AUTHOR=Cheuvront Samuel N. , Sollanek Kurt J. , Kenefick Robert W. 

TITLE=Forecasting individual exercise sweat losses from forecast air temperature and energy expenditure

JOURNAL=Frontiers in Sports and Active Living

VOLUME=Volume 5 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/sports-and-active-living/articles/10.3389/fspor.2023.1277070

DOI=10.3389/fspor.2023.1277070

ISSN=2624-9367

ABSTRACT=Introduction: Recent success in predicting individual sweat losses from air temperature and energy expenditure measurements suggests potential for forecasting individual sweat losses for future combinations of environment and exercise. The purpose of this study was to determine the plausibility of accurately forecasting exercise sweat losses from meteorological air temperature forecasts and planned individual energy expenditure estimates. Potential impact on plasma sodium was also estimated when setting drinking rates equal to forecast sweat losses. Materials and Methods: Individual exercise sweat losses (equated to water needs) and energy expended while running were measured in thirty-three participants along with air temperature and compared to forecasts of the same. Forecast inputs were used in a webapp to forecast exercise sweat losses for comparison to observed values. The bias between forecast and observed exercise sweat losses was used to calculate the potential drinking impact on plasma sodium. Results: The concordance correlation coefficient between forecast and observed values was 0.95, 0.96, and 0.91 for air temperature, energy expenditure, and exercise sweat losses, indicating excellent agreement and none significantly different by t-test. Perfect matching of water intake to sweat losses would have lowered plasma sodium from 140 to 138 mmol/L; calculations using the 95% limits of agreement for bias showed that drinking according to forecast exercise sweat losses would have altered plasma sodium from 140 to between 136 and 141 mmol/L. Conclusions: Outcomes support the strong potential for accurately forecasting exercise sweat losses from commonly available meteorological air temperature forecasts and energy expenditure from planned running distance.