The Effectiveness Of Purported Hyper Hydrating Agents

Published Date: 02 Nov 2017

Abstract……………………………………………………………………………....4-5

Introduction………………………………………………………………………....5-6

Aims and Objectives…………………………………………………...……….….....7

Methods…………………………………………………………………………..….7-10

6a. Data Analysis…………………………………………………………………….10-11

Results……………………………………………………………………………….12-17

7a. Analysis of total body water……………………………………………….…..….12

7b. Analysis of physiological factors………………………………………………....13

7c. Analysis of performance measures…………………………………………....…14-16

7d. Analysis of psychological data………………………………………..………....16-17

Discussion- Effects on hydration status……………………………………….......18-23

8a. Purported benefits of hyper-hydration………………………………………...…..18

8b. Use of Glycerol as a hyper-hydrating agent……………………………………..18-21

8c. Use of the novel αGCG solution as a hyper-hydrating agent……………………21-23

Discussion- Effects on sports performance…………………………………….….24-32

9a. Effects of hyper-hydration on cardiovascular strain and sports performance……24-25

9b. Effects of hyper-hydration on thermoregulation and sports performance……….25-30

9c. Effects of hyper-hydration on sports performance measures…………..………...30-31

9c. Effects of hyper-hydration on psychological variables associated with sports performance………………………………………………………………………..…31-32

Potential disadvantages of hyper-hydration……………………….…………...…33-34

Limitations of this study…………………………………………...…….……….....34-35

Applications and further research…………………………………….....……..….35-36

Conclusion………………………………………………………………...…...…….36-37

Figure List……………………………………………………………………………37-38

Abbreviations………………………………………………………………………….38

Bibliography…………………………………………………………...……...……..39-53

Acknowledgments

I would like to thank Kathryn Dady for undertaking the data collection with me and helping to finalise the testing protocol. Thank you to Jacky Bretherton for her help in developing the methodologies and her on-going support throughout the project. Also I would like to thank Dr Karina Stewart for her assistance in getting ethically approved and for supervising the data collection sessions. Furthermore, thank you to the subjects who participated in the study, without you it would not have been possible! Finally, I would like to thank my fiancé Dinusha for encouraging me to pursue this project and for supporting me throughout all the long hours of research.

All data collection and testing was undertaken with Kathryn Dady.

Abstract

The aim of this study was to determine whether an α-lipoic acid based hyper-hydrating solution (αGCG) exerted a statistically significant difference upon hydration, cardiovascular function, thermoregulatory efficiency or sporting performance when compared with the conventionally studied glycerol solution (Gly), during submaximal exercise in a thermoneutral environment.

A 6-week, single-blind data collection period was undertaken. Subjects fasted overnight and bio-electrical impedance testing was performed, to assess changes in % total body water (TBW), in the fasted state and also pre-exercise and post exercise states, which followed a breakfast, individualised for estimated caloric expenditure. Exercise consisted of 30 minutes submaximal indoor rowing at an individualised intensity. Heart rate, skin temperature, distance rowed, caloric expenditure and power output were also recorded. Rating of perceived exertion (RPE), Thermal Sensation Scale (TSS) and thirst scale (TS) were assessed subjectively. Two repeats were performed for Gly and αGCG, as well as a placebo, in order to increase the reliability of data.

Numerous statistical tests, including general linear model ANOVA’s, paired T-tests, Pearson correlations and multiple regression analyses were performed on every variable. Consumption of the αGCG solution resulted in the greatest %TBW preservation however this was not found to be statistically significant (0.008% increase p ≥ 0.05). Yet consumption of placebo resulted in statistically significantly greater %TBW preservation than Gly (0.003% vs. -1.123% TBW, p≤0.000). αGCG consumption resulted in lowest average skin temperature (30.19±0.9°C, p≤0.05), highest power output (108.38±6.29 watts, p≤0.05), and distance rowed (6082.13±120.2 meters), compared to Gly and placebo. However the lowest thirst sensation was associated with Gly consumption (4.5±0.5, p≤0.05). There was no statistically significant difference between solutions, in relation to %TBW preservation. Furthermore, whilst there were no statistically significant RPE, TSS or heart rate results, data demonstrated that consumption of an αGCG solution, prior to prolonged submaximal exercise, was associated with greater improvements in thermoregulation and athletic performance than Gly or water-based placebo, during submaximal exercise on a rowing ergometer. However this was not via altering %TBW significantly and therefore most likely due to underlying molecular mechanisms that warrant further research, such as the up-regulation of heat stress factors (HSF) and aquaglyceroporin (gAQP) channel activation.

Key Words: Glycerol, Creatine Monohydrate, α-Lipoic Acid, Hyper-Hydration, Sports Performance, Sub-Maximal, Aquaporins, Heat Stress Proteins, CreaT1.

Introduction

Exercise-induced dehydration ≥2% body mass has been shown to decrease sports performance through affecting cardiovascular efficiency, central nervous system function, thermoregulation and metabolic systems (Murray, 2007). The use of Gly as a hyper-hydrating ergogenic aid has been well documented in the literature since the late 1980’s (Riedesel et al., 1987). It is typically taken in a bid to limit dehydration, thereby increasing cardiovascular and thermoregulatory efficiency in athletes. The dosage at which Gly is consumed varies between studies. However meta-analysis studies highlight that successful regimes typically apply 1-1.2g Gly/kg body weight (van Rosendale et al, 2010). Hyper-hydration is defined as manipulating ones diet to induce an excess of body fluid, which exceeds normal fluctuations, having a specific gravity under 1.010 (Van Rosendale et al, 2010, Wingo et al, 2004).

