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Background: The beverage hydration index (BHI) is a composite measure of fluid balance after consuming a test beverage relative to water. BHI is a relatively new measure that has been explored in young, but not yet older, adults., Objective: The aim of this study was to investigate potential differences in BHI between euhydrated younger and older adults after drinking 4 different commercial beverages. We hypothesized that 1) older subjects would remain in positive fluid balance longer than young subjects after ingestion of each test beverage due to decreased urinary excretion rates, 2) glucose (glu)- and amino acid (AA)-based hydration beverages with sodium would have a BHI greater than water in both groups, and 3) the traditional 2-h postingestion BHI may be inappropriate for older adults., Methods: On 5 separate visits, 12 young (23 ± 3 yr, 7 M/5F) and 12 older (67 ± 6 yr, 5 M/7F) subjects consumed 1 L of distilled water, G-20 (6% CHO, 20 mmol/L Na+), G-45 (2.5% CHO, 45 mmol/L Na+), AA-30 (5 AAs, 30 mmol/L Na+), or AA-60 (8 AAs, 60 mmol/L Na+) over 30 min. Blood and urine samples were collected before ingestion and at 0, 60, 120, 180, and 240 min postingestion with additional venous blood sampling at 5, 10, 15, and 30 min postingestion., Results: In young subjects, BHI increased with increasing beverage Na+ concentration, and AA-60 had the highest BHI (AA-60 = 1.24 ± 0.10 compared with water = 1.00, P = 0.01). For older subjects, BHI was highest in AA-30 (AA-30; 1.20 ± 0.13 compared with water, P < 0.01) and was still in flux beyond 2 h in AA-60 (P < 0.05)., Conclusions: Beverage Na+ content progressively increased BHI in young adults independent of glucose or AA content. For older adults, the AA-30 beverage had the highest BHI. A 4-h BHI may be more appropriate for older adults due to attenuated urine excretion rates. This trial was registered at clinicaltrials.gov as NCT03559101., (Copyright © American Society for Nutrition 2019.)

Background: The beverage hydration index (BHI) assesses the hydration potential of any consumable fluid relative to water. The BHI is a relatively new metric, and the impact of body mass, sex, and reproducibility has yet to be investigated., Objectives: To assess the independent impact of body mass and sex on BHI using beverages not previously assessed, including an amino acid-based oral rehydration solution (AA-ORS), a glucose-containing ORS (G-ORS), and a sports drink (SpD), compared with water (control). The reproducibility of the results was examined using statistical modeling (bootstrap analysis)., Design: Using a repeated-measures design, 40 euhydrated and fasted subjects (17 male, 23 female; urine specific gravity <1.025) were studied on 4 separate occasions. During each trial, subjects ingested 1 L of each beverage, and urine output was measured immediately postingestion and at 1-h intervals for the next 4 h. The BHI was calculated as a ratio of each individual's cumulative urine output after drinking 1 L of water over their cumulative urine output after drinking each of the test beverages., Results: The calculated mean ± SD BHIs of the beverages were as follows: water (1.0 ± 0.0), AA-ORS (1.15 ± 0.28), G-ORS (1.21 ± 0.28), and SpD (1.09 ± 0.26). The BHI for both AA-ORS and G-ORS was greater than that for water (P < 0.05). Despite overall differences in body mass, neither body mass nor sex independently affected BHI. Based upon statistical modeling, our results demonstrate excellent reproducibility of outcomes and external validity., Conclusions: Our results suggest that the BHI may be used and interpreted with confidence independently of body mass or sex. Furthermore, a novel carbohydrate-free AA-ORS and a traditional commercially available G-ORS were superior to water in optimizing hydration, whereas SpD was not. This trial was registered at clinicaltrials.gov as NCT03262597.

