The accurate prediction of sweat rate from energy expenditure and air temperature: A proof-of-concept study.

This proof-of-concept study used a web application to predict runner sweat losses using only energy expenditure and air temperature. A field study (FS) of n = 37 runners was completed with n = 40 sweat loss observations measured over one hour (sweat rate, SR). Predictions were also compared to 10 open literature (OL) studies where individual runner SR was reported (n = 82; 109 observations). Three prediction accuracy metrics were used; for FS, the mean absolute error (MAE) and concordance correlation coefficient (CCC) were calculated to include a 95% confidence interval [CI]; for OL, the percentage concordance (PC) was examined against calculation of accumulated under- and overdrinking potential. The MAE for FS runners was 0.141 kg [0.105, 0.177], which was less than estimated scale weighing error on 85% of occasions. The CCC was 0.88 [0.82, 0.93]. The PC for OL was 96% for avoidance of both under- and overdrinking and 93% overall. All accuracy metrics and their CI's were below acceptable error tolerance. Input errors of ±10% and ± 1⁰C for energy expenditure and air temperature dropped the PC to between 84 and 90%. This study demonstrates the feasibility of accurately predicting SR from energy expenditure and air temperature alone. NOVELTY • Results demonstrate that accurate runner SR prediction is possible with knowledge of only energy expenditure and air temperature. • SR prediction error was smaller than body weighing error in 85% of observations. • Accurate runner SR prediction could help mitigate the common risks of over- and under-drinking.