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Chen Y, Zhou L, Zha Y, Wang Y, Wang K, Lu L, Guo P, Zhang Q. Impact of Ambient Temperature on Mortality Burden and Spatial Heterogeneity in 16 Prefecture-Level Cities of a Low-Latitude Plateau Area in Yunnan Province: Time-Series Study. JMIR Public Health Surveill 2024; 10:e51883. [PMID: 39045874 DOI: 10.2196/51883] [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: 08/16/2023] [Revised: 05/14/2024] [Accepted: 05/28/2024] [Indexed: 07/25/2024] Open
Abstract
Background The relation between climate change and human health has become one of the major worldwide public health issues. However, the evidence for low-latitude plateau regions is limited, where the climate is unique and diverse with a complex geography and topography. objectives This study aimed to evaluate the effect of ambient temperature on the mortality burden of nonaccidental deaths in Yunnan Province and to further explore its spatial heterogeneity among different regions. Methods We collected mortality and meteorological data from all 129 counties in Yunnan Province from 2014 to 2020, and 16 prefecture-level cities were analyzed as units. A distributed lagged nonlinear model was used to estimate the effect of temperature exposure on years of life lost (YLL) for nonaccidental deaths in each prefecture-level city. The attributable fraction of YLL due to ambient temperature was calculated. A multivariate meta-analysis was used to obtain an overall aggregated estimate of effects, and spatial heterogeneity among 16 prefecture-level cities was evaluated by adjusting the city-specific geographical characteristics, demographic characteristics, economic factors, and health resources factors. Results The temperature-YLL association was nonlinear and followed slide-shaped curves in all regions. The cumulative cold and heat effect estimates along lag 0-21 days on YLL for nonaccidental deaths were 403.16 (95% empirical confidence interval [eCI] 148.14-615.18) and 247.83 (95% eCI 45.73-418.85), respectively. The attributable fraction for nonaccidental mortality due to daily mean temperature was 7.45% (95% eCI 3.73%-10.38%). Cold temperature was responsible for most of the mortality burden (4.61%, 95% eCI 1.70-7.04), whereas the burden due to heat was 2.84% (95% eCI 0.58-4.83). The vulnerable subpopulations include male individuals, people aged <75 years, people with education below junior college level, farmers, nonmarried individuals, and ethnic minorities. In the cause-specific subgroup analysis, the total attributable fraction (%) for mean temperature was 13.97% (95% eCI 6.70-14.02) for heart disease, 11.12% (95% eCI 2.52-16.82) for respiratory disease, 10.85% (95% eCI 6.70-14.02) for cardiovascular disease, and 10.13% (95% eCI 6.03-13.18) for stroke. The attributable risk of cold effect for cardiovascular disease was higher than that for respiratory disease cause of death (9.71% vs 4.54%). Furthermore, we found 48.2% heterogeneity in the effect of mean temperature on YLL after considering the inherent characteristics of the 16 prefecture-level cities, with urbanization rate accounting for the highest proportion of heterogeneity (15.7%) among urban characteristics. Conclusions This study suggests that the cold effect dominated the total effect of temperature on mortality burden in Yunnan Province, and its effect was heterogeneous among different regions, which provides a basis for spatial planning and health policy formulation for disease prevention.
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Affiliation(s)
- Yang Chen
- School of Public Health, Kunming Medical University, Kunming, China
- Institute for Noncommunicable Disease Prevention and Control, Yunnan Centers for Disease Prevention and Control, Kunming, China
| | - Lidan Zhou
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Yuanyi Zha
- Graduate School, Kunming University of Medical, Kunming, China
| | - Yujin Wang
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Kai Wang
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Lvliang Lu
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Qingying Zhang
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
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Cheng C, Liu Y, Han C, Fang Q, Cui F, Li X. Effects of extreme temperature events on deaths and its interaction with air pollution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 915:170212. [PMID: 38246371 DOI: 10.1016/j.scitotenv.2024.170212] [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: 09/27/2023] [Revised: 12/17/2023] [Accepted: 01/14/2024] [Indexed: 01/23/2024]
Abstract
BACKGROUND Both extreme temperature events (ETEs) and air pollution affected human health, and their effects were often not independent. Previous studies have provided limited information on the interactions between ETEs and air pollution. METHODS We collected data on deaths (non-accidental, cardiovascular, and respiratory) in Zibo City along with daily air pollution and meteorological data from January 2015 to December 2019. Distributed lag non-linear model was used to explore the health effects of ETEs on deaths. Non-parametric binary response model, hierarchical model and joint effect model were used to further explore the interaction between ETEs and air pollution in different seasons. Meanwhile, subgroup analysis by gender and age (≥ 65 years old and < 65 years old) was conducted to identify the vulnerable population. RESULTS ETEs increased death risk, especially for cardiovascular and respiratory deaths. Heat waves had a stronger impact than cold spells. Cold spells had a longer lag and fluctuating trend. Heat waves had a short-term impact, followed by a decrease. Females and those aged ≥ 65 were more affected, but subgroup differences were not significant. During ETEs and non-ETEs, there were different effects on deaths with per IQR increase in air pollutant concentrations. Joint effect models revealed that there was a significant interaction between ETEs and air pollution on non-accidental deaths. The interaction between PM2.5 and cold spells was antagonistic in the cold season. In the warm season, the health effects of heat waves and high O3 concentration were enhanced. The relative excess risk due to interaction (RERI) of cold spells and PM2.5 in total population was -0.09 (95 % CI: -0.17, -0.01), and 9 % (95 % CI: 1 %, 17 %) of the total effect was attributable to interaction. Subgroup analysis confirmed the interactions in females and those aged ≥ 65. CONCLUSIONS Significant association observed between ETEs and deaths. Females and ≥ 65 age groups were vulnerable. There were interactions between ETEs and air pollution. The effect of PM2.5 on deaths decreased during cold spells, while the effect of O3 increased during heat waves. In addition to improving air quality, it is necessary to further strengthen the prevention and control of ETEs.
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Affiliation(s)
- Chuanlong Cheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Ying Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Ma'anshan Center for Disease Control and Prevention, Ma'anshan 243000, Anhui, China
| | - Chuang Han
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qidi Fang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Feng Cui
- Zibo Center for Disease Control and Prevention, Zibo, Shandong, China
| | - Xiujun Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
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Danielli S, Ashrafian H, Darzi A. Healthy city: global systematic scoping review of city initiatives to improve health with policy recommendations. BMC Public Health 2023; 23:1277. [PMID: 37393224 PMCID: PMC10314468 DOI: 10.1186/s12889-023-15908-0] [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: 11/01/2022] [Accepted: 05/12/2023] [Indexed: 07/03/2023] Open
Abstract
BACKGROUND Global health will increasingly be determined by cities. Currently over half of the world's population, over 4 billion people, live in cities. This systematic scoping review has been conducted to understand what cities are doing to improve health and healthcare for their populations. METHODS We conducted a systematic search to identify literature on city-wide initiatives to improve health. The study was conducted in accordance with PRISMA and the protocol was registered with PROSPERO (CRD42020166210). RESULTS The search identified 42,137 original citations, yielding 1,614 papers across 227 cities meeting the inclusion criteria. The results show that the majority of initiatives were targeted at non-communicable diseases. City health departments are making an increasing contribution; however the role of mayors appears to be limited. CONCLUSION The collective body of evidence identified in this review, built up over the last 130 years, has hitherto been poorly documented and characterised. Cities are a meta-system with population health dictated by multiple interactions and multidirectional feedback loops. Improving health in cities requires multiple actions, by multiple actors, at every level. The authors use the term 'The Vital 5'. They are the five most important health risk factors; tobacco use; harmful alcohol use; physical-inactivity, unhealthy diet and planetary health. These 'Vital 5' are most concentrated in deprived areas and show the greatest increase in low and middle income countries. Every city should develop a comprehensive strategy and action plan to address these 'Vital 5'.
