histology and Embryology, College of Basic Medical, Hebei Medical University, Shijiazhuang, China
| | - Shiyang Chang
- Department of Histology and Embryology, College of Basic Medical, Hebei Medical University, Shijiazhuang, China
| |
Collapse
|
2
|
Schwarz M, Peters A, Stafoggia M, de'Donato F, Sera F, Bell ML, Guo Y, Honda Y, Huber V, Jaakkola JJK, Urban A, Vicedo-Cabrera AM, Masselot P, Lavigne E, Achilleos S, Kyselý J, Samoli E, Hashizume M, Fook Sheng Ng C, das Neves Pereira da Silva S, Madureira J, Garland RM, Tobias A, Armstrong B, Schwartz J, Gasparrini A, Schneider A, Breitner S. Temporal variations in the short-term effects of ambient air pollution on cardiovascular and respiratory mortality: a pooled analysis of 380 urban areas over a 22-year period. Lancet Planet Health 2024; 8:e657-e665. [PMID: 39243781 DOI: 10.1016/s2542-5196(24)00168-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 07/17/2024] [Accepted: 07/18/2024] [Indexed: 09/09/2024]
Abstract
BACKGROUND Ambient air pollution, including particulate matter (such as PM10 and PM2·5) and nitrogen dioxide (NO2), has been linked to increases in mortality. Whether populations' vulnerability to these pollutants has changed over time is unclear, and studies on this topic do not include multicountry analysis. We evaluated whether changes in exposure to air pollutants were associated with changes in mortality effect estimates over time. METHODS We extracted cause-specific mortality and air pollution data collected between 1995 and 2016 from the Multi-Country Multi-City (MCC) Collaborative Research Network database. We applied a two-stage approach to analyse the short-term effects of NO2, PM10, and PM2·5 on cause-specific mortality using city-specific time series regression analyses and multilevel random-effects meta-analysis. We assessed changes over time using a longitudinal meta-regression with time as a linear fixed term and explored potential sources of heterogeneity and two-pollutant models. FINDINGS Over 21·6 million cardiovascular and 7·7 million respiratory deaths in 380 cities across 24 countries over the study period were included in the analysis. All three air pollutants showed decreasing concentrations over time. The pooled results suggested no significant temporal change in the effect estimates per unit exposure of PM10, PM2·5, or NO2 and mortality. However, the risk of cardiovascular mortality increased from 0·37% (95% CI -0·05 to 0·80) in 1998 to 0·85% (0·55 to 1·16) in 2012 with a 10 μg/m3 increase in PM2·5. Two-pollutant models generally showed similar results to single-pollutant models for PM fractions and indicated temporal differences for NO2. INTERPRETATION Although air pollution levels decreased during the study period, the effect sizes per unit increase in air pollution concentration have not changed. This observation might be due to the composition, toxicity, and sources of air pollution, as well as other factors, such as socioeconomic determinants or changes in population distribution and susceptibility. FUNDING None.
Collapse
Affiliation(s)
- Maximilian Schwarz
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany.
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany; Department of Environmental Health, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA; Munich Heart Alliance, German Center for Cardiovascular Research, Munich, Germany
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Regional Health Service, ASL ROMA 1, Rome, Italy
| | - Francesca de'Donato
- Department of Epidemiology, Lazio Regional Health Service, ASL ROMA 1, Rome, Italy
| | - Francesco Sera
- Department of Statistics, Computer Science and Applications "G Parenti", University of Florence, Florence, Italy
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, USA; Korea University, Seoul, South Korea
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Yasushi Honda
- Center for Climate Change Adaptation, National Institute for Environmental Studies, Tsukuba, Japan
| | - Veronika Huber
- Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Jouni J K Jaakkola
- Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland; Finnish Institute of Meteorology, Helsinki, Finland
| | - Aleš Urban
- Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic; Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic
| | - Ana Maria Vicedo-Cabrera
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Oeschger Center for Climate Change Research, University of Bern, Bern, Switzerland
| | - Pierre Masselot
- Environment & Health Modelling Lab, Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Eric Lavigne
- School of Epidemiology & Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Souzana Achilleos
- Department of Primary Care and Population Health, University of Nicosia Medical School, Nicosia, Cyprus
| | - Jan Kyselý
- Faculty of Environmental Sciences, Czech University of Life Sciences, Prague, Czech Republic; Institute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Greece
| | - Masahiro Hashizume
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Chris Fook Sheng Ng
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | | | - Joana Madureira
- Department of Environmental Health, Instituto Nacional de Saúde Dr Ricardo Jorge, Porto, Portugal; Instituto de Saúde Pública da Universidade do Porto, Porto, Portugal; Laboratory for Integrative and Translational Research in Population Health, Porto, Portugal
