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Gao Q, Jiang B, Tong M, Zuo H, Cheng C, Zhang Y, Song S, Lu L, Li X. Effects and interaction of humidex and air pollution on influenza: A national analysis of 319 cities in mainland China. JOURNAL OF HAZARDOUS MATERIALS 2025; 490:137865. [PMID: 40058198 DOI: 10.1016/j.jhazmat.2025.137865] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2024] [Revised: 02/27/2025] [Accepted: 03/05/2025] [Indexed: 04/16/2025]
Abstract
Influenza imposes a significant global health burden. This study investigates the effects of humidex and air pollution on influenza and their interactions, using multi-city surveillance data in China. Daily data on reported influenza cases, meteorological factors and air pollution from 319 cities in mainland China over the study period of 2014-2019 were collected. A two-stage analytical framework, comprising distributed lag non-linear model and multivariate meta-analysis, was employed to assess the associations between humidex, air pollution and influenza. Hierarchical and joint effect models were employed to examine their interaction. Nationally, an approximately L-shaped relationship between humidex and influenza was observed, with the highest relative risk (RR) of 2.603 (95 % confidence interval [CI]: 2.195-3.086). Per interquartile range increases in PM2.5, PM10, NO2, SO2, CO and O3 were associated with influenza risk increments of 0.035 (95 % CI: 0.010-0.061), 0.029 (95 % CI: 0.003-0.055), 0.191 (95 % CI: 0.152-0.231), 0.239 (95 % CI: 0.166-0.317), 0.038 (95 % CI: 0.001-0.076) and -0.171 (95 % CI: -0.238--0.099), respectively. A synergistic interaction effect was identified between low humidex and high air pollution as well as different air pollutants. Subgroup analyses indicated females and individuals aged 7-18 years old exhibited higher risks. Stronger effects were observed during winter season and in large cities. This study underscores the urgent need for tailored interventions to mitigate the health impacts in regions with concurrent low humidex and high air pollution.
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Affiliation(s)
- Qi Gao
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Baofa Jiang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Michael Tong
- National Centre for Epidemiology and Population Health, ANU College of Health and Medicine, The Australian National University, Canberra, ACT, 2601, Australia
| | - Hui Zuo
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Chuanlong Cheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yuqi Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Sihao Song
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Xiujun Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
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Wang Z, Ma Y, Cai W, Zhang T, Huang T, Shui T, Yin F, Yang H. Quantifying the temporal trends of the combined effect of temperature and relative humidity on hand, foot, and mouth disease in Yunnan, China. Front Public Health 2025; 13:1553278. [PMID: 40376059 PMCID: PMC12078327 DOI: 10.3389/fpubh.2025.1553278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2024] [Accepted: 04/15/2025] [Indexed: 05/18/2025] Open
Abstract
Background Hand, foot, and mouth disease (HFMD) poses a significant risk to children. While most studies focus on the individual effects of temperature or relative humidity, the combined effect of these factors and their temporal variations remain unclear. Understanding these effects is essential for designing effective public health interventions. Methods Using daily meteorological and HFMD case data collected from 2010 to 2019 in 16 cities in Yunnan Province, China, we compared three composite indices (Humidex, heat index, and temperature-humidity index) to identify the indices that best captured the combined effect of temperature and humidity on HFMD risk. An extended time-varying distributed lag nonlinear model (DLNM) was used to examine how these effects shifted over time across population subgroups. Relative risk (RR) values at the 1%, 25%, 75%, and 99% quantiles were extracted to represent effects at extremely, moderately low, moderately, and extremely high levels. Results The THIa8 demonstrated a monotonic upward exposure-response curve with narrower confidence intervals, more consistent relationships across cities, and the best model fit (Quasi-Akaike information criterion (QAIC) = 283564.2, Akaike information criterion (AIC) = 45.46, and Bayesian information criterion (BIC) = 62.30). HFMD risk decreased at extremely low (RR = 0.677, 95% CI: 0.632, 0.724) and moderately low THIa8 levels (RR = 0.766, 95% CI: 0.713, 0.823) but increased at moderately high (RR = 1.121, 95% CI: 1.084, 1.159) and extremely high THIa8 levels (RR = 1.478, 95% CI: 1.300, 1.680). Temporal analysis revealed a decreased HFMD risk at extremely low THIa8 values from 2010 to 2019, weakened protective effects at moderately low THIa8 values and an increased risk at extremely high THIa8 values. Subgroup analyses revealed that kindergarten children (3 ≤ age < 6 years) and females were particularly vulnerable. Conclusion The THIa8 effectively captures the combined effect of temperature and relative humidity on HFMD risk revealing temporal variations. Adaptive public health strategies are needed to mitigate HFMD transmission under changing environmental conditions.