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Affiliation(s)
- Shaun Danielli
- Kings Health Partners, Guys Hospital, London, SE1 9RT, UK.
- Imperial College London, South Kensington Campus, London, SW7 2NA, UK.
| | - Hutan Ashrafian
- Imperial College London, South Kensington Campus, London, SW7 2NA, UK
| | - Ara Darzi
- Imperial College London, South Kensington Campus, London, SW7 2NA, UK
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Roffia P, Bucciol A, Hashlamoun S. Determinants of life expectancy at birth: a longitudinal study on OECD countries. INTERNATIONAL JOURNAL OF HEALTH ECONOMICS AND MANAGEMENT 2023; 23:189-212. [PMID: 36367604 PMCID: PMC9650666 DOI: 10.1007/s10754-022-09338-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 10/23/2022] [Indexed: 05/05/2023]
Abstract
This paper analyses the influence of several determinants on life expectancy at birth in 36 OECD countries over the 1999-2018 period. We utilized a cross-country fixed-effects multiple regression analysis with year and country dummies and used dynamic models, backward stepwise selection, and Arellano-Bond estimators to treat potential endogeneity issues. The results show the influence of per capita health-care expenditure, incidence of out-of-pocket expenditure, physician density, hospital bed density, social spending, GDP level, participation ratio to labour, prevalence of chronic respiratory diseases, temperature, and total size of the population on life expectancy at birth. In line with previous studies, this analysis confirms the relevance of both health care expenditure and health care system (physicians and hospital beds in our analysis) in influencing a country's population life expectancy. It also outlines the importance of other factors related to population behaviour and social spending jointly considered on this outcome. Policy makers should carefully consider these mutual influences when allocating public funds, particularly after the COVID-19 pandemic period.
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Affiliation(s)
- Paolo Roffia
- Department of Business Administration, University of Verona, Polo S. Marta, Via Cantarane 24, 37129, Verona, Italy.
| | - Alessandro Bucciol
- Department of Economics, University of Verona, Polo S. Marta, Via Cantarane 24, 37129, Verona, Italy
| | - Sara Hashlamoun
- Department of Business Administration, University of Verona, Polo S. Marta, Via Cantarane 24, 37129, Verona, Italy
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Gong W, Li X, Zhou M, Zhou C, Xiao Y, Huang B, Lin L, Hu J, Xiao J, Zeng W, He G, Huang C, Liu T, Du Q, Ma W. Mortality burden attributable to temperature variability in China. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2023; 33:118-124. [PMID: 35332279 PMCID: PMC8944404 DOI: 10.1038/s41370-022-00424-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 02/24/2022] [Accepted: 03/03/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Several studies have investigated the associations between temperature variability (TV) and death counts. However, evidence of TV-attributable years of life lost (YLL) is scarce. OBJECTIVES To investigate the associations between TV and YLL rates (/100,000 population), and quantify average life loss per death (LLD) caused by TV in China. METHODS We calculated daily YLL rates (/100,000 population) of non-accidental causes and cardiorespiratory diseases by using death data from 364 counties of China during 2006-2017, and collected meteorological data during the same period. A distributed lag non-linear model (DLNM) and multivariate meta-analysis were used to estimate the effects of TV at national or regional levels. Then, we calculated the LLD to quantify the mortality burden of TV. RESULTS U-shaped curves were observed in the associations of YLL rates with TV in China. The minimum YLL TV (MYTV) was 2.5 °C nationwide. An average of 0.89 LLD was attributable to TV in total, most of which was from high TV (0.86, 95% CI: 0.56, 1.16). However, TV caused more LLD in the young (<65 years old) (1.87, 95% CI: 1.03, 2.71) than 65-74 years old (0.85, 95% CI: 0.40-1.31) and ≥75 years old (0.40, 95% CI: 0.21-0.59), cerebrovascular disease (0.74, 95% CI: 0.36, 1.11) than respiratory disease (0.54, 95% CI: 0.21, 0.87), South (1.23, 95% CI: 0.77, 1.68) than North (0.41, 95% CI: -0.7, 1.52) and Central China (0.40, 95% CI: -0.02, 0.81). TV-attributed LLD was modified by annual mean temperature, annual mean relative humidity, altitude, latitude, longitude, and education attainment. SIGNIFICANCE Our findings indicate that high and low TVs are both associated with increases in premature death, however the majority of LLD was attributable to high TV. TV-related LLD was modified by county level characteristics. TV should be considered in planning adaptation to climate change or variability. IMPACT (1) We estimated the associations of TV with YLL rates, and quantified the life loss per death (LLD) caused by TV. (2) An average of 0.89 years of LLD were attributable to TV, most of which were from high TVs. (3) TV caused more LLD in the young, cerebrovascular disease, and southern China. (4) The mortality burdens were modified by county level characteristics.
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Affiliation(s)
- Weiwei Gong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, Zhejiang, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, 100050, Beijing, China
| | - Chunliang Zhou
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, 450001, China
| | - Yize Xiao
- Yunnan Center for Disease Control and Prevention, Kunming, 650022, China
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, 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
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Cunrui Huang
- School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Disease Control and Prevention Institute of Jinan University, Guangzhou, 510632, China.
| | - Qingfeng Du
- General Practice Center, The Seventh Affiliated Hospital, Southern Medical University, Foshan, 528200, China.
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 510632, China
- Disease Control and Prevention Institute of Jinan University, Guangzhou, 510632, China
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Tian F, Qi J, Qian Z, Li H, Wang L, Wang C, Geiger SD, McMillin SE, Yin P, Lin H, Zhou M. Differentiating the effects of air pollution on daily mortality counts and years of life lost in six Chinese megacities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 827:154037. [PMID: 35192816 DOI: 10.1016/j.scitotenv.2022.154037] [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: 10/13/2021] [Revised: 02/04/2022] [Accepted: 02/16/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Ambient air pollution has been widely associated with increased mortality and years of life lost (YLL) from various diseases. However, no study has assessed that the effects of air pollution on overall YLL were due to increased number of mortalities or average YLL per death. METHODS We first conducted a time-series study from 2013 to 2016, covering six Chinese megacities. Generalized additive models with a Gaussian link were utilized to estimate the associations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) with daily overall YLL and average YLL per death from various causes, including non-accidental causes, cardiovascular diseases (CVD), respiratory diseases (RD), ischemic heart disease (IHD), chronic obstructive pulmonary diseases (COPD), stroke and acute myocardial infraction (AMI). The city-specific estimates were then pooled by random-effects meta-analysis. RESULTS A total of 1,586,741 deaths from non-accidental causes and 21,916,857 YLLs were recorded in the six cities, providing an average of 13.81 daily YLLs per death. Significant effects of PM2.5 and NO2 on daily overall YLL and daily mortality count were observed, but there were no significant effects on average YLL per death. At the pooled level, each 10 μg/m3 increase in PM2.5 and NO2 was associated with increased YLL and higher mortality due to non-accidental causes [PM2.5: 5.45 years, 95% CI: 1.47, 9.42 and ERR (excess relative risk) = 0.25%, 95% CI: 0.14%, 0.35%; NO2: 20.46 years, 95% CI: 10.77, 30.15 and ERR = 1.13%, 95% CI: 0.63%, 1.63%]. Consistent results and patterns were observed for other cause-specific diseases, including IHD, COPD, stroke and AMI. CONCLUSIONS Our study indicates observed associations between air pollution and YLL might be mainly induced by increasing mortality count, rather than increasing average life lost for each death. More relevant intervention should be performed to reduce the number of deaths due to air pollution.
