Assessment of hydration biomarkers including salivary osmolality during passive and active dehydration

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1 European Journal of Clinical Nutrition (2013), 1 7 & 2013 Macmillan Publishers Limited All rights reserved /13 ORIGINAL ARTICLE Assessment of hydration biomarkers including salivary osmolality during passive and active dehydration CX Muñoz, EC Johnson, JK DeMartini, RA Huggins, AL McKenzie, DJ Casa, CM Maresh and LE Armstrong BACKGROUND/OBJECTIVES: Hydration state can be assessed via body mass change (BMD), serum and urine osmolality (S osm,u osm ), urine-specific gravity (U sg ) and urine volume (U vol ). As no hydration index has been shown to be valid in all circumstances, value exists in exploring novel biomarkers such as salivary osmolality (V osm ). Utilizing acute BMD as the reference standard, this research examined the efficacy of S osm,v osm,u osm,u vol and U sg, during passive (PAS) and active (ACT) heat exposure. SUBJECTS/METHODS: Twenty-three healthy men (age, 22±3 years; mass, 77.3±12.8 kg; height, 179.9±8.8cm; body fat, 10.6±4.5%) completed two randomized 5-h dehydration trials (36±1 1C). During PAS, subjects sat quietly, and during ACT, participants cycled at 68±6% maximal heart rate. Investigators measured all biomarkers at each 1% BMD. RESULTS: Average mass loss during PAS was 1.4±0.3%, and 4.1±0.7% during ACT. Significant between-treatment differences at 1% BMD were observed for S osm (PAS, 296±4; ACT, 301±4 mosm/kg) and U osm (PAS, 895±207; ACT, 661±192 mosm/kg). During PAS, only U osm,u vol and U sg increased significantly ( 1 and 2% BMD versus baseline). During ACT, V osm most effectively diagnosed dehydration X2% (sensitivity ¼ 86%; specificity ¼ 91%), followed by S osm (sensitivity ¼ 83%; specificity ¼ 83%). Reference change values were validated for S osm,u sg and BMD. CONCLUSIONS: The efficacy of indices to detect dehydration X2% differed across treatments. At rest (PAS), only urinary indices increased in concert with body water loss. During exercise (ACT), S osm and V osm exhibited the highest sensitivity and specificity. S osm,u sg and BMD exhibited validity in serial measurements. These findings indicate hydration biomarkers should be selected by considering daily activities. European Journal of Clinical Nutrition advance online publication, 16 October 2013; doi: /ejcn Keywords: hydration indices; dehydration; osmolality; saliva INTRODUCTION Neuroendocrine regulation of fluid and electrolyte balance includes control at the brain, kidneys, intestine and sweat glands. As progressive dehydration results in increased body fluid osmolality, body mass change (BMD), serum and urine osmolality (S osm and U osm, respectively), urine volume (U vol ) and urine-specific gravity (U sg ) are recognized as reliable measures of acute body water loss. 1 5 However, no biomarker incontrovertibly assesses hydration state across all dehydration scenarios, creating value in novel indices. 4,6,7 Although the primary roles of salivary secretion include lubrication, digestion, buffering and antimicrobial action, saliva has attracted scientific interest in recent years as a putative index of dehydration This interest arises from ease of collection, as well as water and ion concentrations, which are similar to extracellular fluid. 11 Dehydration theoretically causes elevated sodium in the extracellular compartment potentially diminishing the required salivary acinar cell salt gradient necessary for water movement from the plasma to primary saliva; this would result in lowered salivary secretions, and subsequently increased salivary osmolality (V osm ). 12 Further, autonomic nervous system responses from exercise or other stimuli likely influences V osm through removal of parasympathetic impulses 13 eliciting reduced salivary secretions and greater osmolality. 14 In healthy populations, investigators consistently report increases in V osm with progressive body mass loss. 8,9,15,16 In addition, V osm, salivary total protein content and salivary flow rate strongly correlate with hemoconcentration and body mass loss. 8,9 Criticisms of saliva as a hydration index stem from assessment in individuals with known fluid imbalances, inconsistent sample collection practices, sample collection following food or fluid intake, 15 and large inter-individual measurement variation. 