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Body Water Regulation and Nutrient Intake

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A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrition and Public Health".

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 34449

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Special Issue Editor

Dr. Colleen X. Munoz

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Guest Editor

Department of Health Sciences, University of Hartford, West Hartford, CT 06117, USA
Interests: hydration physiology; water intake; osmotic stress; stress physiology; exercise performance; chronic health

Special Issue Information

Dear Colleagues,

With growing evidence of the importance of body water regulation in physiological and psychological health and performance, this Special Issue aims to highlight the state-of-the-art in “Body Water Regulation and Nutrient Intake”. Myriad nutritional practices and products are publicly claimed to influence hydration status and optimize daily activities, athletic competitions, and chronic health; yet, the introductory rate of these claims and the evaluation of intake efficacy and safety do not typically align. Regulatory processes that manage body water prove highly complex and involve numerous tissues and systems, rendering hydration physiology an exciting, yet challenging scientific frontier. Further, the processes of water balance might also drive specific nutritional practices and intriguing physiological phenomena. To advance the field of body water regulation and nutrient intake, we invite the submission of both original research and impactful reviews that meaningfully contribute to the understanding of hydration physiology, healthy hydration, and unique observations related to this critical yet often forgotten nutrient: water.

Dr. Colleen X. Munoz
Guest Editor

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Keywords

Hydration physiology
Water balance
Fluid intake
Beverage intake
Osmolyte
Electrolyte
Nutrition
Athletic performance
Health

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Published Papers (7 papers)

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Research

Jump to: Review

16 pages, 1015 KiB

Open AccessArticle

Influence of Nutrient Intake on 24 Hour Urinary Hydration Biomarkers Using a Clustering-Based Approach

by William M. Adams, Michael Wininger, Mitchell E. Zaplatosch, Derek J. Hevel, Jaclyn P. Maher and Jared T. McGuirt

Nutrients 2020, 12(10), 2933; https://doi.org/10.3390/nu12102933 - 25 Sep 2020

Cited by 2 | Viewed by 2682

Abstract

Previous work focusing on understanding nutrient intake and its association with total body water homeostasis neglects to consider the collinearity of types of nutrients consumed and subsequent associations with hydration biomarkers. Therefore, the purpose of this study was to analyze consumption patterns of 23 a priori selected nutrients involved in osmotic homeostasis, as well as their association with 24 h urinary hydration markers among fifty African–American first-year college students through a repeated measures observation in a daily living setting. Through application of hierarchical clustering, we were able to identity four clusters of nutrients based on 24 h dietary recalls: (1) alcohol + pinitol, (2) water + calcium + magnesium + erythritol + inositol + sorbitol + xylitol, (3) total calories + total fat + total protein + potassium + sodium + zinc + phosphorous + arginine, and (4) total carbohydrates + total fiber + soluble fiber + insoluble fiber + mannitol + betaine. Furthermore, we found that consumption of nutrients in Cluster #2 was significantly predictive of urine osmolality (p = 0.004); no other clusters showed statistically significant associations with 24 h urinary hydration biomarkers. We conclude that there may be some nutrients that are commonly consumed concomitantly (at the day level), across a variety of settings and populations, and that a limited subset of the clustering of these nutrients may associate with body water status. Full article

(This article belongs to the Special Issue Body Water Regulation and Nutrient Intake)

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17 pages, 2397 KiB

Open AccessArticle

Impact of Nutrient Intake on Hydration Biomarkers Following Exercise and Rehydration Using a Clustering-Based Approach

by Colleen X. Muñoz, Evan C. Johnson, Laura J. Kunces, Amy L. McKenzie, Michael Wininger, Cory L. Butts, Aaron Caldwell, Adam Seal, Brendon P. McDermott, Jakob Vingren, Abigail T. Colburn, Skylar S. Wright, Virgilio Lopez III, Lawrence E. Armstrong and Elaine C. Lee

Nutrients 2020, 12(5), 1276; https://doi.org/10.3390/nu12051276 - 30 Apr 2020

Cited by 4 | Viewed by 3667

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. Full article

(This article belongs to the Special Issue Body Water Regulation and Nutrient Intake)

