1
|
Wu Q, Xing X, Yang M, Bai Z, He Q, Cheng Q, Hu J, Wang H, Fan Y, Su H, Liu Z, Cheng J. Increased Suicide Mortality and Reduced Life Expectancy Associated With Ambient Heat Exposure. Am J Prev Med 2024; 66:780-788. [PMID: 38311191 DOI: 10.1016/j.amepre.2024.01.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 01/25/2024] [Accepted: 01/28/2024] [Indexed: 02/10/2024]
Abstract
INTRODUCTION Ambient heat exposure is a risk factor for suicide in many regions of the world. However, little is known about the extent to which life expectancy has been shortened by heat-related suicide deaths. This study aimed to evaluate the short-term effects of heat on suicide mortality and quantify the reduced life expectancy associated with heat in China. METHODS A time-stratified, case-crossover analysis in 2023 was performed during the warm season (May to September) from 2016 to 2020 to assess the short-term association between extreme heat (the 95th percentile of mean temperature) and suicide mortality in Anhui Province, China. A subgroup analysis was performed according to sex, age, marital status, suicide type, and region. The attributable fraction and years of life lost due to heat were calculated, and the heat-related life expectancy loss was estimated. RESULTS This study included 9,642 suicide deaths, with an average age of 62.4 years and 58.8% of suicides in males. Suicide risk was associated with an 80.7% increase (95% confidence interval [CI]: 21.4%-68.9%) after exposure to extreme heat (30.6°C) in comparison to daily minimum temperature (7.9°C). Subgroup analysis revealed that heat-related suicide risk was more prominent in the married population than in the unmarried population. Heat was estimated to be associated with 31.7% (95% CI: 18.0%-43.2%) of the suicides, corresponding to 7.0 years of loss in life expectancy for each decedent. CONCLUSIONS Heat exposure was associated with an increased risk of suicide and reduced life expectancy. However, further prospective studies are required to confirm this relationship.
Collapse
Affiliation(s)
- Qiyue Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Xiuya Xing
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China; Public Health Research Institute of Anhui Province, Hefei, China
| | - Min Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Zhongliang Bai
- Department of Health Services Management, School of Health Services Management, Anhui Medical University, Hefei, China
| | - Qin He
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China; Public Health Research Institute of Anhui Province, Hefei, China
| | - Qianyao Cheng
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China; Public Health Research Institute of Anhui Province, Hefei, China
| | - Jingyao Hu
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China; Public Health Research Institute of Anhui Province, Hefei, China
| | - Huadong Wang
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China; Public Health Research Institute of Anhui Province, Hefei, China
| | - Yinguang Fan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Hong Su
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Zhirong Liu
- Anhui Provincial Center for Disease Control and Prevention, Hefei, China; Public Health Research Institute of Anhui Province, Hefei, China.
| | - Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China.
| |
Collapse
|
2
|
Zheng H, Wang Q, Fu J, Ding Z, Cheng J, Xu Z, Xu Y, Xia Y. Geographical variation in the effect of ambient temperature on infectious diarrhea among children under 5 years. ENVIRONMENTAL RESEARCH 2023; 216:114491. [PMID: 36208789 DOI: 10.1016/j.envres.2022.114491] [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: 05/14/2022] [Revised: 09/22/2022] [Accepted: 10/01/2022] [Indexed: 06/16/2023]
Abstract
Understanding the geographical distribution in the association of temperature with childhood diarrhea can assist in formulating effective localized diarrhea prevention practices. This study aimed to identify the geographical variation in terms of temperature thresholds, lag effects, and attributable fraction (AF) in the effects of ambient temperature on Class C Other Infectious Diarrhea (OID) among children <5 years in Jiangsu Province, China. Daily data of OID cases and meteorological variables from 2015 to 2019 were collected. City-specific minimum morbidity temperature (MMT), increasing risk temperature (IRT), maximum risk temperature (MRT), maximum risk lag day (MRD), and lag day duration (LDD) were identified as risk indicators for the temperature-OID relationship using distributed lag non-linear models. The AF of OID incidence due to temperature was evaluated. Multivariable regression was also applied to explore the underlying modifiers of the AF. The geographical distributions of MMT, IRT, and MRT generally decreased with the latitude increment varying between 22.3-34.7 °C, -2.9-18.1 °C, and -6.8-23.2 °C. Considerable variation was shown in the AF ranging from 0.2 to 8.5%, and the AF significantly increased with latitude (95% confidence interval (CI): -3.458, -0.987) and economic status decrement (95% CI: -0.161, -0.019). Our study demonstrated between-city variations in the association of temperature with OID, which should be considered in the localized clinical and public health practices to decrease the incidence of childhood diarrhea.
Collapse
Affiliation(s)
- Hao Zheng
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - QingQing Wang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Jianguang Fu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China; Key Laboratory of Enteric Pathogenic Microbiology, Ministry of Health, Nanjing, China
| | - Zhen Ding
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| | - Zhiwei Xu
- School of Public Health, University of Queensland, Queensland, Australia
| | - Yan Xu
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China; Key Laboratory of Enteric Pathogenic Microbiology, Ministry of Health, Nanjing, China.
| | - Yankai Xia
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China.