Gly forms the backbone of triglyceride molecules (Goulet, 2012). It is osmotically active and therefore capable of establishing osmotic gradients within the body, allowing fluid to be absorbed and retained within intracellular and extracellular compartments. This process is enhanced by Gly’s slow renal clearance time, which prolongs the hyper-hydrating effect (Nelson & Robergs., 2007). Numerous studies have since attempted to justify Gly’s benefit to performance across a wide range of sports such as cycling, mountain bike racing, rowing and triathlon (van Rosendal et al., 2010). However results have, on the whole, been equivocal due to variations in experimental design such as exercise intensity, duration and humidity.

Recent studies however, have been more successful by focusing upon Creatine Monohydrate (CM) as a complimentary hyper-hydrating substance. A combined CM/Gly solution enables CM to increase intracellular water volume (ICF) whilst Gly increases both ICF and extracellular fluid (ECF) volumes, causing an overall net increase in water retention. The CM/Gly supplement also requires 100g of glucose/ 5g CM in order to catalyse CM absorption (Robinson et al, 1999; Steenge et al, 1998; Jeukendrup, 2004). However this is often unpalatable for most subjects, due to high viscosity and sweetness of the solution, caused by the substantial glucose present. α-lipoic acid also catalyses CM uptake and provides a suitable substitute for the majority of the glucose usually required. A novel study by Polyviou et al, (2012), incorporated α-lipoic acid into the CM solution and assessed whether this made the solution more palatable and whether any cardiovascular, thermoregulatory or performance improvements occurred. Results showed an equal improvement in cardiovascular and thermoregulatory responses but no direct impact upon performance when compared with the CM/Gly solution.

In response, this study aimed to assess whether consumption of the novel α-lipoic acid/Gly/CM/glucose (αGCG solution), induced any physiological or psychological advantages over the extensively researched Gly solution. The methods used to collect hydration data typically involve testing urine samples for osmolality or using bioelectrical impedance to assess fluid compartments and their composition (Kern et al., 2001; Armstrong, 2005). Thermoregulatory factors are usually measured with a rectal-probe thermometer, considered as the gold-standard, to assess changes in core body temperature (Wright et al., 2007) and a heart rate monitor to record alterations in the cardiovascular system. In this study, databases PubMed and Google Scholar were utilised to access numerous journals which focused upon the topic area of hyper-hydrating agents. Having read these articles (see bibliography), and noticed the absence of any studies directly comparing Gly and αGCG, the decision was made to undertake a novel research project to compare these solutions in relation to hydration status, cardiovascular function, thermoregulatory efficiency and sports performance. This was a comparison that had not been made within the literature to date.

Aims and Objectives

The aim of this project was to determine whether or not an αGCG solution exerted a statistically significant difference upon hydration, cardiovascular function, thermoregulatory efficiency, psychological factors, or sports performance, when compared with the conventionally studied Gly solution, during submaximal exercise. This perspective had not been covered within the literature thus far and the hope was to provide a novel insight into the potential advantages of the αGCG solution over Gly as a hyper-hydrating agent.

Due to the broad nature of this study, there were a number of specific objectives assigned to hydration, thermoregulatory, cardiovascular and performance factors. Hydration objectives were to determine the effects of Gly and αGCG solutions on preserving total body water during a 30 minute bout of sub-maximal exercise on a rowing ergometer. Thermoregulatory objectives were to continuously assess body temperature as well as collect, subjective data on thermal sensation and thirst. This was to highlight any influence that the solutions may exert upon both temperature homeostasis during sub-maximal exercise, psychological responses relating to dehydration and performance measures. The objective in monitoring the cardiovascular system was to detect any significant alteration in heart rate when the two different solutions were consumed and whether there was any correlation between heart rate and performance. Indicators of sports performance included the total subjective data on perceived exertion, distance rowed (meters) and average power output (watts), following each trial.