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Affiliation(s)
- Zhaohan Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wennian Cai
- National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Tao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tian Huang
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Tiejun Shui
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Haijun Yang
- Yan'an Hospital of Kunming City, Kunming, China
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Liu Y, Song Y, Liu F, Chen Y, Liu Y, Shi J, Li K, Yin Y, Liang Q, Liu N, Ming M, Hua L, Shi Q, Xu J, Yuan R, Li S, Zhang L, Zhao Y, Wang N, Zhang J, Zhang Y, Chang Z, Zhang Z. Effectiveness of the enterovirus A71 vaccine on hand, foot, and mouth disease: a real-world study in China. Clin Microbiol Infect 2025; 31:258-265. [PMID: 39343096 DOI: 10.1016/j.cmi.2024.09.020] [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: 04/26/2024] [Revised: 09/08/2024] [Accepted: 09/23/2024] [Indexed: 10/01/2024]
Abstract
OBJECTIVES For the prevention of hand, foot, and mouth disease (HFMD), enterovirus A71 (EV-A71) vaccines have been used in China since 2016. To better inform vaccination strategies, we assess the real-world effectiveness of EV-A71 vaccination in China. METHODS The analysis was based on surveillance data of HFMD caused by EV-A71 in children under the age of 5 in China, along with meteorological and demographic data. The seasonal autoregressive integrated moving average model and the interrupted time series analysis were used to estimate the effectiveness of the EV-A71 vaccination on the EV-A71 HFMD incidence and to predict the counterfactual cases with no EV-A71 vaccine. RESULTS Between 2010 and 2018, 6 712 613 cases of HFMD caused by EV-A71 were reported in children under 5 years old in 260 Chinese cities. During 2017-2018, the EV-A71 vaccination was associated with a reduction in EV-A71 HFMD incidence, with a relative risk of 0.83 (95% CI, 0.81-0.86), and an estimated reduction of 297 946 (95% CI, 250 534-346 658) cases. However, this association varied across cities (I2 = 85.6%, p < 0.001) and the effectiveness of the EV-A71 vaccination decreased as population density increased. Higher vaccination coverage was associated with greater effectiveness of the EV-A71 vaccination and an earlier point in EV-A71 case reduction. Specifically, when the vaccination coverage exceeded ∼20%, the relative risk was rapidly reduced to below 0.71 (95% CI, 0.69-0.72). DISCUSSION Our study demonstrated that the EV-A71 vaccination was associated with a reduction in the incidence of EV-A71 HFMD, but the association varied with regions and was influenced by vaccination coverage and population density. To optimize EV-A71 HFMD prevention, increasing vaccination coverage (>20%) is recommended for children under 5 years old.
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Affiliation(s)
- Yuanhua Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yang Song
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Fengfeng Liu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yue Chen
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Yang Liu
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jin Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Ke Li
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yun Yin
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Qingqing Liang
- Health Information Center, Guilin Center for Disease Control and Prevention, Guilin, China
| | - Na Liu
- Department of Immunization Program, Suzhou Center for Disease Control and Prevention, Suzhou, China
| | - Ming Ming
- Department of Immunization Program, Taian Center for Disease Control and Prevention, Taian, China
| | - Lei Hua
- Department of Immunization Program, Baoji Center for Disease Control and Prevention, Baoji, China
| | - Qian Shi
- Department of Immunization Program, Chaoyang District Center for Disease Control and Prevention, Beijing, China
| | - Jiayao Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Rui Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Shuting Li
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Lele Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yu Zhao
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Na Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Jidan Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Yanping Zhang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhaorui Chang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhijie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
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Ma W, Shen W, Gong L, Xiao Y, Hou S, Sun L, Li H, Huang F, Wu J. Independent and interactive effects of particulate matter and meteorological factors on hand, foot and mouth disease in Fuyang. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2024; 68:2677-2692. [PMID: 39417841 DOI: 10.1007/s00484-024-02777-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 08/10/2024] [Accepted: 08/31/2024] [Indexed: 10/19/2024]
Abstract
Previous research has demonstrated the influence of environmental factor on the occurrence of infectious diseases. However, there is insufficient and conflicting evidence regarding the association between Hand, foot and mouth disease (HFMD) and environmental variables, particularly the interaction of environmental variables. This study aims to investigate the individual and interactive effects of particulate matter (PM) and meteorological factors on HFMD incidence in Fuyang. The generalized additive models were combined with distributed lag non-linear models to assess the individual effects between PM and meteorological factor on HFMD incidence in Fuyang. Subsequently, a product term was incorporated into the model to investigate the interaction between PM and meteorological factors. Temperature and PM2.5 were identified as the two primary risk factors for HFMD, with relative risks (RR) of 1.586(1.493,1.685) and 1.349(1.325,1.373), respectively. Furthermore, PM exhibited a synergistic effect with meteorological factors. For instance, the RR values for PM2.5 in relation to HFMD were 1.029 (95% CI: 1.024-1.035) and 1 0.117 (95% CI: 1 0.108 - 11 0.127) under different temperature group categories. Notably, HFMD predominantly affects children under the age of five years old and infants aged between zero to one year old demonstrate heightened susceptibility to environmental variables. The results showed that both PM and meteorological factors were risk factors for HFMD, with evidence of an interaction between these variables. These findings have important implications for local HFMD incidence prediction and the development of effective prevention strategies.
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Affiliation(s)
- Wanwan Ma
- Department of Infectious Disease Control and Prevention, Anhui Center for Disease Control and Prevention, 12560 Fanhua Avenue, Shushan District, Hefei, Anhui, 230601, China
| | - Wenbin Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China
| | - Lei Gong
- Department of Infectious Disease Control and Prevention, Anhui Center for Disease Control and Prevention, 12560 Fanhua Avenue, Shushan District, Hefei, Anhui, 230601, China
| | - Yongkang Xiao
- Department of Infectious Disease Control and Prevention, Anhui Center for Disease Control and Prevention, 12560 Fanhua Avenue, Shushan District, Hefei, Anhui, 230601, China
| | - Sai Hou
- Department of Infectious Disease Control and Prevention, Anhui Center for Disease Control and Prevention, 12560 Fanhua Avenue, Shushan District, Hefei, Anhui, 230601, China
| | - Liang Sun
- Department of Infectious Disease Control and Prevention, Fuyang Center for Disease Control and Prevention, Fuyang, Anhui, China
| | - Huaibiao Li
- Department of Infectious Disease Control and Prevention, Fuyang Center for Disease Control and Prevention, Fuyang, Anhui, China
| | - Fen Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
| | - Jiabing Wu
- Department of Infectious Disease Control and Prevention, Anhui Center for Disease Control and Prevention, 12560 Fanhua Avenue, Shushan District, Hefei, Anhui, 230601, China.
