TY - JOUR
T1 - Global, regional, and national burden of mortality associated with short-term temperature variability from 2000–19
T2 - a three-stage modelling study
AU - Wu, Yao
AU - Li, Shanshan
AU - Zhao, Qi
AU - Wen, Bo
AU - Gasparrini, Antonio
AU - Tong, Shilu
AU - Overcenco, Ala
AU - Urban, Aleš
AU - Schneider, Alexandra
AU - Entezari, Alireza
AU - Vicedo-Cabrera, Ana Maria
AU - Zanobetti, Antonella
AU - Analitis, Antonis
AU - Zeka, Ariana
AU - Tobias, Aurelio
AU - Nunes, Baltazar
AU - Alahmad, Barrak
AU - Armstrong, Ben
AU - Forsberg, Bertil
AU - Pan, Shih Chun
AU - Íñiguez, Carmen
AU - Ameling, Caroline
AU - De la Cruz Valencia, César
AU - Åström, Christofer
AU - Houthuijs, Danny
AU - Van Dung, Do
AU - Royé, Dominic
AU - Indermitte, Ene
AU - Lavigne, Eric
AU - Mayvaneh, Fatemeh
AU - Acquaotta, Fiorella
AU - de'Donato, Francesca
AU - Rao, Shilpa
AU - Sera, Francesco
AU - Carrasco-Escobar, Gabriel
AU - Kan, Haidong
AU - Orru, Hans
AU - Kim, Ho
AU - Holobaca, Iulian Horia
AU - Kyselý, Jan
AU - Madureira, Joana
AU - Schwartz, Joel
AU - Jaakkola, Jouni J.K.
AU - Katsouyanni, Klea
AU - Hurtado Diaz, Magali
AU - Ragettli, Martina S.
AU - Hashizume, Masahiro
AU - Pascal, Mathilde
AU - de Sousa Zanotti Stagliorio Coélho, Micheline
AU - Ortega, Nicolás Valdés
AU - Ryti, Niilo
AU - Scovronick, Noah
AU - Michelozzi, Paola
AU - Correa, Patricia Matus
AU - Goodman, Patrick
AU - Nascimento Saldiva, Paulo Hilario
AU - Abrutzky, Rosana
AU - Osorio, Samuel
AU - Dang, Tran Ngoc
AU - Colistro, Valentina
AU - Huber, Veronika
AU - Lee, Whanhee
AU - Seposo, Xerxes
AU - Honda, Yasushi
AU - Guo, Yue Leon
AU - Bell, Michelle L.
AU - Guo, Yuming
N1 - Funding Information:
This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (APP2000581). YW was supported by the China Scholarship Council (number 202006010044). SL was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (number APP2009866). QZ was supported by the Program of Qilu Young Scholars of Shandong University, Jinan, China. BW was supported by the China Scholarship Council (number 202006010043). JK and AU were supported by the Czech Science Foundation (project number 20–28560S). NS was supported by the National Institute of Environmental Health Sciences-funded HERCULES Center (P30ES019776). S-CP and YLG were supported by the Ministry of Science and Technology (Taiwan; MOST 109–2621-M-002–021). YH was supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency. MdSZSC and PHNS were supported by the São Paulo Research Foundation (FAPESP). ST was supported by the Science and Technology Commission of Shanghai Municipality (grant number 18411951600). HO and EI were supported by the Estonian Ministry of Education and Research (IUT34–17). JM was supported by a fellowship of Fundação para a Ciência e a Tecnlogia (SFRH/BPD/115112/2016). AG and FS were supported by the Medical Research Council UK (grant ID MR/R013349/1), the Natural Environment Research Council UK (grant ID NE/R009384/1), and the EU's Horizon 2020 project, Exhaustion (grant ID 820655). AS, SR, and FdD were supported by the EU's Horizon 2020 project, Exhaustion (grant ID 820655). VH was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017–046). AT was supported by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). YG was supported by the Career Development Fellowship (number APP1163693) and Leader Fellowship (number APP2008813) of the Australian National Health and Medical Research Council. Statistics South Africa kindly provided the mortality data, but had no other role in the study. This Article is published in memory of Simona Fratianni, who helped to contribute the data for Romania.
Publisher Copyright:
© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2022/5
Y1 - 2022/5
N2 - Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19. Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901–2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2–4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7–5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3–10·4), followed by Europe (4·4%, 2·2–5·6) and Africa (3·3, 1·9–4·6). Interpretation: Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability. Funding: Australian Research Council, Australian National Health & Medical Research Council.
AB - Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19. Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901–2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2–4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7–5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3–10·4), followed by Europe (4·4%, 2·2–5·6) and Africa (3·3, 1·9–4·6). Interpretation: Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability. Funding: Australian Research Council, Australian National Health & Medical Research Council.
UR - http://www.scopus.com/inward/record.url?scp=85129930277&partnerID=8YFLogxK
U2 - 10.1016/S2542-5196(22)00073-0
DO - 10.1016/S2542-5196(22)00073-0
M3 - Article
C2 - 35550080
AN - SCOPUS:85129930277
SN - 2542-5196
VL - 6
SP - e410-e421
JO - The Lancet Planetary Health
JF - The Lancet Planetary Health
IS - 5
ER -