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Affiliation(s)
- Fei Tian
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Jinlei Qi
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Zhengmin Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, 3545 Lafayette Avenue, Saint Louis, MO 63104, USA
| | - Huan Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Lijun Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China
| | - Sarah Dee Geiger
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Khan Annex, 1206 S. Fourth St, Champaign, IL 61820, USA
| | - Stephen Edward McMillin
- School of Social Work, College for Public Health and Social Justice, Saint Louis University, Tegeler Hall, 3550 Lindell Boulevard, St. Louis. MO 63103, USA
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
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Zhou CL, Lv LS, Jin DH, Xie YJ, Ma WJ, Hu JX, Wang CE, Xu YQ, Zhang XE, Lu C. Temperature Change between Neighboring Days Contributes to Years of Life Lost per Death from Respiratory Disease: A Multicounty Analysis in Central China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19105871. [PMID: 35627408 PMCID: PMC9141323 DOI: 10.3390/ijerph19105871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 05/06/2022] [Accepted: 05/07/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Many epidemiological studies have recently assessed respiratory mortality attributable to ambient temperatures. However, the associations between temperature change between neighboring days and years of life lost are insufficiently studied. Therefore, we assessed the attributable risk of temperature change between neighboring days on life loss due to respiratory disease. METHODS We obtained daily mortality and weather data and calculated crude rates of years of life lost for 70 counties in Hunan Province, Central China, from 2013 to 2017. A time-series design with distributed lag nonlinear model and multivariate meta-regression was used to pool the relationships between temperature change between neighboring days and rates of years of life lost. Then, we calculated the temperature change between neighboring days related to average life loss per death from respiratory disease. RESULTS The total respiratory disease death was 173,252 during the study period. The association between temperature change and years of life lost rates showed a w-shape. The life loss per death attributable to temperature change between neighboring days was 2.29 (95% CI: 0.46-4.11) years, out of which 1.16 (95% CI: 0.31-2.01) years were attributable to moderately high-temperature change between neighboring days, and 0.99 (95% CI: 0.19-1.79) years were attributable to moderately low-temperature change between neighboring days. The temperature change between neighboring days related to life loss per respiratory disease death for females (2.58 years, 95% CI: 0.22-4.93) and the younger group (2.97 years, 95% CI: -1.51-7.44) was higher than that for males (2.21 years, 95% CI: 0.26-4.16) and the elderly group (1.96 years, 95% CI: 0.85-3.08). An average of 1.79 (95% CI: 0.18-3.41) life loss per respiratory disease death was related to non-optimal ambient temperature. CONCLUSIONS The results indicated that more attention should be given to temperature change, and more public health policies should be implemented to protect public health.
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Affiliation(s)
- Chun-Liang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China; (C.-L.Z.); (D.-H.J.); (C.-E.W.); (Y.-Q.X.); (X.-E.Z.)
| | - Ling-Shuang Lv
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China; (C.-L.Z.); (D.-H.J.); (C.-E.W.); (Y.-Q.X.); (X.-E.Z.)
- Correspondence: (L.-S.L.); (C.L.)
| | - Dong-Hui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China; (C.-L.Z.); (D.-H.J.); (C.-E.W.); (Y.-Q.X.); (X.-E.Z.)
| | - Yi-Jun Xie
- Hunan Provincial Climate Center, Changsha 410007, China;
| | - Wen-Jun Ma
- School of Medicine, Jinan University, Guangzhou 510632, China;
| | - Jian-Xiong Hu
- Guangdong Provincial Institute of Public Health, Guangzhou 511430, China;
| | - Chun-E Wang
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China; (C.-L.Z.); (D.-H.J.); (C.-E.W.); (Y.-Q.X.); (X.-E.Z.)
| | - Yi-Qing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China; (C.-L.Z.); (D.-H.J.); (C.-E.W.); (Y.-Q.X.); (X.-E.Z.)
| | - Xing-E Zhang
- Hunan Provincial Center for Disease Control and Prevention, Changsha 410005, China; (C.-L.Z.); (D.-H.J.); (C.-E.W.); (Y.-Q.X.); (X.-E.Z.)
| | - Chan Lu
- XiangYa School of Public Health, Central South University, Changsha 410078, China
- Correspondence: (L.-S.L.); (C.L.)
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Li Q, Samimi C. Sub-Saharan Africa's international migration constrains its sustainable development under climate change. SUSTAINABILITY SCIENCE 2022; 17:1873-1897. [PMID: 35317493 PMCID: PMC8931456 DOI: 10.1007/s11625-022-01116-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 02/09/2022] [Indexed: 06/14/2023]
Abstract
UNLABELLED Sub-Saharan Africa (SSA) is seen as a region of mass migration and population displacement caused by poverty, violent conflict, and environmental stress. However, empirical evidence is inconclusive regarding how SSA's international migration progressed and reacted during its march to achieving the Sustainable Development Goals (SDGs). This article attempts to study the patterns and determinants of SSA's international migration and the cause and effects on sustainable development by developing a Sustainability Index and regression models. We find that international migration was primarily intra-SSA to low-income but high-population-density countries. Along with increased sustainability scores, international migration declined, but emigration rose. Climate extremes tend to affect migration and emigration but not universally. Dry extremes propelled migration, whereas wet extremes had an adverse effect. Hot extremes had an increasing effect but were insignificant. SSA's international migration was driven by food insecurity, low life expectancy, political instability and violence, high economic growth, unemployment, and urbanisation rates. The probability of emigration was mainly driven by high fertility. SSA's international migration promoted asylum seeking to Europe with the diversification of origin countries and a motive for economic wellbeing. 1% more migration flow or 1% higher probability of emigration led to a 0.2% increase in asylum seekers from SSA to Europe. Large-scale international migration and recurrent emigration constrained SSA's sustainable development in political stability, food security, and health, requiring adequate governance and institutions for better migration management and planning towards the SDGs. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s11625-022-01116-z.
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Affiliation(s)
- Qirui Li
- Africa Multiple Cluster of Excellence, University of Bayreuth, 95440 Bayreuth, Germany
- Climatology Research Group, University of Bayreuth, 95447 Bayreuth, Germany
| | - Cyrus Samimi
- Africa Multiple Cluster of Excellence, University of Bayreuth, 95440 Bayreuth, Germany
- Climatology Research Group, University of Bayreuth, 95447 Bayreuth, Germany
- Bayreuth, Centre of Ecology and Environmental Research, University of Bayreuth, 95448 Bayreuth, Germany
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Lv LS, Zhou CL, Jin DH, Ma WJ, Liu T, Xie YJ, Xu YQ, Zhang XE. Impact of ambient temperature on life loss per death from cardiovascular diseases: a multicenter study in central China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:15791-15799. [PMID: 34633619 PMCID: PMC8827384 DOI: 10.1007/s11356-021-16888-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 09/30/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND In the context of global climate change, studies have focused on the ambient temperature and mortality of cardiovascular diseases (CVDs). However, little is known about the effect of ambient temperature on year of life lost (YLL), especially the life loss per death caused by ambient temperature. In this study, we aimed to assess the relationship between ambient temperature and life loss and estimate the impact of ambient temperature on life loss per death. METHODS We collected daily time series of mortality and meteorological data from 70 locations in Hunan province, central China, in periods ranging from Jan. 1, 2013, to Dec. 31, 2017. Crude rates of YLL were calculated per 100,000 people per year (YLL/100,000 population) for each location. A distributed lag nonlinear model and multivariate meta-regression were used to estimate the associations between ambient temperature and YLL rates. Then, the average life loss per death attributable to ambient temperature was calculated. RESULTS There were 711,484 CVD deaths recorded within the study period. The exposure-response curve between ambient temperature and YLL rates was inverted J or U-shaped. Relative to the minimum YLL rate temperature, the life loss risk of extreme cold temperature lasted for 10 to 12 days, whereas the risk of extreme hot temperature appeared immediately and lasted for 3 days. On average, the life loss per death attributable to non-optimum ambient temperatures was 1.89 (95% CI, 1.21-2.56) years. Life loss was mainly caused by cold temperature (1.13, 95% CI, 0.89‑1.37), particularly moderate cold (1.00, 95% CI, 0.78‑1.23). For demographic characteristics, the mean life loss per death was relatively higher for males (2.07, 95% CI, 1.44‑2.68) and younger populations (3.72, 95% CI, 2.06‑5.46) than for females (1.88, 95% CI, 1.21-2.57) and elderly people (1.69, 95% CI, 1.28-2.10), respectively. CONCLUSIONS We found that both cold and hot temperatures significantly aggravated premature death from CVDs. Our results indicated that the whole range of effects of ambient temperature on CVDs should be given attention.
