Comparing the efficacy of different climate indices for prediction of labor loss, body temperatures, and thermal perception in a wide variety of warm and hot climates.

The purpose of this study was to investigate which climate/heat indices perform best in predicting heat-induced loss of physical work capacity (PWC). Integrating data from earlier studies, data from 982 exposures (75 conditions) exercising at a fixed cardiovascular load of 130 beats·min, in varying temperatures (15-50°C), humidities (20-80%), solar radiation (0-800 W·m), wind (0.2-3.5 m·s), and two clothing levels, were used to model the predictive power of ambient temperature, universal thermal climate index (UTCI), wet bulb globe temperature (WBGT), modified physiologically equivalent temperature (mPET), heat index, apparent temperature (AT), and wet bulb temperature (T) for the calculation of PWC, skin temperature (T) and core-to-skin temperature gradient, and thermal perception (thermal sensation vote, TSV) in the heat. , RMSE, and Akaike information criterion were used indicating model performance. Indices not including wind/radiation in their calculation (T, heat index, AT, and T) struggled to provide consistent predictions across variables. For PWC and TSV, UTCI and WBGT had the highest predictive power. For T, and core-to-skin temperature gradient, the physiological models UTCI and mPET worked best in seminude conditions, but clothed, AT, WBGT, and UTCI worked best. For all index predictions, T, vapor pressure, and T were shown to be the worst heat strain predictors. Although UTCI and WBGT had similar model performance using the full dataset, WBGT did not work appropriately in windy, hot-dry, conditions where WBGT predicted lower strain due to wind, whereas the empirical data, UTCI and mPET indicated that wind in fact increased the overall level of thermal strain. The findings of the current study highlight the advantages of using a physiological model-based index like UTCI when evaluating heat stress in dynamic thermal environments. There is an urgent need to determine the optimal heat stress metric when forecasting the impact of heat stress on human performance, physiological stress, and perception. We analyzed a wealth of laboratory data, simulating heart rate (HR)-paced work with wide variations in air temperature, humidity, wind speed, solar radiation, and clothing. We conclude that the universal thermal climate index (UTCI) [followed by wet-bulb globe temperature (WBGT)] is the optimal heat index to reliably predict reductions in performance, and elevations in physiological and perceptual stress.