2,8,15,16 However, observations 15 indicate no interference of food or fluid intake on V osm, 15 min after consumption. Although numerous studies have examined the efficacy of hydration biomarkers, differences in pre-trial hydration practices (volume of prescribed fluid) and the type of dehydration protocols (that is, active (ACT) versus passive (PAS), single versus serial measures) impede selection of valid markers. For example, one recent publication questioned the common prescription of a large fluid bolus (500 ml) 17 before hydration biomarker evaluation, suggesting that this protocol complicates hydration evaluation unnecessarily in some individuals; no literature to our knowledge examines efficacy of hydration biomarkers via a more ecologically valid practice of individuals consuming habitual fluid volumes. Further, variations in autonomic nervous system innervation and rates of body water losses between exercising and resting scenarios potentially perturbs body fluid osmolality and volume differently, complicating interpretation of hydration biomarkers. Therefore, this study utilized BMD as a reference standard to evaluate single and serial measurements of V osm,s osm,u osm,u vol and U sg as hydration indices during 5 h of controlled dehydration Human Performance Laboratory, Department of Kinesiology, University of Connecticut, Storrs, CT, USA. Correspondence: CX Muñoz, Human Performance Laboratory, Department of Kinesiology, University of Connecticut, 2095 Hillside Road, U-1110, Storrs 06269, CT, USA. colleen.munoz@uconn.edu Received 24 May 2013; revised 28 August 2013; accepted 5 September 2013

2 2 in a hot environment, with and without the influence of exercise. Recognizing that dehydration and the resulting autonomic regulatory responses would concentrate body fluids (for example, serum, saliva and urine) more during exercise, we hypothesized that significantly greater differences in all biomarkers from baseline would be observed in ACT versus PAS heat exposure, at a specific body mass loss. In addition, we hypothesized that the ability of V osm to determine dehydration would equal other commonly used biomarkers. MATERIALS AND METHODS Twenty-three healthy male subjects (age ¼ 22±3 years, mass ¼ 77.3±12.8 kg, height ¼ 179.9±8.8 cm and body fat ¼ 10.6±4.5%) participated in this study. Subjects were recreationally active in order to ensure adequate thermoregulatory capability. Exclusionary criteria included a history of exercise heat intolerance, use of tobacco products, metabolic disorders, disease or malfunction of salivary glands, or the use of any medications that alter fluid or electrolyte balance; these criteria ensured subject health and data validity. Before participating, all subjects read and signed informed consent documents approved by the University s Institutional Review Board. Experimental design To assess the influence of exercise on hydration biomarkers and V osm as a novel hydration index compared with commonly used methods of quantifying hydration, subjects completed two dehydration trials in a hot and moderately humid environment (B 36 1 C, B50% relative humidity): (1) PAS dehydration where subjects remained seated for 5 h without fluid intake, and (2) ACT dehydration where subjects cycled at a selfselected moderate intensity for 5 h without fluid intake. Thus, this design examined hydration biomarkers in a mild state of hypertonic hypovolemia, in both the absence and presence of exercise. Subjects completed experimental visits in a counter-balanced and randomized order. Primary outcome measures included BMD, S osm,v osm,u osm,u vol and U sg. Controls To promote adequate fluid replacement and recovery between trials, dehydration visits were separated by a minimum of 48 h. Visits were scheduled at the same time of day±1 h to control for large fluctuations in total body water. Before each experimental visit, subjects attempted to replicate macronutrient intake, and were given instructions on fluid volume consumption to maintain habitual hydration state as measured before experimental visits (see below). To maximize the validity of body mass measurements, subjects were provided cycling shorts (without chamois to limit water retention), did not wear a shirt, and wore the same socks and shoes for each experimental trial. Familiarization Visit one was a familiarization visit during which investigators measured subjects mass (Health o meter, Model 349KLX, Pelstar, Bridgeview, IL, USA), height, body fat percentage (Lange Skinfold Calliper; Beta Technology Inc., Houston, TX, USA) and resting heart rate via telemetry (Polar Electro Inc., FT1, Kempele, Finland). Investigators introduced participants to the saliva collection technique to minimize variation of subsequent measurements. For all saliva sample