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13 pages, 1399 KiB

Open AccessArticle

The Link between Hypermetabolism and Hypernatremia in Severely Burned Patients

by Christopher Rugg, Mathias Ströhle, Stefan Schmid and Janett Kreutziger

Nutrients 2020, 12(3), 774; https://doi.org/10.3390/nu12030774 - 15 Mar 2020

Cited by 4 | Viewed by 3540

Abstract

Hypernatremia is common in critical care, especially in severely burned patients. Its occurrence has been linked to increased mortality. Causes of hypernatremia involve a net gain of sodium or a loss of free water. Renal loss of electrolyte-free water due to urea-induced osmotic diuresis has been described as causative in up to 10% of hypernatremic critical ill patients. In this context, excessive urea production due to protein catabolism acts as major contributor. In severe burn injury, muscle wasting occurs as result of hypermetabolism triggered by ongoing systemic inflammation. In this retrospective study, severely burned patients were analysed for the occurrence of hypernatremia and subsequent signs of hypermetabolism. The urea: creatinine ratio—as a surrogate for hypermetabolism—sufficiently discriminated between two groups. Four of nine hypernatremic burn patients (44%) had a highly elevated urea: creatinine ratio, which was clearly associated with an increased urea production and catabolic index. This hypermetabolism was linked to hypernatremia via an elevated urea- and reduced electrolyte-fraction in renal osmole excretion, which resulted in an increased renal loss of electrolyte-free water. In hypermetabolic severely burned patients, the electrolyte-free water clearance is a major contributor to hypernatremia. A positive correlation to serum sodium concentration was shown. Full article

(This article belongs to the Special Issue Body Water Regulation and Nutrient Intake)

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9 pages, 577 KiB

Open AccessArticle

What Serum Sodium Concentration Is Suggestive for Underhydration in Geriatric Patients?

by Zyta Beata Wojszel

Nutrients 2020, 12(2), 496; https://doi.org/10.3390/nu12020496 - 15 Feb 2020

Cited by 7 | Viewed by 3135

Abstract

Dehydration is a concern among aging populations and can result in hospitalization and other adverse outcomes. There is a need to establish simple measures that can help in detecting low-intake dehydration (underhydration) in geriatric patients. The predictive performance of sodium, urea, glucose, and potassium to discriminate between patients with and without underhydration was evaluated using receiver-operating characteristic (ROC) curve analysis of data collected during the cross-sectional study of patients admitted to the geriatric ward. A total of 358 participants, for whom osmolarity could be calculated with the Khajuria and Krahn equation, were recruited to the study. Impending underhydration (osmolarity > 295 mmol/L) was diagnosed in 58.4% of cases. Serum sodium, urea, fasting glucose, and potassium (individual components of the equation) were significantly higher in dehydrated participants. The largest ROC area of 0.88 was obtained for sodium, and the value 140 mMol/L was found as the best cut-off value, with the highest sensitivity (0.80; 95% CI: 0.74–0.86) and specificity (0.83; 95% CI: 0.75–0.88) for prediction of underhydration. The ROC areas of urea, glucose, and potassium were significantly lower. Serum sodium equal to 140 mmol/L or higher appeared to be suggestive of impending underhydration in geriatric patients. This could be considered as the first-step screening procedure for detecting underhydration in older adults in general practice, especially when limited resources restrict the possibility of more in-depth biochemical assessments. Full article

(This article belongs to the Special Issue Body Water Regulation and Nutrient Intake)

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13 pages, 570 KiB

Open AccessArticle

Impending Low Intake Dehydration at Admission to A Geriatric Ward- Prevalence and Correlates in a Cross-Sectional Study

by Zyta Beata Wojszel

Nutrients 2020, 12(2), 398; https://doi.org/10.3390/nu12020398 - 2 Feb 2020

Cited by 18 | Viewed by 4440

Abstract

Dehydration risk increases with frailty and functional dependency, but a limited number of studies have evaluated this association in hospitalized geriatric patients. This cross-sectional study aimed to assess the prevalence and determinants of dehydration in patients admitted to the geriatric ward. Dehydration was diagnosed when calculated osmolarity was above 295 mMol/L. Logistic regression analyses (direct and stepwise backward) were used to assess determinants of impending dehydration. 358 of 416 hospitalized patients (86.1%) were included: 274 (76.5%) women, and 309 (86.4%) 75+ year-old. Dehydration was diagnosed in 209 (58.4%) cases. Significantly higher odds for impending dehydration were observed only for chronic kidney disease with trends for diabetes and procognitive medication when controlling for several health, biochemical, and nutritional parameters and medications. After adjusting for “dementia” the negative effect of “taking procognitive medications” became a significant one. Chronic kidney disease, diabetes, taking procognitive medications and hypertension were the main variables for the outcome prediction according to the stepwise backward regression analysis. This may indicate an additional benefit of reducing the risk of dehydration when using procognitive drugs in older patients with dementia. Full article