| |
Collapse
|
3
|
Adnan MSG, Dewan A, Botje D, Shahid S, Hassan QK. Vulnerability of Australia to heatwaves: A systematic review on influencing factors, impacts, and mitigation options. ENVIRONMENTAL RESEARCH 2022; 213:113703. [PMID: 35716815 DOI: 10.1016/j.envres.2022.113703] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 06/04/2022] [Accepted: 06/13/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Heatwaves have received major attention globally due to their detrimental effects on human health and the environment. The frequency, duration, and severity of heatwaves have increased recently due to changes in climatic conditions, anthropogenic forcing, and rapid urbanization. Australia is highly vulnerable to this hazard. Although there have been an increasing number of studies conducted in Australia related to the heatwave phenomena, a systematic review of heatwave vulnerability has rarely been reported in the literature. OBJECTIVES This study aims to provide a systematic and overarching review of the different components of heatwave vulnerability (e.g., exposure, sensitivity, and adaptive capacity) in Australia. METHODS A systematic review was conducted using the PRISMA protocol. Peer-reviewed English language articles published between January 2000 and December 2021 were selected using a combination of search keywords in Web of Science, Scopus, and PubMed. Articles were critically analyzed based on three specific heatwave vulnerability components: exposure, sensitivity, and adaptive capacity. RESULTS AND DISCUSSION A total of 107 articles meeting all search criteria were chosen. Although there has been an increasing trend of heat-related studies in Australia, most of these studies have concentrated on exposure and adaptive capacity components. Evidence suggests that the frequency, severity, and duration of heatwaves in Australian cities has been increasing, and that this is likely to continue under current climate change scenarios. This study noted that heatwave vulnerability is associated with geographical and climatic factors, space, time, socioeconomic and demographic factors, as well as the physiological condition of people. Various heat mitigation and adaptation measures implemented around the globe have proven to be efficient in reducing the impacts of heatwaves. CONCLUSION This study provides increased clarity regarding the various drivers of heatwave vulnerability in Australia. Such knowledge is crucial in informing extreme heat adaptation and mitigation planning.
Collapse
Affiliation(s)
- Mohammed Sarfaraz Gani Adnan
- Department of Urban and Regional Planning, Chittagong University of Engineering and Technology (CUET), Chittagong, 4319, Bangladesh; Environmental Change Institute, School of Geography and the Environment, University of Oxford, OX1 3QY, United Kingdom.
| | - Ashraf Dewan
- School of Earth and Planetary Sciences, Curtin University, Perth, WA, 6102, Australia
| | - Dirk Botje
- School of Earth and Planetary Sciences, Curtin University, Perth, WA, 6102, Australia
| | - Shamsuddin Shahid
- Department of Hydraulics & Hydrology, Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310, Johor Bahru, Johor, Malaysia
| | - Quazi K Hassan
- Department of Geomatics Engineering, University of Calgary, 2500 University Drive NW, Calgary Alberta, T2N 1N4, Canada
| |
Collapse
|
4
|
Pan R, Zheng H, Ding Z, Xu Z, Ho HC, Hossain MZ, Huang C, Yi W, Song J, Cheng J, Su H. Attributing hypertensive life expectancy loss to ambient heat exposure: A multicenter study in eastern China. ENVIRONMENTAL RESEARCH 2022; 208:112726. [PMID: 35033548 DOI: 10.1016/j.envres.2022.112726] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/03/2022] [Accepted: 01/10/2022] [Indexed: 06/14/2023]
Abstract
Ambient high temperature is a worldwide trigger for hypertension events. However, the effects of heat exposure on hypertension and years of life lost (YLL) due to heat remain largely unknown. We conducted a multicenter study in 13 cities in Jiangsu Province, China, to investigate 9727 individuals who died from hypertension during the summer months (May to September) between 2016 and 2017. Meteorological observation data (temperature and rainfall) and air pollutants (fine particulate matter and ozone) were obtained for each decedent by geocoding the residential addresses. A time-stratified case-crossover design was used to quantify the association between heat and different types of hypertension and further explore the modification effect of individual and hospital characteristics. Meanwhile, the YLL associated with heat exposure was estimated. Our results show that summer heat exposure shortens the YLL of hypertensive patients by a total of 14,74 years per month. Of these, 77.9% of YLL was mainly due to hypertensive heart disease. YLL due to heat was pronounced for essential hypertension (5.1 years (95% empirical confidence intervals (eCI): 4.1-5.8)), hypertensive heart and renal disease with heart failure (4.4 years (95% eCI: 0.9-5.9)), and hypertensive heart and renal disease (unspecified, 3.5 years (95% eCI: 1.8-4.5)). Moderate heat was associated with a larger YLL than extreme heat. The distance between hospitals and patients and the number of local first-class hospitals can significantly mitigate the adverse effect of heat exposure on longevity. Besides, unmarried people and those under 65 years of age were potentially susceptible groups, with average reduced YLL of 3.5 and 3.9 years, respectively. Our study reveals that heat exposure increases the mortality risk from many types of hypertension and YLL. In the context of climate change, if effective measures are not taken, hot weather may bring a greater burden of disease to hypertension due to premature death.
Collapse
Affiliation(s)
- 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
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, 210009, China
| | - Zhen Ding
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, 210009, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, 288 Herston Road, Herston, QLD, 4006, Australia
| | - Hung Chak Ho
- Department of Urban Planning and Design, The University of Hong Kong, Hong Kong, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, 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
| | - Jian Song
- 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
| | - Jian Cheng
- 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.