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Sun J, Zhang W, Yao G, Gu J, Wu W, Wang D, Du Z, Hao Y. Assessing the modification impact of vaccination on the relationship of the Discomfort Index with hand, foot, and mouth disease in Guizhou: A multicounty study. PLoS Negl Trop Dis 2024; 18:e0012008. [PMID: 38949988 PMCID: PMC11216560 DOI: 10.1371/journal.pntd.0012008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 06/02/2024] [Indexed: 07/03/2024] Open
Abstract
BACKGROUND Hand, foot, and mouth disease (HFMD) is a major public health issue in China while temperature and humidity are well-documented predictors. However, evidence on the combined effect of temperature and humidity is still limited. It also remains unclear whether such an effect could be modified by the enterovirus 71 (EV71) vaccination. METHODS Based on 320,042 reported HFMD cases during the summer months between 2012 and 2019, we conducted a study utilizing Distributed Lag Non-Linear Models (DLNM) and time-varying DLNM to examine how China's HFMD EV71 vaccine strategy would affect the correlation between meteorological conditions and HFMD risk. RESULTS The incidence of HFMD changed with the Discomfort Index in an arm-shaped form. The 14-day cumulative risk of HFMD exhibited a statistically significant increase during the period of 2017-2019 (following the implementation of the EV71 vaccine policy) compared to 2012-2016 (prior to the vaccine implementation). For the total population, the range of relative risk (RR) values for HFMD at the 75th, 90th, and 99th percentiles increased from 1.082-1.303 in 2012-2016 to 1.836-2.022 in 2017-2019. In the stratified analyses, Han Chinese areas show stronger relative growth, with RR values at the 75th, 90th, and 99th percentiles increased by 14.3%, 39.1%, and 134.4% post-vaccination, compared to increases of 22.7%, 41.6%, and 38.8% in minority areas. Similarly, boys showed greater increases (24.4%, 47.7%, 121.5%) compared to girls (8.1%, 28.1%, 58.3%). Additionally, the central Guizhou urban agglomeration displayed a tendency for stronger relative growth compared to other counties. CONCLUSIONS Although the EV71 vaccine policy has been implemented, it hasn't effectively controlled the overall risk of HFMD. There's been a shift in the main viral subtypes, potentially altering population susceptibility and influencing HFMD occurrences. The modulating effects of vaccine intervention may also be influenced by factors such as race, sex, and economic level.
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Affiliation(s)
- Jie Sun
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
- Institute for the Control of Infectious Diseases, Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Guanghai Yao
- Institute for the Control of Infectious Diseases, Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, China
| | - Jing Gu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Dan Wang
- Institute for the Control of Infectious Diseases, Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
- Guangzhou Joint Research Center for Disease Surveillance and Risk Assessment, Sun Yat-sen University & Guangzhou Center for Disease Control and Prevention, Guangzhou, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Peking University, Beijing, China
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Yin Z, Jingesi M, Yin Z, Chen S, Huang S, Cheng J, Li X, Liu N, Wang P, Yin P, Jiang H. Short-term effects of temperature-related indices on emergency ambulance dispatches due to mental and behavioral disorders in Shenzhen, China. Front Public Health 2024; 12:1343550. [PMID: 38883192 PMCID: PMC11177611 DOI: 10.3389/fpubh.2024.1343550] [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: 11/23/2023] [Accepted: 05/03/2024] [Indexed: 06/18/2024] Open
Abstract
Introduction The precise associations between temperature-related indices and mental and behavioral disorders (MBDs) have yet to be fully elucidated. Our study aims to ascertain the most effective temperature-related index and assess its immediate impact on emergency ambulance dispatches (EADs) due to MBDs in Shenzhen, China. Methods EADs data and meteorological data from January 1, 2013, to December 31, 2020, in Shenzhen were collected. Distributed lag non-linear models (DLNMs) were utilized to examine the non-linear and lagged effects of temperature-related indices on EADs due to MBDs. The Quasi Akaike Information criterion (QAIC) was used to determine the optimal index after standardizing temperature-related indices. After adjusting for confounding factors in the model, we estimated the immediate and cumulative effects of temperature on EADs due to MBDs. Results The analysis of short-term temperature effects on EADs due to MBDs revealed Humidex as the most suitable index. Referring to the optimal Humidex (3.2th percentile, 12.00°C), we observed a significant effect of Humidex over the threshold (34.6th percentile, 26.80°C) on EADs due to MBDs at lag 0-5. The cumulative relative risks for high temperature (90th percentile, 41.90°C) and extreme high temperature (99th percentile, 44.20°C) at lag 0-5 were 1.318 (95% CI: 1.159-1.499) and 1.338 (95% CI: 1.153-1.553), respectively. No significant cold effect was observed on EADs due to MBDs. Conclusion High Humidex was associated with more EADs due to MBDs in subtropical regions. Health authorities should implement effective measures to raise public awareness of risks related to high temperature and protect vulnerable populations.
