International Journal of Biometeorology

, Volume 56, Issue 4, pp 569–581

Daily average temperature and mortality among the elderly: a meta-analysis and systematic review of epidemiological evidence


DOI: 10.1007/s00484-011-0497-3

Cite this article as:
Yu, W., Mengersen, K., Wang, X. et al. Int J Biometeorol (2012) 56: 569. doi:10.1007/s00484-011-0497-3


The impact of climate change on the health of vulnerable groups such as the elderly has been of increasing concern. However, to date there has been no meta-analysis of current literature relating to the effects of temperature fluctuations upon mortality amongst the elderly. We synthesised risk estimates of the overall impact of daily mean temperature on elderly mortality across different continents. A comprehensive literature search was conducted using MEDLINE and PubMed to identify papers published up to December 2010. Selection criteria including suitable temperature indicators, endpoints, study-designs and identification of threshold were used. A two-stage Bayesian hierarchical model was performed to summarise the percent increase in mortality with a 1°C temperature increase (or decrease) with 95% confidence intervals in hot (or cold) days, with lagged effects also measured. Fifteen studies met the eligibility criteria and almost 13 million elderly deaths were included in this meta-analysis. In total, there was a 2–5% increase for a 1°C increment during hot temperature intervals, and a 1–2 % increase in all-cause mortality for a 1°C decrease during cold temperature intervals. Lags of up to 9 days in exposure to cold temperature intervals were substantially associated with all-cause mortality, but no substantial lagged effects were observed for hot intervals. Thus, both hot and cold temperatures substantially increased mortality among the elderly, but the magnitude of heat-related effects seemed to be larger than that of cold effects within a global context.


Elderly Meta-analysis Mortality Systematic review Temperature 



Credible interval


Gross domestic product


Markov chain Monte Carlo


Minimum mortality temperature

Copyright information

© ISB 2011

Authors and Affiliations

  1. 1.School of Public Health and Institute of Health and Biomedical InnovationQueensland University of TechnologyBrisbaneAustralia
  2. 2.Discipline of Mathematical Sciences, Faculty of Science and TechnologyQueensland University of TechnologyBrisbaneAustralia
  3. 3.School of Public HealthPeking UniversityBeijingChina
  4. 4.School of Public HealthQueensland University of TechnologyKelvin GroveAustralia

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