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Wen B, Ademi Z, Wu Y, Xu R, Yu P, Liu Y, Yu W, Ye T, Huang W, Yang Z, Zhang Y, Zhang Y, Ju K, Hales S, Lavigne E, Hilario Nascimento Sadiva P, de Sousa Zanotti Stagliorio Coêlho M, Matus P, Kim H, Tantrakarnapa K, Kliengchuay W, Capon A, Bi P, Jalaludin B, Hu W, Green D, Zhang Y, Arblaster J, Phung D, Guo Y, Li S. Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study. ENVIRONMENT INTERNATIONAL 2024; 193:109096. [PMID: 39488998 DOI: 10.1016/j.envint.2024.109096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2024] [Revised: 09/22/2024] [Accepted: 10/22/2024] [Indexed: 11/05/2024]
Abstract
BACKGROUND Non-optimum temperatures are associated with a considerable mortality burden. However, there is a lack of evaluation of labour productivity losses related to premature deaths due to non-optimum temperatures. This study aimed to quantify the labour productivity burden associated with premature deaths related to non-optimum temperatures and explore the potential socio-economic vulnerabilities. METHODS Daily all-cause mortality data were collected from 1,066 locations in 7 countries (Australia, Brazil, Canada, Chile, New Zealand, South Korea, and Thailand). Productivity-Adjusted Life-Year (PALY) loss due to each premature death was calculated to measure the labour productivity loss, by multiplying the years of working life lost by the proportion of the equivalent full-time (EFT) workers. A two-stage times series design and the generalized linear regression model with a quasi-Poisson family were applied to assess the association between non-optimum temperatures and the PALY loss due to premature deaths. RESULTS We observed a U-shaped relationship between temperature and PALY lost due to premature mortality. We estimated that 2.51% (95% eCI: 2.05%, 2.92%) of PALY losses could be attributed to non-optimal temperatures, with cold-related deaths contributing 1.26% (95% eCI: 0.94%, 1.54%) and heat-related deaths contributing 1.25% (95% eCI: 0.96%, 1.51%). Cold temperature contributed to the most PALYs lost in those aged 45-54 and 55-64, while heat-related losses predominated among the 15-44 age group. We also observed that the fractions of PALY lost attributed to extreme heat were positively associated with the relative deprivation index, while negatively associated with GDP per capita. CONCLUSION This multi-country study highlights that non-optimum temperatures led to a considerable labour productivity loss and socioeconomically disadvantaged communities experience greater losses.
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Affiliation(s)
- Bo Wen
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Zanfina Ademi
- Health Economics and Policy Evaluation Research (HEPER) Group, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Australia
| | - Yao Wu
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Rongbin Xu
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Pei Yu
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Yanming Liu
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Wenhua Yu
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Tingting Ye
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Wenzhong Huang
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Zhengyu Yang
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Yiwen Zhang
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Yuxi Zhang
- Sydney Institute of Agriculture, School of Life & Environmental Sciences, The University of Sydney, Eveleigh, NSW 2015, Australia
| | - Ke Ju
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Simon Hales
- Department of Public Health, University of Otago, Wellington, New Zealand
| | - Eric Lavigne
- Population Studies Division, Health Canada, 269 Laurier Avenue West, Ottawa, ON K1A 0K9, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
| | | | | | - Patricia Matus
- School of Medicine, University of the Andes (Chile), Las Condes, Región Metropolitana, 12455, Chile
| | - Ho Kim
- Seoul National University, Seoul 8826, South Korea
| | - Kraichat Tantrakarnapa
- Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Krung Thep Maha Nakhon, 10400, Thailand
| | - Wissanupong Kliengchuay
- Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Krung Thep Maha Nakhon, 10400, Thailand
| | - Anthony Capon
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Bin Jalaludin
- School of Population Health, The University of New South Wales, Sydney, NSW 2052, Australia
| | - Wenbiao Hu
- School of Public Health & Social Work, Queensland University of Technology, Brisbane, QLD 4059, Australia
| | - Donna Green
- School of Biological, Earth & Environmental Sciences, The University of New South Wales, Sydney, NSW 2052, Australia
| | - Ying Zhang
- Sydney School of Public Health, The University of Sydney, Sydney, NSW 2006, Australia
| | - Julie Arblaster
- School of Earth, Atmosphere and Environment, Monash University, Melbourne, VIC 3004, Australia
| | - Dung Phung
- School of Public Health, University of Queensland, Brisbane, QLD 4072, Australia
| | - Yuming Guo
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Shanshan Li
- Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
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Xie Y, Zhou Z, Sun Q, Zhao M, Pu J, Li Q, Sun Y, Dai H, Li T. Social-economic transitions and vulnerability to extreme temperature events from 1960 to 2020 in Chinese cities. iScience 2024; 27:109066. [PMID: 38361620 PMCID: PMC10867637 DOI: 10.1016/j.isci.2024.109066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 12/13/2023] [Accepted: 01/25/2024] [Indexed: 02/17/2024] Open
