TY - JOUR
T1 - Seasonality of mortality under a changing climate
T2 - a time-series analysis of mortality in Japan between 1972 and 2015
AU - Madaniyazi, Lina
AU - Chung, Yeonseung
AU - Kim, Yoonhee
AU - Tobias, Aurelio
AU - Ng, Chris Fook Sheng
AU - Seposo, Xerxes
AU - Guo, Yuming
AU - Honda, Yasushi
AU - Gasparrini, Antonio
AU - Armstrong, Ben
AU - Hashizume, Masahiro
N1 - Funding Information:
YC was supported by a Senior Research grant (2019R1A2C1086194) from the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT (Information and Communication Technologies). YK was supported by JSPS KAKENHI Grant Number JP19K17104. AT was supported by the JSPS Invitational Fellowships for Research in Japan (Grant S18149). YG was supported by the Career Development Fellowship of the Australian National Health and Medical Research Council (Grants APP1107107 and APP1163693). AG was supported by the Medical Research Council UK (Grants MR/M022625/1 and MR/R013349/1), by the Natural Environment Research Council UK (Grant NE/R009384/1), and by the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). YH was supported by the Environment Research and Technology Development Fund (S-14) of the Environmental Restoration and Conservation Agency, Japan.
Funding Information:
This work was primarily supported by the Japanese Society for the Promotion of Science (JSPS) KAKENHI Grant Number 19 K19461.
Publisher Copyright:
© 2021, The Author(s).
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021
Y1 - 2021
N2 - Background: Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. Methods: Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. Results: The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27–1.30), 1.53 (95% CI: 1.50–1.55), and 1.46 (95% CI: 1.44–1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08–1.10), 1.10 (95% CI: 1.08–1.11), and 1.35 (95% CI: 1.32–1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54–1.42), 1.39% (95% CI: 0.82–1.97), and 0.13% (95% CI: − 1.24 to 1.48), respectively. Conclusion: Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.
AB - Background: Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. Methods: Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. Results: The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27–1.30), 1.53 (95% CI: 1.50–1.55), and 1.46 (95% CI: 1.44–1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08–1.10), 1.10 (95% CI: 1.08–1.11), and 1.35 (95% CI: 1.32–1.39), respectively. During the period of rising temperature (1.3 °C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1 °C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54–1.42), 1.39% (95% CI: 0.82–1.97), and 0.13% (95% CI: − 1.24 to 1.48), respectively. Conclusion: Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.
KW - Climate change
KW - Mortality
KW - Seasonality
KW - Temperature
UR - http://www.scopus.com/inward/record.url?scp=85110817657&partnerID=8YFLogxK
U2 - 10.1186/s12199-021-00992-8
DO - 10.1186/s12199-021-00992-8
M3 - Article
C2 - 34217207
AN - SCOPUS:85110817657
SN - 1342-078X
VL - 26
JO - Environmental Health and Preventive Medicine
JF - Environmental Health and Preventive Medicine
IS - 1
M1 - 69
ER -