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Affiliation(s)
- Ziming Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Maidina Jingesi
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhao Yin
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Siyi Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Suli Huang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jinquan Cheng
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Xiaoheng Li
- Department of Environment and Health, Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Ning Liu
- Department of Environment and Health, Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Peng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongwei Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Ji Y, Huang Z, Yuan Z, Xiong J, Li L. Exposure to low humidex increases the risk of hip fracture admissions in a subtropical coastal Chinese city. Bone 2024; 181:117032. [PMID: 38307177 DOI: 10.1016/j.bone.2024.117032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 01/15/2024] [Accepted: 01/30/2024] [Indexed: 02/04/2024]
Abstract
OBJECTIVE The adverse impacts of meteorological factors on human health have attracted great attention. However, no studies have investigated the nonlinear effects of humidex on hip fractures (HF), particularly in middle-aged and older adults. This study aimed to quantify the impacts of humidex, a comprehensive index of temperature and relative humidity, on HF admissions. METHODS Daily HF admissions, meteorological variables and air pollutants in the subtropical coastal city of Shantou, China, from 2015 to 2020 were collected. A generalized linear regression model combined with a distributed lag nonlinear model was applied to explore the exposure-lag-response relationship between humidex and HF admissions. Subgroup analyses were also conducted by gender, age and season. Attributable fractions (AF) and attributable numbers (AN) were used to represent the burden of disease. RESULTS A total of 6200 HF admissions were identified during the study period. Taking the median humidex (31.9) as a reference, the single-day lag effects of low humidex (13, 2.5th percentile) were significant at lag 0 [relative risk (RR) = 1.145, 95 % confidence interval (CI): 1.041-1.259] to lag 2 (RR = 1.049, 95 % CI: 1.010-1.089). The cumulative lag effects of low humidex were significant at lag 0-0 (RR = 1.145, 95 % CI: 1.041-1.259) to lag 0-6 (RR = 1.258, 95 % CI: 1.010-1.567) and reached a maximum at lag 0-3 (RR = 1.330, 95 % CI: 1.113-1.590). High humidex (44, 97.5th percentile) was not associated with the risk of HF. Females and people over the age of 75 appeared to be more susceptible to low humidex. In addition, the adverse effects of low humidex were more pronounced in the cold season. The AF and AN of low humidex on HF admissions were 24.8 % (95 % CI: 10.2-37.1 %) and 1538, respectively. CONCLUSION Low humidex was associated with an increased risk of HF admissions. The government should take timely measures to prevent people from being exposed to low humidex to effectively reduce HF admissions.
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Affiliation(s)
- Yanhu Ji
- School of Public Health, Shantou University, 515063 Shantou, China
| | - Zepeng Huang
- The Second Affiliated Hospital of Shantou University Medical College, 515041 Shantou, China
| | | | - Jianping Xiong
- The First Affiliated Hospital of Shantou University Medical College, 515041 Shantou, China
| | - Liping Li
- School of Public Health, Shantou University, 515063 Shantou, China.
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Li Y, Xia Y, Zhu H, Shi C, Jiang X, Ruan S, Wen Y, Gao X, Huang W, Li M, Xue R, Chen J, Zhang L. Impacts of exposure to humidex on cardiovascular mortality: a multi-city study in Southwest China. BMC Public Health 2023; 23:1916. [PMID: 37794404 PMCID: PMC10548730 DOI: 10.1186/s12889-023-16818-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 09/22/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Many studies have reported the association between ambient temperature and mortality from cardiovascular disease (CVD). However, the health effects of humidity are still unclear, much less the combined effects of temperature and humidity. In this study, we used humidex to quantify the effect of temperature and humidity combined on CVD mortality. METHODS Daily meteorological, air pollution, and CVD mortality data were collected in four cities in southwest China. We used a distributed lag non-linear model (DLNM) in the first stage to assess the exposure-response association between humidex and city-specific CVD mortality. A multivariate meta-analysis was conducted in the second stage to pool these effects at the overall level. To evaluate the mortality burden of high and low humidex, we determined the attributable fraction (AF). According to the abovementioned processes, stratified analyses were conducted based on various demographic factors. RESULTS Humidex and the CVD exposure-response curve showed an inverted "J" shape, the minimum mortality humidex (MMH) was 31.7 (77th percentile), and the cumulative relative risk (CRR) was 2.27 (95% confidence interval [CI], 1.76-2.91). At extremely high and low humidex, CRRs were 1.19 (95% CI, 0.98-1.44) and 2.52 (95% CI, 1.88-3.38), respectively. The burden of CVD mortality attributed to non-optimal humidex was 21.59% (95% empirical CI [eCI], 18.12-24.59%), most of which was due to low humidex, with an AF of 20.16% (95% eCI, 16.72-23.23%). CONCLUSIONS Low humidex could significantly increase the risk of CVD mortality, and vulnerability to humidex differed across populations with different demographic characteristics. The elderly (> 64 years old), unmarried people, and those with a limited level of education (1-9 years) were especially susceptible to low humidex. Therefore, humidex is appropriate as a predictor in a CVD early-warning system.
