TY - JOUR
T1 - Comparison for the effects of different components of temperature variability on mortality
T2 - a multi-country time-series study
AU - Wen, Bo
AU - Wu, Yao
AU - Guo, Yuming
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 - Valencia, César De la Cruz
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 - Diaz, Magali Hurtado
AU - Ragettli, Martina S.
AU - Hashizume, Masahiro
AU - Pascal, Mathilde
AU - Coélho, Micheline de Sousa Zanotti Stagliorio
AU - Ortega, Nicolás Valdés
AU - Ryti, Niilo
AU - Scovronick, Noah
AU - Michelozzi, Paola
AU - Matus Correa, Patricia
AU - Goodman, Patrick
AU - Saldiva, Paulo Hilario Nascimento
AU - Raz, Raanan
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 - Kim, Yoonhee
AU - Guo, Yue Leon
AU - Bell, Michelle L.
AU - Li, Shanshan
N1 - Funding Information:
This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (GNT2000581). BW by China Scholarship Council (number 202006010043); WY by China Scholarship Council (number 202006010044); SL by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (number GNT2009866); JK and AU by the Czech Science Foundation (project number 20\u201328560S); NS by the National Institute of Environmental Health Sciences-funded HERCULES Center (P30ES019776); S-CP and YLG by the Ministry of Science and Technology (Taiwan; MOST 109\u20132621-M-002\u2013021); YH by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency; MdSZSC and PHNS by the S\u00E3o Paulo Research Foundation (FAPESP); ST by the Science and Technology Commission of Shanghai Municipality (grant number 18411951600); HO and EI by the Estonian Ministry of Education and Research (IUT34\u201317); JM by a fellowship of Funda\u00E7\u00E3o para a Ci\u00EAncia e a Tecnlogia (SFRH/BPD/115112/2016); AG by the Medical Research Council UK (grant IDs: MR/V034162/1 and 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 by the EU's Horizon 2020 project, Exhaustion (grant ID 820655); VH by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017\u2013046); AT by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S); YG by Career Development Fellowship (number GNT1163693) and Leader Fellowship (number GNT2008813) 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:
© 2024
PY - 2024/5
Y1 - 2024/5
N2 - Background: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. Objectives: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. Methods: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. Results: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0–7 (0.9 °C). An IQR increase in inter-day TV0–7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0–7 and inter-day TV0–7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. Conclusions: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.
AB - Background: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. Objectives: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. Methods: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. Results: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0–7 (0.9 °C). An IQR increase in inter-day TV0–7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0–7 and inter-day TV0–7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. Conclusions: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.
KW - Inter-day
KW - Intra-day
KW - Mortality
KW - Temperature variability
UR - http://www.scopus.com/inward/record.url?scp=85192145675&partnerID=8YFLogxK
U2 - 10.1016/j.envint.2024.108712
DO - 10.1016/j.envint.2024.108712
M3 - Article
C2 - 38714028
AN - SCOPUS:85192145675
SN - 0160-4120
VL - 187
JO - Environment International
JF - Environment International
M1 - 108712
ER -