| |
Collapse
|
5
|
Tang C, Ji Y, Li Q, Yao Z, Cheng J, He Y, Liu X, Pan R, Wei Q, Yi W, Su H. Effects of different heat exposure patterns (accumulated and transient) and schizophrenia hospitalizations: a time-series analysis on hourly temperature basis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:69160-69170. [PMID: 34286435 DOI: 10.1007/s11356-021-15371-7] [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: 05/21/2021] [Accepted: 07/06/2021] [Indexed: 06/13/2023]
Abstract
Growing studies have shown that high temperature is a potential risk factor of schizophrenia occurrence. Therefore, elaborate analysis of different temperature exposure patterns, such as cumulative heat exposure within a time period and transient exposure at a particular time point, is of important public health significance. This study aims to utilize hourly temperature data to better capture the effects of cumulative and transient heat exposures on schizophrenia during the warm season in Hefei, China. We included the daily mean temperature and daily schizophrenia hospitalizations into the distributed lag non-linear model (DLNM) to simulate the exposure-response curve and determine the heat threshold (19.4 °C). We calculated and applied a novel indicator-daily excess hourly heat (DEHH)-to examine the effects of cumulative heat exposure over a day on schizophrenia hospitalizations. Temperature measurements at each time point were also incorporated in the DLNM as independent exposure indicators to analyze the impact of transient heat exposure on schizophrenia. Each increment of interquartile range (IQR) in DEHH was associated with elevated risk of schizophrenia hospitalizations from lag 1 (RR = 1.036, 95% confidence interval (CI): 1.016, 1.057) to lag 4 (RR = 1.025, 95% CI: 1.005, 1.046). Men and people over 40 years old were more susceptible to DEHH. Besides, we found a greater risk of heat-related schizophrenia hospitalizations between 0 a.m. and 6 a.m. This study revealed the adverse effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our findings need to be further tested in other regions with distinct regional features.
Collapse
Affiliation(s)
- Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Yifu Ji
- Anhui Mental Health Center, Hefei, 230032, Anhui, China
| | - Qingru Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Zhenhai Yao
- Anhui Public Meteorological Service Center, Hefei, 230011, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Qiannan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China.
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China.
| |
Collapse
|
6
|
Wang Q, Zhang Y, Ban J, Zhu H, Xu H, Li T. The relationship between population heat vulnerability and urbanization levels: A county-level modeling study across China. ENVIRONMENT INTERNATIONAL 2021; 156:106742. [PMID: 34224997 DOI: 10.1016/j.envint.2021.106742] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 06/24/2021] [Accepted: 06/24/2021] [Indexed: 06/13/2023]
Abstract
The purpose of this work was to assess population vulnerability to heat-related health risks and its relationship with urbanization levels to provide essential information for the future development and policy-making for climate change adaptation. We constructed a heat vulnerability index (HVI), quantified the population heat vulnerability in each county across China by a principal component analysis (PCA) of multiple factors, and assessed urbanization levels in each county using multisource data. Then, the HVI was validated using the heat-attributable fraction (heat-AF) of nonaccidental mortality based on death monitoring data and meteorological data from 95 counties across China. The results showed that our HVI was significantly positively associated with the heat AF of nonaccidental mortality. A negative correlation was observed between the urbanization level and the HVI. The HVI was generally higher in less urbanized western China and lower in the more urbanized eastern regions. The baseline mortality occupies the top position in the importance ranking of the heat-vulnerability indicators at all three urbanization levels, but the other indicators, including the aging rate, agricultural population rate, education, ethnic structure, economic status, air conditioner ownership rate, and number of hospitals, ranked differently among different urbanization levels. This finding indicates that to reduce population heat vulnerability, the most important approach is to improve the health status of the whole population and reduce baseline mortality; additionally, regional-specific measures and emphasis should be adjusted reasonably along with the process of urbanization according to the characteristics and key factors of local heat vulnerability.
Collapse
Affiliation(s)
- Qing Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yayi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Geomatics and Marine Information, Jiangsu Ocean University, Lianyungang 222005, China
| | - Jie Ban
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Huanhuan Zhu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Hebei University of Science and Technology, Shijiazhuang 050018, China
| | - Huaiyue Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
| |
Collapse
|
7
|
Cheng J, Ho HC, Su H, Huang C, Pan R, Hossain MZ, Zheng H, Xu Z. Low ambient temperature shortened life expectancy in Hong Kong: A time-series analysis of 1.4 million years of life lost from cardiorespiratory diseases. ENVIRONMENTAL RESEARCH 2021; 201:111652. [PMID: 34246637 DOI: 10.1016/j.envres.2021.111652] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 06/26/2021] [Accepted: 07/02/2021] [Indexed: 06/13/2023]
Abstract
Ambient temperature is an important contributor to mortality burden worldwide, most of which is from cold exposure. However, little is known about the cold impact on life expectancy loss. This paper aimed to estimate cold-related life expectancy loss from cause-, age-, and gender-specific cardiovascular and respiratory diseases. Daily deaths from cardiovascular and respiratory diseases and weather records were acquired for Hong Kong, China during 2000-2016. Years of life lost (YLL) that considers life expectancy at the time of death was calculated by matching each death by age and sex to annual life tables. Using a generalized additive model that fits temperature-YLL association, we estimated loss of years in life expectancy from cold. Cold was estimated to cause life expectancy loss of 0.9 years in total cardiovascular disease, with more years of loss in males than in females and in people aged 65 years and older than in people aged up to 64 years. Cold-related life expectancy loss in total respiratory diseases was 1.2 years, with more years of loss in females than in males and comparable years of loss in people aged up to 64 years and in people aged 65 years and older. Among cause-specific diseases, we observed the greatest life expectancy loss in pneumonia (1.5 years), followed by ischaemic heart disease (1.2 years), COPD (1.1 years), and stroke (0.3 years). Between two periods of 2000-2007 and 2008-2016, cold-related life expectancy loss due to cardiovascular disease did not decrease and cold-related life expectancy loss due to respiratory disease even increased by five times. Our findings suggest an urgent need to develop prevention measures against adverse cold effects on cardiorespiratory disease in Hong Kong.