| | - Rebecca M Garland
- Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa
| | - Aurelio Tobias
- Institute of Environmental Assessment and Water Research, Spanish Council for Scientific Research, Barcelona, Spain
| | - Ben Armstrong
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Joel Schwartz
- Department of Environmental Health, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Antonio Gasparrini
- Environment & Health Modelling Lab, Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Breitner
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany
| |
Collapse
|
3
|
Zoran MA, Savastru RS, Savastru DM, Tautan MN. Peculiar weather patterns effects on air pollution and COVID-19 spread in Tokyo metropolis. ENVIRONMENTAL RESEARCH 2023; 228:115907. [PMID: 37080275 PMCID: PMC10111861 DOI: 10.1016/j.envres.2023.115907] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/11/2023] [Accepted: 04/12/2023] [Indexed: 05/03/2023]
Abstract
As a pandemic hotspot in Japan, between March 1, 2020-October 1, 2022, Tokyo metropolis experienced seven COVID-19 waves. Motivated by the high rate of COVID-19 incidence and mortality during the seventh wave, and environmental/health challenges we conducted a time-series analysis to investigate the long-term interaction of air quality and climate variability with viral pandemic in Tokyo. Through daily time series geospatial and observational air pollution/climate data, and COVID-19 incidence and death cases, this study compared the environmental conditions during COVID-19 multiwaves. In spite of five State of Emergency (SOEs) restrictions associated with COVID-19 pandemic, during (2020-2022) period air quality recorded low improvements relative to (2015-2019) average annual values, namely: Aerosol Optical Depth increased by 9.13% in 2020 year, and declined by 6.64% in 2021, and 12.03% in 2022; particulate matter PM2.5 and PM10 decreased during 2020, 2021, and 2022 years by 10.22%, 62.26%, 0.39%, and respectively by 4.42%, 3.95%, 5.76%. For (2021-2022) period the average ratio of PM2.5/PM10 was (0.319 ± 0.1640), showing a higher contribution to aerosol loading of traffic-related coarse particles in comparison with fine particles. The highest rates of the daily recorded COVID-19 incidence and death cases in Tokyo during the seventh COVID-19 wave (1 July 2022-1 October 2022) may be attributed to accumulation near the ground of high levels of air pollutants and viral pathogens due to: 1) peculiar persistent atmospheric anticyclonic circulation with strong positive anomalies of geopotential height at 500 hPa; 2) lower levels of Planetary Boundary Layer (PBL) heights; 3) high daily maximum air temperature and land surface temperature due to the prolonged heat waves (HWs) in summer 2022; 4) no imposed restrictions. Such findings can guide public decision-makers to design proper strategies to curb pandemics under persistent stable anticyclonic weather conditions and summer HWs in large metropolitan areas.
Collapse
Affiliation(s)
- Maria A Zoran
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania.
| | - Roxana S Savastru
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Dan M Savastru
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| | - Marina N Tautan
- IT Department, National Institute of R&D for Optoelectronics, Atomistilor Street 409, MG5, Magurele-Bucharest, 077125, Romania
| |
Collapse
|
4
|
Nawahda A. The effect of research on COVID-19 and PM 2.5 on the localization of humanitarian aid. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:763. [PMID: 37249710 PMCID: PMC10227781 DOI: 10.1007/s10661-023-11372-w] [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: 11/02/2022] [Accepted: 05/09/2023] [Indexed: 05/31/2023]
Abstract
The spatiotemporal variation of the death and tested positive cases is poorly understood during the respiratory coronavirus disease 2019 (COVID-19) pandemic. On the other hand, COVID-19's spread was not significantly slowed by pandemic maps. The aim of this study is to investigate the connection between COVID-19 distribution and airborne PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm). Long-term exposure to high levels of PM2.5 is significantly connected to respiratory diseases in addition to being a potential carrier of viruses. Between April 2020 and March 2021, data on COVID-19-related cases were gathered for all prefectures in Japan. There were 9159, 109,078, and 451,913 cases of COVID-19 that resulted in death, severe illness, and positive tests, respectively. Additionally, we gathered information on PM2.5 from 1119 air quality monitoring stations that were deployed across the 47 prefectures. By using the statistical analysis tools in the Geographical Information System (GIS) software, it was found that the residents of prefectures with high PM2.5 concentrations were the most susceptible to COVID-19. Additionally, the World Health Organization-Air Quality Guidelines (WHO-AQG) relative risk (RR) of 1.04 (95% CI: 1.01-1.08), which was used to compute the PM2.5-caused deaths, was employed as well. Approximately 1716 (95% CI: 429-3,432) cases of PM2.5-related deaths were thought to have occurred throughout the study period. Despite the possibility that the actual numbers of both COVID19 and PM2.5-caused deaths are higher, humanitarian actors could use PM2.5 data to localize the efforts to minimize the spread of COVID-19.