Urine concentration can be used to assess fluid intake adequacy or to diagnose dehydration. However, too often urine concentration is used inappropriately to draw dubious conclusions that could have harmful health and economic consequences. Inappropriate uses of urine concentration relate primarily to convenience sampling (timing) and problems related to convenience sampling (misapplication of thresholds), but a conceptual problem also exists with using urine concentration in isolation. The purpose of this Perspective article is to briefly explain the problematic nature of current practices and to offer a possible solution to improve practice with minimal added complication. When urine is used exclusively to assess fluid intake adequacy and hydration status in adults, we propose that only when urine concentration is high (>850 mmol/kg) and urine excretion rate is low (<850 mL/24 h) should suspicion of inadequate drinking or impending dehydration be considered. Prospective tests of the 850 × 850 thresholds will provide supporting evidence and/or help refine the best thresholds for men and women, young and old., (© 2016 American Society for Nutrition.)

Background: Few dehydration assessment measures provide accurate information; most are based on reference change values and very few are diagnostically accurate from a single observation or measure. Bioelectrical impedance may lack the precision to detect common forms of dehydration in healthy individuals. Limitations in bioimpedance may be addressed by a unique resistance-reactance (RXc)-score graph method, which transforms vector components into z scores for use with any impedance analyzer in any population., Objective: We tested whether the RXc-score graph method provides accurate single or serial assessments of dehydration when compared with gold-standard measures of total body water by using stable isotope dilution (deuterium oxide) combined with body-weight changes., Design: We retrospectively analyzed data from a previous study in which 9 healthy young men participated in 3 trials: euhydration (EUH), extracellular dehydration (ED; via a diuretic), and intracellular dehydration (ID; via exercise in the heat)., Results: Participants lost 4-5% of their body weight during the dehydration trials; volume loss was similar between trials (ID compared with ED group: 3.5 ± 0.8 compared with 3.0 ± 0.6 L; P > 0.05). Despite significant losses of body water, most RXc vector scores for ED and ID groups were classified as "normal" (within the 75% population tolerance ellipse). However, directional displacement of vectors was consistent with loss of volume in both ED and ID conditions compared with the EUH condition and tended to be longer in ED than in ID conditions (P = 0.054)., Conclusions: We conclude that, whereas individual RXc-score graph values do not provide accurate detection of dehydration from single measurements, directional changes in vector values from serial measurements are consistent with fluid loss for both ED and ID conditions. The RXc-score graph method may therefore alert clinicians to changes in hydration state, which may bolster the interpretation of other recognized change measures of hydration., (© 2016 American Society for Nutrition.)

Background: Plasma osmometry and the osmol gap have long been used to provide clinicians with important diagnostic and prognostic patient information., Objective: We compared different equations used for predicting plasma osmolality when its direct measurement was not practical or an osmol gap was of interest and identified the best performers., Design: The osmolality of plasma was measured by using freezing point depression by microosmometer and osmolarity calculated from biosensor measures of select analytes according to the dictates of each formula tested. After a rigid analytic prescreen of 36 originally published equations, a bootstrap regression analysis was used to compare shrinkage and model agreement., Results: Sixty healthy volunteers provided 163 plasma samples for analysis. Of 36 equations considered, 11 equations met the prescreen variables for the bootstrap regression analysis. Of the 11 equations, 8 equations met shrinkage and apparent model error thresholds, and 5 equations were deemed optimal with an original model osmol gap <5 mmol., Conclusions: The use of bootstrap regression provides a unique insight for osmolality prediction equation performance from a very large theoretical population of healthy people. Of the original 36 equations evaluated, 5 equations appeared optimal for the prediction of osmolality when its direct measurement was not practical or an osmol gap was of interest. Note that 4 of 5 optimal equations were derived from a nonhealthy population., (© 2014 American Society for Nutrition.)

