Productivity-adjusted life years lost due to non-optimum temperatures in Brazil: A nationwide time-series study
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Citações na Scopus
2
Tipo de produção
article
Data de publicação
2023
Título da Revista
ISSN da Revista
Título do Volume
Editora
ELSEVIER
Autores
WEN, Bo
ADEMI, Zanfina
WU, Yao
XU, Rongbin
YU, Pei
YE, Tingting
GUO, Yuming
LI, Shanshan
Citação
SCIENCE OF THE TOTAL ENVIRONMENT, v.873, article ID 162368, 7p, 2023
Resumo
Non-optimal temperatures are associated with premature deaths globally. However, the evidence is limited in low-and middle-income countries, and the productivity losses due to non-optimal temperatures have not been quantified. We aimed to estimate the work-related impacts and economic losses attributable to non-optimal temperatures in Brazil. We col-lected daily mortality data from 510 immediate regions in Brazil during 2000 and 2019. A two-stage time-series analysis was applied to evaluate the association between non-optimum temperatures and the Productivity-Adjusted Life-Years (PALYs) lost. The temperature-PALYs association was fitted for each location in the first stage and then we applied meta -analyses to obtain the national estimations. The attributable fraction (AF) of PALY lost due to ambient temperatures and the corresponding economic costs were calculated for different subgroups of the working-age population. A total of 3,629,661 of PALYs lost were attributed to non-optimal temperatures during 2000-2019 in Brazil, corresponding to 2.90 % (95 % CI: 1.82 %, 3.95 %) of the total PALYs lost. Non-optimal temperatures have led to US$104.86 billion (95 % CI: 65.95, 142.70) of economic costs related to PALYs lost and the economic burden was more substantial in males and the population aged 15-44 years. Higher risks of extreme cold temperatures were observed in the South region in Brazil while extreme hot temperatures were observed in the Central West and Northeast regions. In conclusion, non -optimal temperatures are associated with considerable labour losses as well as economic costs in Brazil. Tailored policies and adaptation strategies should be proposed to mitigate the impacts of non-optimal temperatures on the labour supply in a changing climate.
Palavras-chave
Non-optimal temperature, Productivity, Economic cost, Mortality
Referências
- Ademi Z, 2021, PHARMACOECONOMICS, V39, P271, DOI 10.1007/s40273-020-00999-z
- [Anonymous], 2022, LANCET, V400, P407, DOI 10.1016/S0140-6736(22)01480-5
- Arbuthnott K, 2018, ENVIRON INT, V121, P119, DOI 10.1016/j.envint.2018.08.053
- Cai W, 2021, LANCET PUBLIC HEALTH, V6, pe87, DOI 10.1016/S2468-2667(21)00003-7
- Campbell S, 2018, HEALTH PLACE, V53, P210, DOI 10.1016/j.healthplace.2018.08.017
- Chen G., 2021, LANCET PLANET HEALTH, V5, P579
- Chen Gongbo, 2021, Lancet Planet Health, V5, pe579, DOI 10.1016/S2542-5196(21)00200-X
- Dasgupta S, 2021, LANCET PLANET HEALTH, V5, pE455, DOI 10.1016/S2542-5196(21)00170-4
- ECMWF, ERA5 HOURL DAT SINGL
- Fu SH, 2018, PLOS MED, V15, DOI 10.1371/journal.pmed.1002619
- Gasparrini A, 2010, STAT MED, V29, P2224, DOI 10.1002/sim.3940
- Gasparrini A, 2015, LANCET, V386, P369, DOI 10.1016/S0140-6736(14)62114-0
- Gasparrini A, 2017, LANCET PLANET HEALTH, V1, pE360, DOI 10.1016/S2542-5196(17)30156-0
- Green H, 2019, ENVIRON RES, V171, P80, DOI 10.1016/j.envres.2019.01.010
- Guo YM, 2017, ENVIRON HEALTH PERSP, V125, DOI 10.1289/EHP1026
- Hagen I, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac5271
- Hanly P, 2015, INT J CANCER, V136, pE136, DOI 10.1002/ijc.29105
- Hird TR, 2019, DIABETOLOGIA, V62, P1195, DOI 10.1007/s00125-019-4875-4
- Hird TR, 2019, HYPERTENSION, V73, P777, DOI 10.1161/HYPERTENSIONAHA.118.12606
- ILO, 2019, WORK WARM PLAN IMP H
- Kephart JL, 2022, NAT MED, V28, P1700, DOI 10.1038/s41591-022-01872-6
- Lapola DM, 2019, CLIMATIC CHANGE, V154, P477, DOI 10.1007/s10584-019-02459-w
- Lee W, 2022, EPIDEMIOLOGY, V33, P17, DOI 10.1097/EDE.0000000000001430
- Levin RK, 2018, PLOS ONE, V13, DOI 10.1371/journal.pone.0190733
- Lyszczarz B, 2019, J GLOB HEALTH, V9, DOI 10.7189/jogh.09.020418
- Moon J, 2021, ENVIRON RES, V195, DOI 10.1016/j.envres.2021.110762
- Morais Rinaldo Macedo de, 2017, Saúde debate, V41, P101, DOI 10.1590/0103-11042017s09
- OECD, 2014, WORK AG POP
- Rayanakorn A, 2021, PLOS NEGLECT TROP D, V15, DOI 10.1371/journal.pntd.0008985
- Freitas ARR, 2018, FRONT IMMUNOL, V8, DOI 10.3389/fimmu.2017.01903
- Romanello M, 2021, LANCET, V398, P1619, DOI 10.1016/S0140-6736(21)01787-6
- Scovronick N, 2018, ENVIRON RES, V161, P229, DOI 10.1016/j.envres.2017.11.001
- Seedat S, 2021, BMJ-BRIT MED J, V374, DOI 10.1136/bmj.n1972
- Strickland MJ, 2015, J EXPO SCI ENV EPID, V25, P160, DOI 10.1038/jes.2013.16
- Uli RE, 2020, BMJ OPEN, V10, DOI 10.1136/bmjopen-2020-039221
- van Valkengoed AM, 2019, NAT CLIM CHANGE, V9, P158, DOI 10.1038/s41558-018-0371-y
- Weinberger KR, 2020, ENVIRON EPIDEMIOL, V4, DOI 10.1097/EE9.0000000000000096
- Weinberger Kate R, 2019, Environ Epidemiol, V3, pe072, DOI 10.1097/EE9.0000000000000072
- Ye T., 2021, LANCET PLANETARY HLT, V5, P599
- Yue X, 2018, NAT COMMUN, V9, DOI [10.1038/s41467-018-07921-4|, 10.1038/s41467-018-07921-4]
- Zhao Q, 2021, LANCET PLANET HEALTH, V5, pE415, DOI 10.1016/S2542-5196(21)00081-4
- Zomer E, 2021, APPL HEALTH ECON HEA, V19, P941, DOI 10.1007/s40258-021-00649-1