The regional drivers of heat susceptibility in Germany
Abstract
Background: Various indicators were suggested to drive heat susceptibility, but it is unclear which are most important for the German context. This study investigates high-dimensional heterogeneity in the effect of hot days on emergency hospitalizations across German districts.
Methods: We obtained emergency hospitalization rates per 1,000 in 3-day windows for the summers of 2005-2023 from the German DRG-Statistic. These were linked with temperature and dew point information from the E-OBS and HOSTRADA database. A hot day was defined as at least one day above the 98th percentile of the district-level summer heat index. Regional characteristics of the demographic, health/social, and natural/built environment domain were selected from the INKAR database as potential drivers of heterogeneity. We used a generalized random forest clustered at the district-level, where outcome and propensity scores were modelled with fixed effects estimators to control for seasonality and district-level confounding. We divided the conditional average treatment effects (CATE) of heat into quartiles and identified the most important drivers of heterogeneity based on the variable importance and observed distribution across quartiles.
Results: The occurrence of at least one heat day decreased the emergency hospitalization rate by -0.27 (95%CI: -0.21, -0.33) per 1,000 per 3-day window, with substantial variation across districts. The top three indicators for predicting effect heterogeneity on the district-level were the percentage of people seeking protection, monthly air pollution levels, and living space per person. The observed indicator profile of the highest CATE quartile furthermore included a larger population below age 6, higher car density, and a lower number of hospital beds.
Conclusions: There is substantial variation in heat susceptibility across and within districts in Germany, with a complex interplay of indicators from different domains driving heterogeneity.
Key messages: • There is substantial variation in heat susceptibility across and within districts in Germany, with a complex interplay of indicators from different domains driving heterogeneity.
• Causal forests present a useful tool for identifying high-dimensional drivers of environmental health inequalities on a regional level.
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BibTeX
@article{gueltzow2026regional,
title = {{The regional drivers of heat susceptibility in Germany}},
author = {M Gueltzow and T Benmarhnia and C Irrgang and M Ebeling},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.1267},
url = {https://doi.org/10.1093/eurpub/ckag169.1267},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - The regional drivers of heat susceptibility in Germany
AU - M Gueltzow
AU - T Benmarhnia
AU - C Irrgang
AU - M Ebeling
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.1267
UR - https://doi.org/10.1093/eurpub/ckag169.1267
AB - Background: Various indicators were suggested to drive heat susceptibility, but it is unclear which are most important for the German context. This study investigates high-dimensional heterogeneity in the effect of hot days on emergency hospitalizations across German districts. Methods: We obtained emergency hospitalization rates per 1,000 in 3-day windows for the summers of 2005-2023 from the German DRG-Statistic. These were linked with temperature and dew point information from the E-OBS and HOSTRADA database. A hot day was defined as at least one day above the 98th percentile of the district-level summer heat index. Regional characteristics of the demographic, health/social, and natural/built environment domain were selected from the INKAR database as potential drivers of heterogeneity. We used a generalized random forest clustered at the district-level, where outcome and propensity scores were modelled with fixed effects estimators to control for seasonality and district-level confounding. We divided the conditional average treatment effects (CATE) of heat into quartiles and identified the most important drivers of heterogeneity based on the variable importance and observed distribution across quartiles. Results: The occurrence of at least one heat day decreased the emergency hospitalization rate by -0.27 (95%CI: -0.21, -0.33) per 1,000 per 3-day window, with substantial variation across districts. The top three indicators for predicting effect heterogeneity on the district-level were the percentage of people seeking protection, monthly air pollution levels, and living space per person. The observed indicator profile of the highest CATE quartile furthermore included a larger population below age 6, higher car density, and a lower number of hospital beds. Conclusions: There is substantial variation in heat susceptibility across and within districts in Germany, with a complex interplay of indicators from different domains driving heterogeneity. Key messages: • There is substantial variation in heat susceptibility across and within districts in Germany, with a complex interplay of indicators from different domains driving heterogeneity. • Causal forests present a useful tool for identifying high-dimensional drivers of environmental health inequalities on a regional level.
SN - 1101-1262
SN - 1464-360X
ER -