Abstract
Climate change leads to more frequent and intense extreme temperature events, causing a significant number of excess deaths. Using an epidemiological approach, we analyze all-cause deaths related to heatwaves and cold spells in 2,852 Chinese counties from 1960 to 2020. Economic losses associated with these events are determined through the value of statistical life. Findings reveal that cold-related cumulative excess deaths (1,133 thousand) are approximately 2.5 times higher than heat-related deaths, despite an increase in heat-related fatalities in recent decades. Monetized mortality due to heat-related events is estimated at 1,284 billion CNY, while cold-related economic loss is 1,510 billion CNY. Notably, cities located in colder regions experience more heat-related excess deaths, and vice versa. Economic development does not significantly reduce mortality risks to heatwaves across China. This study provides insights into the spatial-temporal heterogeneity of heatwaves and cold spells mortality, essential for policymakers ensuring long-term climate adaptation and sustainability.
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Affiliation(s)
- Yang Xie
- School of Economics and Management, Beihang University, Beijing, China
| | - Ziqiao Zhou
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Qinghua Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Mengdan Zhao
- School of Economics and Management, Beihang University, Beijing, China
| | - Jinlu Pu
- School of Economics and Management, Beihang University, Beijing, China
| | - Qiutong Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yue Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hancheng Dai
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
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Ji JS, Xia Y, Liu L, Zhou W, Chen R, Dong G, Hu Q, Jiang J, Kan H, Li T, Li Y, Liu Q, Liu Y, Long Y, Lv Y, Ma J, Ma Y, Pelin K, Shi X, Tong S, Xie Y, Xu L, Yuan C, Zeng H, Zhao B, Zheng G, Liang W, Chan M, Huang C. China's public health initiatives for climate change adaptation. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 40:100965. [PMID: 38116500 PMCID: PMC10730322 DOI: 10.1016/j.lanwpc.2023.100965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 10/01/2023] [Accepted: 11/01/2023] [Indexed: 12/21/2023]
Abstract
China's health gains over the past decades face potential reversals if climate change adaptation is not prioritized. China's temperature rise surpasses the global average due to urban heat islands and ecological changes, and demands urgent actions to safeguard public health. Effective adaptation need to consider China's urbanization trends, underlying non-communicable diseases, an aging population, and future pandemic threats. Climate change adaptation initiatives and strategies include urban green space, healthy indoor environments, spatial planning for cities, advance location-specific early warning systems for extreme weather events, and a holistic approach for linking carbon neutrality to health co-benefits. Innovation and technology uptake is a crucial opportunity. China's successful climate adaptation can foster international collaboration regionally and beyond.
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Affiliation(s)
- John S. Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Yanjie Xia
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Linxin Liu
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Weiju Zhou
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National School of Public Health, Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Guanghui Dong
- Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Qinghua Hu
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jingkun Jiang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National School of Public Health, Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Tiantian Li
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yi Li
- Public Meteorological Service Centre, China Meteorological Administration, Beijing, China
| | - Qiyong Liu
- National Institute of Infectious Diseases at China, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanxiang Liu
- Public Meteorological Service Centre, China Meteorological Administration, Beijing, China
| | - Ying Long
- School of Architecture, Tsinghua University, Beijing, China
| | - Yuebin Lv
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jian Ma
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Yue Ma
- School of Architecture, Tsinghua University, Beijing, China
| | - Kinay Pelin
- School of Climate Change and Adaptation, University of Prince Edward Island, Prince Edward Island, Canada
| | - Xiaoming Shi
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Shilu Tong
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Queensland University of Technology, Brisbane, Australia
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, China
| | - Lei Xu
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Changzheng Yuan
- School of Public Health, Zhejiang University, Hangzhou, China
| | - Huatang Zeng
- Shenzhen Health Development Research and Data Management Center, Shenzhen, China
| | - Bin Zhao
- Department of Building Science, School of Architecture, Tsinghua University, Beijing, China
| | - Guangjie Zheng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
| | - Wannian Liang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Margaret Chan
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
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