Dehydration (body water deficit) is a physiologic state that can have profound implications for human health and performance. Unfortunately, dehydration can be difficult to assess, and there is no single, universal gold standard for decision making. In this article, we review the physiologic basis for understanding quantitative dehydration assessment. We highlight how phenomenologic interpretations of dehydration depend critically on the type (dehydration compared with volume depletion) and magnitude (moderate compared with severe) of dehydration, which in turn influence the osmotic (plasma osmolality) and blood volume-dependent compensatory thresholds for antidiuretic and thirst responses. In particular, we review new findings regarding the biological variation in osmotic responses to dehydration and discuss how this variation can help provide a quantitative and clinically relevant link between the physiology and phenomenology of dehydration. Practical measures with empirical thresholds are provided as a starting point for improving the practice of dehydration assessment.

Background: The water-deficit equation {WD(1) = 0.6 × B(m) × [1 - (140 ÷ Na(+))]; B(m) denotes body mass} is used in medicine and nutrition to estimate the volume (L) of water required to correct dehydration during the initial stages of fluid-replacement therapy. Several equation assumptions may limit its accuracy, but none have been systematically tested., Objectives: We quantified the potential error in WD(1) for the estimation of free water (FW) and total body water (TBW) losses and systematically evaluated its assumptions., Design: Thirty-six euhydrated volunteers were dehydrated (2.2-5.8% B(m)) via thermoregulatory sweating. Assumptions within WD(1) were tested by substituting measured euhydrated values for assumed or unknown values. These included the known (premorbid) B(m) (WD(2)), a proposed correction for unknown B(m) (WD(3)), the TBW estimated from body composition (WD(4)), the actual plasma sodium (WD(5)), the substitution of plasma osmolality (Posm) for sodium (WD(6)), and actual Posm (WD(7))., Results: Dehydration reduced TBW by 3.49 ± 0.91 L, 57% of which (2.02 ± 0.96 L) was FW loss, and increased plasma sodium from 139 (range: 135-143 mmol/L) to 143 (range: 141-148 mmol/L) mmol/L. Calculations for WD(1) through WD(7) all underestimated TBW loss by 1.5-2.5 L (P < 0.05). WD(1) through WD(5) underestimated FW by 0.5 L to 1.0 L (P < 0.05), but WD(6) and WD(7) estimated FW loss to within 0.06-0.16 L (P > 0.05)., Conclusions: WD(1) grossly underestimates TBW and FW losses. Corrections for unknowns and assumptions (WD(2) through WD(5)) improved estimates little. The use of WD(6) = 0.6 × B(m) × [1 - (290 ÷ Posm)] accurately estimates FW but still underestimates TBW losses by >40%.

Background: Well-recognized markers for static (one time) or dynamic (monitoring over time) dehydration assessment have not been rigorously tested for their usefulness in clinical, military, and sports medicine communities., Objective: This study evaluated the components of biological variation and the accuracy of potential markers in plasma, urine, saliva, and body mass (B(m)) for static and dynamic dehydration assessment., Design: We studied 18 healthy volunteers (13 men and 5 women) while carefully controlling hydration and numerous preanalytic factors. Biological variation was determined over 3 consecutive days by using published methods. Atypical values based on statistical deviations from a homeostatic set point were examined. Measured deviations in body fluid were produced by using a separate, prospective dehydration experiment and evaluated by receiver operating characteristic (ROC) analysis to quantify diagnostic accuracy., Results: All dehydration markers displayed substantial individuality and one-half of the dehydration markers displayed marked heterogeneity of intraindividual variation. Decision levels for all dehydration markers were within one SD of the ROC criterion values, and most levels were nearly identical to the prospective group means after volunteers were dehydrated by 1.8-7.0% of B(m). However, only plasma osmolality (P(osm)) showed statistical promise for use in the static dehydration assessment. A diagnostic decision level of 301 plusmn 5 mmol/kg was proposed. Reference change values of 9 mmol/kg (P(osm)), 0.010 [urine specific gravity (U(sg))], and 2.5% change in B(m) were also statistically valid for dynamic dehydration assessment at the 95% probability level., Conclusions: P(osm) is the only useful marker for static dehydration assessment. P(osm), U(sg), and B(m) are valid markers in the setting of dynamic dehydration assessment.