This study, performed at the Waterfront Technology Center (Camden, NJ), was a randomized, double-blind, parallel-arm, controlled trial, which recruited 100 adult volunteers (50 male, 50 female), between 25 to 49 years of age. Eligible participants were healthy, non-smoking adults, having a body-mass index less of 29 or less and free from any medication for at least one week prior to the participation in the study. Female participants were excluded from the study if they were pregnant, breast-feeding, menstruating at the time of screening, or if they had taken oral contraceptives in the previous 3 months. Subjects were instructed to refrain from strenuous activity, alcohol, and to limit excessive caffeine intake (>2 six-ounce cups) for at least 24 h prior to their assigned arrival on the study date. This clinical study was approved by the Institutional Review Board, and written informed consent was obtained from all subjects at the time of enrollment and prior to participating in this study. The study was registered (ClinicalTrials.gov Identifier: NCT02118883) and conducted in accordance and compliance with Good Clinical Practice and the Declaration of Helsinki.
Design of study
The two different fluid replacement beverages consisted of standard bottled water as the control (CON), having a normal pH with minerals added for taste (Dasani®, The Coca-Cola Company, Atlanta, GA). The electrolyzed, high-pH ALK with added minerals for taste acted as the experimental treatment beverage (Essentia®, Essentia Water, LLC, Bothell, WA). Supplies of both water samples were stored in the same climate-controlled indoor location and covered to prevent prolonged light exposure.
Subjects were permitted to consume food and water at will prior to the study. Following a baseline assessment, participants were asked to refrain from food or fluid intake. Baseline assessments for body mass, bioelectrical impedance and vital signs (heart rate (HR), systolic (SBP) and diastolic blood pressure (DBP), respiration rate, body temperature) were collected at the initiation of the study prior to exercise. Blood samples were collected by venipuncture for evaluation of whole blood viscosity and plasma osmolality. Following baseline measures, the subjects performed moderate aerobic exercise sessions (using their choice of a treadmill, stationary bicycle, and/or elliptical trainer) in a warm environment (30 °C, 70% relative humidity) until they reached a dehydrated state. The duration of exercise varied between subjects; however, the dehydration threshold target was standardized to 2.0 ± 0.2% body weight loss due to the effects of a period of exercise in producing mild dehydration. During the exercise period, participants dried themselves thoroughly before each body mass measurement. A disposable paper gown of known weight was provided during body mass measurements. After the exercise period was completed and a dehydrated state attained, study participants moved to a thermo-neutral environment (21 °C, 60% relative humidity), where they rested for 20 min. After this rest period, vital signs, weight and bioimpedance were assessed. In addition, blood samples were collected for assessment of blood viscosity and plasma osmolality.
A prior study, assessing the effect of oral carbohydrate solution on rates of absorption reported an approximate 3% reduction in plasma volume during a 105-min interval after beverage consumption [10]. The present study incorporated a follow-up period of 120 min, which was considered to be sufficiently long in duration to show any effect of rehydration during recovery. The 120-min follow-up period (T000 to T120 min), which followed exercise and rest, was divided into a 30-min rehydration period and a 90-min recovery period. Participants were rehydrated orally by CON or ALK (T000 to T030 min). The mass of the water consumed during the rehydration period was calculated according to a participant’s body mass change during the exercise period. The recommended amount of rehydration fluids was determined using a formula of 20 mL of oral hydration per 1 kg of subject body weight, i.e. 2% of pre-exercise, baseline body weight. Water volumes poured into containers were measured using a precision scale (Intelligent-Lab PD-3000, Intelligent Weighing Technology, Inc. Camarillo, CA) by an unblinded coordinator who had no contact with any participants or study results throughout the study. Subjects were required to consume the entire quantity of designated water following exercise ad libitum within 30 min (T000 to T030 min). Blood samples were collected for whole blood viscosity and plasma osmolality at T015 min and T030 min during this rehydration period.