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Affiliation(s)
- Yang Li
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China
| | - Yizhang Xia
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China
- School of Public Health, Chengdu Medical College, No.783, Xindu Road, Xindu District, Chengdu, 610500, China
| | - Hongbin Zhu
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China
| | - Chunli Shi
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China
| | - Xianyan Jiang
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China
| | - Shijuan Ruan
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China
| | - Yue Wen
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China
| | - Xufang Gao
- Chengdu Center for Disease Control and Prevention, No.6, Longxiang Road, Wuhou District, Chengdu, 610041, China
| | - Wei Huang
- Zigong Center for Disease Control and Prevention, No.826, Huichuan Road, Ziliujing District, Zigong, 643000, China
| | - Mingjiang Li
- Panzhi hua Center for Disease Control and Prevention, No.996, Jichang Road, Dong District, Panzhi hua, 617067, China
| | - Rong Xue
- Guangyuan Center for Disease Control and Prevention, No.996, Binhebei Road,Lizhou District, Guangyuan, 628017, China
| | - Jianyu Chen
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China.
| | - Li Zhang
- Sichuan Provincial Center for Disease Control and Prevention, No.6, Zhongxue Road, Wuhou District, Chengdu, 610041, China.
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9
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Tan C, Li S, Li Y, Peng Z. Dynamic modeling and data fitting of climatic and environmental factors and people's behavior factors on hand, foot, and mouth disease (HFMD) in Shanghai, China. Heliyon 2023; 9:e18212. [PMID: 37576260 PMCID: PMC10412780 DOI: 10.1016/j.heliyon.2023.e18212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 07/08/2023] [Accepted: 07/11/2023] [Indexed: 08/15/2023] Open
Abstract
Background Hand, foot, and mouth disease (HFMD) appear to be a multi-wave outbreak with unknown mechanisms. We investigate the effects of climatic and environmental factors and changes in people's behavior factors that may be caused by external factors: temperature, relative humidity, and school opening and closing. Methods Distributed lag nonlinear model (DLNM) and dynamic model are used to research multi-wave outbreaks of HFMD. Climatic and environmental factors impact on transmission rate β ( t ) is modeled through DLNM and then substituted into this relationship to establish the dynamic model with reported case data to test for validity. Results Relative risk (RR) of HFMD infection increases with increasing temperature. The RR of infection first increases and then decreases with the increase of relative humidity. For the model fitting HFMD dynamic, time average basic reproduction number [ R 0 ] of Stage I (without vaccine) and Stage II (with EV71 vaccine) are 1.9362 and 1.5478, respectively. Temperature has the highest explanatory power, followed by school opening and closing, and relative humidity. Conclusion We obtain three conclusions about the prevention and control of HFMD. 1) According to the temperature, relative humidity and school start time, the outbreak peak of HFMD should be warned and targeted prevention and control measures should be taken. 2) Reduce high indoor temperature when more than 31.5 oC, and increase low relative humidity when less than 77.5% by opening the window for ventilation, adding houseplants, using air conditioners and humidifiers, reducing the incidence of HFMD and the number of infections. 3) The risk of HFMD transmission during winter vacations is higher than during summer vacations. It is necessary to strengthen the publicity of HFMD prevention knowledge before winter vacations and strengthen the disinfection control measures during winter vacations in children's hospitals, school classrooms, and other places where children gather to reduce the frequency of staff turnover during winter vacations.
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Affiliation(s)
- Changlei Tan
- School of Information and Mathematics, Yangtze University, Jingzhou, 434023, Hubei, PR China
- Information Engineering College, Hunan Applied Technology University, Changde, 415100, Hunan, PR China
| | - Shuang Li
- College of Mathematics and Information Science, Henan Normal University, Xinxiang, 453000, Henan, PR China
| | - Yong Li
- School of Information and Mathematics, Yangtze University, Jingzhou, 434023, Hubei, PR China
| | - Zhihang Peng
- School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, PR China
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10
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Cai W, Luo C, Geng X, Zha Y, Zhang T, Zhang H, Yang C, Yin F, Ma Y, Shui T. City-level meteorological conditions modify the relationships between exposure to multiple air pollutants and the risk of pediatric hand, foot, and mouth disease in the Sichuan Basin, China. Front Public Health 2023; 11:1140639. [PMID: 37601186 PMCID: PMC10433208 DOI: 10.3389/fpubh.2023.1140639] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 06/26/2023] [Indexed: 08/22/2023] Open
Abstract
Background Several studies have examined the effects of city-level meteorological conditions on the associations between meteorological factors and hand, foot, and mouth disease (HFMD) risk. However, evidence that city-level meteorological conditions modify air pollutant-HFMD associations is lacking. Methods For each of the 17 cities in the Sichuan Basin, we obtained estimates of the relationship between exposures to multiple air pollutants and childhood HFMD risk by using a unified distributed lag nonlinear model (DLNM). Multivariate meta-regression models were used to identify the effects of city-level meteorological conditions as effect modifiers. Finally, we conducted subgroup analyses of age and sex to explore whether the modification effects varied in different subgroups. Results The associations between PM2.5/CO/O3 and HFMD risk showed moderate or substantial heterogeneity among cities (I 2 statistics: 48.5%, 53.1%, and 61.1%). Temperature conditions significantly modified the PM2.5-HFMD association, while relative humidity and rainfall modified the O3-HFMD association. Low temperatures enhanced the protective effect of PM2.5 exposure against HFMD risk [PM2.5 <32.7 μg/m3 or PM2.5 >100 μg/m3, at the 99th percentile: relative risk (RR) = 0.14, 95% CI: 0.03-0.60]. Low relative humidity increased the adverse effect of O3 exposure on HFMD risk (O3 >128.7 μg/m3, at the 99th percentile: RR = 2.58, 95% CI: 1.48-4.50). However, high rainfall decreased the risk of HFMD due to O3 exposure (O3: 14.1-41.4 μg/m3). In addition, the modification effects of temperature and relative humidity differed in the female and 3-5 years-old subgroups. Conclusion Our findings revealed moderate or substantial heterogeneity in multiple air pollutant-HFMD relationships. Temperature, relative humidity, and rainfall modified the relationships between PM2.5 or O3 exposure and HFMD risk.
