Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019

Jiangmei Liu; Tao Liu; Katrin G Burkart; Haidong Wang; Guanhao He; Jianxiong Hu; Jianpeng Xiao; Peng Yin; Lijun Wang; Xiaofeng Liang; Fangfang Zeng; Jeffrey D Stanaway; Michael Brauer; Wenjun Ma; Maigeng Zhou

doi:10.1016/j.lanwpc.2022.100493

Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019

Lancet Reg Health West Pac. 2022 Jun 16:24:100493. doi: 10.1016/j.lanwpc.2022.100493. eCollection 2022 Jul.

Authors

Jiangmei Liu¹, Tao Liu², Katrin G Burkart^{3

4}, Haidong Wang^{3

4}, Guanhao He⁵, Jianxiong Hu⁵, Jianpeng Xiao⁵, Peng Yin¹, Lijun Wang¹, Xiaofeng Liang², Fangfang Zeng², Jeffrey D Stanaway^{3

4}, Michael Brauer^{3

4

6}, Wenjun Ma², Maigeng Zhou¹

Affiliations

¹ The National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention.
² Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
³ Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
⁴ Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
⁵ Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
⁶ School of Population and Public Health, The University of British Columbia, Vancouver, BC, Canada.

Abstract

Background: Non-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019.

Methods: The global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019.

Findings: We estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level.

Interpretation: A substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China.

Funding: National Key Research and Development Program.

Keywords: China; Mortality Burden; Non-optimal temperatures.