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Thi Khanh HN, De Troeyer K, Smith P, Demoury C, Casas L. The impact of ambient temperature and air pollution on SARS-CoV2 infection and Post COVID-19 condition in Belgium (2021-2022). ENVIRONMENTAL RESEARCH 2024; 246:118066. [PMID: 38159667 DOI: 10.1016/j.envres.2023.118066] [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: 09/01/2023] [Revised: 12/08/2023] [Accepted: 12/26/2023] [Indexed: 01/03/2024]
Abstract
INTRODUCTION The associations between non-optimal ambient temperature, air pollution and SARS-CoV-2 infection and post COVID-19 condition (PCC) remain constrained in current understanding. We conducted a retrospective analysis to explore how ambient temperature affected SARS-CoV-2 infection in individuals who later developed PCC compared to those who did not. We investigated if these associations were modified by air pollution. METHODS We conducted a bidirectional time-stratified case-crossover study among individuals who tested positive for SARS-CoV-2 between May 2021 and June 2022. We included 6302 infections, with 2850 PCC cases. We used conditional logistic regression and distributed lag non-linear models to obtain odds ratios (OR) and 95% confidence intervals (CI) for non-optimal temperatures relative to the period median temperature (10.6 °C) on lags 0 to 5. For effect modification, daily average PM2.5 concentrations were categorized using the period median concentration (8.8 μg/m3). Z-tests were used to compare the results by PCC status and PM2.5. RESULTS Non-optimal cold temperatures increased the cumulative odds of infection (OR = 1.93; 95%CI:1.67-2.23, OR = 3.53; 95%CI:2.72-4.58, for moderate and extreme cold, respectively), with the strongest associations observed for non-PCC cases. Non-optimal heat temperatures decreased the odds of infection except for moderate heat among PCC cases (OR = 1.32; 95%CI:0.89-1.96). When PM2.5 was >8.8 μg/m3, the associations with cold were stronger, and moderate heat doubled the odds of infection with later development of PCC (OR = 2.18; 95%CI:1.01-4.69). When PM2.5 was ≤8.8 μg/m3, exposure to non-optimal temperatures reduced the odds of infection. CONCLUSION Exposure to cold increases SARS-CoV2 risk, especially on days with moderate to high air pollution. Heated temperatures and moderate to high air pollution during infection may cause PCC. These findings stress the need for mitigation and adaptation strategies for climate change to reduce increasing trends in the frequency of weather extremes that have consequences on air pollution concentrations.
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Affiliation(s)
- Huyen Nguyen Thi Khanh
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium; Institute of Environmental Medicine (IMM), Karolinska Institutet, Sweden.
| | - Katrien De Troeyer
- Social Epidemiology and Health Policy, Department Family Medicine and Population Health, University of Antwerp, Doornstraat 331, 2610, Wilrijk, Belgium.
| | - Pierre Smith
- Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium; Institute of Health and Society (IRSS), Université catholique de Louvain, Brussels, Belgium.
| | - Claire Demoury
- Risk and Health Impact Assessment, Sciensano, Brussels, Belgium.
| | - Lidia Casas
- Social Epidemiology and Health Policy, Department Family Medicine and Population Health, University of Antwerp, Doornstraat 331, 2610, Wilrijk, Belgium; Institute for Environment and Sustainable Development (IMDO), University of Antwerp, Belgium.
