The short-term association between environmental variables and mortality: evidence from Europe
Jens Robben, Katrien Antonio, Torsten Kleinow

TL;DR
This study develops a machine learning framework to analyze how weather and air pollution influence weekly mortality rates in European regions, revealing temperature's key role and regional differences in environmental impacts.
Contribution
It introduces a novel modeling approach combining baseline seasonal trends with environmental anomaly features to explain short-term mortality deviations in Europe.
Findings
Temperature features are most influential in explaining mortality deviations.
Environmental factors are especially relevant in southern European regions.
Evidence of harvesting effects related to heat waves was observed.
Abstract
Using fine-grained, publicly available data, this paper studies the short-term association between environmental factors, i.e., weather and air pollution characteristics, and weekly mortality rates in small geographical regions in Europe. Hereto, we develop a mortality modeling framework where a baseline model describes a region-specific, seasonal trend observed within the historical weekly mortality rates. Using a machine learning algorithm, we then explain deviations from this baseline using features constructed from environmental data that capture anomalies and extreme events. We illustrate our proposed modeling framework through a case study on more than 550 NUTS 3 regions (Nomenclature of Territorial Units for Statistics, level 3) in 20 European countries. Using interpretation tools, we unravel insights into which environmental features are most important when estimating excess or…
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Taxonomy
TopicsGlobal Health Care Issues · Climate Change and Health Impacts · Insurance, Mortality, Demography, Risk Management