collection, subjects rinsed the mouth with water and rested for 15 min. Subjects then provided unstimulated saliva by sitting quietly for 2 min, allowing saliva to passively accumulate in the mouth. Upon 2 min of collection, subjects allowed the saliva to passively flow through a straw into a cuvette; technical limitations did not permit recording of flow rate. Following the familiarization visit, subjects recorded all food and fluid intake for 3 days to establish habitual daily fluid intake. From these records, subjects were required to consume their habitual fluid volume dispersed throughout 24 h and consume 125 ml every 30 min during the first 2 of the 3 h, before their experimental visit to ensure sufficient hydration status necessary to safely complete experimental trials. Overall, this pre-trial hydration protocol closely mimicked habitual hydration practices of these free-living individuals. In addition, subjects were instructed to replicate their diet the day before each experimental visit. Experimental trials Upon arriving to the lab, subjects consumed a standardized breakfast (one banana, one bagel, one tablespoon cream cheese or peanut butter and five ounces water). This breakfast has previously shown to provide energy without eliciting gastrointestinal distress or negatively influencing performance. Following breakfast, subjects inserted a rectal thermistor (YSI 401 rectal probe, Yellow Spring, OH, USA) cm beyond the external anal sphincter for rectal temperature measurement, and researchers inserted a cannula into a superficial antecubital vein for blood collection. Subsequently, subjects sat quietly for approximately 5 min to obtain resting heart rate measurement, and provided a saliva sample. Immediately before entering the environmental chamber, subjects emptied their bladder, allowing investigators to measure pre-trial U vol (Ohaus Corp., Model RC3RS, Columbia, MD, USA), U osm (freezing point depression; Advanced Instruments, Model 3320, Norwood, MA, USA) and U sg (Atago Inc., Model A300CL, Spartan, Tokyo, Japan), and provided S osm and V osm samples (measured via freezing point depression). The same two investigators measured all saliva, urine and plasma samples to minimize inter-tester variation. All samples were measured during testing hours. After entering the environmental chamber (Minus-Eleven Inc., Model 2000, Malden, MA, USA; B36 1C, B50% relative humidity), investigators recorded environmental conditions. Each trial involved a 5-h protocol consisting of a 25:5-min activity to rest ratio. For ACT, subjects cycled (Cycle Ops, Club Pro 300 PT, Madison, WI, USA) at a self-selected moderate intensity during the 25-min activity period, while during PAS they sat in a chair. During each 5-min rest period, subjects were measured for BMD with their shoes off and were towel dried. If a percent body mass loss was reached, subjects then expelled all possible urine into a designated container and were seated to obtain samples of saliva and blood. BMD was recorded before bladder void at each percent BMD to assess sweat loss. Statistics Data analysis was performed with SPSS version 19.0 (IBM Corporation, Champaign, IL, USA). Within PAS and ACT, statistical measures included descriptive analysis (means, s.d. and s.e.m., and one-way repeated-measures analysis of variance to quantify changes across BMD. Comparisons were made between PAS and ACT via one-way ANOVA with hydration markers at only 0 and 1% BMD to ensure sufficient sample size, and only included those subjects who provided samples for both trials at each BMD. An alpha level of Po0.05 defined significance. Unless otherwise noted, data are represented as means±s.d. To analyze biomarker efficacy during ACT, analysis included (1) receiver operating characteristic (ROC) curves to determine a sufficiently hydrated versus dehydrated criterion value for each diagnostic test, (2) area under the ROC curve to provide a summary of the diagnostic test accuracy and (3) sensitivity, specificity and positive likelihood ratio ( þ LR) to aid clinical decision making (Johns Hopkins Medicine Web-Based Calculator for ROC Curves, Baltimore, MD, USA). 18 For a more conservative analysis, repeated measures for ROC analyses were disregarded. 19 Area under the ROC curves were statistically compared 20 with a Bonferroni correction for comparisons among all variables (total of 10). Less than 2% BMD defined a sufficiently hydrated condition, whereas X 2% BMD was considered a dehydrated condition. 