The association between environmental variables and short-term mortality: evidence from Europe

Environmental Variables

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Jens Robben of the Faculty of Economics and Business, KU Leuven and LRisk, Leuven Research Center on Insurance and Financial Risk Analysis, KU Leuven. 

Katrien Antonio  of the Faculty of Economics and Business, KU Leuven; Faculty of Economics and Business, University of Amsterdam; LRisk, Leuven Research Center on Insurance and Financial Risk Analysis, KU Leuven; LStat, Leuven Statistics Research Center, KU Leuven and RCLR, Research Centre for Longevity Risk, University of Amsterdam. 

Torsten Kleinow of the Faculty of Economics and Business, University of Amsterdam and RCLR, Research Centre for Longevity Risk, University of Amsterdam.  the Research Centre for Longevity Risk, University of Amsterdam, and Netspar

Abstract:

Using fine-grained, publicly available data, this paper studies the association between environmental factors, i.e., variables capturing weather and air pollution characteristics, and weekly mortality rates in small geographical regions in Europe.

Hereto, we develop a mortality modelling framework where a baseline captures a region-specific, seasonal historical trend observed within the weekly mortality rates. Using a machine learning algorithm, we then explain deviations from this baseline using anomalies and extreme indices constructed from the environmental data. We illustrate our proposed modelling framework through a case study on more than 550 NUTS 3 regions (Nomenclature of Territorial Units for Statistics, level 3) located in 20 different European countries. Through interpretation tools, we unravel insights into which environmental features are most important when estimating excess or deficit mortality with respect to the baseline and explore how these features interact. Moreover, we investigate harvesting effects of the environmental features through our constructed weekly mortality modelling framework.

Our findings show that temperature-related features exert the most significant influence in explaining deviations in mortality from the baseline. Furthermore, we find that environmental features prove particularly beneficial in southern regions for explaining elevated levels of mortality over short time periods.

Keywords:

Weekly mortality modelling; high-resolution gridded datasets; environmental data

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