Collapse
Affiliation(s)
- Jian Cheng
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, 81 Meishan Road, 230022, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, 81 Meishan Road, 230022, 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
| | - Hong Su
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, 81 Meishan Road, 230022, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, 81 Meishan Road, 230022, Hefei, China
| | - Cunrui Huang
- School of Public Health, Sun Yat-sen University, 74 Zhongshan 2nd Rd., Guangzhou, 510080, China
| | - Rubing Pan
- School of Public Health, Department of Epidemiology and Biostatistics, Anhui Medical University, 81 Meishan Road, 230022, Hefei, China; Anhui Province Key Laboratory of Major Autoimmune Disease, 81 Meishan Road, 230022, Hefei, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, 210009, Nanjing, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, 288 Herston Road, Herston, Brisbane, Queensland, 4006, Australia.
| |
Collapse
|
8
|
Xu Z, Tong S, Ho HC, Lin H, Pan H, Cheng J. Associations of heat and cold with hospitalizations and post-discharge deaths due to acute myocardial infarction: what is the role of pre-existing diabetes? Int J Epidemiol 2021; 51:134-143. [PMID: 34387661 DOI: 10.1093/ije/dyab155] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 07/08/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND The existing evidence suggests that pre-existing diabetes may modify the association between heat and hospitalizations for acute myocardial infarction (AMI). METHODS This study included patients who were hospitalized for AMI from 1 January 2005 to 31 December 2013 in Brisbane, Australia, and also included those who died within 2 months after discharge. A time-stratified case-crossover design with conditional logistic regression was used to quantify the associations of heat and cold with hospitalizations and post-discharge deaths due to AMI in patients with and without pre-existing diabetes. Stratified analyses were conducted to explore whether age, sex and suburb-level green space and suburb-level socio-economic status modified the temperature-AMI relationship. Heat and cold were defined as the temperature above/below which the odds of hospitalizations/deaths due to AMI started to increase significantly. RESULTS There were 14 991 hospitalizations for AMI and 1811 died from AMI within 2 months after discharge during the study period. Significant association between heat and hospitalizations for AMI was observed only in those with pre-existing diabetes (odds ratio: 1.19, 95% confidence interval: 1.00-1.41) [heat (26.3°C) vs minimum morbidity temperature (22.2°C)]. Cold was associated with increased odds of hospitalizations for AMI in both diabetes and non-diabetes groups. Significant association between cold and post-discharge deaths from AMI was observed in both diabetes and non-diabetes groups. CONCLUSIONS Individuals with diabetes are more susceptible to hospitalizations due to AMI caused by heat and cold.
Collapse
Affiliation(s)
- Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - 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
| | - 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
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Haifeng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Major Autoimmune Disease, Hefei, China
| |
Collapse
|
9
|
Li N, Ma J, Liu F, Zhang Y, Ma P, Jin Y, Zheng ZJ. Associations of apparent temperature with acute cardiac events and subtypes of acute coronary syndromes in Beijing, China. Sci Rep 2021; 11:15229. [PMID: 34315978 PMCID: PMC8316341 DOI: 10.1038/s41598-021-94738-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 07/07/2021] [Indexed: 11/09/2022] Open
Abstract
Limited evidence is available on apparent temperature (AT) and hospital admissions for acute cardiac events. We examined the associations of AT with admissions for acute cardiac events and acute coronary syndrome (ACS), and explored the effect difference between ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction ACS (NSTE-ACS). Poisson regression with distributed lag non-linear model was applied to examine the temperature-lag-admission associations. Stratified analyses were performed by gender and age-groups for acute cardiac events. A total of 11,657 acute cardiac events admissions were collected from hospital-based chest pain centers in Beijing, during 2017-2019. The single day effect of low AT (- 11 °C, 2.5th percentile) appeared on the 2nd day and persisted until the 11th day, with estimated relative risk (RR) ranging from 1.44 (95% CI: 1.159, 1.790) to 1.084 (95% CI: 1.022, 1.150) for acute cardiac events and from 1.034 (95% CI: 1.010, 1.059) to 1.006 (95% CI: 1.000, 1.011) for ACS. The single day effect of high AT (34 °C, 97.5th percentile) was only observed on the current day. The cold effect on acute cardiac events was more pronounced among female and older patients. The cumulative effect of high AT on STEMI admissions and low AT on NSTE-ACS reached a peak RR peak of 2.545 (95% CI: 1.016, 6.375) and 3.71 (95% CI: 1.315, 10.469) on lag 0-6 days, respectively. Both high and low ATs were associated with increased risk of acute cardiac events and ACS admissions. STEMI admissions may be more sensitive to high AT while NSTE-ACS to low AT.
Collapse
Affiliation(s)
- Na Li
- Department of Global Health, Peking University School of Public Health, 38 Xue Yuan Road, Haidian District, Beijing, 100191, China.,Institute for Global Health and Development, Peking University, Beijing, China
| | - Junxiong Ma
- Department of Global Health, Peking University School of Public Health, 38 Xue Yuan Road, Haidian District, Beijing, 100191, China.,Institute for Global Health and Development, Peking University, Beijing, China
| | - Fangjing Liu
- Department of Global Health, Peking University School of Public Health, 38 Xue Yuan Road, Haidian District, Beijing, 100191, China.,Institute for Global Health and Development, Peking University, Beijing, China
| | - Yan Zhang
- Institute of Cardiovascular Disease, Peking University First Hospital, Beijing, China
| | - Pengkun Ma
- Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing, China
| | - Yinzi Jin
- Department of Global Health, Peking University School of Public Health, 38 Xue Yuan Road, Haidian District, Beijing, 100191, China. .,Institute for Global Health and Development, Peking University, Beijing, China.