Additional data were collected during the 90-min recovery period (T030 to T120 min) to fully assess any potential variations in measured parameters. Blood viscosity and plasma osmolality were assessed seven times: at baseline and at six subsequent intervals (T000, T015, T030, T060, T090, and T120 min). Bioimpedance analysis and body mass change measurements were performed five times: at baseline and at four subsequent intervals (T000, T045, T075, and T120 min). Vital signs were evaluated a total of three times: at baseline, as well as at T000 and T120 min. A flow sheet showing time points for each biomarker evaluation is represented in Fig. 1.
Measured parameters
Whole blood viscosity
Whole blood viscosity, the inherent resistance of blood to flow, was used as a measurement of intravascular hydration status. Blood viscosity was assessed across a physiologic range of shear rates of 1-1000 s-1 in increments of 0.1 s-1 using an automated scanning capillary tube viscometer (Hemathix SCV-200, Health Onvector, King of Prussia, PA). This instrument has been validated using rotating cone-and-plate and couette type viscometers across a range of shear rates [11]. Approximately 3 cc of whole blood were collected for each blood viscosity test. Each blood sample was processed and analyzed at 37 °C within 24 h after being collected. Blood viscosity levels were reported in millipoise units (1 centipoise [cP] = 1 millipascal-seconds [mPa•s] = 10 millipoises [mP]). Blood viscosity values, measured at a high shear rate of 300 s-1, were reported as systolic blood viscosity, and those measured at a low shear rate of 5 s-1 were reported as diastolic blood viscosity.
Plasma osmolality
Once retrieving a blood sample, the plasma osmolality was assessed within 24 h. Each sample was centrifuged at 5 °C for 10 min at 1000 x g, and the plasma component was shipped to a reference laboratory (Laboratory Corporation of America, Burlington, NC), which performed the analysis using a freezing-point depression osmometer (Advanced Instruments, Norwood, MA).
Bioelectrical impedance
Bioelectrical impedance analysis, or bioimpedance, was performed on site using a bioimpedance analyzer (Quantum IV, RJL Systems, Clinton, MI). Subjects assumed a supine position with their arms 30° from the body and their legs not touching. Electrodes were placed on the right hand and right foot of each subject and removed after each measurement. On the subject’s hand, the signal electrode was placed on the skin of the metacarpophalangeal joint of the middle finger, and the detecting electrode was placed on skin of the wrist. On the foot, the signal electrode was placed on the skin at the base of the second toe, and the detecting electrode was placed on the skin at the top of the ankle. The following indices were recorded during each measurement: impedance, reactance, capacitance, phase angle, total body water, intracellular water, and extracellular water.
Body mass
Body mass index (BMI) was measured using a digital floor scale (HealthOMeter 349KLX, Pelstar, LLC, McCook, IL). Measurements were performed using a nude, dry weight, with a dry gown of known weight provided for comfort.
Determination of sample size
The scanning capillary viscometer used to assess the primary endpoint in this study was previously employed in a preliminary study of dehydration and rehydration by high-pH alkaline water in 15 nonsmoking, apparently healthy firefighters. The variability of systolic blood viscosity measurements (high-shear viscosity) and the rehydration effect of high-pH alkaline on systolic viscosity observed in this prior study population were used to determine the sample size for this study [12]. In this firefighter trial, dehydration induced by fighting mock fires in training session with full equipment produced mean systolic viscosity values of 42.7 mP, and after rehydration, mean systolic blood viscosity was significantly reduced to 38.8 mP (p = 0.003). A standard deviation of 2.6 mP observed at baseline was used in determining our sample size for the present study. We postulated that high-pH ALK would demonstrate 40% greater rehydration effect than CON, that is, rehydration by CON was hypothesized to reduce mean systolic blood viscosity to 40.5 mP while ALK was hypothesized to reduce systolic blood viscosity to 38.8 mP from a dehydrated level of 42.7 mP. The present study was powered to detect such a contrast with 90% power using a type I error rate of 5%. This required 100 participants or 50 in the CON group and 50 individuals in the ALK group.
