Estimating the burden of disease attributable to high ambient temperature across climate zones: methodological framework with a case study

Int J Epidemiol. 2023 Jun 6;52(3):783-795. doi: 10.1093/ije/dyac229.

Abstract

Background: With high temperature becoming an increasing health risk due to a changing climate, it is important to quantify the scale of the problem. However, estimating the burden of disease (BoD) attributable to high temperature can be challenging due to differences in risk patterns across geographical regions and data accessibility issues.

Methods: We present a methodological framework that uses Köppen-Geiger climate zones to refine exposure levels and quantifies the difference between the burden observed due to high temperatures and what would have been observed if the population had been exposed to the theoretical minimum risk exposure distribution (TMRED). Our proposed method aligned with the Australian Burden of Disease Study and included two parts: (i) estimation of the population attributable fractions (PAF); and then (ii) estimation of the BoD attributable to high temperature. We use suicide and self-inflicted injuries in Australia as an example, with most frequent temperatures (MFTs) as the minimum risk exposure threshold (TMRED).

Results: Our proposed framework to estimate the attributable BoD accounts for the importance of geographical variations of risk estimates between climate zones, and can be modified and adapted to other diseases and contexts that may be affected by high temperatures.

Conclusions: As the heat-related BoD may continue to increase in the future, this method is useful in estimating burdens across climate zones. This work may have important implications for preventive health measures, by enhancing the reproducibility and transparency of BoD research.

Keywords: High temperature; burden of disease; climate change; methodological framework.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Australia / epidemiology
  • Climate Change
  • Cold Temperature*
  • Cost of Illness
  • Hot Temperature*
  • Humans
  • Reproducibility of Results
  • Temperature