2,21 Diagnostic accuracy was not calculated for PAS because of insufficient sample size X 2% BMD. Analytical (CV A ) and biological variation (intra-individual (CV I ) and interindividual (CV G )) were calculated for all variables 22 as CV ¼ s.d./mean and expressed as a percentage. For CV A, 20 measurements of solution standards specific to the range of the variable were used when possible; otherwise, actual samples were used. Reference change values (RCVs) were calculated as follows and presented as a percentage: RCV ¼ 2½ *Z*(CVA2 þ CVI2)½, where Z equals 1.65 s.d. for a one-tailed 95% probability. The index of individuality (II) was calculated as follows: II ¼ (CV A 2 þ CV I 2)½/CV G. Population-based reference intervals have high usefulness in tests with high II (4 1.4), whereas tests have low usefulness with low II (o 0.6). The index of heterogeneity (IH) was calculated as follows: IH ¼ (CV A 2 þ CV I 2)½/(2/(n 1))½, where n is the number of samples obtained from each subject (in this study, n ¼ 2). The RCV was valid if IHo1 þ 2(1/(2n)½) or as in our study, if IHo2. Samples collected for calculation of II and IH were obtained pre-trial on 2 days. RESULTS Of the 23 subjects, all participated in PAS and all but one subject participated in ACT (because of an injury sustained outside European Journal of Clinical Nutrition (2013) 1 7 & 2013 Macmillan Publishers Limited

3 of this investigation). Sample sizes are noted for appropriate analysis; any missing samples occurred because of inability to provide a sample, insufficient sample volume, the 5-h trial completion occurred before reaching a specific body mass loss, or the subject was removed from the heat chamber because of signs and symptoms of heat and/or dehydration-related complications. Representing greater difficulty in providing salivary and urine samples with increasing dehydration, the following values describe the number of individuals who reached a specific BMD beyond 3% along with the number of salivary and urinary samples obtained: 21 reached 3% BMD with 19 and 9, respectively; 13 reached 4% BMD with 10 and 10, respectively; 6 reached 5% BMD with 5 and 6, respectively. Average ambient temperature (PAS ¼ 36±1 1C, ACT ¼ 36±1 1C) and relative humidity (PAS ¼ 49±2%, ACT ¼ 48±3%) remained stable during all experimental sessions. Participants consumed 3.2±1.4 l (fluid in beverages and food; no differences between trials, PAS ¼ 3.46±1.5 l, ACT ¼ 3.18±1.6 l) 24 h before dehydration trials, which is consistent with normal fluid recommendations. 23 No differences existed between sessions for pre-trial body mass (PAS ¼ 77.0±12.1 kg, ACT ¼ 77.6±12.1 kg) or diet (macronutrient, sodium and total fluid intake content) before experimental trials. Upon trial completion, total average mass loss during PAS ¼ 1.4±0.3% and ACT ¼ 4.1±0.7%. Time to reach BMD during PAS transpired as 1% ¼ 221±47 min (n ¼ 23), and 2% ¼ an additional 79±0 min (n ¼ 6); during ACT, 1% ¼ 78±21 min (n ¼ 22), 2% ¼ an additional 64±36 min (n ¼ 22), 3% ¼ an additional 72±52 min 9 (n ¼ 21), 4% ¼ an additional 36±45 min 9 (n ¼ 13) and 5% ¼ an additional 37±36 min 9 (n ¼ 6). Average percent heart rate of predicted max 24 during PAS ¼ 37±5% and ACT 68±6%. Table 1 presents pre-trial hydration biomarker values in response to 24-h habitual fluid intake; no differences existed between PAS and ACT in pre-trial variables. Between trial (PAS versus ACT) comparisons at 0 and 1% BMD with subjects who were able to provide samples for both trials, displayed significant differences at only 1% BMD in S osm,v osm and U osm, with no other statistical differences detected (Table 1). A main effect across BMD was seen in all variables and trials (Po0.05), except for S osm and V osm during PAS. Change in all hydration biomarkers consistently increased (serum, saliva, and U osm, and U sg ) and decreased (U vol ) with progressive loss in body mass attributable to sweat loss (Figure 1). However, extent of change was greater during ACT than PAS. The ROC curve analysis generated criterion values, area under the ROC curve, and sensitivity and specificity percentages for each diagnostic test (Table 2). No biomarker produced statistically greater diagnostic accuracy compared with any other. þ LRs were calculated for each criterion value and for measured values corresponding to a þ LRE10 and þ LRE2 (Table 3). In relation to the criterion value, Figure 2 depicts individual data points for all hydration biomarkers during ACT. For all hydration biomarkers, coefficients of variation (CV A,CV I, CV G ), II, IH, as well as RCV presented as percentages, units and corresponding decision levels are displayed in Table 4. According to established