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Rida J, Bouchriti Y, Ait Haddou M, Achbani A, Sine H, Serhane H. Meteorological factors and climate change impact on asthma: a systematic review of epidemiological evidence. J Asthma 2024:1-10. [PMID: 38953539 DOI: 10.1080/02770903.2024.2375272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Accepted: 06/28/2024] [Indexed: 07/04/2024]
Abstract
OBJECTIVE This systematic review aimed to investigate the epidemiological data about meteorological factors and climate change (CC) impact on asthma. DATA SOURCES A search was performed using three databases (Web of Science, Science Direct, and MEDLINE) for all relevant studies published from January 1, 2018, to December 31, 2022. STUDY SELECTIONS This systematic review complied with the PRISMA document's requirements, including studies related to meteorological factors and CC impact on asthma. The search included studies published in English or French language, and was based on title, abstract, and complete text. Documents not meeting inclusion requirements were excluded. RESULTS We identified 18 studies published in the last five years that were eligible for inclusion in this review. We found that these studies concerned European, Asian, American, and Oceanic cities. Extreme variations in temperature, humidity, wind speed, exceptional incidents like hurricanes, cold and heat waves, and seasonal shifts were strongly correlated with the worsening of asthmatic symptoms, particularly in childhood. In addition, excessive concentrations of air pollutants and aeroallergens were linked to pediatric asthma emergency hospital admissions. CONCLUSIONS A significant association between the consequences of CC and asthma in adults particularly in children has been demonstrated. Future research should quantify the impact of global change in climate regarding the aeroallergens' distribution in terms of geography and time. It is also necessary to research the impact of air pollution on asthmatic health, like sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and particles having an aerodynamic diameter lower than 2.5 µm (PM2.5).
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Affiliation(s)
- Jamila Rida
- Research Laboratory of Innovation in Health Sciences, Faculty of Medicine and Pharmacy, Ibn Zohr University, Agadir, Morocco
- High Institute of Nursing Professions and Health Techniques, Health Sciences and Environment Laboratory, Health Sciences, Epidemiology and Human Pathologies Research Team, Agadir, Morocco
| | - Youssef Bouchriti
- High Institute of Nursing Professions and Health Techniques, Health Sciences and Environment Laboratory, Health Sciences, Epidemiology and Human Pathologies Research Team, Agadir, Morocco
- Geosciences, Environment and Geomatic Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
| | - Mohamed Ait Haddou
- Geosciences, Environment and Geomatic Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
- Department of Geography, Faculty of Humanities and Social Sciences, Ibn Tofail University, Kenitra, Morocco
| | - Abderrahmane Achbani
- Laboratory of Cell Biology and Molecular Genetics, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
- High Institute of Nursing Professions and Health Techniques, Marrakesh, Morocco
| | - Hasnaa Sine
- Laboratory of Cell Biology and Molecular Genetics, Faculty of Sciences, Ibn Zohr University, Agadir, Morocco
- High Institute of Nursing Professions and Health Techniques, Marrakesh, Morocco
| | - Hind Serhane
- Research Laboratory of Innovation in Health Sciences, Faculty of Medicine and Pharmacy, Ibn Zohr University, Agadir, Morocco
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Li W, Wang J, Huang W, Yan Y, Liu Y, Zhao Q, Chen M, Yang L, Guo Y, Ma W. The association between humidex and tuberculosis: a two-stage modelling nationwide study in China. BMC Public Health 2024; 24:1289. [PMID: 38734652 PMCID: PMC11088084 DOI: 10.1186/s12889-024-18772-8] [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: 02/21/2024] [Accepted: 05/03/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND Under a changing climate, the joint effects of temperature and relative humidity on tuberculosis (TB) are poorly understood. To address this research gap, we conducted a time-series study to explore the joint effects of temperature and relative humidity on TB incidence in China, considering potential modifiers. METHODS Weekly data on TB cases and meteorological factors in 22 cities across mainland China between 2011 and 2020 were collected. The proxy indicator for the combined exposure levels of temperature and relative humidity, Humidex, was calculated. First, a quasi-Poisson regression with the distributed lag non-linear model (DLNM) was constructed to examine the city-specific associations between humidex and TB incidence. Second, a multivariate meta-regression model was used to pool the city-specific effect estimates, and to explore the potential effect modifiers. RESULTS A total of 849,676 TB cases occurred in the 22 cities between 2011 and 2020. Overall, a conspicuous J-shaped relationship between humidex and TB incidence was discerned. Specifically, a decrease in humidex was positively correlated with an increased risk of TB incidence, with a maximum relative risk (RR) of 1.40 (95% CI: 1.11-1.76). The elevated RR of TB incidence associated with low humidex (5th humidex) appeared on week 3 and could persist until week 13, with a peak at approximately week 5 (RR: 1.03, 95% CI: 1.01-1.05). The effects of low humidex on TB incidence vary by Natural Growth Rate (NGR) levels. CONCLUSION A J-shaped exposure-response association existed between humidex and TB incidence in China. Humidex may act as a better predictor to forecast TB incidence compared to temperature and relative humidity alone, especially in regions with higher NGRs.
