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Chen L, Yuan W, Geng M, Xu R, Xing Y, Wen B, Wu Y, Ren X, Shi Y, Zhang Y, Song X, Qin Y, Wang R, Jiang J, Dong Z, Liu J, Guo T, Song Z, Wang L, Ma Y, Dong Y, Song Y, Ma J. Differentiated impacts of short-term exposure to fine particulate constituents on infectious diseases in 507 cities of Chinese children and adolescents: A nationwide time-stratified case-crossover study from 2008 to 2021. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 928:172299. [PMID: 38614340 DOI: 10.1016/j.scitotenv.2024.172299] [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: 01/11/2024] [Revised: 03/11/2024] [Accepted: 04/05/2024] [Indexed: 04/15/2024]
Abstract
This study assesses the association of short-term exposure to PM2.5 (particles ≤2.5 μm) on infectious diseases among Chinese children and adolescents. Analyzing data from 507 cities (2008-2021) on 42 diseases, it focuses on PM2.5 components (black carbon (BC), ammonium (NH4+), inorganic nitrate (NO3-), organic matter (OM), and sulfate (SO42-)). PM2.5 constituents significantly associated with incidence. Sulfate showed the most substantial effect, increasing all-cause infectious disease risk by 2.72 % per interquartile range (IQR) increase. It was followed by BC (2.04 % increase), OM (1.70 %), NO3- (1.67 %), and NH4+ (0.79 %). Specifically, sulfate and BC had pronounced impacts on respiratory diseases, with sulfate linked to a 10.73 % increase in seasonal influenza risk and NO3- to a 16.39 % rise in tuberculosis. Exposure to PM2.5 also marginally increased risks for gastrointestinal, enterovirus, and vectorborne diseases like dengue (7.46 % increase with SO42-). Sexually transmitted and bloodborne diseases saw an approximate 6.26 % increase in incidence, with specific constituents linked to diseases like hepatitis C and syphilis. The study concludes that managing PM2.5 levels could substantially reduce infectious disease incidence, particularly in China's middle-northern regions. It highlights the necessity of stringent air quality standards and targeted disease prevention, aligning PM2.5 management with international guidelines for public health protection.
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Affiliation(s)
- Li Chen
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China
| | - Wen Yuan
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Mengjie Geng
- Division of Infectious Disease Control and Prevention, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
| | - Yi Xing
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Bo Wen
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
| | - Yao Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
| | - Xiang Ren
- Division of Infectious Disease Control and Prevention, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yue Shi
- Division of Infectious Disease Control and Prevention, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yi Zhang
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Xinli Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Yang Qin
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - RuoLin Wang
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Jianuo Jiang
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Ziqi Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Jieyu Liu
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Tongjun Guo
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Zhiying Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Liping Wang
- Division of Infectious Disease Control and Prevention, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yinghua Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China
| | - Yanhui Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China.
| | - Yi Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China.
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China
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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.
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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.
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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.
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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
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Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020. Trop Med Infect Dis 2022; 7:tropicalmed7110341. [DOI: 10.3390/tropicalmed7110341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/27/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
Abstract
The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet’s ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate conditions, with two respiratory infections, influenza and pneumonia, in Chiang Mai, Thailand, which has been considered the most polluted city on Earth during the hot season. We used a seasonal-trend decomposition procedure based on loess regression (STL) and a seasonal cycle subseries (SCS) plot to determine the seasonality of the two diseases. In addition, multivariable negative binomial regression (NBR) models were used to assess the association between the diseases and environmental variables (temperature, precipitation, relative humidity, PM2.5, and PM10). The data revealed that influenza had a clear seasonal pattern during the cold months of January and February, whereas the incidence of pneumonia showed a weak seasonal pattern. In terms of forecasting, the preceding month’s PM2.5 and temperature (lag1) had a significant association with influenza incidence, while the previous month’s temperature and relative humidity influenced pneumonia. Using air pollutants as an indication of respiratory disease, our models indicated that PM2.5 lag1 was correlated with the incidence of influenza, but not pneumonia. However, there was a linear association between PM10 and both diseases. This research will help in allocating clinical and public health resources in response to potential environmental changes and forecasting the future dynamics of influenza and pneumonia in the region due to air pollution.
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