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Affiliation(s)
- Ling-Shuang Lv
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Chun-Liang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China.
| | - Dong-Hui Jin
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Wen-Jun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Yi-Jun Xie
- Hunan Provincial Climate Center, Changsha, 410007, China
| | - Yi-Qing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Xing-E Zhang
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
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10
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Zeng W, Yu M, Mai W, Zhou M, Zhou C, Xiao Y, Hou Z, Xu Y, Liu T, Hu J, Xu X, Lin L, Hu R, Li J, Jin D, Qin M, Gong W, Yin P, Xu Y, Xiao J, Li X, He G, Chen S, Zhang Y, Huang C, Rutherford S, Wu X, Huang B, Ma W. Age-specific disparity in life loss per death attributable to ambient temperature: A nationwide time-series study in China. ENVIRONMENTAL RESEARCH 2022; 203:111834. [PMID: 34358501 DOI: 10.1016/j.envres.2021.111834] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 07/30/2021] [Accepted: 08/01/2021] [Indexed: 06/13/2023]
Abstract
Age-specific discrepancy of mortality burden attributed to temperature, measured as years of life lost (YLL), has been rarely investigated. We investigated age-specific temperature-YLL rates (per 100,000) relationships and quantified YLL per death caused by non-optimal temperature in China. We collected daily meteorological data, population data and daily death counts from 364 locations in China during 2006-2017. YLL was divided into three age groups (0-64 years, 65-74 years, and ≥75 years). A distributed lag non-linear model was first employed to estimate the associations of temperature with age-specific YLL rates in each location. Then we pooled the associations using a multivariate meta-analysis. Finally, we calculated age-specific average YLL per death caused by temperature by cause of death and region. We observed greater effects of cold and hot temperature on YLL rates for the elderly compared with the young population by region or cause of death. However, YLL per death due to non-optimal temperature for different regions or causes of death decreased with age, with 2.0 (95 % CI:1.5, 2.5), 1.2 (1.1, 1.4) and 1.0 years (0.9, 1.2) life loss per death for populations aged 0-64 years, 65-74 years and over 75 years, respectively. Most life loss per death results from moderate temperature, especially moderate cold for all age groups. The effect of non-optimal temperature on YLL rates is smaller for younger populations than older ones, while the temperature-related life loss per death was more prominent for younger populations.
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Affiliation(s)
- Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Min Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
| | - Weizhen Mai
- School of Public Health, Southern Medical University, Guangzhou, China.
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China.
| | - Chunliang Zhou
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
| | - Yize Xiao
- Yunnan Center for Disease Control and Prevention, Kunming, China.
| | - Zhulin Hou
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China.
| | - Yanjun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Xiaojun Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Ruying Hu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
| | - Junhua Li
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
| | - Donghui Jin
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
| | - Mingfang Qin
- Yunnan Center for Disease Control and Prevention, Kunming, China.
| | - Weiwei Gong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
| | - Peng Yin
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, China.
| | - Yiqing Xu
- Department of Environment and Health, Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Siqi Chen
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Yonghui Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Cunrui Huang
- School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | | | - Xianbo Wu
- School of Public Health, Southern Medical University, Guangzhou, China.
| | - Biao Huang
- Jilin Provincial Center for Disease Control and Prevention, Changchun, China.
| | - Wenjun Ma
- School of Public Health, Southern Medical University, Guangzhou, China.
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11
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Zheng H, Yi W, Ding Z, Xu Z, Ho HC, Cheng J, Hossain MZ, Song J, Fan Y, Ni J, Wang Q, Xu Y, Wei J, Su H. Evaluation of life expectancy loss associated with submicron and fine particulate matter (PM 1 and PM 2.5) air pollution in Nanjing, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:68134-68143. [PMID: 34268691 DOI: 10.1007/s11356-021-15244-z] [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: 05/05/2021] [Accepted: 06/28/2021] [Indexed: 06/13/2023]
Abstract
Particulate matters with an aerodynamic diameter ≤1 μm (PM1) significantly increased mortality risk, and the effect of PM1 was even greater than that of PM2.5 (aerodynamic diameter ≤2.5 μm). But the quantitative impact of PM1 on life expectancy was unknown. We aim to examine the extent to which that people's life expectancy was shortened by PM1 and PM2.5. We obtained daily data on deaths, PM1 and PM2.5 records, and weather variables during 2016-2017 in Nanjing, China. Years of life lost (YLLs) were calculated by matching each decedent's age and sex to the Chinese life table. The fitted nonlinear dose-response associations of YLLs with PM1 and PM2.5 were estimated by utilizing a generalized additive model with a Gaussian link that controlled for confounding factors including meteorological variables, day of week, and long-term trend and seasonality. The effect estimates were presented as the YLLs when PM1 and PM2.5 concentrations fell in different ranges. Life expectancy losses attributable to PM1 and PM2.5 were calculated. Stratified analyses were also performed by age, sex, and death causes. Significant PM-YLL associations were observed, with greater increases in YLLs associated with PM1 (68.9 thousand). PM1 was estimated to reduce life expectancy, which was greater than PM2.5 (PM1: 1.67 years; PM2.5: 1.55 years). For PM1, greater years of loss in PM-related life expectancy were found in the female group, ≥65 years group, and cardiovascular disease group. Exposure to PM1 had a greater impact on life expectancy loss than did PM2.5. Constant efforts are urgently needed to control PM1 air pollution to improve people's longevity.
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Affiliation(s)
- Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, 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, Hefei, China
| | - Zhen Ding
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - 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
| | - 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, Hefei, China
| | - Mohammad Zahid Hossain
- International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B), Dhaka, Bangladesh
| | - 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, Hefei, China
| | - Yinguang Fan
- 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, Hefei, China
| | - Jing Ni
- 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, Hefei, China
| | - Qingqing Wang
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Yan Xu
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China
| | - Jing Wei
- Department of Chemical and Biochemical Engineering, Iowa Technology Institute, Center for Global and Regional Environmental Research, The University of Iowa, Iowa City, IA, USA.
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - 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, Hefei, China.
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12
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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.
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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.
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13
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Sahib S, Sharma A, Muresanu DF, Zhang Z, Li C, Tian ZR, Buzoianu AD, Lafuente JV, Castellani RJ, Nozari A, Patnaik R, Menon PK, Wiklund L, Sharma HS. Nanodelivery of traditional Chinese Gingko Biloba extract EGb-761 and bilobalide BN-52021 induces superior neuroprotective effects on pathophysiology of heat stroke. PROGRESS IN BRAIN RESEARCH 2021; 265:249-315. [PMID: 34560923 DOI: 10.1016/bs.pbr.2021.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Military personnel often exposed to high summer heat are vulnerable to heat stroke (HS) resulting in abnormal brain function and mental anomalies. There are reasons to believe that leakage of the blood-brain barrier (BBB) due to hyperthermia and development of brain edema could result in brain pathology. Thus, exploration of suitable therapeutic strategies is needed to induce neuroprotection in HS. Extracts of Gingko Biloba (EGb-761) is traditionally used in a variety of mental disorders in Chinese traditional medicine since ages. In this chapter, effects of TiO2 nanowired EGb-761 and BN-52021 delivery to treat brain pathologies in HS is discussed based on our own investigations. We observed that TiO2 nanowired delivery of EGb-761 or TiO2 BN-52021 is able to attenuate more that 80% reduction in the brain pathology in HS as compared to conventional drug delivery. The functional outcome after HS is also significantly improved by nanowired delivery of EGb-761 and BN-52021. These observations are the first to suggest that nanowired delivery of EGb-761 and BN-52021 has superior therapeutic effects in HS not reported earlier. The clinical significance in relation to the military medicine is discussed.
