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Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019
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 C...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213765/ https://www.ncbi.nlm.nih.gov/pubmed/35756888 http://dx.doi.org/10.1016/j.lanwpc.2022.100493 |
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author | Liu, Jiangmei Liu, Tao Burkart, Katrin G. Wang, Haidong He, Guanhao Hu, Jianxiong Xiao, Jianpeng Yin, Peng Wang, Lijun Liang, Xiaofeng Zeng, Fangfang Stanaway, Jeffrey D. Brauer, Michael Ma, Wenjun Zhou, Maigeng |
author_facet | Liu, Jiangmei Liu, Tao Burkart, Katrin G. Wang, Haidong He, Guanhao Hu, Jianxiong Xiao, Jianpeng Yin, Peng Wang, Lijun Liang, Xiaofeng Zeng, Fangfang Stanaway, Jeffrey D. Brauer, Michael Ma, Wenjun Zhou, Maigeng |
author_sort | Liu, Jiangmei |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9213765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-92137652022-06-23 Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019 Liu, Jiangmei Liu, Tao Burkart, Katrin G. Wang, Haidong He, Guanhao Hu, Jianxiong Xiao, Jianpeng Yin, Peng Wang, Lijun Liang, Xiaofeng Zeng, Fangfang Stanaway, Jeffrey D. Brauer, Michael Ma, Wenjun Zhou, Maigeng Lancet Reg Health West Pac Articles 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. Elsevier 2022-06-16 /pmc/articles/PMC9213765/ /pubmed/35756888 http://dx.doi.org/10.1016/j.lanwpc.2022.100493 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Articles Liu, Jiangmei Liu, Tao Burkart, Katrin G. Wang, Haidong He, Guanhao Hu, Jianxiong Xiao, Jianpeng Yin, Peng Wang, Lijun Liang, Xiaofeng Zeng, Fangfang Stanaway, Jeffrey D. Brauer, Michael Ma, Wenjun Zhou, Maigeng Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019 |
title | Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019 |
title_full | Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019 |
title_fullStr | Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019 |
title_full_unstemmed | Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019 |
title_short | Mortality burden attributable to high and low ambient temperatures in China and its provinces: Results from the Global Burden of Disease Study 2019 |
title_sort | mortality burden attributable to high and low ambient temperatures in china and its provinces: results from the global burden of disease study 2019 |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9213765/ https://www.ncbi.nlm.nih.gov/pubmed/35756888 http://dx.doi.org/10.1016/j.lanwpc.2022.100493 |
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