| | - Zhi-Jie Zheng
- Department of Global Health, Peking University School of Public Health, 38 Xue Yuan Road, Haidian District, Beijing, 100191, China.,Institute for Global Health and Development, Peking University, Beijing, China
| |
Collapse
|
10
|
Cheng J, Bambrick H, Frentiu FD, Devine G, Yakob L, Xu Z, Li Z, Yang W, Hu W. Extreme weather events and dengue outbreaks in Guangzhou, China: a time-series quasi-binomial distributed lag non-linear model. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2021; 65:1033-1042. [PMID: 33598765 DOI: 10.1007/s00484-021-02085-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 01/14/2021] [Accepted: 01/19/2021] [Indexed: 06/12/2023]
Abstract
Dengue transmission is climate-sensitive and permissive conditions regularly cause large outbreaks in Asia-Pacific area. As climate change progresses, extreme weather events such as heatwaves and unusually high rainfall are predicted more intense and frequent, but their impacts on dengue outbreaks remain unclear so far. This paper aimed to investigate the relationship between extreme weather events (i.e., heatwaves, extremely high rainfall and extremely high humidity) and dengue outbreaks in China. We obtained daily number of locally acquired dengue cases and weather factors for Guangzhou, China, for the period 2006-2015. The definition of dengue outbreaks was based on daily number of locally acquired cases above the threshold (i.e., mean + 2SD of daily distribution of dengue cases during peaking period). Heatwave was defined as ≥2 days with temperature ≥ 95th percentile, and extreme rainfall and humidity defined as daily values ≥95th percentile during 2006-2015. A generalized additive model was used to examine the associations between extreme weather events and dengue outbreaks. Results showed that all three extreme weather events were associated with increased risk of dengue outbreaks, with a risk increase of 115-251% around 6 weeks after heatwaves, 173-258% around 6-13 weeks after extremely high rainfall, and 572-587% around 6-13 weeks after extremely high humidity. Each extreme weather event also had good capacity in predicting dengue outbreaks, with the model's sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve all exceeding 86%. This study found that heatwaves, extremely high rainfall, and extremely high humidity could act as potential drivers of dengue outbreaks.
Collapse
Affiliation(s)
- Jian Cheng
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
- Department of Epidemiology and Biostatistics & Anhui Province Key Laboratory of Major Autoimmune Disease, School of Public Health, Anhui Medical University, Anhui, China
| | - Hilary Bambrick
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Francesca D Frentiu
- Centre for Immunology and Infection Control, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Gregor Devine
- Mosquito Control Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Laith Yakob
- Department of Disease Control, London School of Hygiene and Tropical Medicine, London, UK
| | - Zhiwei Xu
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Zhongjie Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early Warning of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Weizhong Yang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early Warning of Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Population Medicine & Public Health, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China
| | - Wenbiao Hu
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, 4059, Australia.
| |
Collapse
|
11
|
Wang Y, Liu Y, Ye D, Li N, Bi P, Tong S, Wang Y, Cheng Y, Li Y, Yao X. Temperatures and health costs of emergency department visits: A multisite time series study in China. ENVIRONMENTAL RESEARCH 2021; 197:111023. [PMID: 33745933 DOI: 10.1016/j.envres.2021.111023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 02/26/2021] [Accepted: 03/12/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Evidence is limited regarding the association between temperatures and health costs. OBJECTIVES We tried to investigate the association between temperatures and emergency department visits (EDVs) costs in China. METHODS Daily data on EDVs costs, weather, air pollution were collected from 17 sites in China during 2014-2018. A quasi-Poisson generalized additive regression with distributed lag nonlinear model was applied to assess the temperature-EDVs cost association. Random-effect meta-analysis was used to pool the estimates from each site. Attributable fractions and national attributable EDVs costs due to heat and cold were calculated. RESULTS Relative risk (RR) due to extreme heat over 0-7 lag days was 1.14 [95% confidence intervals (CI): 1.08-1.19] and 1.11 (95% CI: 1.07-1.16) for EDVs examination (including treatment) and medicine cost, respectively. People aged 18-44 and those with genitourinary diseases were at higher risk from heat. 0.72% of examination cost and 0.57% of medicine cost were attributed to extreme heat, costing 274 million Chinese Yuan annually. Moderate heat had lower RR but higher attributable fraction of EDVs costs. Exposure to extreme cold over 0-21 lag days increased the risk of medicine cost for people aged 18-44 [RR: 1.30 (95% CI: 1.10-1.55)] and those with respiratory diseases [RR: 1.56 (95% CI: 1.14-2.14)], but had non-statistically significant attributable fraction of the total EDVs cost. CONCLUSIONS Exposure to heat and cold resulted in remarkable health costs. More resources and preparedness are needed to tackle such a challenge as our climate is rapidly changing.
Collapse
Affiliation(s)
- Yu Wang
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yue Liu
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dianxiu Ye
- National Climate Center, China Meteorological Administration, Beijing, China
| | - Na Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Shilu Tong
- Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; Center for Global Health, Nanjing Medical University, Nanjing, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Yan Wang
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yibin Cheng
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yonghong Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Xiaoyuan Yao
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
| |
Collapse
|
12
|
Zhu R, Fang H, Chen M, Hu X, Cao Y, Yang F, Xia K. Screen time and sleep disorder in preschool children: identifying the safe threshold in a digital world. Public Health 2020; 186:204-210. [PMID: 32861085 DOI: 10.1016/j.puhe.2020.07.028] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 06/23/2020] [Accepted: 07/19/2020] [Indexed: 12/01/2022]
Abstract
OBJECTIVES Sleep disorder is a common problem in children that can jeopardize their health and well-being. With the popularity of electronic devices such as portable tablets and smartphones in the 21st century, children are spending much more time on screen, but the impact of such change on children's sleep disorder has been less investigated so far. This study aims to examine the dose-response association between time spent on different electronic devices and children's sleep disorder. STUDY DESIGN The design of this study is a cross-sectional study. METHODS We randomly selected 2278 children aged 3-6 years from 15 kindergartens in Tongling, China. The potentially non-linear association between screen-viewing time (i.e. television [TV], computer, iPad, Phone) and the risk of sleep disorder was examined using a logistic generalized additive model. RESULTS We observed a J-shaped association between TV viewing time and the risk of sleep disorder, with a threshold of 1 h/day. For each 1 h/day increment in TV viewing time over the threshold, the risk of sleep disorder increased by 12.35% (95% confidence interval: 1.87-23.92%). This association seemed to be greater for girls than boys and for TV viewing at weekend than on weekdays, but the difference was not statistically significant (P-value>0.05). We did not find adequate evidence of an adverse effect of more time spent on computer, iPad and Phone. CONCLUSIONS This study suggests a positive but non-linear relationship between time spent on watching TV and sleep disorder in Chinese preschool children. Setting the TV viewing time limit less than 1 h/day may help reduce the risk of developing sleep disorder. Further investigation is also needed to examine and compare the effects of heavy use of other electronic devices on sleep disorder.