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Affiliation(s)
- Wen Li
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Shandong University Climate Change and Health Center, Jinan, Shandong, China
| | - Jia Wang
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenzhong Huang
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yu Yan
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Shandong University Climate Change and Health Center, Jinan, Shandong, China
| | - Yanming Liu
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Qi Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Shandong University Climate Change and Health Center, Jinan, Shandong, China
| | - Mingting Chen
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Liping Yang
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Wei Ma
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
- Shandong University Climate Change and Health Center, Jinan, Shandong, 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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Zhang J, Tao Y, Wang Y, Ji X, Wu Y, Zhang F, Wang Z. Independent and interaction effects of prenatal exposure to high AQI and extreme Humidex on the risk of preterm birth: A large sample population study in northern China. Reprod Toxicol 2024; 124:108544. [PMID: 38246475 DOI: 10.1016/j.reprotox.2024.108544] [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: 10/17/2023] [Revised: 12/29/2023] [Accepted: 01/17/2024] [Indexed: 01/23/2024]
Abstract
The combined effects of air pollution and extreme temperature on PTB remain unclear. To evaluate the independent effect and interaction effect of prenatal extreme exposure to air quality index (AQI) and Humidex, on PTB. Based on the National Health Care Data Platform of Shandong University, women who gave birth in 2019-2020 were selected for the study. First, the independent effects of AQI and Humidex on PTB were assessed by logistic regression model. Subsequently, the interaction effects of AQI and Humidex on PTB were estimated separately by calculation of the relative excess risk of interaction (RERI). A total of 34365 pregnant women were included and 1975 subjects were diagnosed with PTB. We observed a significant increase in the odds of PTB associated with maternal high AQI exposure, with an OR of 1.70 (95% CI: 1.59, 1.81). Similarly, extreme exposure to Humidex also demonstrated an elevated PTB odds, with a low Humidex OR of 2.48 (95% CI: 2.23, 2.76) and a high Humidex OR of 1.48 (95% CI: 1.31, 1.67). Finally, we observed an interaction between high AQI and extreme Humidex during the 1st trimester. Interaction effects were noted between high AQI and low Humidex throughout the entire trimester and the 2nd trimester. This study suggests that prenatal exposure to high AQI and extreme Humidex could increase the odds of PTB, with effects exhibiting the sensitivity window and a cumulative trend. Additionally, there is an interaction between AQI and Humidex.
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Affiliation(s)
- Jiatao Zhang
- Department of Occupational and Environmental Health, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China
| | - Yu Tao
- Department of Occupational and Environmental Health, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China
| | - Yongchao Wang
- Institute for Medical Dataology, Shandong University, Shandong, PR China
| | - Xiaokang Ji
- Institute for Medical Dataology, Shandong University, Shandong, PR China
| | - Yanling Wu
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China
| | - Fengmei Zhang
- Department of Occupational and Environmental Health, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China.
| | - Zhiping Wang
- Department of Occupational and Environmental Health, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, PR China; Institute for Medical Dataology, Shandong University, Shandong, PR China.
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Zhao H, Yang Y, Feng C, Wang W, Yang C, Yin Y, Gong L, Lin T. Nonlinear effects of humidex on risk of outpatient visit for allergic conjunctivitis among children and adolescents in Shanghai, China: A time series analysis. J Glob Health 2023; 13:04132. [PMID: 37921044 PMCID: PMC10623378 DOI: 10.7189/jogh.13.04132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2023] Open
Abstract
Background Various epidemiological studies have focused on the adverse health outcomes of meteorological factors. However, there has been little research on the impact of humidex on allergic conjunctivitis, especially in child and adolescent populations. We aimed to explore the impact of humidex, a comprehensive index of relative humidity and temperature, on child and adolescent allergic conjunctivitis admissions. Methods Outpatient visit data for allergic conjunctivitis, meteorological factors and air pollutants in Shanghai for the 2017-2022 period were retrieved. For the purpose of analysing the nonlinear connection and lag impact between humidex and admissions for paediatric and adolescent allergic conjunctivitis, the distributed lag nonlinear model (DLNM) was fitted. Results A total of 147 090 cases were included in our cohort. We found a significantly nonlinear effect on humidex and allergic conjunctivitis. In the single-day lag pattern, the relative risks (RR) of allergic conjunctivitis were significant at lag 0 (RR = 1.08, 95% confidence interval (CI) = 1.05-1.11) to lag 2 (RR = 1.01, 95% CI = 1.00-1.01), lag 5 (RR = 1.01, 95% CI = 1.00-1.01) to lag 9 (RR = 1.01, 95% CI = 1.00-1.01), and lag 14 (RR = 1.02, 95% CI: 1.01-1.03). In the cumulative-lag day pattern, the RR of allergic conjunctivitis were significant at lag 0-0 (RR = 1.08, 95% CI = 1.05-1.11) to lag 0-14 (RR = 1.21, 95% CI = 1.13-1.28). We found that boys, children aged 7-17 years, and children in the warm season were more vulnerable to humidex. In addition, the highest attributable fraction (AF) and attributable number (AN) of humidex are at lag 0-14 (AF = 0.17, AN = 25 026). Conclusions Humidex exposure markedly increased the risk of allergic conjunctivitis, especially in highly high humidex. Appropriate public health management is needed for disease management and early intervention.
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Affiliation(s)
- Han Zhao
- Department of Ophthalmology, Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Hunan Clinical Research Center of Ophthalmic Disease, Changsha, Hunan, China
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Yun Yang
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Changming Feng
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Wushuang Wang
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Chenhao Yang
- Department of Ophthalmology, Children's Hospital of Fudan University, Shanghai, China
| | - Yue Yin
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Lan Gong
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
| | - Tong Lin
- Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, China
- Laboratory of Myopia, NHC Key Laboratory of Myopia (Fudan University), Chinese Academy of Medical Sciences, Shanghai, China
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Ding J, Han S, Wang X, Yao Q. Impact of air pollution changes and meteorology on asthma outpatient visits in a megacity in North China Plain. Heliyon 2023; 9:e21803. [PMID: 38027642 PMCID: PMC10651508 DOI: 10.1016/j.heliyon.2023.e21803] [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: 07/18/2023] [Revised: 09/08/2023] [Accepted: 10/28/2023] [Indexed: 12/01/2023] Open
Abstract
The effects of air pollution and meteorology on asthma is less studied in North China Plain. In the last decade, air quality in this region is markedly mitigated. This study compared the short-term effects of air pollutants on daily asthma outpatient visits (AOV) within different sex and age groups from 2014 to 2016 and 2017-2019 in Tianjin, with the application of distributed lag nonlinear model. Moreover, relative humidity (RH) and temperature as well as the synergistic impact with air pollutants were assessed. Air pollutants-associated risk with linear (different reference values were used) and non-linear assumptions were compared. In 2014-2016, PM10 and PM2.5 exhibited a larger impact on AOV, with the corresponding cumulative excess risks (ER) for every 10 μg/m3 increase at 1.04 % (95%CI:0.67-1.40 %, similarly hereafter) and 0.79 % (0.35-1.23 %), as well as increased to 43 % (26-63 %) and 20 % (10-31 %) at severe pollution. In 2017-2019, NO2 and MDA8 O3 exhibited a larger impact on AOV, with a cumulative ER for every 10 μg/m3 increase at 1.0 (0.63-1.4 %) and 0.36 % (0.15-0.57 %), with corresponding values of 7.9 % (4.8-11 %) and 5.6 % (2.3-9.0 %), at severe pollution. SO2 associated risk was only significant from 2014 to 2016. Cold effect, including extremely low temperature exposure and sharp temperature drop could generate a pronounced increase in AOV at 9.6 % (3.8-16 %) and 24 % (9.1-41 %), respectively. Moderate low temperature combined with air pollutants can enhance AOV during winter. Higher temperature in spring and autumn could trigger asthma by increasing pollen levels. Low RH resulted in AOV increase by 4.6 % (2.4-6.9), while higher RH generated AOV increase by 3.4 % (1.6-5.3). Females, children, and older adults tended to have a higher risk for air pollution, non-optimum temperature, and RH. As air pollution-associated risks on AOV tends to be weaker due to air quality improvement in recent years, the impact of extreme meteorological condition amidst climate change on asthma visits warrants further attention.
