Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study

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 prem...

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Main Authors: Bo Wen, Zanfina Ademi, Yao Wu, Rongbin Xu, Pei Yu, Yanming Liu, Wenhua Yu, Tingting Ye, Wenzhong Huang, Zhengyu Yang, Yiwen Zhang, Yuxi Zhang, Ke Ju, Simon Hales, Eric Lavigne, Paulo Hilario Nascimento Sadiva, Micheline de Sousa Zanotti Stagliorio Coêlho, Patricia Matus, Ho Kim, Kraichat Tantrakarnapa, Wissanupong Kliengchuay, Anthony Capon, Peng Bi, Bin Jalaludin, Wenbiao Hu, Donna Green, Ying Zhang, Julie Arblaster, Dung Phung, Yuming Guo, Shanshan Li
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:Environment International
Online Access:http://www.sciencedirect.com/science/article/pii/S0160412024006822
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author Bo Wen
Zanfina Ademi
Yao Wu
Rongbin Xu
Pei Yu
Yanming Liu
Wenhua Yu
Tingting Ye
Wenzhong Huang
Zhengyu Yang
Yiwen Zhang
Yuxi Zhang
Ke Ju
Simon Hales
Eric Lavigne
Paulo Hilario Nascimento Sadiva
Micheline de Sousa Zanotti Stagliorio Coêlho
Patricia Matus
Ho Kim
Kraichat Tantrakarnapa
Wissanupong Kliengchuay
Anthony Capon
Peng Bi
Bin Jalaludin
Wenbiao Hu
Donna Green
Ying Zhang
Julie Arblaster
Dung Phung
Yuming Guo
Shanshan Li
author_facet Bo Wen
Zanfina Ademi
Yao Wu
Rongbin Xu
Pei Yu
Yanming Liu
Wenhua Yu
Tingting Ye
Wenzhong Huang
Zhengyu Yang
Yiwen Zhang
Yuxi Zhang
Ke Ju
Simon Hales
Eric Lavigne
Paulo Hilario Nascimento Sadiva
Micheline de Sousa Zanotti Stagliorio Coêlho
Patricia Matus
Ho Kim
Kraichat Tantrakarnapa
Wissanupong Kliengchuay
Anthony Capon
Peng Bi
Bin Jalaludin
Wenbiao Hu
Donna Green
Ying Zhang
Julie Arblaster
Dung Phung
Yuming Guo
Shanshan Li
author_sort Bo Wen
collection DOAJ
description 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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spelling doaj-art-f323c6f251b64c7585d1e569b80bd2342024-11-22T07:35:44ZengElsevierEnvironment International0160-41202024-11-01193109096Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country studyBo Wen0Zanfina Ademi1Yao Wu2Rongbin Xu3Pei Yu4Yanming Liu5Wenhua Yu6Tingting Ye7Wenzhong Huang8Zhengyu Yang9Yiwen Zhang10Yuxi Zhang11Ke Ju12Simon Hales13Eric Lavigne14Paulo Hilario Nascimento Sadiva15Micheline de Sousa Zanotti Stagliorio Coêlho16Patricia Matus17Ho Kim18Kraichat Tantrakarnapa19Wissanupong Kliengchuay20Anthony Capon21Peng Bi22Bin Jalaludin23Wenbiao Hu24Donna Green25Ying Zhang26Julie Arblaster27Dung Phung28Yuming Guo29Shanshan Li30Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaHealth Economics and Policy Evaluation Research (HEPER) Group, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaSydney Institute of Agriculture, School of Life & Environmental Sciences, The University of Sydney, Eveleigh, NSW 2015, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaDepartment of Public Health, University of Otago, Wellington, New ZealandPopulation Studies Division, Health Canada, 269 Laurier Avenue West, Ottawa, ON K1A 0K9, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, CanadaLaboratory of Urban Health, Faculty of Medicine, University of São Paulo/INSPER, São Paulo, SP 05508-060, BrazilLaboratory of Urban Health, Faculty of Medicine, University of São Paulo/INSPER, São Paulo, SP 05508-060, BrazilSchool of Medicine, University of the Andes (Chile), Las Condes, Región Metropolitana, 12455, ChileSeoul National University, Seoul 8826, South KoreaSocial and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Krung Thep Maha Nakhon, 10400, ThailandSocial and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Krung Thep Maha Nakhon, 10400, ThailandSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaSchool of Public Health, The University of Adelaide, Adelaide, SA 5005, AustraliaSchool of Population Health, The University of New South Wales, Sydney, NSW 2052, AustraliaSchool of Public Health & Social Work, Queensland University of Technology, Brisbane, QLD 4059, AustraliaSchool of Biological, Earth & Environmental Sciences, The University of New South Wales, Sydney, NSW 2052, AustraliaSydney School of Public Health, The University of Sydney, Sydney, NSW 2006, AustraliaSchool of Earth, Atmosphere and Environment, Monash University, Melbourne, VIC 3004, AustraliaSchool of Public Health, University of Queensland, Brisbane, QLD 4072, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, AustraliaClimate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia; Corresponding author at: Shanshan Li, Climate, Air Quality Research (CARE) Unit, School of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC 3004, Australia.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.http://www.sciencedirect.com/science/article/pii/S0160412024006822
spellingShingle Bo Wen
Zanfina Ademi
Yao Wu
Rongbin Xu
Pei Yu
Yanming Liu
Wenhua Yu
Tingting Ye
Wenzhong Huang
Zhengyu Yang
Yiwen Zhang
Yuxi Zhang
Ke Ju
Simon Hales
Eric Lavigne
Paulo Hilario Nascimento Sadiva
Micheline de Sousa Zanotti Stagliorio Coêlho
Patricia Matus
Ho Kim
Kraichat Tantrakarnapa
Wissanupong Kliengchuay
Anthony Capon
Peng Bi
Bin Jalaludin
Wenbiao Hu
Donna Green
Ying Zhang
Julie Arblaster
Dung Phung
Yuming Guo
Shanshan Li
Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study
Environment International
title Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study
title_full Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study
title_fullStr Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study
title_full_unstemmed Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study
title_short Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study
title_sort non optimum temperatures led to labour productivity burden by causing premature deaths a multi country study
url http://www.sciencedirect.com/science/article/pii/S0160412024006822
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