Chronical Illness-related Limitations of the Ability to Cope With Rising Temperatures, Third Wave

Overview

The CLIMATE-III 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, and the degree of urbanisation of the patients' administration district are associated with these effects. Study participants from Germany and Italy will be included in the sample.

The CLIMATE-III 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 general practitioner (GP) practices in Germany and Italy. 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 Monday. 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 Thursday 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, somatosensory amplification, perceived risk for adverse health effects of heat, intention to implement protective behaviour, perceived benefit of this behavior, self-efficacy, and health literacy. Local data on temperatures and humidity will be provided by the meteorological services of Germany and Italy. 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.

Conditions