Collapse
Affiliation(s)
- R Zhu
- Department of Child Healthcare, Tongling Maternal and Child Healthcare Hospital, The 4th People's Hospital of Tongling, Tongling, China.
| | - H Fang
- Department of Child Healthcare, Tongling Maternal and Child Healthcare Hospital, The 4th People's Hospital of Tongling, Tongling, China
| | - M Chen
- Department of Child Healthcare, Tongling Maternal and Child Healthcare Hospital, The 4th People's Hospital of Tongling, Tongling, China
| | - X Hu
- Department of Child Healthcare, Tongling Maternal and Child Healthcare Hospital, The 4th People's Hospital of Tongling, Tongling, China
| | - Y Cao
- Department of Child Healthcare, Tongling Maternal and Child Healthcare Hospital, The 4th People's Hospital of Tongling, Tongling, China
| | - F Yang
- Department of Child Healthcare, Tongling Maternal and Child Healthcare Hospital, The 4th People's Hospital of Tongling, Tongling, China
| | - K Xia
- Department of Child Healthcare, Tongling Maternal and Child Healthcare Hospital, The 4th People's Hospital of Tongling, Tongling, China
| |
Collapse
|
13
|
Cheng J, Bambrick H, Tong S, Su H, Xu Z, Hu W. Winter temperature and myocardial infarction in Brisbane, Australia: Spatial and temporal analyses. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 715:136860. [PMID: 32040995 DOI: 10.1016/j.scitotenv.2020.136860] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2019] [Revised: 01/09/2020] [Accepted: 01/20/2020] [Indexed: 06/10/2023]
Abstract
Myocardial infarction (MI) incidence often peaks in winter, but it remains unclear how winter temperature affects MI temporally and spatially. We examined the short-term effects of winter temperature on the risk of MI and explored spatial associations of winter MI hospitalizations with temperature and socioeconomic status (area-based index) in Brisbane, Australia. We used a distributed lag non-linear model to fit the association at the city level between population-weighted daily mean temperature and daily MI hospitalizations during 11 winters of 2005-2015. For each winter, a Bayesian spatial conditional autoregressive model was fitted to examine the associations at postal code level of MI hospitalisations with temperature and socioeconomic status measured as the Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD). Area-specific winter temperature was categorised into three levels: cold (<25th percentile of average winter temperature across postal areas), mild (25th-75th percentile) and warm (>75th percentile). This study included 4978 MI hospitalizations. At the city level, each 1 °C drop in temperature below a threshold of 15.6 °C was associated with a relative risk (RR) of 1.016 (95% confidence interval (CI): 1.008-1.024) for MI hospitalizations on the same day. Low temperature had a much delayed and transient effect on women but an immediate and longer-lasting effect on men. Winter MI incidence rate varied spatially in Brisbane, with a higher incidence rate in warmer areas (RR for mild areas: 1.214, 95%CI: 1.116-1.320; RR for warm areas: 1.251, 95%CI: 1.127-1.389; cold areas as the reference) and in areas with lower socioeconomic levels (RR: 0.900, 95%CI: 0.886-0.914 for each decile increase in IRSAD). This study provides compelling evidence that short-term winter temperature drops were associated with an elevated risk of MI in the subtropical region with a mild winter. Particular attention also needs to be paid to people living in relatively warm and socioeconomically disadvantaged communities in winter.
Collapse
Affiliation(s)
- Jian Cheng
- School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia; Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia; Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Shilu Tong
- School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia; Shanghai Children's Medical Center, Shanghai Jiao Tong University, Shanghai, China; School of Public Health, Anhui Medical University, Hefei, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Zhiwei Xu
- School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia; Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Wenbiao Hu
- School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia; Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia.
| |
Collapse
|
14
|
Wang Y, Liu Y, Ye D, Li N, Bi P, Tong S, Wang Y, Cheng Y, Li Y, Yao X. High temperatures and emergency department visits in 18 sites with different climatic characteristics in China: Risk assessment and attributable fraction identification. ENVIRONMENT INTERNATIONAL 2020; 136:105486. [PMID: 31991239 DOI: 10.1016/j.envint.2020.105486] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2019] [Revised: 12/20/2019] [Accepted: 01/11/2020] [Indexed: 06/10/2023]
Abstract
BACKGROUND Health impacts of high temperatures on hospital emergency department visits (EDVs) have been less reported, especially from developing countries. OBJECTIVES To investigate high temperature-EDVs relationship in various regions with different climatic characteristics, to explore the regional differences, to identify vulnerable populations, and to provide scientific evidence for climate change adaptation strategies in China. METHODS Daily data on weather, air pollution and EDVs were collected from 18 sites in China from June to August during 2014-2017. A quasi-Poisson generalized additive regression model was applied to examine the high temperature-EDVs relationship in each site. Site-specific risks of EDVs were pooled using a random effect meta-analysis model. Stratified analyses were performed by gender, age-groups, cause-specific EDVs and regions. Attributable fractions of EDVs due to high temperatures were calculated in different regions. RESULTS 1 °C increase in daily mean temperature was associated with 1.07% (95% CI, 0.46-1.67%) increase in EDVs across all study regions. The negative health effects from high temperatures were worse for the people living in southern China, in subtropical monsoon climate zone or in counties, with percentage change of 1.96% (95% CI, 0.92-3.02%), 1.35% (95% CI, 0.95-1.76%) and 1.41% (95% CI, 0.48-2.34%), respectively. People under 18 were more vulnerable to high temperatures. Exposure to high temperatures increased EDVs risks from endocrine, respiratory, and digestive diseases and injury. The attributable fraction due to high temperatures was 8.64% for overall EDVs, 11.70% for the people living in southern China, 10.80% for people living in subtropical monsoon climate zone and 12.65% for the county population. CONCLUSIONS Exposure to high temperatures resulted in extra burden to China's already overloaded hospital emergency departments. More resources are needed to meet increasing demands and effective preventative measurements are warranted to tackle such a challenge. Further studies should pay more attention to both heat and cold-related EDVs risks and socioeconomic cost for better climate change adaptation.