usefulness cutoffs for population-based reference intervals, only U vol expressed low individuality II41.4; 22 whereas S osm had the next highest usefulness among variables (II ¼ 0.96). RCV were considered valid if IHo2; 22 variables considered capable of valid RCV included S osm,u sg and BMD. DISCUSSION This study examined dynamic, continuous responses of hydration biomarkers in the context of 5-h exposure to a hot environment with (ACT) and without (PAS) exercise, utilizing acute BMD as the reference standard. We hypothesized that significantly greater differences would be observed during ACT versus PAS at a specific body mass loss, attributable to variation in neural autonomic regulatory responses and resulting body fluid concentration. In addition, we hypothesized that the ability of V osm to determine dehydration would equal other common biomarkers. The first hypothesis was not confirmed, but with differences observed even at 1% BMD in S osm,v osm and U osm, this data suggest meaningful differences between modes of dehydration that likely persist or increase in severity with greater body water loss. Meanwhile, strong evidence supported the second hypothesis. The primary findings of this study during PAS involved large, progressive responses to dehydration in U osm,u vol and U sg, with relatively smaller changes in S osm and V osm. In contrast, responses during ACT involved greater changes of S osm and V osm (Figure 1) than were observed in all urine variables, reflecting the well-documented hemoconcentration during exercise and heat exposure. 25 Although autonomic regulation likely influenced S osm and V osm too, blunted urine variable responses implies increased extracellular osmolality; this subsequently creates a reduced sodium gradient and diminishes water content in the primary saliva, accounting in part for the observed changes in V osm. Serum and urinary indices As anticipated, ACT elicited a more concentrated extracellular compartment than PAS (Figure 1 and Table 1). During ACT, the changes in urine variables (Figure 1) reflect diversion of cardiac output away from the kidneys, 26 reduced glomerular filtration during exercise in the heat 27 and decreased urine electrolyte, protein and water excretion. 28 Further, urine variables poorly discerned between moderate and more severe body water loss (Figure 1). Although, when U osm was compared during ACT and PAS at the same body mass loss ( 1% BMD; Table 1), a seemingly paradoxical concentration decrease occurred during ACT. However, renal osmolar (PAS ¼ 0.49±0.26 mosm/min, ACT ¼ 0.72±0.23 mosm/min) and free water clearance (PAS ¼ 0.89±0.65 ml/min, ACT ¼ 1.18±0.79 ml/min) support 3 Table 1. Hydration indices at 0% (pre-trial) and 1% body mass change during PAS and ACT dehydration Hydration biomarker 0% Mass change 1% Mass change n P-value PAS ACT PAS ACT Serum osmolality (mosm/kg) 295±4 296±4 296±4 301±4 22 o0.01 a Salivary osmolality (mosm/kg) 68±14 64±9 74±14 90±24 21 o0.01 a Urine osmolality (mosm/kg) 466± ± ± ± a Urine volume (ml) 266.8± ± ± ± Urine-specific gravity 1.011± ± ± ± Abbreviations: ACT, active; PAS, passive. Variation in sample size (n) at 1% body mass change attributable to number of paired samples (sample provided by subject for both PAS and ACT). a Indicates differences between PAS and ACT at 1% body mass change (Po0.05). & 2013 Macmillan Publishers Limited European Journal of Clinical Nutrition (2013) 1 7

4 4 Figure 1. Hydration biomarker change (D means±s.e.) with body mass loss via PAS (left) and ACT (right) dehydration: S osm (a), V osm (b), U osm (c), U vol (d) and U sg (e). Significant differences (Po0.05) indicated with * compared with 0% mass change, w compared with 1% mass change, z compared with 2% mass change and y compared with 3% mass change. greater osmolar clearance and water retention during ACT than PAS. Overall, these results indicate that (a) exercise exaggerated S osm change and (b) urinary biomarkers provided the most effective indication of mild hypertonic hypovolemia ( 1% BMD) during PAS heat exposure. Salivary osmolality As expected, V osm demonstrated greater change in osmolality during ACT than PAS, in response to a 1% body mass loss (Table 1 and Figure 1). This finding indicates that V osm either lacks responsiveness to mild dehydration (1%; which was evident in 2% mass loss after 24-h fluid restriction in previous literature 10 and confirmed acutely over 5 h in the present investigation) and/or is magnified during exercise. In support of the latter, a documented parasympathetic impulse removal during exercise 13 explains decreased salivary secretion and concomitantly increased osmolality. 14 Similarly, previous publications describe V osm as a less effective discriminator of mild dehydration ( 1 to 2% BMD) at rest, 2,10 and V osm as an effective marker of European Journal of Clinical Nutrition (2013) 1 7 & 2013 Macmillan Publishers Limited

