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dc.contributor.authorHaresh T. Suppiahen
dc.contributor.authorNg, Ee Lingen
dc.contributor.authorWee, Jerichoen
dc.contributor.authorBernadette Cherianne Taimen
dc.contributor.authorMinh Huynhen
dc.contributor.authorPaul B. Gastinen
dc.contributor.authorChia, Michaelen
dc.contributor.authorLow, Chee Yongen
dc.contributor.authorLee, Jason Kai Weien
dc.identifier.citationSuppiah, H. T., Ng, E. L., Wee, J., Taim, B. C., Huynh, M., Gastin, P. B., Chia, M., Low, C. Y., & Lee, J. K. (2021). Hydration status and fluid replacement strategies of high-performance adolescent athletes: An application of machine learning to distinguish hydration characteristics. Nutrients, 13(11), Article 4073.
dc.identifier.issn2072-6643 (online)-
dc.description.abstractThere are limited data on the fluid balance characteristics and fluid replenishment behaviors of high-performance adolescent athletes. The heterogeneity of hydration status and practices of adolescent athletes warrant efficient approaches to individualizing hydration strategies. This study aimed to evaluate and characterize the hydration status and fluid balance characteristics of highperformance adolescent athletes and examine the differences in fluid consumption behaviors during training. In total, 105 high-performance adolescent athletes (male: 66, female: 39; age 14.1 1.0 y) across 11 sports had their hydration status assessed on three separate occasions‒upon rising and before a low and a high-intensity training session (pre-training). The results showed that 20‒44% of athletes were identified as hypohydrated, with 21‒44% and 15‒34% of athletes commencing low- and high-intensity training in a hypohydrated state, respectively. Linear mixed model (LMM) analyses revealed that athletes who were hypohydrated consumed more fluid (F (1.183.85)) = 5.91, (p = 0.016). Additional K-means cluster analyses performed highlighted three clusters: “Heavy sweaters with sufficient compensatory hydration habits,” “Heavy sweaters with insufficient compensatory hydration habits” and “Light sweaters with sufficient compensatory hydration habits”. Our results highlight that high-performance adolescent athletes with ad libitum drinking have compensatory mechanisms to replenish fluids lost from training. The approach to distinguish athletes by hydration characteristics could assist practitioners in prioritizing future hydration intervention protocols.-
dc.rightsCopyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://
dc.subjectTraining intensityen
dc.subjectYoung sportsmenen
dc.titleHydration status and fluid replacement strategies of high-performance adolescent athletes: An application of machine learning to distinguish hydration characteristicsen
dc.description.versionPublished versionen
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