Methods

All methodologies were ethically approved by the University of the West of England, Bristol, prior to testing taking place. 4 healthy male subjects, considered to be ‘recreationally active’ (participating in exercise for a minimum of 5 hours per week) were randomly selected to participate in this study. A compulsory familiarisation session was provided to allow subjects to gain greater knowledge of the study, test out equipment and have their weight, height and estimated maximum heart rate (eMHR) measurements taken. eMHR was determined using the formula 202- 0.55-age proposed by Whyte et al, 2008 which accounts for gender differences and the overestimation in HR associated with the commonly used 220-age formula (Gulati et al, 2010). The value 220 was a superficial estimate derived from unpublished maximum heart rate data in 1971 (Robergs and Landwehr., 2002). 202 has recently been recognised as a more accurate maximum HR value than 220, when calculating eMHR, and furthermore 0.55 is included in the revised formula as a gender correction factor accounting for the fact that males may have a greater maximum HR than females (Whyte et al, 2008).According to the formula proposed Whyte et al, (2008), 70% of every subjects eMHR was 133 BPM. This correlates to 49% estimated VO2Max when applied to the regression equation, %MHR = 0.64 × %VO2 Max + 37, proposed by Swain et al, 1994. This exercise intensity was chosen as a similar study by Latzka et al, 1997, which assessed Gly hyper-hydration, at 45% VO2Max, demonstrated significant results. Information packs, informed consent forms and Par-Q medical questionnaires were provided to ensure subject eligibility. Following the successful completion of these documents, a 6-week, single-blind data collection period began. Two repeats were performed for Gly and αGCG, as well as a placebo, in order to increase the reliability of data. Gly solutions comprised 1gGly/Kg subject’s body weight (Sports Supplements Ltd), diluted in 500ml of bottled water (Highland Spring Group Ltd). αGCG solutions comprised 250mg α-lipoic acid (Health Aid Ltd), 1gGly/Kg subject’s body weight (Sports Supplements Ltd), 20g CM (Sports Supplements Ltd) and 25g glucose (Thornton&Ross Ltd) diluted in 500ml of bottled water (Highland Spring Group Ltd). The placebo comprised 500ml of bottled water (Highland Spring Group Ltd). All 3 solutions were also mixed with 15ml of sugar-free double concentrate orange squash (Sainsbury’s Ltd) in order to improve palatability and to prevent subjects from differentiating between solutions, thus eliminating a potential bias. The doses of 20g CM, 25g glucose and 250mg α-lipoic acid were all determined via studies which highlighted successful hyper-hydration results when consuming these doses (Polyviou et al, 2012; Kilduff et al, 2003). 24-hour recalls for red-meat consumption and exercise were recorded to account for the potential interaction of additional CM, with the results. CM consumption, external to the study, could result in false-positive results because the extra CM could be responsible for changes in %TBW, rather than the 20g dose provided. It is essential to record intake as red meat typically contains 350mg CM/100g of meat highlighting it as a potent external source of CM with the potential to affect results (Williams, 2007). Subjects were assigned a testing day and required to fast from 11PM until the chosen solution was provided, to ensure changes in %TBW were due to the solution consumed, and not a factor external to this study. An initial Tanita (model TBF-300A) bioimpedence test was performed, to assess body composition, 90 minutes prior to beginning exercise. The Tanita output included weight, fat-free mass, fat-mass, %TBW, body mass index and basal metabolic rate. This 90 minute gap was determined by calculating a point of optimal concentration, using the half-lives for each supplement (Harris et al, 2010; Murray 1987; Teichert et al, 2003; Jeukendrup, 2004). Also at this point, breakfast snacks were provided. These were individually standardised using MET values, which quantify the energy expenditure related to physical activities, and the subject’s body weight and height, in order to rule out biases arising from differences in energy input (Ainsworth et al, 2011). Laboratory air temperature was internally controlled at 21°C, throughout the 6 week testing period, to ensure temperature variations did not compromise the validity of results. At the laboratory a secondary bio-electrical impedance test was performed and skin-temperature thermistors were connected to a Biopac (model MP35) and then attached to the subject, providing continual skin temperature readings. Biopac is data acquisition equipment, capable of measuring a wide range of inputs, including temperature (Biopac, 2012). A Polar heart rate monitor (model FT-1) was attached via wrist watch and chest transmitter. Following a standardised warm-up, at 24 strokes per-minute, initial RPE, TSS and TS assessments took place, to assess the effect of the solution on psychologic function. The subjects then rowed at 70% eMHR (49% VO2max). At 5 minute intervals, heart rate, RPE, TSS, TS and skin temperature were recorded. At 30 minutes final heart rate, RPE, TSS, TS, and temperature data was taken and a final bioimpedence test performed. Power output (watts) and distance covered (meters) was also recorded from the rowing machine output (Concept 2 model D-PM3). A standardised warm-down at 24 strokes per-minute was then performed. Finally, subjects were given time to rest and consume high carbohydrate drinks and snacks to aid recovery processes.

Data Analysis

Following data collection, numerous statistical tests were employed, using Minitab version 16. Anderson-Darling normality tests were performed on every variable to assess whether a parametric or non-parametric test was suitable. Pearson correlation tests were then performed to highlight any relationships between the change in %TBW resulting from each drink and the independent variables. Paired T-tests were used, at the 95% confidence interval, to check for significant differences between the mean %TBW effects of the placebo vs. Gly and placebo vs. αGCG at both pre vs. post exercise and fasting vs. pre exercise. In order to test whether improving fitness was responsible for the distances covered; a paired T-test was also performed on week vs. distance covered, in order to expose any significant relationship. Next, 3 ‘general linear model’ analysis of variance (ANOVA) tests were employed. ANOVA 1 assessed the effect of subject, solution and the interaction between subject and solution on caloric expenditure, distance covered, power output, heart rate and skin temperature. ANOVA 2 assessed the effect of subject, solution and the interaction between subject and solution on %TBW change for placebo, Gly and αGCG. ANOVA 3 assessed the effect of subject, solution and the interaction between subject and solution on RPE, TSS and TS. ANOVA tests were employed to assess whether there was statistically significant variation between the data collected for dependent variables when each solution was consumed. Finally, multiple regression analysis was performed on each subjects average change in %TBW for each solution vs. calorific expenditure, distance covered, power output, heart rate and skin temperature and each subjects average change in %TBW for each solution vs. RPE, TSS and TS. Multiple regression analysis facilitated the identification of which physiological and psychological variables were the strongest predictors for the change in %TBW.

Figure 1: Schematic Diagram of Study Itinerary.

Results

Heart rate, RPE and TSS were all excluded from the results, as these variables were deemed to be statistically insignificant by all statistical tests employed p≥0.05.

Figure 2: Boxplot highlighting average changes in %TBW for each solution consumed (Fasting vs. Pre-Exercise).

Figure 2 highlights the Gly solution as increasing %TBW to a greater extent (1.033%) than both Placebo (-0.018%) and αGCG (-0.21%).

% TBW differences for fasting vs. pre-exercise, for Gly, αGCG and Placebo solutions were statistically insignificant, p≥0.05. Solution was statistically insignificant in explaining fasting vs. pre-exercise %TBW variation, p ≥ 0.05. Inter-subject variation was the key contributor for fasting vs.pre-exercise %TBW variation p ≤ 0.005. R2 adj for %TBWchange vs. subject and solution was 62.18%.

Figure 3: Boxplot highlighting average changes in %TBW for each solution consumed (Pre vs. Post Exercise).

Figure 3 shows that consumption of αGCG resulted in the greatest preservation of TBW with an increase of 0.008%. The placebo solution was more effective than Gly in maintaining TBW 0.003% vs. -1.123%.