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Affiliation(s)
- Jing Ding
- Tianjin Environmental Meteorological Center, Tianjin 300070, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300070, China
| | - Suqin Han
- Tianjin Environmental Meteorological Center, Tianjin 300070, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300070, China
| | - Xiaojia Wang
- Tianjin Environmental Meteorological Center, Tianjin 300070, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300070, China
| | - Qing Yao
- Tianjin Environmental Meteorological Center, Tianjin 300070, China
- CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300070, 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: 2.0] [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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McDermott-Levy R, Pennea E, Moore C. Protecting Children's Health: Asthma and Climate Change. MCN Am J Matern Child Nurs 2023; 48:188-194. [PMID: 36943899 DOI: 10.1097/nmc.0000000000000927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
ABSTRACT Children are particularly vulnerable to the impacts of climate change. Their lungs are developing, making children with asthma especially susceptible to temperature extremes, variations in precipitation, poor air quality, and changes in pollen and flora. Structural and social determinants of health, such as racism and poverty, that disproportionately affect children of color are linked to higher rates of asthma and negative effects of climate change. These factors lead to increased absences from school and social activities, loss of work for caregivers, and increased health care costs, thus negatively affecting children, their families, and the greater community. Nurses must support caregivers and children to link climate change to asthma care, be involved in health education; climate change mitigation and adaptation strategies and policies; and develop the evidence to address climate change and asthma strategies. We address the impacts of climate change on children with asthma and nursing adaptation responses.
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Zhou Y, Ji A, Tang E, Liu J, Yao C, Liu X, Xu C, Xiao H, Hu Y, Jiang Y, Li D, Du N, Li Y, Zhou L, Cai T. The role of extreme high humidex in depression in chongqing, China: A time series-analysis. ENVIRONMENTAL RESEARCH 2023; 222:115400. [PMID: 36736551 DOI: 10.1016/j.envres.2023.115400] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/18/2023] [Accepted: 01/30/2023] [Indexed: 06/18/2023]
Abstract
As global climate change intensifies, people are paying increasing attention to the impact of temperature changes on adverse mental health outcomes, especially depression. While increasing attention has been paid to the effect of temperature, there is little research on the effect of humidity. We aimed to investigate the association between humidex, an index combining temperature and humidity to reflect perceived temperature, and outpatient visits for depression from 2014 to 2019 in Chongqing, the largest and one of the most hot and humid cities of China. We also aimed to further identify susceptible subgroups. A distributed lag non-linear model (DLNM) was used to explore the concentration-response relationship between humidex and depression outpatient visits. Hierarchical analysis was carried out by age and gender. A total of 155,436 visits for depression were collected from 2014 to 2019 (2191 days). We found that depression outpatient visits were significantly associated with extremely high humidex (≥40). The significant positive single-lag day effect existed at lag 0 (RR = 1.029, 95%CI: 1.000-1.059) to lag 2 (RR = 1.01, 95%CI: 1.004-1.028), and lag 12 (RR = 1.013, 95%CI: 1.002-1.024). The significant cumulative adverse effects lasted from lag 01 to lag 014. Hierarchical analyses showed that females and the elderly (≥60 years) appeared to be more susceptible to extremely high humidex. The attributable numbers (AN) and fraction (AF) of extremely high humidex on depression outpatients were 1709 and 1.10%, respectively. Extremely high humidex can potentially increase the risk of depression, especially in females and the elderly. More protective measures should be taken in vulnerable populations.
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Affiliation(s)
- Yumeng Zhou
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ailing Ji
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, 401331, China
| | - Enjie Tang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Jianghong Liu
- Department of Family and Community Health, University of Pennsylvania School of Nursing, Philadelphia, PA, 19104, USA
| | - Chunyan Yao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Xiaoling Liu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710032, China
| | - Hua Xiao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yuegu Hu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yuexu Jiang
- Department of Nutrition and Food Hygiene, School of Public Health Guizhou Medical University, Guiyang, 550025, China
| | - Dawei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ning Du
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yafei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Laixin Zhou
- Medical Department, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Tongjian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
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10
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Wu X, Ge Y, Gong D, Zhang X, Hu S, Liu Q. Reconstruction of the hourly fine-resolution apparent temperature (Humidex) with the aerodynamic parameters. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 866:161253. [PMID: 36603631 DOI: 10.1016/j.scitotenv.2022.161253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 10/21/2022] [Accepted: 12/24/2022] [Indexed: 06/17/2023]
Abstract
Apparent temperature is the preferred measure of hotness or coldness expressed to depict the human sense. Spatially explicit measurement of the hourly apparent temperature is essential for capturing the threats to bioclimatic comfort and preventing potential mortality/morbidity risk from heat or cold. However, existing apparent temperature products only provide daily observations at the spatial resolution of several dozen kilometers, resulting in some substantial underestimations for some life-threatening thermal stresses highly localized in space and time. Furthermore, some data-driven models lack mechanical constraints on the turbulent exchange between the surface and the atmosphere, making some unsatisfactory accuracy. Here, we propose Humidex reconstruction model incorporating atmospheric dynamics theory and aerodynamic parameters (i.e., heat and momentum roughness lengths for natural surfaces and three urban canopy geometry parameters for artificial surfaces), capable of developing an hourly dataset at fine-grained spatial resolution (0.01° × 0.01°). In this study, a total of 2952 h in four seasons were selected to test the seasonal performance of this model, taking the Yangtze River Delta as an example. The results show that the Humidex products from this model generally outperform the existing comparable products, with the hourly population root mean square error (RMSE) ranging from 1 to 2 °C in winter and autumn and 2-3 °C in spring and summer. Moreover, the constraint of aerodynamic parameters can reduce RMSE with a significant margin for each season, up to 2 °C, especially in areas with dense woodlands or buildings. In addition, the results demonstrate the excellent performance of this model in capturing short-lived thermal health threats, which are easily overlooked when observed data only provides a daily variation. This indicates that the model can allow researchers and practitioners investigate the fine-grained spatial and temporal evolution of thermal stress and its impact on public health, tourism, learning, and work performance.
