Multifactorial Regression Model For Predicting The Level Of Heat Sensitivity In Healthy Young People In The Context Of Global Warming

Abstract

The aim: To create a mathematical model for predicting the level of heat sensitivity in healthy young people based on multivariate regression analysis. Materials and methods: 150 healthy young people aged 17-20 years answered the questionnaire “Levels of heat sensitivity”, underwent a heat test and mathematical analysis of the heart rate, after which the results were used to build a regression model of heat sensitivity. Results: The model of mathematical prediction of heat sensitivity (CHSL1/CHSL2), which we proposed for the first time, takes into account the most significant factors that influence the determination of higher and lower sensitivity to heat (Q1-Q6, %LF2, %HF1, %HF2, HR1, HR2), so its use will allow timely identification of individuals who are particularly susceptible to the effects of elevated ambient temperature and prevent the development of potential negative consequences of this exposure. Conclusions: Based on the results obtained, it is possible to use this prognostic model in the future to develop a diagnostic system for determining the level of heat sensitivity.