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Demoury C, Aerts R, Berete F, Lefebvre W, Pauwels A, Vanpoucke C, Van der Heyden J, De Clercq EM. Impact of short-term exposure to air pollution on natural mortality and vulnerable populations: a multi-city case-crossover analysis in Belgium. Environ Health 2024; 23:11. [PMID: 38267996 PMCID: PMC10809644 DOI: 10.1186/s12940-024-01050-w] [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: 10/04/2023] [Accepted: 01/07/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND The adverse effect of air pollution on mortality is well documented worldwide but the identification of more vulnerable populations at higher risk of death is still limited. The aim of this study was to evaluate the association between natural mortality (overall and cause-specific) and short-term exposure to five air pollutants (PM2.5, PM10, NO2, O3 and black carbon) and identify potential vulnerable populations in Belgium. METHODS We used a time-stratified case-crossover design with conditional logistic regressions to assess the relationship between mortality and air pollution in the nine largest Belgian agglomerations. Then, we performed a random-effect meta-analysis of the pooled results and described the global air pollution-mortality association. We carried out stratified analyses by individual characteristics (sex, age, employment, hospitalization days and chronic preexisting health conditions), living environment (levels of population density, built-up areas) and season of death to identify effect modifiers of the association. RESULTS The study included 304,754 natural deaths registered between 2010 and 2015. We found percentage increases for overall natural mortality associated with 10 μg/m3 increases of air pollution levels of 0.6% (95% CI: 0.2%, 1.0%) for PM2.5, 0.4% (0.1%, 0.8%) for PM10, 0.5% (-0.2%, 1.1%) for O3, 1.0% (0.3%, 1.7%) for NO2 and 7.1% (-0.1%, 14.8%) for black carbon. There was also evidence for increases of cardiovascular and respiratory mortality. We did not find effect modification by individual characteristics (sex, age, employment, hospitalization days). However, this study suggested differences in risk of death for people with preexisting conditions (thrombosis, cardiovascular diseases, asthma, diabetes and thyroid affections), season of death (May-September vs October-April) and levels of built-up area in the neighborhood (for NO2). CONCLUSIONS This work provided evidence for the adverse health effects of air pollution and contributed to the identification of specific population groups. These findings can help to better define public-health interventions and prevention strategies.
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Affiliation(s)
- Claire Demoury
- Risk and Health Impact Assessment, Sciensano, Brussels, Belgium.
| | - Raf Aerts
- Risk and Health Impact Assessment, Sciensano, Brussels, Belgium
- Division Ecology, Evolution and Biodiversity Conservation, KU Leuven, Louvain, Belgium
- Center for Environmental Sciences, University of Hasselt, Hasselt, Belgium
| | | | - Wouter Lefebvre
- Flemish Institute for Technological Research (VITO), Mol, Belgium
| | - Arno Pauwels
- Risk and Health Impact Assessment, Sciensano, Brussels, Belgium
- Health Information, Sciensano, Brussels, Belgium
| | | | | | - Eva M De Clercq
- Risk and Health Impact Assessment, Sciensano, Brussels, Belgium
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Li M, Fang W, Meng R, Hu J, He G, Hou Z, Zhou M, Zhou C, Zhu S, Xiao Y, Yu M, Huang B, Xu X, Lin L, Jin D, Qin M, Yin P, Xu Y, Liu T, Ma W. The comparison of mortality burden between exposure to dry-cold events and wet-cold events: A nationwide study in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166859. [PMID: 37673238 DOI: 10.1016/j.scitotenv.2023.166859] [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: 03/24/2023] [Revised: 08/17/2023] [Accepted: 09/03/2023] [Indexed: 09/08/2023]
Abstract
BACKGROUND Most previous studies have focused on the health effect of temperature or humidity, and few studies have explored the combined health effects of exposure to temperature and humidity. This study aims to estimate the relationship between humidity-cold events and mortality, and then to compare the mortality burden between exposure to dry-cold events and wet-cold events, and finally to explore whether there was an additive interaction of temperature and humidity on mortality. METHODS In the study, Daily mortality data during 2006-2017 were collected from Centers for Disease Control and Prevention in China, and daily mean temperature and daily mean relative humidity data from 698 weather stations in China were obtained from the China Meteorological Data Sharing Service system. We first employed time-series design with a distributed lag nonlinear model and a multivariate meta-analysis model to examine the association between humidity-cold events with mortality. RESULTS We found that humidity-cold events significantly increased mortality risk, and the effect of wet-cold events (RR:1.24, 95%CI:1.20,1.29) was higher than that of dry-cold events (RR:1.14, 95%CI:1.10,1.18). Dry-cold events and wet-cold events accounted for 2.41 % and 2.99 % excess deaths, respectively with higher burden for the elderly ≥85 years old, Central China and CVD. In addition, there is a synergistic additive interaction between low temperature and high humidity in winter. CONCLUSION This study showed that humidity-cold events significantly increased mortality risk, and the effect of wet-cold events was higher than that of dry-cold events.
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Affiliation(s)
- Muyun Li
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Wen Fang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Sui Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Yize Xiao
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310009, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun 130062, China
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Donghui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Mingfang Qin
- Yunnan Provincial Center for Disease Control and Prevention, Kunming 650034, China
| | - Peng Yin
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
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