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Affiliation(s)
- Xilin Wu
- State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Academy of Sciences, Beijing 100049, China
| | - Yong Ge
- State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Academy of Sciences, Beijing 100049, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China.
| | - Daoyi Gong
- Key Laboratory of Environmental Change and Natural Disasters, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Xining Zhang
- State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Academy of Sciences, Beijing 100049, China
| | - Shan Hu
- State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Academy of Sciences, Beijing 100049, China
| | - Qingsheng Liu
- State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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11
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Wu Y, Liang M, Liang Q, Yang X, Sun Y. A distributed lag non-linear time-series study of ambient temperature and healthcare-associated infections in Hefei, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2023; 33:258-267. [PMID: 34915779 DOI: 10.1080/09603123.2021.2017862] [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: 09/08/2021] [Accepted: 12/08/2021] [Indexed: 06/14/2023]
Abstract
Little is known about the effects of temperature on healthcare-associated infections (HAIs). A distributed lag non-linear model was used to estimate the association between ambient temperature and HAIs in Hefei, China. In total, 9,592 HAIs were included. The effect of low temperature (-0.1°C, 2.5th percentile) was significant on the current day (RR = 1.108, 95%CI:1.003-1.222), and then appeared on the 4th day (RR = 1.045, 95%CI:1.007-1.084) and the 5th day (RR = 1.033, 95%CI:1.006-1.061). The cumulative lag effects of low temperature lasted from the 5th to 10th days (RR = 1.123-1.143), and a long-term cumulative lag effect was observed on the 14th day (RR = 1.157, 95%CI:1.001-1.338). The lag effect of high temperature (31.0°C, 97.5th percentile) was not statistically significant. However, the effects of temperatures on HAIs were not significant among gender or age subgroups. This study suggests that the low temperatures have acute and lag effects on HAIs in Hefei, China.
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Affiliation(s)
- Yile Wu
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Mingming Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Qiwei Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Department of Hospital infection Prevention and Control, Children's Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xiyao Yang
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Yehuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
- Center for Evidence-Based Practice, Anhui Medical University, Hefei, Anhui, China
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12
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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: 6] [Impact Index Per Article: 6.0] [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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13
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Wang H, Ma Y, Cheng B, Li H, Feng F, Zhang C, Zhang Y. Health effect of temperature change on respiratory diseases in opposite phase in semi-arid region. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:12953-12964. [PMID: 36117224 DOI: 10.1007/s11356-022-23056-y] [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: 06/28/2022] [Accepted: 09/13/2022] [Indexed: 06/15/2023]
Abstract
The impact of temperature variation on health has attracted increasing attention under global climate change. A distributed lag non-linear model (DLNM) was performed to estimate the risk of two indicators of temperature change (diurnal temperature range (DTR) and temperature change between neighboring days (TCN)) on respiratory hospital visits in Lanzhou, a semi-arid climate city in western China from 2012 to 2018. The whole year is divided into two different temperature change periods according to the TCN of each solar term. The results showed that extreme high DTR can apparently enlarge respiratory risk, and it indicated strong cumulative relative risk (RR) in the temperature drop period. Extreme low TCN had strong adverse effects on respiratory diseases especially in temperature rise period, with the greatest RR of 1.068 (95% CI 1.004, 1.136). The effect of extreme high TCN was more obvious in temperature drop period, with a RR of 1.082 (95% CI 1.021, 1.148) at lag 7. Females were more affected by extreme temperature changes. Young people were more vulnerable to DTR, while TCN has a greater impact on the elderly.
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Affiliation(s)
- Hang Wang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Yuxia Ma
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China.
| | - Bowen Cheng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Heping Li
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Fengliu Feng
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
| | - Caixia Zhang
- Dingxi First People's Hospital, Dingxi, 743000, China
| | - Yifan Zhang
- College of Atmospheric Sciences, Key Laboratory of Semi-Arid Climate Change, Ministry of Education, Lanzhou University, Lanzhou, 730000, China
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14
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Jin X, Xu Z, Liang Y, Sun X, Yan S, Wu Y, Li Y, Mei L, Cheng J, Wang X, Song J, Pan R, Yi W, Yang Z, Su H. The modification of air particulate matter on the relationship between temperature and childhood asthma hospitalization: An exploration based on different interaction strategies. ENVIRONMENTAL RESEARCH 2022; 214:113848. [PMID: 35817164 DOI: 10.1016/j.envres.2022.113848] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 06/28/2022] [Accepted: 07/05/2022] [Indexed: 06/15/2023]
Abstract
The influence of temperature on childhood asthma was self-evident, yet the issue of whether the relationship will be synergized by air pollution remains unclear. The study aimed to investigate whether the relationship between short-term temperature exposure and childhood asthma hospitalization was modified by particulate matter (PM). Data on childhood asthma hospitalization, meteorological factors, and air pollutants during 2013-2016 in Hefei, China, were collected. First, a basic Poisson regression model combined with a distributed lag nonlinear model was used to assess the temperature-childhood asthma hospitalization relationship. Then, two interactive strategies were applied to explore the modification effect of PM on the temperature-childhood asthma hospitalization association. We found a greater effect of cold (5th percentile of temperature) on asthma during days with higher PM2.5 (RR: 2.16, 95% CI: 1.38, 3.38) or PM10 (RR: 1.87, 95% CI:1.20, 2.91) than that during days with lower PM2.5 (RR: 1.64, 95% CI: 1.06, 2.54) or PM10 (RR: 1.52, 95% CI: 0.98, 2.36). In addition, we observed a greater modification effect of PM2.5 on the cold-asthma association than did PM10, with a per 10 μg/m3 increase in PM2.5 and PM10 associated with increases of 0.065 and 0.025 for the RR corresponding to the 5th temperature percentile, respectively. For the temperature-related AF, moderate cold showed the largest change magnitude with the PM levels rising compared with other temperature ranges. For the subgroup, Females and those aged 6-18 years were more sensitive to the modification effect of PM2.5 or PM10 on the cold-asthma association. Our findings demonstrated that particulate matter could modify the associations between temperature and childhood asthma hospitalization.