5 Table 2. Receiver operating characteristic curve analysis of hydration biomarkers during active dehydration when only a single measurement is available 5 Hydration biomarker AUC Est. s.e. Criterion value Sensitivity Specificity Serum osmolality (mosm/kg) 0.91 a % 83% Salivary osmolality (mosm/kg) 0.94 a % 91% Urine osmolality (mosm/kg) 0.80 ab % 65% Urine volume (ml) 0.87 a % 79% Urine-specific gravity 0.89 a % 81% Abbreviation: AUC, area under the ROC curve. a Denotes AUC was significantly different from chance. b Denotes AUC was significantly different from salivary osmolality (Po0.05); a trend was observed between serum and urine Osmolality (P ¼ 0.06). Table 3. þ LRs and corresponding values for hydration biomarkers during active dehydration when only a single measurement is available Hydration biomarker þ LR Measured value Serum osmolality mosm/kg mosm/kg mosm/kg Salivary osmolality mosm/kg mosm/kg mosm/kg Urine osmolality mosm/kg mosm/kg mosm/kg Urine volume ml ml ml Urine-specific gravity Abbreviation: þ LR, positive likelihood ratio. moderate-to-severe dehydration (4 2% BMD) during exercise. 2,8,10 Interestingly, we found that only B25% of the variation found in V osm resulted because of exercise intensity. However, as with serum and urinary hydration biomarkers, extended time between resting measurements during PAS likely allowed fluid equilibration among body fluid compartments and consequently blunted changes of V osm. Previous findings regarding V osm as a hydration biomarker 2,8,16 suggest that V osm accurately tracks BMD during moderate-tosevere hypertonic hypovolemia, which was induced by exercise. However, four weaknesses of V osm have been previously identified. First, great inter-individual variation in euhydrated V osm values require within-subject serial measurements to evaluate hydration status and complicated comparisons between individuals. 2,8,15,16 Second, reduced salivary secretion and increased concentration with strenuous exercise and/or significant body fluid losses make sample collection difficult. Third, at least 15 min must separate food and fluid consumption before salivary sample collection, 15 possibly inconveniencing the user. Fourth, as noted by investigators in this study, some individuals naturally secrete viscous saliva independent of any effects of exercise or dehydration. Diagnostic accuracy Diagnostic accuracy statistics allow for clinical evaluation using single measurement, and absolute values. ROC curve analysis for PAS experiments was not completed because of the small sample size and body mass loss in 5 h. However, the ROC curve analysis for ACT (Table 2) provides criterion values for dehydration during exercise in the heat following habitual fluid consumption practices. With the greatest area under the curve, V osm demonstrated the highest accuracy in detecting dehydration (X 2%) closely followed by S osm, although these were not statistically different; this supports the greater changes observed in these variables during ACT (Table 1 and Figure 1). The V osm criterion value of 108 mosm/kg was associated with a þ LR of 9.65 (Table 3). This indicates that a V osm value of 108 mosm/kg occurs nearly 10 times more often in a person who is dehydrated, than in a person who is sufficiently hydrated. With this value, a clinician can be confident that a V osm of 108 mosm/kg reflects dehydration in an individual who has been exercising. 29 When applying this criterion value in a practical setting or comparing it with other literature, the circumstances leading to the dehydrated state should be considered (for example, ACT versus PAS protocol, prehydration practices, collection and analytical methods). Whereas the current investigation provides greater criterion values for dehydration (X 2%) compared with previous literature 2,16,30 for some indices, differences in instrumentation and methodologies influence absolute and criterion values. Specifically, the present investigation examined (1) serum as opposed to plasma osmolality, (2) delayed as opposed to first morning urine and (3) greater ecological validity via habitual pre-trial hydration practices. Reference change values RCVs permit clinical evaluation of serial measurements; a change greater than the RCV is deemed