Collapse
Affiliation(s)
- Amin Nawahda
- Faculty of Engineering, Palestine Technical University-Kadoorie (PTUK), Tulkarem, Palestine.
| |
Collapse
|
5
|
Hasegawa K, Tsukahara T, Nomiyama T. Short-term associations of low-level fine particulate matter (PM 2.5) with cardiorespiratory hospitalizations in 139 Japanese cities. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 258:114961. [PMID: 37137261 DOI: 10.1016/j.ecoenv.2023.114961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 04/09/2023] [Accepted: 04/24/2023] [Indexed: 05/05/2023]
Abstract
There have been few studies in non-western countries on the relationship between low levels of daily fine particulate matter (PM2.5) exposure and morbidity or mortality, and the impact of PM2.5 concentrations below 15 μg/m3, which is the latest World Health Organization Air Quality Guideline (WHO AQG) value for the 24-h mean, is not yet clear. We assessed the associations between low-level PM2.5 exposure and cardiorespiratory admissions in Japan. We collected the daily hospital admission count data, air pollutant data, and meteorological condition data recorded from April 2016 to March 2019 in 139 Japanese cities. City-specific estimates were obtained from conditional logistic regression models in a time-stratified case-crossover design and pooled by random-effect models. We estimated that every 10-μg/m3 increase in the concurrent-day PM2.5 concentration was related to a 0.52% increase in cardiovascular admissions (95% CI: 0.13-0.92%) and a 1.74% increase in respiratory admissions (95% CI: 1.41-2.07%). These values were nearly the same when the datasets were filtered to contain only daily PM2.5 concentrations <15 μg/m3. The exposure-response curves showed approximately sublinear-to-linear curves with no indication of thresholds. These associations with cardiovascular diseases weakened after adjusting for nitrogen dioxide or sulfur dioxide, but associations with respiratory diseases were almost unchanged when additionally adjusted for other pollutants. This study demonstrated that associations between daily PM2.5 and daily cardiorespiratory hospitalizations might persist at low concentrations, including those below the latest WHO AQG value. Our findings suggest that the updated guideline value may still be insufficient from the perspective of public health.
Collapse
Affiliation(s)
- Kohei Hasegawa
- Department of Preventive Medicine and Public Health, School of Medicine, Shinshu University, 3-1-1 Asahi, Matsumoto, Nagano 390-8621, Japan.
| | - Teruomi Tsukahara
- Department of Preventive Medicine and Public Health, School of Medicine, Shinshu University, 3-1-1 Asahi, Matsumoto, Nagano 390-8621, Japan; Department of Occupational Medicine, School of Medicine, Shinshu University, 3-1-1 Asahi, Matsumoto, Nagano 390-8621, Japan
| | - Tetsuo Nomiyama
- Department of Preventive Medicine and Public Health, School of Medicine, Shinshu University, 3-1-1 Asahi, Matsumoto, Nagano 390-8621, Japan; Department of Occupational Medicine, School of Medicine, Shinshu University, 3-1-1 Asahi, Matsumoto, Nagano 390-8621, Japan
| |
Collapse
|
6
|
Guo Q, He Z, Wang Z. Change in Air Quality during 2014-2021 in Jinan City in China and Its Influencing Factors. TOXICS 2023; 11:210. [PMID: 36976975 PMCID: PMC10056825 DOI: 10.3390/toxics11030210] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 06/18/2023]
Abstract
Air pollution affects climate change, food production, traffic safety, and human health. In this paper, we analyze the changes in air quality index (AQI) and concentrations of six air pollutants in Jinan during 2014-2021. The results indicate that the annual average concentrations of PM10, PM2.5, NO2, SO2, CO, and O3 and AQI values all declined year after year during 2014-2021. Compared with 2014, AQI in Jinan City fell by 27.3% in 2021. Air quality in the four seasons of 2021 was obviously better than that in 2014. PM2.5 concentration was the highest in winter and PM2.5 concentration was the lowest in summer, while it was the opposite for O3 concentration. AQI in Jinan during the COVID epoch in 2020 was remarkably lower compared with that during the same epoch in 2021. Nevertheless, air quality during the post-COVID epoch in 2020 conspicuously deteriorated compared with that in 2021. Socioeconomic elements were the main reasons for the changes in air quality. AQI in Jinan was majorly influenced by energy consumption per 10,000-yuan GDP (ECPGDP), SO2 emissions (SDE), NOx emissions (NOE), particulate emissions (PE), PM2.5, and PM10. Clean policies in Jinan City played a key role in improving air quality. Unfavorable meteorological conditions led to heavy pollution weather in the winter. These results could provide a scientific reference for the control of air pollution in Jinan City.
Collapse
Affiliation(s)
- Qingchun Guo
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
- Institute of Huanghe Studies, Liaocheng University, Liaocheng 252000, China
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, China
| | - Zhenfang He
- School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
- Institute of Huanghe Studies, Liaocheng University, Liaocheng 252000, China
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Zhaosheng Wang
- National Ecosystem Science Data Center, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| |
Collapse
|