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Affiliation(s)
- Wennian Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Caiying Luo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xiaoran Geng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yuanyi Zha
- Graduate School of Kunming Medical University, Kunming, China
| | - Tao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Huadong Zhang
- Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - Changhong Yang
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Tiejun Shui
- Yunnan Center for Disease Control and Prevention, Kunming, China
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11
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Fang W, Li Z, Gao J, Meng R, He G, Hou Z, Zhu S, Zhou M, Zhou C, Xiao Y, Yu M, Huang B, Xu X, Lin L, Xiao J, Jin D, Qin M, Yin P, Xu Y, Hu J, Liu T, Huang C, Ma W. The joint and interaction effect of high temperature and humidity on mortality in China. ENVIRONMENT INTERNATIONAL 2023; 171:107669. [PMID: 36508749 DOI: 10.1016/j.envint.2022.107669] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 11/20/2022] [Accepted: 11/28/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Although many studies have reported the mortality effect of temperature, there were few studies on the mortality risk of humidity, let alone the joint effect of temperature and humidity. This study aimed to investigate the joint and interaction effect of high temperature and relative humidity on mortality in China, which will deepen understanding the health risk of mixture climate exposure. METHODS The mortality and meteorological data were collected from 353 locations in China (2013-2017 in Jilin, Hunan, Guangdong and Yunnan provinces, 2009-2017 in Zhejiang province, and 2006-2011 in other Provinces). We defined location-specific daily mean temperature ≥ 75th percentile of distribution as high temperature, while minimum mortality relative humidity as the threshold of high relative humidity. A time-series model with a distributed lag non-linear model was first employed to estimate the location-specific associations between humid-hot events and mortality, then we conducted meta-analysis to pool the mortality effect of humid-hot events. Finally, an additive interaction model was used to examine the interactive effect between high temperature and relative humidity. RESULTS The excess rate (ER) of non-accidental mortality attributed to dry-hot events was 10.18% (95% confidence interval (CI): 8.93%, 11.45%), which was higher than that of wet-hot events (ER = 3.21%, 95% CI: 0.59%, 5.89%). The attributable fraction (AF) of mortality attributed to dry-hot events was 10.00% (95% CI: 9.50%, 10.72%) with higher burden for females, older people, central China, cardiovascular diseases and urban city. While for wet-hot events, AF was much lower (3.31%, 95% CI: 2.60%, 4.30%). We also found that high temperature and low relative humidity had synergistic additive interaction on mortality risk. CONCLUSION Dry-hot events may have a higher risk of mortality than wet-hot events, and the joint effect of high temperature and low relative humidity may be greater than the sum of their individual effects.
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Affiliation(s)
- Wen Fang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Zhixing Li
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jinghua Gao
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Ruilin Meng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, 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
| | - Sui Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, 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
| | - 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
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, 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
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
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12
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Huang K, Hu CY, Yang XY, Zhang Y, Wang XQ, Zhang KD, Li YQ, Wang J, Yu WJ, Cheng X, Cao JY, Zhang T, Kan XH, Zhang XJ. Contributions of ambient temperature and relative humidity to the risk of tuberculosis admissions: A multicity study in Central China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:156272. [PMID: 35644395 DOI: 10.1016/j.scitotenv.2022.156272] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 05/08/2022] [Accepted: 05/23/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND As a communicable disease and major public health issue, many studies have quantified the associations between tuberculosis (TB) and meteorological factors with inconsistent results. The purpose of this multicenter study was to characterize the associations between ambient temperature, humidity and the risk of TB hospitalizations and to investigate potential heterogeneity. METHOD Data on daily hospitalizations for TB, meteorological factors and ambient air pollutants for 16 cities in Anhui Province were collected from 2015 to 2020. A distributed lag nonlinear model (DLNM) was performed to obtain the estimates of meteorological-TB relationships by cities. Then, we used the multivariate meta-regression model to pool the city-specific estimates with air pollution, demographic indicators, medical resource and latitude as potential modifiers to explore the sources of heterogeneity. Finally, we divided the whole province into three regions to validate the meteorological-TB relationships by regions. RESULTS The overall pooled temperature-TB association presented an approximate S-shaped curve, with relative risk (RR) peaking at 5 °C (RR = 1.536, 95% CI: 1.303-1.811) compared to the reference temperature (27 °C). Lag-response curve suggested that low temperature exposure increased the risk of TB hospitalizations at lag 0 and 1 day (lag0 day: RR = 1.136, 95% CI: 1.048-1.231, lag1 day: RR = 1.052, 95% CI: 1.023-1.082). However, the overall exposure-response curve between relative humidity and TB showed almost horizontal line with reference relative humidity to 78%. The residual heterogeneity ranged from 27.1% to 36.9%, with air pollution, latitude and medical resource explained the largest proportion. CONCLUSION We found that low temperature exposure is associated with an acute increased risk of TB hospitalizations in Anhui Province. The association between temperature and TB admission varies depending on air pollution, latitude, and medical resources. Since the effect of short-term exposure to humidity is not significant, further studies are supposed to focus on the long-term effect of humidity.