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Affiliation(s)
- Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xu Wang
- Anhui Provincial Children's Hospital, Hefei, Anhui, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zeyu Yang
- Anhui Provincial Children's Hospital, Hefei, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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15
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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: 8] [Impact Index Per Article: 4.0] [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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16
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Chen Y, Kong D, Fu J, Zhang Y, Zhao Y, Liu Y, Chang Z, Liu Y, Liu X, Xu K, Jiang C, Fan Z. Associations between ambient temperature and adult asthma hospitalizations in Beijing, China: a time-stratified case-crossover study. Respir Res 2022; 23:38. [PMID: 35189885 PMCID: PMC8862352 DOI: 10.1186/s12931-022-01960-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 02/15/2022] [Indexed: 11/30/2022] Open
Abstract
Background Studies on the associations between ambient temperature and asthma hospitalizations are limited, and the results are controversial. We aimed to assess the short-term effects of ambient temperature on the risk of asthma hospitalizations and quantify the hospitalization burdens of asthma attributable to non-optimal temperature in adults in Beijing, China. Methods We collected daily asthma hospitalizations, meteorological factors and air quality data in Beijing from 2012 to 2015. We applied a time-stratified case-crossover design and fitted a distributed lag non-linear model with a conditional quasi-Poisson regression to explore the association between ambient temperature and adult asthma hospitalizations. The effect modifications of these associations by gender and age were assessed by stratified analyses. We also computed the attributable fractions and numbers with 95% empirical confidence intervals (eCI) of asthma hospitalizations due to extreme and moderate temperatures. Results From 2012 to 2015, we identified a total of 18,500 hospitalizations for asthma among adult residents in Beijing, China. Compared with the optimal temperature (22 °C), the cumulative relative risk (CRR) over lag 0–30 days was 2.32 with a 95% confidence interval (CI) of 1.57–3.42 for extreme cold corresponding to the 2.5th percentile (− 6.5 °C) of temperature distribution and 2.04 (95% CI 1.52–2.74) for extreme heat corresponding to the 97.5th percentile (29 °C) of temperature distribution. 29.1% (95% eCI 17.5–38.0%) of adult asthma hospitalizations was attributable to non-optimum temperatures. Moderate cold temperatures yielded most of the burdens, with an attributable fraction of 20.3% (95% eCI 9.1–28.7%). The temperature-related risks of asthma hospitalizations were more prominent in females and younger people (19–64 years old). Conclusions There was a U-shaped association between ambient temperature and the risk of adult asthma hospitalizations in Beijing, China. Females and younger patients were more vulnerable to the effects of non-optimum temperatures. Most of the burden was attributable to moderate cold. Our findings may uncover the potential impact of climate changes on asthma exacerbations. Supplementary Information The online version contains supplementary material available at 10.1186/s12931-022-01960-8.
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Affiliation(s)
- Yuxiong Chen
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Dehui Kong
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Jia Fu
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Yongqiao Zhang
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Yakun Zhao
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Yanbo Liu
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Zhen'ge Chang
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Yijie Liu
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Xiaole Liu
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Kaifeng Xu
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China
| | - Chengyu Jiang
- Department of Biochemistry, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Zhongjie Fan
- Department of Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, No.1 Shuaifuyuan Wangfujing Dongcheng District,, Beijing, 100730, China.
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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: 3.3] [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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Ghada W, Estrella N, Ankerst DP, Menzel A. Universal thermal climate index associations with mortality, hospital admissions, and road accidents in Bavaria. PLoS One 2021; 16:e0259086. [PMID: 34788302 PMCID: PMC8598056 DOI: 10.1371/journal.pone.0259086] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 10/13/2021] [Indexed: 11/18/2022] Open
Abstract
When meteorological conditions deviate from the optimal range for human well-being, the risks of illness, injury, and death increase, and such impacts are feared in particular with more frequent and intense extreme weather conditions resulting from climate change. Thermal indices, such as the universal thermal climate index (UTCI), can better assess human weather-related stresses by integrating multiple weather components. This paper quantifies and compares the seasonal and spatial association of UTCI with mortality, morbidity, and road accidents in the federal state of Bavaria, Germany. Linear regression was applied to seasonally associate daily 56 million hospital admissions and 2.5 million death counts (1995-2015) as well as approximately 930,000 road accidents and 1.7 million people injured (2002-2015) with spatially interpolated same day- and lagged- (up to 14 days) average UTCI values. Additional linear regressions were performed stratifying by age, gender, region, and district. UTCI effects were clear in all three health outcomes studied: Increased UTCI resulted in immediate (1-2 days) rises in morbidity and even more strongly in mortality in summer, and lagged (up to 14 days) decreases in fall, winter, and spring. The strongest UTCI effects were found for road accidents where increasing UTCI led to immediate decreases in daily road accidents in winter but pronounced increases in all other seasons. Differences in UTCI effects were observed e.g. between in warmer north-western regions (Franconia, more districts with heat stress-related mortality, but hospital admissions for lung, heart and external reasons decreasing with summer heat stress), the touristic alpine regions in the south (immediate effect of increasing UTCI on road accidents in summer), and the colder south-eastern regions (increasing hospital admissions for lung, heart and external reasons in winter with UTCI). Districts with high percentages of elderly suffered from higher morbidity and mortality, particularly in winter. The influences of UTCI as well as the spatial and temporal patterns of this influence call for improved infrastructure planning and resource allocation in the health sector.