% TBW differences for pre vs. post-exercise, for Gly, αGCG and Placebo solutions were statistically insignificant, p≥0.05. Placebo was more effective than Gly in preserving %TBW 0.003% vs. -1.123%, paired T-tests p ≤ 0.000. Solution was deemed a statistically insignificant factor in explaining %TBW variation, p ≥ 0.05. Inter-subject variation was the key contributor for pre vs. post-exercise %TBW variation p ≤ 0.005. R2 adj for %TBW change vs. subject and solution was 86.99%.

Figure 4: Line Plot of Average Skin Temperature for Placebo, Glycerol and αGCG Over the 30 Minute Testing Period.

Figure 4 highlights that average skin temperature (°C) was consistently lower at each 5 minute interval when αGCG was consumed. αGCG average skin temperature was 30.19±0.9 compared with 30.6±0.38 for Gly and 31.49±1.72 for placebo.

Gly, αGCG and placebo solutions all demonstrated a statistically significant difference between time and temperature, p≤0.05.

Figure 5: Boxplot highlighting the average Caloric Expenditure when Glycerol, αGCG and Placebo Solutions were consumed.

Figure 5 shows that consumption of the αGCG solution, resulted in the highest caloric expenditure (Kcals), 334.13±12.75, followed by Gly, 324.38±14.57 and placebo, 318.31±10.03.

There was no statistically significant difference between change in %TBW and caloric expenditure for Gly, p≥0.05. There was a statistically significant difference between αGCG and placebo, p≤0.05.Statistically significant correlations for all 3 drinks were noted between caloric expenditure and distance covered, as well as caloric expenditure and power output, p≤0.000.

Figure 6: Boxplot of the Average Power Output (Watts) when Glycerol, αGCG and Placebo Solutions were consumed.

Figure 6 shows that the greatest average power output (watts) was achieved when αGCG was consumed, 108.38±6.29 compared to Gly, 101.63±8.59 and placebo, 99.25±6.28.

Solution and inter-subject variation, for example fitness levels, age and body composition, were statistically significant power output determinants, p≤0.05. R2Adj for solution and inter-subject variation was 27.31%. Statistically significant correlations were discovered between distance covered and power output, as well as caloric expenditure and power output, p≤0.000. Between placebo and αGCG, there was a statistically significant difference between power output and %TBW, p≤0.05 but not for Gly.

Figure 7: Boxplot Showing the Average Distance Covered when Glycerol, αGCG and Placebo Solutions were consumed.

Figure 7 shows that the greatest average distance covered (meters) was achieved when αGCG was consumed 6082.13±120.2. Average distance covered when Gly was consumed was 5909±119.56 and for placebo, 5840.38±384.94.

There was a statistically significant difference between distance and %TBW for placebo and αGCG, p≤0.05, but not for Gly. Statistically significant correlations were observed between caloric expenditure with distance covered and power output with distance covered, p≤0.05.

Figure 8: A Scatterplot of Average Distance Rowed (Meters) Over the 6 Week Testing Period.

Figure 8 highlights a positive correlation between performance, week number and distance covered.

A statistically significant difference between week number and distance covered was noted, p≤0.000.

Figure 9: Line Plot Demonstrating Average Changes in Perceived Thirst, over the 30 Minute Testing period, When Glycerol, αGCG and Placebo Solutions were consumed.

Figure 9 shows that lowest average TS score was achieved with consumption of the Gly solution, 4.5±0.5 and that αGCG had average TS of 5.5±1 and placebo had an average TS of 6±1.5.

No statistically significant correlations were observed between % TBW change and Gly TS, p≥0.05. Statistically significant correlations were observed between %TBW change and αGCG TS, and %TBW change and placebo TS, p≤0.05. R2 Adj for αGCG TS was 43.3% and for placebo TS, 59.4%, p≤0.05.

Figure 9: Table with Variables Assessed for Each Solution with Averages, Standard Deviations and p-values.

Solution

Average Heart Rate

(BPM)

Over 30 Minutes

Average Temperature

(°C) Over 30 Minutes

Average Caloric Expenditure

(Kcals)

Over 30 Minutes

Average Power Output

(Watts)

Average Distance

(Meters)

Average RPE

Over 30 Minutes

Average TSS

Over 30 Minutes

Average TS

Over 30 Minutes

Glycerol

131.77±1

p≥0.05

30.6±0.38

p≤0.05

334.13±12.75

p ≥0.05

101.63±8.59

p ≤0.05

5909±119.56

p ≥0.05

12±2

p ≥0.05

4.5±0.5

p ≥0.05

4.5±0.5

p ≥0.05

αGCG

133.39±1.95

p≥0.05

30.19±0.9

p≤0.05

324.38±14.57

p ≤0.05

108.38±6.29

p ≤0.05

6082.13±120.2

p ≤0.05

11.5±1

p ≥0.05

5±0.5

p ≥0.05

5.5±1

p ≤0.05

Placebo

130.98±2.96

p≥0.05

31.49±1.72

p≤0.05

318.31±10.03

p ≤0.05

99.25±6.28

p ≤0.05

5840.38±384.94 p ≤0.05

11.25±2

p ≥0.05

4±1

p ≥0.05

6±1.5

p ≤0.05

p≤ = statistically significant difference between post exercise %TBW for each drink and variable

p≥0.05 no statistically significant difference between post exercise %TBW for each drink and variable