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Affiliation(s)
- Kai Huang
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei 230601, China; Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Cheng-Yang Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Xi-Yao Yang
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei 230601, China
| | - Yunquan Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Medical College, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Xin-Qiang Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Kang-Di Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Ying-Qing Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Jie Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Wen-Jie Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Xin Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China
| | - Ji-Yu Cao
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, Anhui, China
| | - Tao Zhang
- Anhui Chest Hospital, 397 Jixi Road, Hefei 230022, China
| | - Xiao-Hong Kan
- Anhui Chest Hospital, 397 Jixi Road, Hefei 230022, China; Anhui Medical University Clinical College of Chest, 397 Jixi Road, Hefei 230022, China.
| | - Xiu-Jun Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei 230032, China.
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13
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Chen S, Dai M, Hu J, Cheng J, Duan Y, Zou X, Su Y, Liu N, Jingesi M, Chen Z, Yin P, Huang S, He Q, Wang P. Evaluating the predictive ability of temperature-related indices on the stroke morbidity in Shenzhen, China: Under cross-validation methods framework. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:156425. [PMID: 35660600 DOI: 10.1016/j.scitotenv.2022.156425] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/29/2022] [Accepted: 05/30/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Composite temperature-related indices have been utilized to comprehensively reflect the impact of multiple meteorological factors on health. We aimed to evaluate the predictive ability of temperature-related indices, choose the best predictor of stroke morbidity, and explore the association between them. METHODS We built distributed lag nonlinear models to estimate the associations between temperature-related indices and stroke morbidity and then applied two types of cross-validation (CV) methods to choose the best predictor. The effects of this index on overall stroke, intracerebral hemorrhage (ICH), and ischemic stroke (IS) morbidity were explored and we explained how this index worked using heatmaps. Stratified analyses were conducted to identify vulnerable populations. RESULTS Among 12 temperature-related indices, the alternative temperature-humidity index (THIa) had the best overall performance in terms of root mean square error when combining the results from two CVs. With the median value of THIa (25.70 °C) as the reference, the relative risks (RRs) of low THIa (10th percentile) reached a maximum at lag 0-10, with RRs of 1.20 (95%CI:1.10-1.31), 1.49 (95%CI:1.29-1.73) and 1.12 (95%CI:1.03-1.23) for total stroke, ICH and IS, respectively. According to the THIa formula, we matched the effects of THIa on stroke under various combinations of temperature and relative humidity. We found that, although the low temperature (<20 °C) had the greatest adverse effect, the modification effect of humidity on it was not evident. In contrast, lower humidity could reverse the protective effect of temperature into a harmful effect at the moderate-high temperature (24 °C-27 °C). Stratification analyses showed that the female was more vulnerable to low THIa in IS. CONCLUSIONS THIa is the best temperature-related predictor of stroke morbidity. In addition to the most dangerous cold weather, the government should pay more attention to days with moderate-high temperature and low humidity, which have been overlooked in the past.
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Affiliation(s)
- Siyi Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Mengyi Dai
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jing Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jinquan Cheng
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Yanran Duan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuan Zou
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Youpeng Su
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ning Liu
- Department of Environment and Health, Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Maidina Jingesi
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ziwei Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Suli Huang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Qingqing He
- School of Resource and Environmental Engineering, Wuhan University of Technology, Wuhan, China
| | - Peng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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14
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Li C, Zhu Y, She K, Jia Y, Liu T, Han C, Fang Q, Cheng C, Han L, Liu Y, Zhang Y, Li X. Modified effects of air pollutants on the relationship between temperature variability and hand, foot, and mouth disease in Zibo City, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:44573-44581. [PMID: 35133585 DOI: 10.1007/s11356-022-18817-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 01/19/2022] [Indexed: 06/14/2023]
Abstract
Hand, foot, and mouth disease (HFMD) poses a great disease burden in China. However, there are few studies on the relationship between temperature variability (TV) and HFMD. Moreover, whether air pollutions have modified effects on this relationship is still unknown. Therefore, this study aims to explore the modified effects of air pollutants on TV-HFMD association in Zibo City, China. Daily data of HFMD cases, meteorological factors, and air pollutants from 2015 to 2019 were collected for Zibo City. TV was estimated by calculating standard deviation of minimum and maximum temperatures over the exposure days. We used generalized additive model to estimate the association between TV and HFMD. The modified effects of air pollutants were assessed by comparing the estimated TV-HFMD associations between different air stratums. We found that TV increased the risk of HFMD. The effect was strongest at TV03 (4 days of exposure), when the incidence of HFMD increased by 3.6% [95% CI: 1.3-5.9%] for every 1℃ increases in TV. Males, children aged 0-4 years, were more sensitive to TV. We found that sulfur dioxide (SO2) enhanced TV's effects on all considered exposure days, while ozone (O3) reduced TV's effects on some exposure days in whole concerned population. However, we did not detect significant effect modification by particulate matter less than 10 microns in aerodynamic diameter (PM10). These findings are of significance in developing policies and public health practices to reduce the risks of HFMD by integrating changes in temperatures and air pollutants.