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Affiliation(s)
- Seaab Sahib
- Department of Chemistry & Biochemistry, University of Arkansas, Fayetteville, AR, United States
| | - Aruna Sharma
- International Experimental Central Nervous System Injury & Repair (IECNSIR), Department of Surgical Sciences, Anesthesiology & Intensive Care Medicine, Uppsala University Hospital, Uppsala University, Uppsala, Sweden.
| | - Dafin F Muresanu
- Department of Clinical Neurosciences, University of Medicine & Pharmacy, Cluj-Napoca, Romania; "RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
| | - Zhiqiang Zhang
- Department of Neurosurgery, Chinese Medicine Hospital of Guangdong Province, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Yuexiu, Guangzhou, China
| | - Cong Li
- Department of Neurosurgery, Chinese Medicine Hospital of Guangdong Province, The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Yuexiu, Guangzhou, China
| | - Z Ryan Tian
- Department of Chemistry & Biochemistry, University of Arkansas, Fayetteville, AR, United States
| | - Anca D Buzoianu
- Department of Clinical Pharmacology and Toxicology, "Iuliu Hatieganu" University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - José Vicente Lafuente
- LaNCE, Department of Neuroscience, University of the Basque Country (UPV/EHU), Leioa, Bizkaia, Spain
| | - Rudy J Castellani
- Department of Pathology, University of Maryland, Baltimore, MD, United States
| | - Ala Nozari
- Anesthesiology & Intensive Care, Massachusetts General Hospital, Boston, MA, United States
| | - Ranjana Patnaik
- Department of Biomaterials, School of Biomedical Engineering, Indian Institute of Technology, Banaras Hindu University, Varanasi, India
| | - Preeti K Menon
- Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Lars Wiklund
- International Experimental Central Nervous System Injury & Repair (IECNSIR), Department of Surgical Sciences, Anesthesiology & Intensive Care Medicine, Uppsala University Hospital, Uppsala University, Uppsala, Sweden
| | - Hari Shanker Sharma
- International Experimental Central Nervous System Injury & Repair (IECNSIR), Department of Surgical Sciences, Anesthesiology & Intensive Care Medicine, Uppsala University Hospital, Uppsala University, Uppsala, Sweden.
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14
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Whitaker J, Harling G, Sie A, Bountogo M, Hirschhorn LR, Manne-Goehler J, Bärnighausen T, Davies J. Non-fatal injuries in rural Burkina Faso amongst older adults, disease burden and health system responsiveness: a cross-sectional household survey. BMJ Open 2021; 11:e045621. [PMID: 34049913 PMCID: PMC8166610 DOI: 10.1136/bmjopen-2020-045621] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVES This study aimed to evaluate the epidemiology of injury as well as patient-reported health system responsiveness following injury and how this compares with non-injured patient experience, in older individuals in rural Burkina Faso. DESIGN Cross-sectional household survey. Secondary analysis of the CRSN Heidelberg Ageing Study dataset. SETTING Rural Burkina Faso. PARTICIPANTS 3028 adults, over 40, from multiple ethnic groups, were randomly sampled from the 2015 Nouna Health and Demographic Surveillance Site census. PRIMARY AND SECONDARY OUTCOME MEASURES Primary outcome was incidence of injury. Secondary outcomes were incidence of injury related disability and patient-reported health system responsiveness following injury. RESULTS 7.7% (232/3028) of the population reported injury in the preceding 12 months. In multivariable analyses, younger age, male sex, highest wealth quintile, an abnormal Generalised Anxiety Disorder score and lower Quality of Life score were all associated with injury. The most common mechanism of injury was being struck or hit by an object, 32.8%. In multivariable analysis, only education was significantly negatively associated with odds of disability (OR 0.407, 95% CI 0.17 to 0.997). Across all survey participants, 3.9% (119/3028) reported their most recent care seeking episode was following injury, rather than for another condition. Positive experience and satisfaction with care were reported following injury, with shorter median wait times (10 vs 20 min, p=0.002) and longer consultation times (20 vs 15 min, p=0.002) than care for another reason. Injured patients were also asked to return to health facilities more often than those seeking care for another reason, 81.4% (95% CI 73.1% to 87.9%) vs 54.8% (95% CI 49.9% to 53.6%). CONCLUSIONS Injury is an important disease burden in this older adult rural low-income and middle-income country population. Further research could inform preventative strategies, including safer rural farming methods, explore the association between adverse mental health and injury, and strengthen health system readiness to provide quality care.
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Affiliation(s)
- John Whitaker
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- King's Centre for Global Health and Health Partnerships, School of Population Health & Environmental Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
- Academic Department of Military Surgery and Trauma, Royal Centre for Defence Medicine, Birmingham, UK
| | - Guy Harling
- Institute for Global Health, University College London, London, UK
- Department of Epidemiology, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
- Africa Health Research Institute, KwaZulu-Natal, South Africa
- MRC/Wits Rural Public Health & Health Transitions Research Unit (Agincourt), University of the Witwatersrand School of Public Health, Johannesburg, South Africa
| | - Ali Sie
- Centre de Recherche en Sante de Nouna, Nouna, Burkina Faso
| | | | - Lisa R Hirschhorn
- Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Jennifer Manne-Goehler
- Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Till Bärnighausen
- Africa Health Research Institute, KwaZulu-Natal, South Africa
- Heidelberg Institute of Global Health (HIGH), Faculty of Medicine and University Hospitals, University of Heidelberg, Heidelberg, Germany
| | - Justine Davies
- Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- MRC/Wits Rural Public Health & Health Transitions Research Unit (Agincourt), University of the Witwatersrand School of Public Health, Johannesburg, South Africa
- Centre for Global Surgery, Department of Global Health, Stellenbosch University, Stellenbosch, Western Cape, South Africa
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15
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Ebi KL, Vanos J, Baldwin JW, Bell JE, Hondula DM, Errett NA, Hayes K, Reid CE, Saha S, Spector J, Berry P. Extreme Weather and Climate Change: Population Health and Health System Implications. Annu Rev Public Health 2021; 42:293-315. [PMID: 33406378 PMCID: PMC9013542 DOI: 10.1146/annurev-publhealth-012420-105026] [Citation(s) in RCA: 156] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Extreme weather and climate events, such as heat waves, cyclones, and floods, are an expression of climate variability. These events and events influenced by climate change, such as wildfires, continue to cause significant human morbidity and mortality and adversely affect mental health and well-being. Although adverse health impacts from extreme events declined over the past few decades, climate change and more people moving into harm's way could alter this trend. Long-term changes to Earth's energy balance are increasing the frequency and intensity of many extreme events and the probability of compound events, with trends projected to accelerate under certain greenhouse gas emissions scenarios. While most of these events cannot be completely avoided, many of the health risks could be prevented through building climate-resilient health systems with improved risk reduction, preparation, response, and recovery. Conducting vulnerability and adaptation assessments and developing health system adaptation plans can identify priority actions to effectively reduce risks, such as disaster risk management and more resilient infrastructure. The risks are urgent, so action is needed now.