Collapse
Affiliation(s)
- Yu Wang
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yue Liu
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Dianxiu Ye
- National Climate Center, China Meteorological Administration, Beijing, China
| | - Na Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, South Australia, Australia
| | - Shilu Tong
- Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei, China; School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Yan Wang
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yibin Cheng
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yonghong Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Xiaoyuan Yao
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China.
| |
Collapse
|
15
|
Pan R, Zhang X, Gao J, Yi W, Wei Q, Xu Z, Duan J, Bai L, Cheng Q, Zhang Y, Su H. Impacts of heat and cold on hospitalizations for schizophrenia in Hefei, China: An assessment of disease burden. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 694:133582. [PMID: 31394323 DOI: 10.1016/j.scitotenv.2019.133582] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 07/23/2019] [Accepted: 07/23/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Compared with risk data (e.g., RR or OR), attributable fraction (AF) provides more information on the formulation of policies and measures in the field of public health. However, to date, existing AF evidence is scarce for the relationship between temperature and the hospitalizations for SCZ. OBJECTIVES Our primary goal is to estimate the attributable burden of hospitalizations for SCZ related to cold and heat, respectively. Furthermore, to identify vulnerable populations due to heat and cold. METHODS Poisson generalized linear models combined with DLNMs were used to estimate the association between hospitalizations for SCZ and temperature from 2005 to 2014. The minimum risk temperature (MRT) was used as a reference, to calculate the burden of disease caused by cold and heat. RESULTS We found that the majority hospitalizations attributed to heat (70.9%). In different individual levels, men are more sensitive to heat exposure while women are more vulnerable to cold. Among different age groups, the results showed that the attributable risk was slightly higher in the over-40s than in the under-40s. Besides, under different marital conditions, it showed that the unmarried had a little higher attributional risk than the married. CONCLUSIONS We should pay attention to the impact of heat on hospitalizations for SCZ, especially in those over 40 years old, men and non-married. Our research will provide a basis for policymakers to develop intervention strategies to minimize the impact of adverse temperatures on hospitalizations for SCZ, thereby reducing the burden of disease.
Collapse
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
| | - Xulai Zhang
- Fourth People's Hospital of Hefei, Anhui, 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
| | - 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
| | - 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
| | - Lijun Bai
- 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
| | - Qiang Cheng
- 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
| | - Yanwu Zhang
- 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.
| |
Collapse
|
16
|
Cheng J, Xu Z, Bambrick H, Su H, Tong S, Hu W. Impacts of exposure to ambient temperature on burden of disease: a systematic review of epidemiological evidence. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2019; 63:1099-1115. [PMID: 31011886 DOI: 10.1007/s00484-019-01716-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 03/25/2019] [Accepted: 03/27/2019] [Indexed: 05/21/2023]
Abstract
Ambient temperature is an important determinant of mortality and morbidity, making it necessary to assess temperature-related burden of disease (BD) for the planning of public health policies and adaptive responses. To systematically review existing epidemiological evidence on temperature-related BD, we searched three databases (PubMed, Web of Science, and Scopus) on 1 September 2018. We identified 97 studies from 56 counties for this review, of which 75 reported the fraction or number of health outcomes (include deaths and diseases) attributable to temperature, and 22 reported disability-adjusted life years (include years of life lost and years lost due to disability) related to temperature. Non-optimum temperatures (i.e., heat and cold) were responsible for > 2.5% of mortality in all included high-income countries/regions, and > 3.0% of mortality in all included middle-income countries. Cold was mostly reported to be the primary source of mortality burden from non-optimum temperatures, but the relative role of three different temperature exposures (i.e., heat, cold, and temperature variability) in affecting morbidity and mortality remains unclear so far. Under the warming climate scenario, almost all projections assuming no population adaptation suggested future increase in heat-related but decrease in cold-related BD. However, some studies emphasized the great uncertainty in future pattern of temperature-related BD, largely depending on the scenarios of climate, population adaptation, and demography. We also identified important discrepancies and limitations in current research methodologies employed to measure temperature exposures and model temperature-health relationship, and calculate the past and project future temperature-related BD. Overall, exposure to non-optimum ambient temperatures has become and will continue to be a considerable contributor to the global and national BD, but future research is still needed to develop a stronger methodological framework for assessing and comparing temperature-related BD across different settings.
