1. Impact of Nutrient Intake on Hydration Biomarkers Following Exercise and Rehydration Using a Clustering-Based Approach
- Author
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Aaron R. Caldwell, Jakob L. Vingren, Laura J. Kunces, Brendon P. McDermott, Skylar Wright, Adam D. Seal, Lawrence E. Armstrong, Colleen X. Muñoz, Amy L. McKenzie, Elaine C. Lee, Abigail T. Colburn, Cory L. Butts, Evan C. Johnson, Michael Wininger, and Virgilio Lopez
- Subjects
Adult ,Male ,Body water ,Drinking ,030209 endocrinology & metabolism ,lcsh:TX341-641 ,Organism Hydration Status ,Urine ,collinearity ,Article ,Machine Learning ,03 medical and health sciences ,chemistry.chemical_compound ,Eating ,Young Adult ,0302 clinical medicine ,Nutrient ,Glycemic load ,medicine ,Cluster Analysis ,Humans ,Nutritional Physiological Phenomena ,Food science ,Aged ,Nutrition and Dietetics ,Pinitol ,exercise ,Urine specific gravity ,Glycopeptides ,copeptin ,030229 sport sciences ,Middle Aged ,sport nutrition ,Bicycling ,Plasma osmolality ,nutrition ,chemistry ,Linear Models ,Fluid Therapy ,Female ,Mannitol ,lcsh:Nutrition. Foods and food supply ,hydration ,Biomarkers ,Food Science ,medicine.drug ,clustering - Abstract
We investigated the impact of nutrient intake on hydration biomarkers in cyclists before and after a 161 km ride, including one hour after a 650 mL water bolus consumed post-ride. To control for multicollinearity, we chose a clustering-based, machine learning statistical approach. Five hydration biomarkers (urine color, urine specific gravity, plasma osmolality, plasma copeptin, and body mass change) were configured as raw- and percent change. Linear regressions were used to test for associations between hydration markers and eight predictor terms derived from 19 nutrients merged into a reduced-dimensionality dataset through serial k-means clustering. Most predictor groups showed significant association with at least one hydration biomarker: 1) Glycemic Load + Carbohydrates + Sodium, 2) Protein + Fat + Zinc, 3) Magnesium + Calcium, 4) Pinitol, 5) Caffeine, 6) Fiber + Betaine, and 7) Water, potassium + three polyols, and mannitol + sorbitol showed no significant associations with any hydration biomarker. All five hydration biomarkers were associated with at least one nutrient predictor in at least one configuration. We conclude that in a real-life scenario, some nutrients may serve as mediators of body water, and urine-specific hydration biomarkers may be more responsive to nutrient intake than measures derived from plasma or body mass.
- Published
- 2020