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Affiliation(s)
- Kristie L Ebi
- Center for Health and the Global Environment, University of Washington, Seattle, Washington 98195, USA;
| | - Jennifer Vanos
- School of Sustainability, Arizona State University, Tempe, Arizona 85287, USA
| | - Jane W Baldwin
- Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York 10964, USA
| | - Jesse E Bell
- Department of Environmental, Agricultural, and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, Nebraska 68198, USA
| | - David M Hondula
- School of Geographical Sciences, Arizona State University, Tempe, Arizona 85287, USA
| | - Nicole A Errett
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington 98195, USA
| | - Katie Hayes
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, M5S 2S2, Canada
| | - Colleen E Reid
- Geography Department, University of Colorado, Boulder, Colorado 80309, USA
| | - Shubhayu Saha
- Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, USA
| | - June Spector
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington 98195, USA
- Department of Medicine, School of Medicine, University of Washington, Seattle, Washington 98195, USA
| | - Peter Berry
- Faculty of Environment, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
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16
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Liu T, Zhou C, Zhang H, Huang B, Xu Y, Lin L, Wang L, Hu R, Hou Z, Xiao Y, Li J, Xu X, Jin D, Qin M, Zhao Q, Gong W, Yin P, Xu Y, Hu J, Xiao J, Zeng W, Li X, Chen S, Guo L, Rong Z, Zhang Y, Huang C, Du Y, Guo Y, Rutherford S, Yu M, Zhou M, Ma W. Ambient Temperature and Years of Life Lost: A National Study in China. Innovation (N Y) 2021; 2:100072. [PMID: 34557729 PMCID: PMC8454660 DOI: 10.1016/j.xinn.2020.100072] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 12/12/2020] [Indexed: 12/27/2022] Open
Abstract
Although numerous studies have investigated premature deaths attributable to temperature, effects of temperature on years of life lost (YLL) remain unclear. We estimated the relationship between temperatures and YLL, and quantified the YLL per death caused by temperature in China. We collected daily meteorological and mortality data, and calculated the daily YLL values for 364 locations (2013–2017 in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces, and 2006–2011 in other locations) in China. A time-series design with a distributed lag nonlinear model was first employed to estimate the location-specific associations between temperature and YLL rates (YLL/100,000 population), and a multivariate meta-analysis model was used to pool location-specific associations. Then, YLL per death caused by temperatures was calculated. The temperature and YLL rates consistently showed U-shaped associations. A mean of 1.02 (95% confidence interval: 0.67, 1.37) YLL per death was attributable to temperature. Cold temperature caused 0.98 YLL per death with most from moderate cold (0.84). The mean YLL per death was higher in those with cardiovascular diseases (1.14), males (1.15), younger age categories (1.31 in people aged 65–74 years), and in central China (1.34) than in those with respiratory diseases (0.47), females (0.87), older people (0.85 in people ≥75 years old), and northern China (0.64) or southern China (1.19). The mortality burden was modified by annual temperature and temperature variability, relative humidity, latitude, longitude, altitude, education attainment, and central heating use. Temperatures caused substantial YLL per death in China, which was modified by demographic and regional characteristics. Years of life lost (YLL) is used to estimate the effects of temperature Both low and high temperatures can increase the YLLs Average 1.02 YLL per death is attributed to temperature exposure Temperature causes larger YLLs per death in males, younger people, and central China
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Affiliation(s)
- Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Haoming Zhang
- Yunnan Center for Disease Control and Prevention, Kunming, 650022, China
| | - Biao Huang
- Health Hazard Factors Control Department, Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Yanjun 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
| | - Lijun Wang
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China
| | - Ruying Hu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Zhulin Hou
- Health Hazard Factors Control Department, Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Yize Xiao
- Yunnan Center for Disease Control and Prevention, Kunming, 650022, China
| | - Junhua Li
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, China
| | - Xiaojun Xu
- 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 Center for Disease Control and Prevention, Kunming, 650022, China
| | - Qinglong Zhao
- Health Hazard Factors Control Department, Jilin Provincial Center for Disease Control and Prevention, Changchun, 130062, China
| | - Weiwei Gong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, 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
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Siqi Chen
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Lingchuan Guo
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Zuhua Rong
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Yonghui Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Cunrui Huang
- School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yaodong Du
- Guangdong Provincial Climate Center, Guangzhou, 510080, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3800, Australia
| | | | - Min Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Maigeng Zhou
- The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
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Hondula DM, Kuras ER, Betzel S, Drake L, Eneboe J, Kaml M, Munoz M, Sevig M, Singh M, Ruddell BL, Harlan SL. Novel metrics for relating personal heat exposure to social risk factors and outdoor ambient temperature. ENVIRONMENT INTERNATIONAL 2021; 146:106271. [PMID: 33395929 DOI: 10.1016/j.envint.2020.106271] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 10/04/2020] [Accepted: 11/05/2020] [Indexed: 06/12/2023]
Abstract
A more precise understanding of individual-level heat exposure may be helpful to advance knowledge about heat-health impacts and effective intervention strategies, especially in light of projected increases in the severity and frequency of extreme heat events. We developed and interrogated different metrics for quantifying personal heat exposure and explored their association with social risk factors. To do so, we collected simultaneous personal heat exposure data from 64 residents of metropolitan Phoenix, Arizona. From these data, we derived five exposure metrics: Mean Individually Experienced Temperature (IET), Maximum IET, Longest Exposure Period (LEP), Percentage Minutes Above Threshold (PMAT), and Degree Minutes Above Threshold (DMAT), and calculated each for Day Hours, Night Hours, and All Hours of the study period. We then calculated effect sizes for the associations between those metrics and four social risk factors: neighborhood vulnerability, income, home cooling type, and time spent outside. We also investigated exposure misclassification by constructing linear regression models of observations from a regional weather station and hourly IET for each participant. Our analysis revealed that metric choice and timeframe added depth and nuance to our understanding of differences in exposure within and between populations. We found that time spent outside and income were the two risk factors most strongly associated with personal heat exposure. We also found evidence that Mean IET is a good, but perhaps not optimal, measure for assessing group differences in exposure. Most participants' IETs were poorly correlated with regional weather station observations and the slope and correlation coefficient for linear regression models between regional weather station data and IETs varied widely among participants. We recommend continued efforts to investigate personal heat exposure, especially in combination with physiological indicators, to improve our understanding of links between ambient temperatures, social risk factors, and health outcomes.
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Affiliation(s)
- David M Hondula
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA.
| | - Evan R Kuras
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA; Department of Environmental Conservation, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Summer Betzel
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Lauren Drake
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Jason Eneboe
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Miranda Kaml
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Mary Munoz
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Mara Sevig
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Marianna Singh
- School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85281, USA
| | - Benjamin L Ruddell
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011, USA
| | - Sharon L Harlan
- Department of Health Sciences and Department of Sociology and Anthropology, Northeastern University, Boston, MA 02115, USA
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Dimitrova A, Ingole V, Basagaña X, Ranzani O, Milà C, Ballester J, Tonne C. Association between ambient temperature and heat waves with mortality in South Asia: Systematic review and meta-analysis. ENVIRONMENT INTERNATIONAL 2021; 146:106170. [PMID: 33395923 DOI: 10.1016/j.envint.2020.106170] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/16/2020] [Accepted: 09/26/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND South Asia is highly vulnerable to climate change and is projected to experience some of the highest increases in average annual temperatures throughout the century. Although the adverse impacts of ambient temperature on human health have been extensively documented in the literature, only a limited number of studies have focused on populations in this region. OBJECTIVES Our aim was to systematically review the current state and quality of available evidence on the direct relationship between ambient temperature and heat waves and all-cause mortality in South Asia. METHODS The databases Pubmed, Web of Science, Scopus and Embase were searched from 1990 to 2020 for relevant observational quantitative studies. We applied the Navigation Guide methodology to assess the strength of the evidence and performed a meta-analysis based on a novel approach that allows for combining nonlinear exposure-response associations without access to data from individual studies. RESULTS From the 6,759 screened papers, 27 were included in the qualitative synthesis and five in a meta-analysis. Studies reported an association of all-cause mortality with heat wave episodes and both high and low daily temperatures. The meta-analysis showed a U-shaped pattern, with increasing mortality for both high and low temperatures, but a statistically significant association was found only at higher temperatures - above 31° C for lag 0-1 days and above 34° C for lag 0-13 days. Effects were found to vary with cause of death, age, sex, location (urban vs. rural), level of education and socio-economic status, but the profile of vulnerabilities was somewhat inconsistent and based on a limited number of studies. Overall, the strength of the evidence for ambient temperature as a risk factor for all-cause mortality was judged as limited and for heat wave episodes as inadequate. CONCLUSIONS The evidence base on temperature impacts on mortality in South Asia is limited due to the small number of studies, their skewed geographical distribution and methodological weaknesses. Understanding the main determinants of the temperature-mortality association as well as how these may evolve in the future in a dynamic region such as South Asia will be an important area for future research. Studies on viable adaptation options to high temperatures for a region that is a hotspot for climate vulnerability, urbanisation and population growth are also needed.