Effects on Hydration Status

The vast majority of Gly hyper-hydration studies have been performed in hyperthermic environments, using fluid retention to assess Gly hyper-hydration (Nishijima et al, 2007; Latzka et al, 1997; Kavouras et al, 2006). Significant alterations in fluid retention have been observed under these conditions; ranging from 25-134.3% (Goulet et al, 2007). However this study aimed to investigate whether similar differences could be replicated in terms of %TBW change, in a thermoneutral environment. There was no significant difference in %TBW for fasting vs. pre-exercise, suggesting that the sensitivity of the bio-electrical impedance machine may have been insufficient or that the fluid had not been fully absorbed when testing took place. Inter-subject variation was the key predictor of %TBW change for both fasting vs. pre-exercise and pre vs. post-exercise, p≤0.000, for which it accounted for 62.18% and 86.99% of variation respectively. This suggests that, although doses were standardised for body weight, individual differences between subjects such as muscle mass and metabolic rate were influential in determining %TBW change. There was an average pre vs. post-exercise %TBW difference of -1.123%, highlighting Gly as less effective than αGCG, + 0.008%, and placebo, +0.003%, in maintaining fluid balance. Yet this relationship was statistically insignificant, corroborating findings by Polyviou et al, (2012). The relatively small change in %TBW, is similar to the 1.4% TBW decrease reported by Nishijima et al, (2007), whose study was performed at 30.3±0.6°C compared to this studies’ 21°C. This interestingly suggests that Gly exerts a similar effect both in hyperthermic and thermoneutral environments, counteracting the general consensus that changes in %TBW, induced by Gly consumption, only occur during exercise under heat stress. This was shown to be statistically insignificant in this study possibly due to a small sample population. This study found the placebo solution more effective at maintaining %TBW than Gly (p≤0.000). These results are supported by Goulet et al, (2002) who demonstrated that a water-based placebo solution significantly increased %TBW compared to a Gly solution. This may be because the placebo solution had a prolonged absorption time, dependent upon gastric emptying and intestinal absorption, and hence a prolonged ‘hydration effect’ compared to the Gly solution which acted more rapidly (Leiper et al, 1998). It is important to recognise that the long-term effects of Gly hyper-hydration may be limited as 50% of ingested Gly is removed within 2 hours (Dini et al, 2007). This reduces Gly’s usefulness in ultra-endurance events, making it useful for intermediate-endurance events.

Gly is a 3-carbon alcohol providing structural support to triglyceride molecules. It has been extensively studied because of its ability to increase the fluid compartments of the body via a number of mechanisms (Robergs & Griffin, 1998). Gly is absorbed primarily via the small intestine and to a lesser extent by the stomach, after which it is evenly distributed throughout most of the body, except the cerebral spinal fluid and aqueous humour (Nelson & Robergs, 2007). A by-product of Gly consumption is increased osmolality of the intracellular and extracellular compartments, which facilitates a concentration gradient capable of directly promoting fluid reabsorption in the medulla of the kidney and stimulating active transport in the proximal tubules (Nelson & Robergs, 2007; Goulet et al, 2007). Moreover, there is a reduced renal free-water clearance, diuresis and increased fluid retention (Freund et al, 1995). This was originally attributed to enhanced anti diuretic hormone (ADH) secretion, which occurred specifically due to the presence of Gly (Wagner, 1999). However recent studies disagree with this theory, suggesting that decreased free-water clearance occurs independently of hormonal input from ADH, although this has not yet been proven either way (O’Brien et al, 2006; Easton et al, 2007). This process occurs to a greater extent with Gly than with commercial sports drink consumption (Van Rosendale et al, 2009).

Figure 10: Flow chart highlighting the proposed mechanisms by which glycerol supplementation induces enhanced fluid retention, increasing %TBW.

CM was a key active ingredient present in the αGCG solution. It is a popular non-essential dietary compound notorious for facilitating improvements in muscle bulk and maximal strength as well as decreasing neuromuscular fatigue (Sobolewski et al, 2011; Buford et al, 2007). Significant research has focused upon CM and its ability to increase ICF volume and hence its effects on hydration status (Kilduff et al, 2003; Easton et al, 2007, Powers et al, 2003), proven by increased anterior compartment pressure studies (Hile et al, 2006). In terms of CM uptake, the addition of carbohydrate (CHO) can increase this by ≤60% (Beis et al, 2011), when consumed in a ratio of 100g glucose to 5g CM (Green et al, 1996). However this makes the solution unpalatable for most subjects due to solution viscosity (Polyviou et al, 2012). In response, this study substituted 375g of the 400g of glucose, usually required, with 250mg α-lipoic acid, an insulin potentiating anti-oxidant proven to increase CM uptake, catalysing water retention within the skeletal muscle similarly to the CM-glucose combination (Burke et al, 2003; Polyviou et al, 2012). The results of this study also indicate that α-lipoic acid is a suitable replacement for glucose, as the post-exercise %TBW for αGCG was the highest at + 0.008%, highlighting that the α-lipoic acid, CM and glucose combination was more effective than Gly at preserving %TBW. The αGCG solution had the greatest %TBW preservation potentially due to the synergistic action of the α-lipoic acid, CM and glucose on ICF volume and the effect of Gly on both ICF and ECF volume, resulting in a greater hydration status effect than if the supplements had been taken in isolation. This theory is strengthened as αGCG preserved %TBW to a greater extent, 0.013%, compared to Gly alone and is further reinforced by Easton et al, (2007). Skeletal muscle, which accommodates ≤ 95% of CM, has a finite capacity due to the intrinsic down regulation of CM transporters and therefore, excess CM is excreted via the urine (Persky et al, 2003). Consequently, subjects in this study were required to fast overnight and record any red meat consumed, which may have caused CM supplied by the αGCG solution to be excreted.

