Global drivers of minimum mortality temperatures in cities

Area of Science:

• Environmental Health
• Climatology
• Epidemiology

Background:

• Human mortality exhibits a significant temperature dependence, with minimum mortality temperature (MMT) being a key indicator.
• Current MMT estimations are sporadic, region-limited, and lack identified drivers, hindering comprehensive impact assessments for heat-related mortality and climate change.
• There is a need for a generalized model to estimate MMTs and understand their drivers across diverse geographical and socio-economic contexts.

Purpose of the Study:

• To systematically establish a generalized model for estimating MMTs in cities based on climatic, topographic, and socio-economic drivers.
• To identify and quantify the key drivers influencing MMT across a large sample of cities.
• To enable spatially comprehensive impact studies on heat-related mortality and facilitate temporal transfer for climate change assessments.

Main Methods:

• Utilized 400 MMTs from diverse cities to develop a generalized estimation model.
• Employed non-linear parametric regression, comparing a sigmoid model against alternatives using Akaike Information Criterion (AICc) and Root Mean Square Error (RMSE).
• Applied the validated model to estimate MMTs for 599 European cities (>100,000 inhabitants).

Main Results:

• A sigmoid model demonstrated superior performance in estimating MMTs.
• Long-term climate, elevation, and socio-economic factors were identified as significant drivers of MMT.
• Estimated MMTs in European cities showed a clear south-to-north decrease (27.8°C to 16°C), with socio-economic factors explaining regional pattern disruptions.

Conclusions:

• The developed generalized model provides a method to approximate MMTs independently of daily mortality data availability.
• Quantified climatic and non-climatic drivers of MMT, allowing for consideration of future climate and socio-economic changes.
• This approach enhances MMT comparability beyond local limits, supporting spatially comprehensive heat-related mortality impact assessments.