(This article belongs to the Special Issue Body Water Regulation and Nutrient Intake)

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12 pages, 902 KiB

Open AccessArticle

Mild Dehydration Identification Using Machine Learning to Assess Autonomic Responses to Cognitive Stress

by Hugo F. Posada-Quintero, Natasa Reljin, Aurelie Moutran, Dimitrios Georgopalis, Elaine Choung-Hee Lee, Gabrielle E. W. Giersch, Douglas J. Casa and Ki H. Chon

Nutrients 2020, 12(1), 42; https://doi.org/10.3390/nu12010042 - 23 Dec 2019

Cited by 16 | Viewed by 4301

Abstract

The feasibility of detecting mild dehydration by using autonomic responses to cognitive stress was studied. To induce cognitive stress, subjects (n = 17) performed the Stroop task, which comprised four minutes of rest and four minutes of test. Nine indices of autonomic control based on electrodermal activity (EDA) and pulse rate variability (PRV) were obtained during both the rest and test stages of the Stroop task. Measurements were taken on three consecutive days in which subjects were “wet” (not dehydrated) and “dry” (experiencing mild dehydration caused by fluid restriction). Nine approaches were tested for classification of “wet” and “dry” conditions: (1) linear (LDA) and (2) quadratic discriminant analysis (QDA), (3) logistic regression, (4) support vector machines (SVM) with cubic, (5) fine Gaussian kernel, (6) medium Gaussian kernel, (7) a k-nearest neighbor (KNN) classifier, (8) decision trees, and (9) subspace ensemble of KNN classifiers (SE-KNN). The classification models were tested for all possible combinations of the nine indices of autonomic nervous system control, and their performance was assessed by using leave-one-subject-out cross-validation. An overall accuracy of mild dehydration detection was 91.2% when using the cubic SE-KNN and indices obtained only at rest, and the accuracy was 91.2% when using the cubic SVM classifiers and indices obtained only at test. Accuracy was 86.8% when rest-to-test increments in the autonomic indices were used along with the KNN and QDA classifiers. In summary, measures of autonomic function based on EDA and PRV are suitable for detecting mild dehydration and could potentially be used for the noninvasive testing of dehydration. Full article

(This article belongs to the Special Issue Body Water Regulation and Nutrient Intake)

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Review

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31 pages, 2003 KiB

Open AccessReview

Thirst and Drinking Paradigms: Evolution from Single Factor Effects to Brainwide Dynamic Networks

by Lawrence E. Armstrong and Stavros A. Kavouras

Nutrients 2019, 11(12), 2864; https://doi.org/10.3390/nu11122864 - 22 Nov 2019

Cited by 23 | Viewed by 12154

Abstract

The motivation to seek and consume water is an essential component of human fluid–electrolyte homeostasis, optimal function, and health. This review describes the evolution of concepts regarding thirst and drinking behavior, made possible by magnetic resonance imaging, animal models, and novel laboratory techniques. The earliest thirst paradigms focused on single factors such as dry mouth and loss of water from tissues. By the end of the 19th century, physiologists proposed a thirst center in the brain that was verified in animals 60 years later. During the early- and mid-1900s, the influences of gastric distention, neuroendocrine responses, circulatory properties (i.e., blood pressure, volume, concentration), and the distinct effects of intracellular dehydration and extracellular hypovolemia were recognized. The majority of these studies relied on animal models and laboratory methods such as microinjection or lesioning/oblation of specific brain loci. Following a quarter century (1994–2019) of human brain imaging, current research focuses on networks of networks, with thirst and satiety conceived as hemispheric waves of neuronal activations that traverse the brain in milliseconds. Novel technologies such as chemogenetics, optogenetics, and neuropixel microelectrode arrays reveal the dynamic complexity of human thirst, as well as the roles of motivation and learning in drinking behavior. Full article

(This article belongs to the Special Issue Body Water Regulation and Nutrient Intake)

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