significant. Applying this statistic to the context of dehydration regardless of dehydration method, RCV can be used to detect body water loss after accounting for normal variation observed within the individual and analytical device. Only U vol had a large enough index of individuality (II) to be considered useful for population-based reference intervals (Table 4). Meanwhile, based on the index of heterogeneity (IH) three variables (S osm,u sg and BMD) demonstrated valid RCV; U vol did not demonstrate a valid RCV, suggesting poor acute serial detection of dehydration. Although U vol was not evaluated in previous literature, all other outcomes impeccably correspond with previous findings. 2 The current findings shed light on the influence of 5-h heat and exercise-induced dehydration on the responses of hydration biomarkers in individuals practicing typical fluid consumption habits before dehydrating. Previous reports eloquently describe the diagnostic accuracy of various hydration indices. 2,16 However, because protocols involved exercise and heat exposure, these values have little external validity regarding PAS dehydration scenarios. For example, differences between PAS and ACT experiments at 1% BMD (Table 1) were 5, 16 and 234 mosm/ kg for S osm,v osm and U osm, respectively. Future studies should evaluate acute diagnostic accuracy during resting dehydration protocols. In conclusion, this investigation presents two scenarios to be considered during hydration assessment: (1) PAS versus ACT dehydration, and (2) single versus serial measurements. In the comparison of hydration biomarkers, urinary indices changed & 2013 Macmillan Publishers Limited European Journal of Clinical Nutrition (2013) 1 7

6 6 Figure 2. Individual data points for S osm (a), V osm (b), U osm (c), U vol (d) and U sg (e) during ACT dehydration. Vertical dotted lines differentiate dehydrated (X 2% BMD) from sufficiently hydrated (o 2% BMD). Horizontal dotted lines represent the criterion value determined by the ROC curve analysis. Table 4. Analytical and biological coefficients of variation and indices of variability for hydration biomarkers when serial measurements are available Hydration biomarker CV A CV I CV G II IH RCV (%) RCV (unit) Decision level Serum osmolality (mosm/kg) ±4 Salivary osmolality (mosm/kg) ±16 Urine osmolality (mosm/kg) ±257 Urine volume (ml) Negligible ±150 Urine-specific gravity Negligible ±0.006 Body mass (% loss) Negligible %±0.2 Abbreviations: CV A, coefficient of variation for the analytical device. When possible, CV A was measured with standard solutions specific to the measurement range; otherwise, actual samples were used. All values are expressed as a percentage; CV I, intra-individual coefficient of variation; CV G, inter-individual coefficient of variation; II, index of individuality; IH, index of heterogeneity; RCV, reference change value expressed as a percentage, or specific to the unit of measurement. CV I and CV G measured with all pre-trial samples from passive dehydration and active dehydration trials and are expressed as percentages. significantly during PAS, in concert with mild body water loss ( 1 to 2% BMD). However during ACT, S osm and V osm were the most effective indices as evidenced by their high sensitivity and specificity. Further, for single measurement scenarios, the high diagnostic accuracy of S osm and V osm suggests great utility during combined exercise and heat exposures. For serial measurement scenarios conducted during ACT or PAS dehydration, S osm,u sg and BMD appear to be the most appropriate indices. Therefore, the efficacy of hydration biomarkers depends on previous or concurrent activities of the individual, as well as the frequency of sample collections. Thus, we suggest that hydration biomarkers should be selected with anticipated daily activities in mind. CONFLICT OF INTEREST The authors declare no conflict of interest. ACKNOWLEDGEMENTS We are grateful to the test participants for their perseverance during these difficult experiments. We acknowledge the technical assistance of Colin Shaughnessy, Corey Dwyer, Ethan Talbot, Dylan Rausch and Ted Pert during data collection. Professor Craig Denegar provided valuable statistical guidance. This research was funded by the US Government, Technical Support Working Group via a grant awarded to Cantimer, Inc., Menlo Park, CA, USA and the University of Connecticut, Office of Sponsored Programs, Storrs, CT, USA. European Journal of Clinical Nutrition (2013) 1 7 & 2013 Macmillan Publishers Limited

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