Many publications dealt with the monitoring of heat-related mortality. Fewer analyses referred to indicators of heat-related morbidity. The aim of this work was to describe the heat-related morbidity using rescue service data from the city of Frankfurt/Main, Germany for the time period 2014-2022, with regard to the questions: 1) How do rescue service deployments develop over the years? Is there a trend identifiable towards a decrease in deployments over the years, e.g. as an effect of either (physiological) adaptation of the population or of the measures for prevention of heat-related morbidity? 2) Which heat parameters (days with a heat warning, heat days, heat weeks, heat waves) are most strongly associated with heat-related morbidity in terms of rescue service deployments and might therefore be additionally used as an easily communicable and understandable heat-warning indicator? Rescue service data were provided by the interdisciplinary medical supply compass system "IVENA" and adjusted for population development including age development. The effect of various indicators for heat exposure, such as days with a heat warning from the German meteorological service based on the scientific concept of "perceived heat", heat days, heat wave days and heat week days on different endpoints for heat morbidity (deployments in total as well as for heat associated diagnoses) was calculated using both difference-based (difference +/- 95% CI) and ratio-based (ratio +/- 95% CI) effect estimators. Rescue services deployments in summer months increased overall from 2014 to 2022 in all age groups over the years (2698 to 3517/100.000 population). However, there was a significant decrease in 2020, which could be explained by the special situation of the COVID-19 pandemic, probably caused by the absence of tourists and commuters from the city. In addition, no data are available on the actual implementation of the measures by the population. Therefore, an effect of the measures taken to prevent heat-associated morbidity in Frankfurt am Main could not be directly demonstrated, and our first question cannot be answered on the basis of these data. Almost all heat definitions used for exposure (day with a heat warning, heat day, heat wave day, heat week day) showed significant effects on heat-associated diagnoses in every year. When analysing the effect on all de-ployments, the effect was in part strongly dependent on individual years: Heat wave days and heat week days even showed negative effects in some years. The definition heat day led to a significant increase in rescue service deployments in all single years between 2014 and 2022 (ratio 2014-2022 1.09 (95CI 1.07-1.11); with a range of 1.05 (95CI 1.01-1.09) in 2020 and 1.14 (95CI 1.08-1.21) in 2014), this was not the case for days with a heat warning (ratio 2014-2022 1.04 (95CI1.02-1.05); with a range of 1.01 (95CI 0.97-1.05) in 2017 and 1.16 (95CI 1.10-1.23). Thus being not inferior to the heat warning day, the "heat day" defined as >= 32 degrees C maximum temperature, easily obtainable from the weather forecast, can be recommended for the activities of the public health authorities (warning, surveillance etc.) regarding heat health action planning.
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