Humans exercising in the heat: A review on sweat models and a comparison to recent experimental datasets

Sweating is a vital thermoregulatory mechanism in humans for maintaining thermal balance during exercise and exposure to hot environments. The development of models that predict sweat rate based on body temperature has been ongoing for over half a century. Here, we compared predicted water loss rates (WLR) from these models to actual observations collected during 780 participant-exposures in three independent laboratory-based experiments. In these experiments, male participants aged 19-50 years cycled or walked at various intensities (metabolic heat productions between 200 and 970 W), in air temperatures ranging from -40°C to 50°C, relative humidities (14% to 95%), and air velocities (<0.2 to 10 m/s), while wearing different clothing ensembles (thermal insulation 0.20 to 3.75 clo). The models' performances were evaluated by the coefficient of determination (R²) and Root Mean Square Error (RMSE). Performance varied greatly with a maximum R² value of 0.5 and RMSE values ranging from 10.4 to 4.9 g/min. Models with a lower sweat onset core temperature setpoint performed better and most models generally underestimated the water loss at higher WLR. Optimization of the core and skin temperature setpoints suggests preferred core temperature setpoints within a narrow range (36.2°C to 36.6°C). Even with optimized inputs, R² values were around 0.5, meaning only 50% of the variance in observed WLR was explained by the models. Better model consideration of relations between body temperature and sweat rate, and the incorporation of non-thermal exercise-induced sweat promotion, may reduce model underpredictions at higher exercise intensities.