Statistical analyses
Statistical analyses were performed using SAS (Statistical Analysis System, Version 9.3, 2012, Cary, NC). The data were analyzed using both descriptive and inferential statistics. Four separate analyses were pre-planned: comparison of percent change in biomarkers, comparison of the slopes of regression lines, absolute differences, and mixed model analyses.
A comparison of the percentage change of each outcome measure was performed during the rehydration and recovery period. Such an analysis was intended to compensate for the individual differences at baseline and at T000 min values. For example, the percentage change in the endpoint parameter from T000 to T120 was computed for whole blood viscosity (WBV) as:
$$ \frac{\mathrm{WBV}\left(\mathrm{T}000\right)\ \hbox{--}\ \mathrm{W}\mathrm{B}\mathrm{V}\left(\mathrm{T}120\right)}{\mathrm{WBV}\left(\mathrm{T}000\right)} $$
Mean values for each treatment group and estimates of standard errors for each enabled confidence intervals were to be computed and conclusions made based on these differences.
Fitting a line to each set of endpoint data for each variable, CON versus ALK were examined and statistical tests were conducted on the difference of the slope parameter for each line to determine if there was a significant overall treatment effect on the rate of rehydration during the recovery period. Regression procedure (PROC REG) was used in SAS to provide estimates of the best fitting line and of the slope and intercept parameters and to generate the data plots. Faster rehydration would be demonstrated for the group having a steeper slope for the line fit to the data between T000 and T120 min.
Absolute changes between baseline and each subsequent time point were also computed for each of the outcome parameters. Keeping the two assigned treatment groups separate, a plot of the mean values was performed for each of the outcome parameters at each time point starting at baseline and continuing through T120 min after commencing rehydration. By graphing each of the endpoints (y-axis) vs. time (x-axis), an initial change in the outcome measure between baseline and T000 was expected, as the latter was at or near the maximum point of dehydration and thus an expected inflection point of the endpoint parameters. Subsequently, a gradual restoration in these measures was expected as rehydration occurred. The mean value at T000 was expected to serve to indicate the dehydration level for each group. Mean and standard errors for each time point were to be computed, allowing tests at any particular time point to be made comparing the two treatment groups. Structuring 95% confidence intervals (using mean ± 1.96 S.E.) around each point enabled differences to be tested at every time point.
A final pre-planned analysis was employed for validation using a linear model approach but allowing for repeated measures generated for the outcome variables at all time points. In this analysis, a mixed model was used to specify observations at the different time points as random effects, and included fixed effects such as treatment (i.e., ALK vs. CON), age, baseline levels, and weight loss at end of exercise (%) in the analysis. Then, the treatment effect was estimated while controlling for these covariates. Using mixed model procedure (PROC MIXED) in SAS, the treatment effect comparing ALK vs. CON was tested for each of the outcome variables.
Data displays of key outcome variables at each time point starting at baseline and continuing through T120 min after start of rehydration are provided in Figs. 2, 3, 4 and 5. Mean and standard errors for each time point were computed, allowing tests at any particular time point to be made comparing the two groups. Structuring 95% confidence intervals using mean ± 1.96 S.E. enabled absolute differences to be tested. As shown in Figs. 2, 3, 4 and 5, the 95% confidence intervals are displayed graphically for the two treatment arms using error bars. Each pair of confidence intervals displayed for the two treatment arms observably overlapped.
The linear mixed models account for the correlational structure inherent in these repeated measures data, as intra-individual measures are more highly correlated than inter-individual measures. Since there was only one primary endpoint and only one endpoint was used to estimate the sample size, all statistical tests were conducted at the alpha = 0.05 level; no Bonferroni correction was employed. For the mixed model analyses, a linear model approach was used while allowing for the repeated measures to be generated for outcome assessment. The treatment effect was tested while controlling for the following covariates: time point, age, dehydration weight change, a gender-treatment-arm interaction effect, as well as baseline levels for systolic blood viscosity, diastolic blood viscosity, and plasma osmolality. Analyses of all outcome variables were performed using a mixed model, which takes into account intra-individual correlations across repeated measures.