The mechanism, by which the αGCG solution facilitates greater CM absorption into the skeletal muscle, is a highly complex multi-step process. In vitro studies have demonstrated that α-lipoic acid induces the release of glucose into the bloodstream by up-regulating GLUT-4 protein expression, complexes responsible for bidirectional inter-membrane glucose transport (Burke et al, 2003; Saengsirisuwan et al, 2001). The consequent flux in blood glucose, compounded by the addition of 25g glucose within the αGCG solution, elicits an insulin response, inducing insulin release from pancreatic β-cells. Insulin was originally deemed incapable of influencing CM uptake (Willott et al, 1999) however recent studies highlight insulin as capable of increasing skeletal muscle CM accumulation up to 3-fold (Tipton et al, 2008; Persky et al, 2003). The exact mechanism by which this occurs is under debate however there is significant evidence that the αGCG solution increases CM uptake compared to isolated CM consumption. It is most likely that insulin stimulates the expression of sodium-chloride dependant CM transporter proteins (CreaT1), resulting in enhanced CM uptake (Steenge et al, 1998; Persky et al, 2001; Schoch et al, 2006; Persky et al, 2003). Furthermore, the extent to which CM uptake occurs is dependent upon muscle fibre type and post-supplementation exercise intensity. Type II fibres have greater CreaT1 density and therefore demonstrate greater insulin-response effects (Casey et al, 1996; Brault et al, 2003). As muscle fibre composition varies between individuals, this likely explains why inter-subject variation was the key contributor for pre vs. post-exercise variation in %TBW, p ≤ 0.005, R2 Adj 86.99%. Greater post-supplementation exercise intensity, results in greater heart rate and stroke volume and hence cardiac output, increasing insulin delivery and expression of CreaT’s and CM uptake. (Persky et al, 2003). However this variable is not likely to have contributed towards the inter-subject variation observed within this study, as exercise intensity was standardised at 49% VO2max.

Figure 11: Flow chart highlighting the mechanism by which α-lipoic acid supplementation induces increased CM uptake into the skeletal muscle.

Effects of Hyper-Hydration on Cardiovascular Strain and Sports Performance

Dehydration and thermal stress are causally linked to exacerbating cardiovascular strain when performing sport (Shirreffs, 2005), therefore hyper-hydration has the potential to limit the extent to which this occurs. The majority of studies (Polyviou et al, 2012; Goulet et al, 2002) have reported significant decreases in heart rate when a Gly-based beverage is consumed. However the results of this study found no correlation between Gly consumption and decreased heart rate, despite being controlled, or perceived thermal strain, p≥0.05 and are supported by Kavouras et al (2006) and O’Brien et al (2006), whose results also found no cardiovascular benefits associated with Gly. The lack of a significant difference between solutions highlights that Gly did not have any advantageous impact upon measures of cardiovascular strain. Most studies have demonstrated that CM supplementation attenuates an elevated heart rate (Polyviou et al, 2012; Beis et al, 2011), systolic blood pressure and mean arterial pressure (Sobolewski et al, 2011). This study found no correlation between αGCG consumption and decreased heart rate or TSS, p≥0.05, and is supported by Easton et al, 2007 who failed to identify attenuations in heart rate, when Gly and CM are combined. Studies that demonstrated reduced cardiovascular strain were typically conducted in a hyperthermic environment. Consequently, the thermoneutral environment in which this study was performed is likely to explain why there were no statistically significant reductions in cardiovascular strain (Shirreffs, 2005).

Effects of Hyper-Hydration on Thermoregulation and Sports Performance

The majority of studies assess thermoregulation via core temperature methods, demonstrating Gly-induced decreases in core temperature (Van Rosendale et al, 2010; Nelson & Robergs, 2007), indicating enhanced thermoregulation. However this study used a non-invasive skin temperature thermistor method, in order to satisfy ethical approval, and to assess whether similar relationships could be observed between these results and the correlations usually observed with core temperature methods. Results showed average skin temperature for Gly was significantly lower than when placebo was consumed (30.6±0.38°C vs. 31.49±1.72°C, p≤0.05), this was expected and demonstrates that consumption of Gly is advantageous over a placebo, in terms of thermoregulation, during submaximal exercise in a thermoneutral environment. This also suggests that skin temperature measures are an effective method for assessing thermoregulatory changes, following supplementation with Gly. Numerous studies have highlighted the positive effects of both CM and Gly supplementation on human thermoregulatory mechanisms (Nishijima et al, 2007; Goulet et al, 2007; Wright et al, 2007; Greenwood et al, 2003). Gly consumption is associated with increases in plasma volume, ICF and ECF, which enhances the body’s specific heat capacity and sports performance in hot conditions (Beis et al, 2011; Kavouras et al, 2006). Gly has also been positively correlated with increased sweat rate, another mechanism by which the body maintains thermic homeostasis during exercise, although not measured within this study (Van Rosendale et al, 2010; Nelson & Robergs, 2007).

Limited research has been carried out on the αGCG solution and thermoregulation; however Polyviou et al, (2012) demonstrated αGCG consumption attenuated increases in core temperature, to a greater extent than a Gly/CM solution. Interestingly, the skin temperature results of this study support the findings by Polyviou et al, (2012) as the αGCG solution had the lowest average skin temperature compared to both Gly and Placebo (30.19±0.9°C vs. 30.6±0.38°C and 31.49±1.72°C, p≤0.05). This shows that consumption of an αGCG solution is more effective in attenuating rises in skin temperature, resulting from prolonged submaximal exercise in a thermoneutral environment, compared to the conventional Gly solution or placebo. However no significant correlation was found between any solution and TSS, in particular Gly p ≥0.05, which agrees with the findings of Easton et al, (2007), who recorded that when Gly and CM are combined, there is no interaction with TSS whatsoever. This is an expected result as Gly does not permeate the blood brain barrier (BBB) and so is unlikely to influence subjective variables significantly (Van Rosendale et al, 2009). Consumption of CM-based solutions can limit the extent to which core temperature rises in response to prolonged bouts of exercise (Beis et al, 2011; Kern et al, 2001). The mechanism by which CM exerts effects upon thermoregulation is debatable. One theory is that prolonged exercise induces dehydration, causing ECF to become hyperosmotic, to a greater extent than CM hyper-hydrated skeletal muscle cells. The difference in osmolality facilitates a concentration gradient favouring ECF influx, which reduces the risk of heat-damage and improves thermoregulation (Sobolewski et al, 2011; Lopez et al, 2009; Weiss et al, 2006). However it is also possible that, due to CM’s osmotically active nature, it may prevent fluid efflux from the ICF compartments during times of heat stress, compounding physiological damage and exacerbating disruption to thermoregulation (Sobolewski et al, 2011; Lopez et al, 2009; Weiss et al, 2006).