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Affiliation(s)
- Wael Ghada
- Department of Life Science Systems, Technical University of Munich, Freising, Germany
| | - Nicole Estrella
- Department of Life Science Systems, Technical University of Munich, Freising, Germany
| | - Donna P. Ankerst
- Department of Life Science Systems, Technical University of Munich, Freising, Germany
- Department of Mathematics, Technical University of Munich, Garching, Germany
| | - Annette Menzel
- Department of Life Science Systems, Technical University of Munich, Freising, Germany
- Institute for Advanced Study, Technical University of Munich, Garching, Germany
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Wang X, Xu Z, Su H, Ho HC, Song Y, Zheng H, Hossain MZ, Khan MA, Bogale D, Zhang H, Wei J, Cheng J. Ambient particulate matter (PM 1, PM 2.5, PM 10) and childhood pneumonia: The smaller particle, the greater short-term impact? THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 772:145509. [PMID: 33571778 DOI: 10.1016/j.scitotenv.2021.145509] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 01/25/2021] [Accepted: 01/25/2021] [Indexed: 05/06/2023]
Abstract
BACKGROUND Smaller sizes of ambient particulate matter (PM) can be more toxic and can be breathed into lower lobes of a lung. Children are particularly vulnerable to PM air pollution because of their adverse effects on both lung functions and lung development. However, it remains unknown whether a smaller PM has a greater short-term impact on childhood pneumonia. AIMS We compared the short-term effects on childhood pneumonia from PM with aerodynamic diameters ≤1 μm (PM1), ≤2.5 μm (PM2.5), and ≤10 μm (PM10), respectively. METHODS Daily time-series data (2016-2018) on pneumonia hospitalizations in children aged 0-17 years, records of air pollution (PM1, PM2.5, PM10, and gaseous pollutants), and weather conditions were obtained for Hefei, China. Effects of different PM were quantified using a quasi-Poisson generalized additive model after controlling for day of the week, holiday, seasonality and long-term time trend, and weather variables. Stratified analyses (gender, age, and season) were also performed. RESULTS For each 10 μg/m3 increase in PM1, PM2.5, and PM10 concentrations over the past three days (lag 0-2), the risk of pneumonia hospitalizations increased by 10.28% (95%CI: 5.88%-14.87%), 1.21% (95%CI: 0.34%-2.09%), and 1.10% (95%CI: 0.44%-1.76%), respectively. Additionally, both boys and girls were at risk of PM1 effects, while PM2.5 and PM10 effects were only seen in boys. Children aged ≤12 months and 1-4 years were affected by PM1, but PM2.5 and PM10 were only associated with children aged 1-4 years. Furthermore, PM1 effects were greater in autumn and winter, while greater PM2.5 and PM10 effects were evident only in autumn. CONCLUSION This study suggests a greater short-term impact on childhood pneumonia from PM1 in comparison to PM2.5 and PM10. Given the serious PM pollution in China and other rapid developing countries due to various combustions and emissions, more investigations are needed to determine the impact of different PM on childhood respiratory health.
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Affiliation(s)
- Xu Wang
- Department of Science and Education, Children's Hospital of Anhui Medical University (Anhui Provincial Children's Hospital), Hefei, Anhui, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Hong Su
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China; School of Geography and Remote Sensing, Guangzhou University, Guangzhou, China
| | - Yimeng Song
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China; Smart Cities Research Institute, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | | | - Daniel Bogale
- College of Health Sciences, Arsi University, Asela, Ethiopia
| | - Heng Zhang
- Sir Run Run Shaw Hospital (SRRSH), affiliated with the Zhejiang University School of Medicine, Zhejiang, China
| | - Jing Wei
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China; Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - Jian Cheng
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China.
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Liu X, He Y, Tang C, Wei Q, Xu Z, Yi W, Pan R, Gao J, Duan J, Su H. Association between cold spells and childhood asthma in Hefei, an analysis based on different definitions and characteristics. ENVIRONMENTAL RESEARCH 2021; 195:110738. [PMID: 33485910 DOI: 10.1016/j.envres.2021.110738] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 01/04/2021] [Accepted: 01/07/2021] [Indexed: 06/12/2023]
Abstract
As the global climate continues to warm, there is an increased focus on heat, but the role of low temperatures on health has been overlooked, especially for developing countries. Methods We collected the admission data of childhood asthma in 2013-2016 from Anhui Provincial Children's Hospital, as well as meteorological data from the Meteorological Bureau for the study period and collected data of pollutants from 10 monitoring stations around Hefei city. Poisson's generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM) was used to estimate the short-term effects of cold spell on childhood asthma in cold seasons (November to March). 16 definitions of cold spells were clearly compared, which combining 4 temperature indexes (daily minimum and mean temperature; daily minimum and mean apparent temperature), 2 temperature thresholds (2.5th and 5th) and 3 durations of at least 2-4 days. We then have an analysis of the modifying effect of characteristics of cold spells and individuals(gender and age), with a view to discovering the susceptible population to cold spell. Results There was significant association between cold spells and admission risk for childhood asthma. And the definition, in which daily minimum apparent temperature falls below 5th percentile for at least 3 consecutive days, produced the optimum model fit performance. Based on this optimal fit we found that, for the total population, the effect of cold spell lasted approximately five days (lag1-lag5), with the largest effect occurring in lag 3 (RR = 1.110; 95% CI: 1.052-1.170). In subgroup analysis, the cumulative effect of lag0-7 was higher in males and school-age children than in females and other age groups, respectively. In addition, we found that the effect of is higher as the duration increases. Conclusion This study suggests an association between cold spell and childhood asthma, and minimum AT may be a better indicator to define the cold spells. Boys and school-age children are more vulnerable to cold spell. And one of our very interesting findings is that if a cold spell lasts for several days, the impact of the cold spell on those later days is likely to be greater than that of the previous days. In conclusion, we should pay more attention to the protection of boys and school-aged children in our future public health protection and give more attention to those cold spells that last longer. Therefore, we recommend that schools and health authorities need to take targeted measures to reduce the risk of asthma in children during the cold spell.