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Affiliation(s)
- Chunyu Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Yuchen Zhu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Kaili She
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Yan Jia
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Tingxuan Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Chuang Han
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Qidi Fang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Chuanlong Cheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Luyi Han
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Ying Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China
| | - Ying Zhang
- School of Public Health, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, 2006, Australia
| | - Xiujun Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44# Wenhuaxi Road, Lixia District, Jinan, 250012, Shandong, China.
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15
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Zhao R, Gao Q, Hao Q, Wang S, Zhang Y, Li H, Jiang B. The exposure-response association between humidex and bacillary dysentery: A two-stage time series analysis of 316 cities in mainland China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 797:148840. [PMID: 34303970 DOI: 10.1016/j.scitotenv.2021.148840] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 06/22/2021] [Accepted: 06/30/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Many studies have reported the interactive effects between relative humidity and temperature on infectious diseases. However, evidence regarding the combined effects of relative humidity and temperature on bacillary dysentery (BD) is limited, especially for large-scale studies. To address this research need, humidex was utilized as a comprehensive index of relative humidity and temperature. We aimed to estimate the effect of humidex on BD across mainland China, evaluate its heterogeneity, and identify potential effect modifiers. METHODS Daily meteorological and BD surveillance data from 2014 to 2016 were obtained for 316 prefecture-level cities in mainland China. Humidex was calculated on the basis of relative humidity and temperature. A multicity, two-stage time series analysis was then performed. In the first stage, a common distributed lag non-linear model (DLNM) was established to obtain city-specific estimates. In the second stage, a multivariate meta-analysis was conducted to pool these estimates, assess the significance of heterogeneity, and explore potential effect modifiers. RESULTS The pooled cumulative estimates showed that humidex could promote the transmission of BD. The exposure-response relationship was nearly linear, with a maximum cumulative relative risk (RR) of 1.45 [95% confidence interval (CI): 1.29-1.63] at a humidex value of 40.94. High humidex had an acute adverse effect on BD. The humidex-BD relationship could be modified by latitude, urbanization rate, the natural growth rate of population, and the number of primary school students per thousand persons. CONCLUSIONS High humidex could increase the risk of BD incidence. Thus, it is suitable to incorporate humidex as a predictor into the early warning system of BD and to inform the general public in advance to be cautious when humidex is high. This is especially true for regions with higher latitude, higher urbanization rates, lower natural growth rates of population, and lower numbers of primary school students per thousand persons.
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Affiliation(s)
- Ran Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Qi Gao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Qiang Hao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Shuzi Wang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Yiwen Zhang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Hao Li
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China
| | - Baofa Jiang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, People's Republic of China; Shandong University Climate Change and Health Center, Jinan 250012, Shandong Province, People's Republic of China.
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16
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Liu Z, Wang S, Zhang Y, Xiang J, Tong MX, Gao Q, Zhang Y, Sun S, Liu Q, Jiang B, Bi P. Effect of temperature and its interactions with relative humidity and rainfall on malaria in a temperate city Suzhou, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:16830-16842. [PMID: 33394450 DOI: 10.1007/s11356-020-12138-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Accepted: 12/16/2020] [Indexed: 06/12/2023]
Abstract
Malaria is a climate-sensitive infectious disease. Many ecological studies have investigated the independent impacts of ambient temperature on malaria. However, the optimal temperature measures of malaria and its interaction with other meteorological factors on malaria transmission are less understood. This study aims to investigate the effect of ambient temperature and its interactions with relative humidity and rainfall on malaria in Suzhou, a temperate climate city in Anhui Province, China. Weekly malaria and meteorological data from 2005 to 2012 were obtained for Suzhou. A distributed lag nonlinear model was conducted to quantify the effect of different temperature measures on malaria. The best measure was defined as that with the minimum quasi-Akaike information criterion. GeoDetector and Poisson regression models were employed to quantify the interactions of temperature, relative humidity, and rainfall on malaria transmission. A total of 13,382 malaria cases were notified in Suzhou from 2005 to 2012. Each 5 °C rise in average temperature over 10 °C resulted in a 22% (95% CI: 17%, 28%) increase in malaria cases at lag of 4 weeks. In terms of cumulative effects from lag 1 to 8 weeks, each 5 °C increase over 10 °C caused a 175% growth in malaria cases (95% CI: 139%, 216%). Average temperature achieved the best performance in terms of model fitting, followed by minimum temperature, most frequent temperature, and maximum temperature. Temperature had an interactive effect on malaria with relative humidity and rainfall. High temperature together with high relative humidity and high rainfall could accelerate the transmission of malaria. Meteorological factors may affect malaria transmission interactively. The research findings could be helpful in the development of weather-based malaria early warning system, especially in the context of climate change for the prevention of possible malaria resurgence.
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Affiliation(s)
- Zhidong Liu
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan City, Shandong Province, People's Republic of China
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
| | - Shuzi Wang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Ying Zhang
- School of Public Health, China Studies Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Jianjun Xiang
- School of Public Health, Fujian Medical University, Fuzhou, People's Republic of China
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Michael Xiaoliang Tong
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Qi Gao
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Yiwen Zhang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China
| | - Shuyue Sun
- National Meteorological Center, China Meteorological Administration, Beijing, People's Republic of China
| | - Qiyong Liu
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China
- State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, People's Republic of China
| | - Baofa Jiang
- Shandong University Climate Change and Health Center, Jinan City, Shandong Province, People's Republic of China.
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, No. 44 Wenhuaxi Road, Jinan City, 250012, Shandong Province, People's Republic of China.
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
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