Figure 12: Flow chart highlighting the proposed mechanisms by which creatine monohydrate supplementation may influence thermoregulation.

At a molecular level, there are several mechanisms by which both the Gly αGCG solutions exert effects upon thermoregulation. Aquaglyceroproins (gAQP’s) are water and Gly-transporting protein structures, capable of shifting fluid to the skin to facilitate sweating, a process involved in thermoregulatory homeostasis (Lee et al, 2012). They differ from other aquaporin proteins (APQ’s) which only facilitate water transport (Tradtrantip et al, 2009). Furthermore, there is a correlation between increased gAQP expression and improved marathon performance (Martinez et al, 2009). gAPQ’s enable water and Gly diffusion into peripheral skin layers, forming a water-reservoir; lipid synthesis prevents Gly accumulation within these tissues (Draelos, 2012). Water molecules are then readily available for diffusion through sweat gland specific AQP-5, fixing exercise-induced hydration abnormalities (Shibasaki and Crandall 2011; King et al 2004; Verdier-Sévrain and Bonté, 2007). This process enables rapid thermoregulatory recalibration by rapid fluid loss via sweat glands in thermoregulatory-straining conditions, such as prolonged exercise (Nejsum et al, 2002). Consumption of Gly not only underpins this thermoregulatory mechanism but also increases gAQP mRNA expression, and hence gAQP proteins, heightening the contribution of gAQP fluid transport in mediating thermoregulation during prolonged exercise (Schrader et al 2012). It has been argued that AQP-5 is not involved in sweat release (Song et al, 2002); however this study was conducted on animal models during an isolated, 10 minute, exposure to exercise and thermal stress. The human body is likely to utilise AQP-5 as part of an integrative response to prolonged exposure to heat stress, which may be induced by prolonged exercise (Martinez et al, 2009). This study found Gly less effective at maintaining %TBW than αGCG and placebo, -1.123% vs. + 0.008% +0.003%, which may be due to this mechanism shifting fluid to the skin to enhance thermoregulation, whilst reducing ICF and ECF volumes. This supported by Gly having a lower average skin temperature than placebo, 30.6±0.38°C vs. 31.49±1.72°C (p≤0.05), indicative of enhanced thermoregulation. Unfortunately, gAQP activation was beyond the scope of this study. However this molecular mechanism likely explains the paradoxical issue of improved thermoregulation occurring alongside a decreased % TBW.

Figure 13: Diagrammatic representation of glycerol- mediated water transport, favouring thermoregulation, via aquaporin protein complexes.

αGCG contained α-lipoic acid which is linked to heat stress protein (HSP) up-regulation (Oksala et al, 2006; Mirjana et al, 2012). HSP’s are molecular chaperones that transport repair proteins and restrict protein aggregation during exposure to thermal stress, such as during prolonged exercise, providing a thermoregulatory-protective mechanism (Iguchi et al, 2012). α-lipoic acid directly modulates heat stress factor 1 (HSF-1) expression, the gene responsible for stimulating HSP synthesis (McCarty, 2006). This mechanism occurs to a greater extent under times of oxidative stress, such as the prolonged exercise in this study (Oksala et al, 2006). α-lipoic acid therefore not only up-regulates HSP’s but promotes their synthesis. The results of this study show that with αGCG consumption, there was the lowest average skin temperature compared to both Gly and Placebo (30.19±0.9°C vs. 30.6±0.38°C and 31.49±1.72°C, p≤0.05). Although not directly measured, this may be partly due to increased HSP expression, resulting from raised concentrations of α-lipoic acid. Furthermore, with α-lipoic acid supplementation; there is an increased synthesis and expression of HSP-60 and HSP-70, as well as the normalisation of HSP-72 levels in patients suffering from low HSP levels (Oksala et al, 2006; Kapakin et al, 2012; McCarty, 2006; Strokov et al, 2000). Increased HSP expression acts to directly preserve thermoregulatory homeostasis and therefore could be a factor contributing to the results gathered in this study. Due to increased oestrogen levels, the expression of HSP mRNA is significantly lower in females when consuming α-lipoic acid (Paroo et al, 2002; Rosene et al, 2004). As such, the thermoregulatory ergogenic effect observed within this study, following αGCG supplementation, may be reduced if the protocol were to be repeated with female subjects.

Figure 14: Flow chart showing the cascade by which α-lipoic acid consumption enhances HSF-1 expression and HSP synthesis, enhancing thermoregulation and improving performance.

Effects of Hyper-Hydration on Sports Performance Measures

From an athletes perspective, the aim of consuming Gly or αGCG solutions is to improve athletic performance. Performance measures recorded within this study, include distance rowed (meters), caloric expenditure (Kcals) and power output (watts). The results demonstrated significant correlations between these three variables, p≤0.05. This is logical as power output dictates both caloric expenditure and distance covered (see figure 15) (Concept2, 2012). Interestingly, the highest power output, caloric expenditure and distance covered were recorded with consumption of αGCG, highlighting this as the most effective ergogenic solution out of the three (108.38±6.29 watts, 324.38±14.57 Kcals and 6082.13±120.2 meters), counteracting results by Polyviou et al, (2012) who found that αGCG was not advantageous to performance. Although no studies have compared these solutions together before, research has shown that, with CM supplementation, there is increased power output and muscle peak torque (Wright et al, 2007; Oopik et al, 1998), reinforcing the results of this study. Gly was also more effective than the placebo in all three performance measures (101.63±8.59 watts, 334.13±12.75 Kcals and 5909±119.56 meters), and is supported by similar results by Van Rosendale et al, 2010 and Goulet et al, 2007. The results of this study demonstrate that both αGCG and Gly solutions are advatageous to submaximal rowing performance. It was also hypothesised that improvements in performance could be due to a ‘training adaptation’ effect over the 6 week testing period. Results showed a positive correlation between week number and distance rowed, p≤0.000, demonstrating that improvements in fitness, over the 6 week testing period, as well as the solution consumed are predictors of sports performance and explain the results gathered.

