Chronical Illness-related Limitations of the Ability to Cope with Rising Temperatures: an Observational Study, 2nd Wave

Overview

The CLIMATE-II Observational Study examines to what extent chronically ill patients experience adverse health effects because of heat and whether the patients' specific health behavior, somatosensory amplification, risk and benefit perception, self-efficacy, health literacy, degree of urbanisation of the patients' administration district and characteristics of the patients' neighborhood are associated with these effects.

The CLIMATE-II Observational Study aims to analyse to what extent chronically ill patients experience adverse health effects because of heat and whether the patients' specific health behavior, self-efficacy, or other factors are associated with these effects. This cohort study is based on an online survey of patients with chronic illness who are recruited in GP practices across all regions of Germany. After the baseline assessment, participants fill out symptom diaries on 12 specific days of observation over a maximum period of 12 weeks. The specific days of observation are selected based on the maximum temperature that can be expected within the respective weeks. The weather forecast will be checked every Thursday. If, in the upcoming 4 days, the maximum temperature is expected to exceed 30°C, the warmest day in this time frame will be chosen. Otherwise, the weather forecast will be checked again on Monday to choose the warmest of the remaining days of the week. On each day of observation, patients are notified by email at 6 pm. Baseline assessment includes socio-demographic data, chronic diseases, health behavior, somatosensory amplification, perceived risk for adverse health effects because of heat, perceived benefit of protective behavior against heat, perceived social support, self-efficacy, and health literacy. Local data on temperatures and humidity will be assessed by the measurement stations of Germany's National Meteorological Service. Degree of urbanisation of administration districts is provided by the German Federal Institute for Research on Building, Urban Affairs and Spatial Development. Data will be analyzed by multivariable, multilevel regression analyses adjusted for possible confounders and random effects on the administration district and practice within administration district level.