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Affiliation(s)
- Asya Dimitrova
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Plaça de la Mercè, 10, 08002 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Vijendra Ingole
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Xavier Basagaña
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Plaça de la Mercè, 10, 08002 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Otavio Ranzani
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Carles Milà
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Joan Ballester
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain
| | - Cathryn Tonne
- Barcelona Institute for Global Health (ISGlobal), Barcelona Biomedical Research Park (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Plaça de la Mercè, 10, 08002 Barcelona, Spain; CIBER Epidemiología y Salud Pública, Avda. Monforte de Lemos 3-5, Madrid, Spain.
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19
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Arbuthnott K, Hajat S, Heaviside C, Vardoulakis S. Years of life lost and mortality due to heat and cold in the three largest English cities. ENVIRONMENT INTERNATIONAL 2020; 144:105966. [PMID: 32771827 DOI: 10.1016/j.envint.2020.105966] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 07/03/2020] [Accepted: 07/08/2020] [Indexed: 06/11/2023]
Abstract
There is a well-established relationship between temperature and mortality, with older individuals being most at risk in high-income settings. This raises the question of the degree to which lives are being shortened by exposure to heat or cold. Years of life lost (YLL) take into account population life expectancy and age at which mortality occurs. However, YLL are rarely used as an outcome-metric in studies of temperature-related mortality. This represents an important gap in knowledge; to better comprehend potential impacts of temperature in the context of climate change and an ageing population, it is important to understand the relationship between temperature and YLL, and also whether the risks of temperature related mortality and YLL have changed over recent years. Gridded temperature data derived from observations, and mortality data were provided by the UK Met Office and the Office for National Statistics (ONS), respectively. We derived YLL for each death using sex-specific yearly life expectancy from ONS English-national lifetables. We undertook an ecological time-series regression analysis, using a distributed-lag double-threshold model, to estimate the relationship between daily mean temperature and daily YLL and mortality between 1996 and 2013 in Greater London, the West Midlands including Birmingham, and Greater Manchester. Temperature-thresholds, as determined by model best fit, were set at the 91st (for heat-effects) and 35th (for cold-effects) percentiles of the mean temperature distribution. Secondly, we analysed whether there had been any changes in heat and cold related risk of YLL and mortality over time. Heat-effects (lag 0-2 days) were greatest in London, where for each 1 °C above the heat-threshold the risk of mortality increased by 3.9% (CI 3.5%, 4.3%) and YLL increased by 3.0% (2.5%, 3.5%). Between 1996 and 2013, the proportion of total deaths and YLL attributable to heat in London were 0.50% and 0.40% respectively. Cold-effects (lag 0-27 days) were greatest in the West Midlands, where for each 1 °C below the cold-threshold, risk of mortality increased by 3.1% (2.4%, 3.7%) and YLL also increased by 3.1% (2.2%, 3.9%). The proportion of deaths and YLL attributable to cold in the West Midlands were 3.3% and 3.2% respectively. We found no evidence of decreasing susceptibility to heat and cold over time. The addition of life expectancy information into calculations of temperature-related risk and mortality burdens for English cities is novel. We demonstrate that although older individuals are at greatest risk of temperature-related mortality, heat and cold still make a significant contribution to the YLL due to premature death.
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Affiliation(s)
- Katherine Arbuthnott
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK; Chemicals and Environmental Effects Department, Centre for Radiation, Chemical and Environmental Hazards, Public Health England, Didcot OX11 0RQ, UK.
| | - Shakoor Hajat
- Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London WC1H 9SH, UK
| | - Clare Heaviside
- Institute for Environmental Design and Engineering, University College London, Central House, 14 Woburn Place, London WC1H ONN, UK
| | - Sotiris Vardoulakis
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT 2601 Australia
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The Impact of Non-optimum Ambient Temperature on Years of Life Lost: A Multi-county Observational Study in Hunan, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17082699. [PMID: 32295256 PMCID: PMC7215980 DOI: 10.3390/ijerph17082699] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 04/01/2020] [Accepted: 04/08/2020] [Indexed: 12/27/2022]
Abstract
The ambient temperature–health relationship is of growing interest as the climate changes. Previous studies have examined the association between ambient temperature and mortality or morbidity, however, there is little literature available on the ambient temperature effects on year of life lost (YLL). Thus, we aimed to quantify the YLL attributable to non-optimum ambient temperature. We obtained data from 1 January 2013 to 31 December 2017 of 70 counties in Hunan, China. In order to combine the effects of each county, we used YLL rate as a health outcome indicator. The YLL rate was equal to the total YLL divided by the population of each county, and multiplied by 100,000. We estimated the associations between ambient temperature and YLL with a distributed lag non-linear model (DNLM) in a single county, and then pooled them in a multivariate meta-regression. The daily mean YLL rates were 22.62 y/(p·100,000), 10.14 y/(p·100,000) and 2.33 y/(p·100,000) within the study period for non-accidental, cardiovascular, and respiratory disease death. Ambient temperature was responsible for advancing a substantial fraction of YLL, with attributable fractions of 10.73% (4.36–17.09%) and 16.44% (9.09–23.79%) for non-accidental and cardiovascular disease death, respectively. However, the ambient temperature effect was not significantly for respiratory disease death, corresponding to 5.47% (−2.65–13.60%). Most of the YLL burden was caused by a cold temperature than the optimum temperature, with an overall estimate of 10.27% (4.52–16.03%) and 15.94% (8.82–23.05%) for non-accidental and cardiovascular disease death, respectively. Cold and heat temperature-related YLLs were higher in the elderly and females than the young and males. Extreme cold temperature had an effect on all age groups in different kinds of disease-caused death. This study highlights that general preventative measures could be important for moderate temperatures, whereas quick and effective measures should be provided for extreme temperatures.
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21
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Liu J, Ma Y, Wang Y, Li S, Liu S, He X, Li L, Guo L, Niu J, Luo B, Zhang K. The Impact of Cold and Heat on Years of Life Lost in a Northwestern Chinese City with Temperate Continental Climate. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16193529. [PMID: 31547211 PMCID: PMC6801473 DOI: 10.3390/ijerph16193529] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 09/06/2019] [Accepted: 09/13/2019] [Indexed: 12/16/2022]
Abstract
Cold spells and heat waves in a changing climate are well known as great public-health concerns due to their adverse effects on human health. However, very few studies have quantified health impacts of heat and cold in the region of Northwestern China. The purpose of the present study was to evaluate the effects of cold and heat on years of life lost (YLL) in Lanzhou, a city with temperate continental climate. We compiled a daily dataset including deaths, weather variables, and air pollutants in Lanzhou, China, from 2014–2017. We used a distributed lag non-linear model to estimate single-day and cumulative effects of heat and cold on daily YLL. Results indicated that both cold and heat were associated with increased YLL for registered residents in Lanzhou. Estimated heat effects appeared immediately in the first two days, while estimated cold effects lasted over a longer period (up to 30 days). Cold significantly increased the YLL of all residents except for males and those with respiratory diseases (≥65 years). Our results showed that both heat and cold had more pronounced effects on cardiovascular diseases compared to respiratory diseases. Males might be more vulnerable to heat, while females might suffer more YLL from cold. The effects of cold or heat on the elderly might appear earlier and last longer than those for other age groups.