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Affiliation(s)
- Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Qiannan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zihan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jiaojiao Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jun Duan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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21
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Hu Y, Cheng J, Jiang F, Liu S, Li S, Tan J, Yin Y, Tong S. Season-stratified effects of meteorological factors on childhood asthma in Shanghai, China. ENVIRONMENTAL RESEARCH 2020; 191:110115. [PMID: 32846175 DOI: 10.1016/j.envres.2020.110115] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 07/19/2020] [Accepted: 08/14/2020] [Indexed: 06/11/2023]
Abstract
OBJECTIVES There has been increasing interest in identifying the adverse effects of ambient environmental factors on asthma exacerbations (AE), but season-stratified effects of meteorological factors on childhood asthma remain unclear. We explored the season-stratified effects of meteorological factors on childhood AE in Shanghai, China. METHODS Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to examine the lagged and nonlinear effects of meteorological factors on childhood AE after adjustment for putative confounders. We also performed a season-stratified analysis to determine whether the season modified the relationship between meteorological factors and childhood AE. RESULTS There were 23,103 emergency department visits (EDVs) for childhood AE, including 15,466 boys and 7637 girls during 2008-2017. Most meteorological factors (e.g., temperature, diurnal temperature range (DTR), relative humidity (RH) and wind speed (WS)) were significantly associated with EDVs for childhood AE, even after adjustment for the confounding effects of air pollutants. In the whole year, extreme cold, moderate heat, higher DTR, lower RH and WS increased the relative risk (RR) for childhood AE. In the cold season, lower RH and wind speed increased the risks of childhood AE (RRlag0-28 for the 5th percentile (p5) of RH: 9.744, 95% CI: 3.567, 26.616; RRlag0-28 for the p5 of wind speed: 10.671, 95% CI: 1.096, 103.879). In the warm season, higher temperature and DTR, lower RH and WS increased the RR for childhood AE (RRlag0-5 for the p95 of temperature: 1.871, 95% CI: 1.246, 2.810; RRlag0-2 for the p95 of DTR: 1.146, 95% CI: 1.010, 1.300; RRlag0-5 for the p5 of RH: 1.931, 95% CI: 1.191, 3.128; RRlag0-2 for the p5 of WS: 1.311, 95% CI: 1.005, 1.709). CONCLUSIONS Extreme meteorological factors appeared to be triggers of EDVs for childhood AE in Shanghai and the effects modified by season. These findings provide evidence for developing season-specific and tailored strategies to prevent and control childhood AE.
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Affiliation(s)
- Yabin Hu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jian Cheng
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia
| | - Fan Jiang
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institution, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shijian Liu
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shenghui Li
- School of Public Health, Shanghai Jiaotong University, Shanghai, China
| | - Jianguo Tan
- Shanghai Key Laboratory of Meteorology and Health (Shanghai Meteorological Service), Shanghai, China
| | - Yong Yin
- Department of Respiratory Medicine, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China.
| | - Shilu Tong
- Department of Clinical Epidemiology and Biostatistics, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, China; School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
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Belotti JT, Castanho DS, Araujo LN, da Silva LV, Alves TA, Tadano YS, Stevan SL, Corrêa FC, Siqueira HV. Air pollution epidemiology: A simplified Generalized Linear Model approach optimized by bio-inspired metaheuristics. ENVIRONMENTAL RESEARCH 2020; 191:110106. [PMID: 32882238 DOI: 10.1016/j.envres.2020.110106] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 07/30/2020] [Accepted: 08/18/2020] [Indexed: 06/11/2023]
Abstract
Studies in air pollution epidemiology are of paramount importance in diagnosing and improve life quality. To explore new methods or modify existing ones is critical to obtain better results. Most air pollution epidemiology studies use the Generalized Linear Model, especially the default version of R, Splus, SAS, and Stata softwares, which use maximum likelihood estimators in parameter optimization. Also, a smooth time function (usually spline) is generally used as a pre-processing step to consider seasonal and long-term tendencies. This investigation introduces a new approach to GLM, proposing the estimation of the free coefficients through bio-inspired metaheuristics - Particle Swarm Optimization (PSO), Genetic Algorithms, and Differential Evolution, as well as the replacement of the spline function by a simple normalization procedure. The considered case studies comprise three important cities of São Paulo state, Brazil with distinct characteristics: São Paulo, Campinas, and Cubatão. We considered the impact of particles with an aerodynamic diameter less than 10 μm (PM10), ambient temperature, and relative humidity in the number of hospital admissions for respiratory diseases (ICD-10, J00 to J99). The results showed that the new approach (especially PSO) brings performance gains compared to the default version of statistical software like R.
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Affiliation(s)
| | | | | | | | | | - Yara S Tadano
- Federal University of Technology - Parana (UTFPR), Brazil
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23
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Huang K, Yang XJ, Hu CY, Ding K, Jiang W, Hua XG, Liu J, Cao JY, Sun CY, Zhang T, Kan XH, Zhang XJ. Short-term effect of ambient temperature change on the risk of tuberculosis admissions: Assessments of two exposure metrics. ENVIRONMENTAL RESEARCH 2020; 189:109900. [PMID: 32980000 DOI: 10.1016/j.envres.2020.109900] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 06/20/2020] [Accepted: 06/30/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Although the effects of seasonal variations and ambient temperature on the incidence of tuberculosis (TB) have been well documented, it is still unknown whether ambient temperature change is an independent risk factor for TB. The aim of this study was to assess the association between ambient temperature change and the risk of TB admissions. METHOD A distributed lag non-linear model (DLNM) combined with Poisson generalized linear regression model was performed to assess the association between ambient temperature change and the risk of TB admissions from 2014 to 2018 in Hefei, China. Two temperature change metrics including temperature change between neighboring days (TCN) and diurnal temperature range (DTR) were used to assess the effects of temperature change exposure. Subgroup analyses were performed by gender, age and season. Besides, the attributable risk was calculated to evaluated the public health significance. RESULTS The overall exposure-response curves suggested that there were statistically significant associations between two temperature change metrics and the risk of TB admissions. The maximum lag-specific relative risk (RR) of TB admissions was 1.088 (95%CI: 1.012-1.171, lag 4 day) for exposing to large temperature drop (TCN= -4 °C) in winter. Besides, the overall cumulative risk of TB admissions increased continuously and peaked at a lag of 7 days (RR=1.350, 95%CI: 1.120-1.628). Subgroup analysis suggested that exposure to large temperature drop had an adverse effect on TB admissions among males, females and adults. Similarly, large level of DTR exposure (DTR=15 °C) in spring also increased the risk of TB admissions on lag 0 day (RR=1.039, 95%CI: 1.016-1.063), and the cumulative RRs peaked at a lag of 1 days (RR=1.029, 95%CI: 1.012-1.047). We also found that females and elderly people were more vulnerable to the large level of DTR exposure. Additionally, the assessment of attributable risk suggested that taking target measures for the upcoming large temperature drop (b-AF = 4.17%, 95% eCI: 1.24%, 7.22%, b-AN = 1195) may achieve great public health benefits for TB prevention. CONCLUSION This study suggests that ambient temperature change is associated with the risk of TB admissions. Besides, TCN may be a better predictor for the TB prevention and public health.
