Literature DB >> 30928859

A systematic review and meta-analysis of the association between daily mean temperature and mortality in China.

Qianlai Luo1, Shanshan Li2, Yuming Guo2, Xuemei Han3, Jouni J K Jaakkola4.   

Abstract

PURPOSE: We summarized the evidence on the effects of heat and cold exposures on mortality in China. We included studies published on this topic in both Chinese and English, thereby filling a gap in knowledge using data from a country that consists of one-fifth of the world's population.
METHODS: We conducted a systematic search of peer-reviewed studies on the association between daily mean temperature and mortality published from 2001 up to July 2018. We searched one Chinese database (China National Knowledge infrastructure, http://www.cnki.net) and three English databases (PubMed, Scopus, Web of Science). We converted the effect estimates of heat/cold to rate ratios (RRs) associated with 1° increase/decrease beyond the heat/cold reference temperatures. For studies that provided lag-specific estimates, we used both the maximum and minimum of RR estimates. We calculated summary effect estimates for all-cause and cause-specific mortalities, as well as RRs stratified by sex, age, and socioeconomic status. We also investigated patterns of heat and cold adaptation at different latitudes, and at different reference temperatures.
RESULTS: In total, 45 articles were included in this systematic review. For every 1° temperature increase/decrease beyond reference points, the rate of non-accidental mortality increased by 2% (RR, 1.02; 95% confidence interval (95% CI [1.01-1.02]) for heat and 4% (RR, 1.04; 95% CI [1.03-1.04]) for cold, respectively; the rate of cardiovascular mortality increased 3% (RR, 1.03; 95% CI [1.03-1.04]) for heat and 6% (RR, 1.06; 95% CI [1.04-1.07]) for cold; the rate of respiratory mortality increased 2% (RR, 1.02; 95% CI [1.01-1.03]) for heat and 2% (RR, 1.02; 95% CI [1.00-1.04]) for cold; the rate of cerebrovascular mortality increased 2% (RR, 1.02; 95% CI [1.02-1.03]) for heat and 3% (RR, 1.03; 95% CI [1.02-1.04]) for cold. We identified a variation in optimal temperature range related to latitude of the residential area, and differences in people's capability to adapt to heat versus cold.
CONCLUSION: We found consistent evidence of the association between temperature and mortality, as well as evidence of patterns in human adaptation, and we discussed the implications of our findings.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  China; Meta-analysis; Mortality; Systematic literature review; Temperature

Mesh:

Year:  2019        PMID: 30928859     DOI: 10.1016/j.envres.2019.03.044

Source DB:  PubMed          Journal:  Environ Res        ISSN: 0013-9351            Impact factor:   6.498


  5 in total

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2.  An Occupational Heat-Health Warning System for Europe: The HEAT-SHIELD Platform.

Authors:  Marco Morabito; Alessandro Messeri; Pascal Noti; Ana Casanueva; Alfonso Crisci; Sven Kotlarski; Simone Orlandini; Cornelia Schwierz; Christoph Spirig; Boris R M Kingma; Andreas D Flouris; Lars Nybo
Journal:  Int J Environ Res Public Health       Date:  2019-08-13       Impact factor: 3.390

3.  The association between ambient temperature and mortality of the coronavirus disease 2019 (COVID-19) in Wuhan, China: a time-series analysis.

Authors:  Gaopei Zhu; Yuhang Zhu; Zhongli Wang; Weijing Meng; Xiaoxuan Wang; Jianing Feng; Juan Li; Yufei Xiao; Fuyan Shi; Suzhen Wang
Journal:  BMC Public Health       Date:  2021-01-11       Impact factor: 3.295

4.  Time-series analysis of daily ambient temperature and emergency department visits in five US cities with a comparison of exposure metrics derived from 1-km meteorology products.

Authors:  Nikita Thomas; Stefanie T Ebelt; Andrew J Newman; Noah Scovronick; Rohan R D'Souza; Shannon E Moss; Joshua L Warren; Matthew J Strickland; Lyndsey A Darrow; Howard H Chang
Journal:  Environ Health       Date:  2021-05-07       Impact factor: 5.984

5.  Mortality Related to Air Temperature in European Cities, Based on Threshold Regression Models.

Authors:  Lida Dimitriadou; Panagiotis Nastos; Kostas Eleftheratos; John Kapsomenakis; Christos Zerefos
Journal:  Int J Environ Res Public Health       Date:  2022-03-28       Impact factor: 3.390

  5 in total

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