Geographical Variations of the Minimum Mortality Temperature at a Global Scale: A Multicountry Study


Background: Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale. Methods: We collected data from 658 communities in 43 countries under different climates. We estimated temperature-mortality associations to derive the MMT for each community using Poisson regression with distributed lag nonlinear models. We investigated the variation in MMT by climatic zone using a mixed-effects meta-analysis and explored the association with climatic and socioeconomic indicators. Results: The geographical distribution of MMTs varied considerably by country between 14.2 and 31.1 °C decreasing by latitude. For climatic zones, the MMTs increased from alpine (13.0 °C) to continental (19.3 °C), temperate (21.7 °C), arid (24.5 °C), and tropical (26.5 °C). The MMT percentiles (MMTPs) corresponding to the MMTs decreased from temperate (79.5th) to continental (75.4th), arid (68.0th), tropical (58.5th), and alpine (41.4th). The MMTs indreased by 0.8 °C for a 1 °C rise in a community’s annual mean temperature, and by 1 °C for a 1 °C rise in its SD. While the MMTP decreased by 0.3 centile points for a 1 °C rise in a community’s annual mean temperature and by 1.3 for a 1 °C rise in its SD. Conclusions: The geographical distribution of the MMTs and MMTPs is driven mainly by the mean annual temperature, which seems to be a valuable indicator of overall adaptation across populations. Our results suggest that populations have adapted to the average temperature, although there is still more room for adaptation.

Environmental Epidemiology
Gabriel Carrasco-Escobar
Gabriel Carrasco-Escobar
Assistant Professor

My research interests include infectious diseases epidemiology, causal inference, global health, Climate Change, Data Science, Urban Health, and Geospatial modeling & viz.