Collapse
Affiliation(s)
- Jian Cheng
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Zhiwei Xu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Shilu Tong
- Shanghai Children's Medical Centre, Shanghai Jiao-Tong University, Shanghai, China
- School of Public Health, Institute of Environment and Human Health, Anhui Medical University, Hefei, China
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Wenbiao Hu
- School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, 4059, Australia.
| |
Collapse
|
17
|
Cheng J, Xu Z, Bambrick H, Su H, Tong S, Hu W. Impacts of heat, cold, and temperature variability on mortality in Australia, 2000-2009. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 651:2558-2565. [PMID: 30340191 DOI: 10.1016/j.scitotenv.2018.10.186] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 09/15/2018] [Accepted: 10/13/2018] [Indexed: 04/13/2023]
Abstract
OBJECTIVES Evidence is limited on the relative contribution of different temperature exposures (i.e., heat, cold and significant temperature variability) to mortality. This study aims to examine mortality risk and associated mortality burden from heat, cold, and temperature variability in Australia. METHODS We collected daily time-series data on all-cause deaths and weather variables for the five most populous Australian cities (Sydney, Melbourne, Brisbane, Adelaide, and Perth), from 2000 to 2009. Temperature variability was calculated from the standard deviation of hourly temperatures between two adjacent days. Three-stage analysis was used. We firstly used quasi-Poisson regression models to model the associations of mortality with heat (mean temperature) during the warm season, with cold (mean temperature) during the cold season, and with temperature variability all year round, while controlling for long-term trend and seasonality, day of week, and population change over time. We then estimated the effects of different non-optimum temperatures using the simplified log-linear regression model. Finally, we computed and compared the fraction (%) of deaths attributable to different non-optimum temperatures. RESULTS The greatest percentage increase in mortality was for cold (2.0%, 95% confidence interval (CI): 1.4%, 2.6%), followed by heat (1.2%, 95% CI: 0.7%, 1.7%), and temperature variability (0.5%, 95% CI: 0.3%, 0.7%). There was no clear temporal pattern in mortality risk associated with any temperature exposure in Australia. Heat, cold and temperature variability together resulted in 42,414 deaths during the study period, accounting for about 6.0% of all deaths. Most of attributable deaths were due to cold (61.4%), and noticeably, contribution from temperature variability (28.0%) was greater than that from heat (10.6%). CONCLUSIONS Exposure to either cold or heat or a large variation in temperature was associated with increased mortality risk in Australia, but population adaptation appeared to have not occurred in most cities studied. Most of the temperature-induced deaths were attributable to cold, and contributions from temperature variability were greater than that from heat. Our findings highlight that, in addition to heat and cold, temperature variability needs to be considered in assessing and projecting the health impacts of climate change.
Collapse
Affiliation(s)
- Jian Cheng
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Zhiwei Xu
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Hilary Bambrick
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Anhui, China
| | - Shilu Tong
- School of Public Health and Social Work, Queensland University of Technology, Queensland, Australia; School of Public Health, Institute of Environment and Human Health, Anhui Medical University, Anhui, China; Shanghai Children's Medical Centre, Shanghai Jiao-Tong University, Shanghai, China
| | - Wenbiao Hu
- School of Public Health and Social Work & Institute of Health and Biomedical Innovation, Queensland University of Technology, Queensland, Australia.
| |
Collapse
|
18
|
Zhao Q, Li S, Coelho MSZS, Saldiva PHN, Hu K, Arblaster JM, Nicholls N, Huxley RR, Abramson MJ, Guo Y. Geographic, Demographic, and Temporal Variations in the Association between Heat Exposure and Hospitalization in Brazil: A Nationwide Study between 2000 and 2015. ENVIRONMENTAL HEALTH PERSPECTIVES 2019; 127:17001. [PMID: 30620212 PMCID: PMC6371650 DOI: 10.1289/ehp3889] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
BACKGROUND Limited evidence is available regarding the association between heat exposure and morbidity in Brazil and how the effect of heat exposure on health outcomes may change over time. OBJECTIVES This study sought to quantify the geographic, demographic and temporal variations in the heat–hospitalization association in Brazil from 2000–2015. METHODS Data on hospitalization and meteorological conditions were collected from 1,814 cities during the 2000–2015 hot seasons. Quasi-Poisson regression with constrained lag model was applied to examine city-specific estimates, which were then pooled at the regional and national levels using random-effect meta-analyses. Stratified analyses were performed by sex, 10 age groups, and 11 cause categories. Meta-regression was used to examine the temporal change in estimates of heat effect from 2000 to 2015. RESULTS For every 5°C increase in daily mean temperature during the 2000–2015 hot seasons, the estimated risk of hospitalization over lag 0-7 d rose by 4.0% [95% confidence interval (CI): 3.7%, 4.3%] nationwide. Estimated 6.2% [95% empirical CI (eCI): 3.3%, 9.1%] of hospitalizations were attributable to heat exposure, equating to 132 cases (95% eCI: 69%, 192%) per 100,000 residents. The attributable rate was greatest in children [Formula: see text] and was highest for hospitalizations due to infectious and parasitic diseases. Women of reproductive age and those [Formula: see text] had higher heat burden than men. The attributable burden was greatest for cities in the central west and the inland of the northeast; lowest in the north and eastern coast. Over the 16-y period, the estimated heat effects declined insignificantly at the national level. CONCLUSIONS In Brazil's hot seasons, 6% of hospitalizations were estimated to be attributed to heat exposure. As there was no evidence indicating that thermal adaptation had occurred at the national level, the burden of hospitalization associated with heat exposure in Brazil is likely to increase in the context of global warming. https://doi.org/10.1289/EHP3889.
Collapse
Affiliation(s)
- Qi Zhao
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | | | - Paulo H N Saldiva
- Institute of Advanced Studies, University of São Paulo, São Paulo, Brazil
| | - Kejia Hu
- Institute of Island and Coastal Ecosystems, Ocean College, Zhejiang University, Zhoushan, China
| | - Julie M Arblaster
- School of Earth, Atmosphere and Environment, Monash University, Melbourne, Australia
- Centre of Excellence for Climate Extremes, Australian Research Council, Sydney, Australia
| | - Neville Nicholls
- School of Earth, Atmosphere and Environment, Monash University, Melbourne, Australia
| | - Rachel R Huxley
- College of Science, Health and Engineering, La Trobe University, Melbourne, Australia
| | - Michael J Abramson
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| |
Collapse
|