文章基本信息

标题：Impact of Nutrient Intake on Hydration Biomarkers Following Exercise and Rehydration Using a Clustering-Based Approach
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作者：Colleen X. Muñoz ; Evan C. Johnson ; Laura J. Kunces 等
期刊名称：Nutrients
电子版ISSN：2072-6643
出版年度：2020
卷号：12
期号：5
页码：1276-1292
DOI：10.3390/nu12051276
出版社：MDPI Publishing
摘要：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.
关键词：hydration; nutrition; sport nutrition; exercise; copeptin; collinearity; clustering hydration ; nutrition ; sport nutrition ; exercise ; copeptin ; collinearity ; clustering