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Affiliation(s)
- Jiangtao Liu
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou 730000, Gansu, China.
| | - Yueling Ma
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou 730000, Gansu, China.
| | - Yuhong Wang
- Lanzhou Municipal Center for Disease Control, Lanzhou 730000, Gansu, China.
| | - Sheng Li
- Lanzhou Municipal Center for Disease Control, Lanzhou 730000, Gansu, China.
| | - Shuyu Liu
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou 730000, Gansu, China.
| | - Xiaotao He
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou 730000, Gansu, China.
| | - Lanyu Li
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou 730000, Gansu, China.
| | - Lei Guo
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou 730000, Gansu, China.
| | - Jingping Niu
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou 730000, Gansu, China.
| | - Bin Luo
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou 730000, Gansu, China.
- Shanghai Key Laboratory of Meteorology and Health, Shanghai Meteorological Service, Shanghai 200030, China.
| | - Kai Zhang
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
- Southwest Center for Occupational and Environmental Health, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
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22
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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.
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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.
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23
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Kim SE, Lee H, Kim J, Lee YK, Kang M, Hijioka Y, Kim H. Temperature as a risk factor of emergency department visits for acute kidney injury: a case-crossover study in Seoul, South Korea. Environ Health 2019; 18:55. [PMID: 31200714 PMCID: PMC6570878 DOI: 10.1186/s12940-019-0491-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Accepted: 05/21/2019] [Indexed: 06/09/2023]
Abstract
BACKGROUND Previous studies show that escalations in ambient temperature are among the risk factors for acute kidney injury (AKI). However, it has not been adequately studied in our location, Seoul, South Korea. In this study, we aimed to examine the association between ambient temperatures and AKI morbidity using emergency department (ED) visit data. METHODS We obtained data on ED visits from the National Emergency Medical Center for 21,656 reported cases of AKI from 2010 to 2014. Time-stratified case-crossover design analysis based on conditional logistic regression was used to analyze short-term effects of ambient temperature on AKI after controlling for relevant covariates. The shape of the exposure-response curve, effect modification by individual demographic characteristics, season, and comorbidities, as well as lag effects, were investigated. RESULTS The odds ratio (OR) per 1 °C increase at lag 0 was 1.0087 (95% confidence interval [CI]: 1.0041-1.0134). Risks were higher during the warm season (OR = 1.0149; 95% CI: 1.0065-1.0234) than during the cool season (OR = 1.0059; 95% CI: 1.0003-1.0116) and even higher above 22.3 °C (OR = 1.0235; 95% CI: 1.0230-1.0239). CONCLUSIONS This study provides evidence that ED visits for AKI were associated with ambient temperature. Early detection and treatment of patients at risk is important in both clinical and economic concerns related to AKI.
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Affiliation(s)
- Satbyul Estella Kim
- Center for Climate Change Adaptation, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, 305-8506, Japan
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Hyewon Lee
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Jayeun Kim
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea
| | - Young Kyu Lee
- Division of Nephrology, Department of Internal Medicine, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea
| | - Minjin Kang
- Research and Analysis Team, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea
| | - Yasuaki Hijioka
- Center for Climate Change Adaptation, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, 305-8506, Japan.
| | - Ho Kim
- Institute of Health and Environment, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea.
- Department of Health Sciences, Graduate School of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, Republic of Korea.
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24
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Luan G, Yin P, Wang L, Zhou M. Association between ambient temperature and chronic obstructive pulmonary disease: a population-based study of the years of life lost. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2019; 29:246-254. [PMID: 30303404 DOI: 10.1080/09603123.2018.1533533] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Accepted: 10/04/2018] [Indexed: 06/08/2023]
Abstract
Limited evidence on the burden of chronic obstructive pulmonary disease (COPD) attributable to ambient temperature. We aim to explore the association between ambient temperature and years of life lost (YLL), and to get a more intuitive understanding of the dangers of COPD in China. Death and meteorological data of 31 Chinese provincial capital cities during 2008-2013 was analyzed in this study. Distributed Lag Non-linear Model (DLNM) was used to estimate the association between ambient temperature and mortality. The attributable fraction (AF) to cold effect ranged from 8.19 (95%CI: -8.52,19.38) to 28.98 (95%CI: -64.78,67.59), while the AF to heat effect varied from 0.02 (95%CI: -0.13,0.05) to 5.73 (95%CI: 0.31,10.22). Cold effect was higher than heat effect on COPD in women and elderly, heat effect was higher in men and younger. Low temperature can cause more serious disease burden of COPD than high temperature.
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Affiliation(s)
- Guijie Luan
- a Shandong Center for Disease Control and Prevention , Jinan , China
| | - Peng Yin
- b National Center for Chronic and Noncommunicable Disease Control and Prevention , Chinese Center for Disease Control and Prevention , Beijing , China
| | - Lijun Wang
- b National Center for Chronic and Noncommunicable Disease Control and Prevention , Chinese Center for Disease Control and Prevention , Beijing , China
| | - Maigeng Zhou
- b National Center for Chronic and Noncommunicable Disease Control and Prevention , Chinese Center for Disease Control and Prevention , Beijing , China
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25
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Jiao A, Yu C, Xiang Q, Zhang F, Chen D, Zhang L, Hu K, Zhang L, Zhang Y. Impact of summer heat on mortality and years of life lost: Application of a novel indicator of daily excess hourly heat. ENVIRONMENTAL RESEARCH 2019; 172:596-603. [PMID: 30875513 DOI: 10.1016/j.envres.2019.01.056] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2018] [Revised: 01/30/2019] [Accepted: 01/31/2019] [Indexed: 06/09/2023]
Abstract
BACKGROUND Previous studies have widely assessed heat-mortality relationships across global regions, while the epidemiological evidence regarding the heat effect on years of life lost (YLL) is relatively sparse. Current investigations using daily mean data cannot take hourly temperature variation into consideration and may underestimate heat effects. We developed a novel indicator, daily excess hourly heat (DEHH), to precisely evaluate the potential heat effects on mortality and YLL. METHODS Hourly data on temperature and daily information, including concentrations of air pollutants, relative humidity, and records of all registered deaths were obtained in Wuhan, China during the warm seasons (May-September) of 2009-2012. DEHH, developed in this study, is defined as daily total hourly temperatures that exceed a specific heat threshold. By performing time series regression analyses, we assessed the changes in daily mortality and YLL per interquartile range (IQR) increase in DEHH across different lag days. RESULTS The heat threshold evaluated by the Akaike Information Criterion for DEHH calculation is 30 °C (92th percentile of whole-year mean temperature distribution). Daily average DEHH was 13.9 °C, with an IQR of 19.9 °C. Linear exposure-response curves were found between DEHH and two health outcomes. Generally, heat effects lasted for 2-3 days and DEHH at lag 0-1 was most strongly associated with increased mortality and YLL. The effects were especially remarkable for stroke and ischemic heart disease mortality. Most intense effect on YLL was found in non-accidental deaths (20.11, 95% confidence interval: 8.90-31.33) at lag 0-1. More DEHH-related mortality and YLL from cardiovascular deaths were observed among males. People aged 0-74 years and males suffered more from YLL burden due to high temperatures. CONCLUSIONS Our study demonstrated that DEHH may be an alternative indicator to precisely measure heat effects on daily mortality and YLL. Further DEHH-based evidence from large scale investigations is needed so as to better understand heat-associated health burden and improve public response to extremely high temperatures.
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Affiliation(s)
- Anqi Jiao
- Department of Preventive Medicine, School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Chuanhua Yu
- Department of Preventive Medicine, School of Health Sciences, Wuhan University, Wuhan 430071, China; Global Health Institute, Wuhan University, Wuhan 430072, China
| | - Qianqian Xiang
- Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - Faxue Zhang
- Department of Preventive Medicine, School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Dieyi Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan 430071, China
| | - Lan Zhang
- Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China
| | - Kejia Hu
- Institute of Island and Coastal Ecosystems, Ocean College, Zhejiang University, Zhoushan 316021, China
| | - Ling Zhang
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China
| | - Yunquan Zhang
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China; Department of Preventive Medicine, School of Health Sciences, Wuhan University, Wuhan 430071, China.
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