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Affiliation(s)
- Kai Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xiao-Jing Yang
- 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
| | - Kun Ding
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Wen Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Xiao-Guo Hua
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, China
| | - Jie Liu
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, 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
| | - Chen-Yu Sun
- AMITA Health Saint Joseph Hospital Chicago, 2900 N. Lake Shore Drive, Chicago, 60657, Illinois, USA
| | - 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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Wei Q, Zhong L, Gao J, Yi W, Pan R, Gao J, Duan J, Xu Z, He Y, Liu X, Tang C, Su H. Diurnal temperature range and childhood asthma in Hefei, China: Does temperature modify the association? THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 724:138206. [PMID: 32247134 DOI: 10.1016/j.scitotenv.2020.138206] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 03/23/2020] [Accepted: 03/23/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND The present study aimed to understand the effect of diurnal temperature range (DTR) on childhood asthma in Hefei, China, and to explore the effect of temperature on the DTR-asthma association. MATERIALS AND METHODS Daily data on hospital admissions for childhood asthma, air pollutants, and weather variables in Hefei, China, from 1st January 2014 to 31st December 2015, were collected. A generalized additive model combined with a distributed lag non-linear model was used to quantify the effects of DTR on the total, age- and gender-specific hospital admissions for childhood asthma. A non-parametric bivariate response surface model, and a generalized additive model combined with a stratified parametric model were used to explore the interaction between DTR and temperature. RESULTS We observed that high DTR was associated with an increase in hospital admissions for childhood asthma. When DTR increased from 6.7 °C to 16.8 °C (99% percentile), hospital admissions for childhood asthma increased by 13% (relative risk: 1.13, 95% confidence interval: 1.07, 1.12). The analysis stratified, by mean temperature level, suggested that when DTR increased by 1 °C at low temperatures, asthma hospitalizations in total children, girls, boys and school-age children increased by 5.0% (95% CI: 2.6%, 7.5%), 3.7% (95% CI: 0.4%, 5.7%), 2.9% (95% CI: 0.8%, 4.4%) and 5.0% (95% CI: 2.6%, 7.5%), respectively. CONCLUSIONS This study suggests that the impact of high DTR should be considered among public health advice for children with existing asthma. Those days with high DTR and low mean temperature need extra attention.
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Affiliation(s)
- Qiannan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Liqin Zhong
- The Second People's Hospital of Hefei, Hefei, Anhui 230011, China
| | - Jiaqi Gao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Jiaojiao Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Jun Duan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Zihan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China.
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Pan R, Wang X, Yi W, Wei Q, Gao J, Xu Z, Duan J, He Y, Tang C, Liu X, Zhou Y, Son S, Ji Y, Zou Y, Su H. Interactions between climate factors and air quality index for improved childhood asthma self-management. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 723:137804. [PMID: 32213400 DOI: 10.1016/j.scitotenv.2020.137804] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2019] [Revised: 03/06/2020] [Accepted: 03/06/2020] [Indexed: 06/10/2023]
Abstract
BACKGROUND Daily air quality index (AQI) forecast can provide early warning information, and it is not clear whether it is appropriate for childhood asthma hospitalizations (CAHs). Furthermore, little is known about the effects of AQI on CAHs, as well as the interactions between temperature, humidity and AQI. METHODS We collected 32,238 cases in Hefei from 2013 to 2016 and estimated the association between daily CAHs and AQI by combining the Poisson Generalized Linear Models (PGLMs) with the Distributed Lag Nonlinear Models (DLNMs). The interaction between AQI and temperature was tested by stratifying AQI and temperature, as well as humidity. RESULTS AQI was associated with an increased risk of hospitalizations for childhood asthma. The adverse effect first appeared on the 3rd day, with the RR of 1.011 (95%CI: 1.000-1.023) and continued until the 19th day of lag (RR = 1.010, 95%CI: 1.001-1.020). In the subgroup analysis, the male and pre-school children were more sensitive to AQI, and there are seasonal differences in the effects of AQI on CAHs. Besides, in a stratified analysis with an AQI of 150, we found synergies between temperature, humidity and AQI. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for the interaction between temperature and AQI were 1.157 (95%CI: 1.029-1.306) and 0.122 (95%CI: 0.022-0.223) respectively. For the humidity, the IRR and RERI were 1.090 (95%CI: 1.056-1.206) and 0.083 (95%CI: 0.083-0.143) respectively. Exploring different subgroups in the interaction analyses, it was worth noting that female and pre-school children were more sensitive to the interaction between AQI and temperature, while school-age children were more sensitive to the interaction between AQI and humidity. CONCLUSIONS The study found that not only AQI can significantly increase the risk of CAHs, but also that under the context of climate change, temperature and humidity have a synergistic effect on AQI, suggesting that considering only the warning information of air pollution is not enough to strengthen the prevention of childhood asthma hospitalization.
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Affiliation(s)
- Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Xu Wang
- Anhui provincial Children's hospital, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Qiannan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Jiaojiao Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Zihan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Jun Duan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Yu Zhou
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Shasha Son
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Yanhu Ji
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Yanfeng Zou
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China.
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