Figure 15: Diagram Highlighting the Relationship between Distance Rowed, Caloric Expenditure and Power Output on Maximal Sports Performance.

Power Output (Watts)

Maximal performance

Distance Rowed (Meters)

Caloric Expenditure (Kcals)

Discussion

Effects of Hyper-Hydration on Psychological Variables Associated with Sports Performance

It has been stated within the literature that Gly does not cross the blood brain barrier and is therefore unlikely to affect psychological variables (Van Rosendale et al, 2009). This is supported by the majority of studies (Mehmet et al, 2011; Goulet et al, 2007), that demonstrate no relationship between the consumption of a Gly solution and changes in TS compared to water. However, in contradiction, although not statistically significant (p≥0.05), this study observed a lower thirst scale rating with Gly compared to both placebo and αGCG (4.5±0.5 vs. 6±15 and.5±0.5) and is supported by Wingo et al, (2004) who observed lower perceived thirst when a Gly-based beverage was consumed, compared with a placebo. This indicates that whilst Gly is unable to permeate the BBB to exert psychological effects, there may be an indirect mechanism responsible for decreasing perceived thirst. One possible explanation may be that decreased perceived thirst is an indirect result of physiological changes, associated with Gly consumption, such as the lower skin temperature observed within this study. However because TS is a subjective assessment, it is not possible to measure quantitatively in order to prove this theory and further research is required to determine the exact cause of decreased TS when a Gly-based beverage is consumed.

CM however, does cross the BBB and is therefore more likely to influence psychological variables than Gly (Van Rosendale et al, 2009). The results of this study suggest that the αGCG solution effects the psychological variable TS greater than the placebo (5±0.5 vs. 6±15), but to a lesser extent than Gly (4.5±0.5). However this relationship was deemed statistically significant (p≤0.05), suggesting that psychological changes induced by CM may be more potent than those induced by Gly. The R2 adj for αGCG was 43.3% demonstrating that TS is a significant contributory factor to %TBW change. RPE and TSS were deemed statistically insignificant, p≥0.05. These results are supported by Beis et al, (2011), who found no correlation between RPE and TSS following CM supplementation. Nevertheless, studies suggest CM supplementation promotes decreased RPE, during prolonged exercise (Easton et al, 2007). CM crosses the BBB and interacts with modulators controlling serotonin (5-HT) and dopamine receptor activity, dictating thermo-physiological variables, such as mean skin temperature and heart rate, which have the cumulative effect of lowering perceived effort (Hadjicharalambous et al, 2008), during periods of exercise-induced heat stress (Bridge et al, 2003). Whilst RPE was lowered due to the cumulative effect of CM supplementation, no significant sports performance effects were recorded in the study by Hadjicharalambous et al (2008), unlike this study when αGCG consumption resulted in greater distance rowed, caloric expenditure and power output compared to both Gly and placebo.

Potential Disadvantages of Hyper-Hydration

Whilst the advantages of hyper-hydration are well documented (Nelson & Robergs., 2007; Polyviou et al, 2012; Bemben et al, 2001; Patlar et al, 2011), there are associated disadvantages. It is a common perception that hyper-hydration strategies increase the likelihood of voiding during competition (Latzka et al, 1997; Jeukendrup, 2011). However in fact, with Gly or αGCG consumption, there is a lowered renal free-water clearance, reducing the need to void, counteracting the perception that all hyper-hydration strategies are disadvantageous (Nelson & Robergs, 2007; Goulet et al, 2007; Freund et al, 1995). In the long term, advantages in α-lipoic acid supplementation on hydration status may be equivocal because prolonged α-lipoic acid supplementation results in reduced reactive oxygen species (ROS). Reduced ROS is associated with reduced mitochondrial biogenesis, consequently negatively affecting an athlete’s aerobic capacity (Strobel et al, 2011). This therefore questions the advantage of long-term αGCG supplementation.

Hyper-hydration increases body mass, but it has been demonstrated that athletes can significantly improve performance via weight loss methods, opposing hyper-hydration techniques (Goulet, 2012). However recent studies now suggest that individualising hydration strategies are the best approach. Endurance athletes with a high sweat rate may benefit from hyper-hydration because, by the mid-point of their race, the majority of excess bodyweight is lost, preserving hydration and promoting maximal performance (Lopez et al, 2012). Fluid loss is also linked to a decreased exercise oxygen cost, which promotes maximal performance, compounding the argument against utilising hyper-hydration to improve sports performance as they increase body weight (Beis et al, 2011).

Perhaps the most significant limitation for elite athletes is the decision, by the World Anti-Doping Agency (WADA), to ban Gly use from 2010 onwards (WADA, 2012). This decision was made because, due to its ability to enhance fluid retention, Gly can act as a masking agent hiding other banned substances from detection (Thevis et al, 2012, Jeukendrup, 2011). Whilst undoubtedly, some athletes may use Gly hyper-hydration strategies to mask illegal substances within blood, Gly hyper-hydration can be used legitimately, as proven by Polyviou et al, (2012) whose research showed that a 7-day Gly regimen, did not alter blood doping-relevant parameters significantly. This highlights that, whilst Gly is currently be a banned substance, it may become a legal supplement in the future. WADA have been precautionary in banning Gly ahead of the Olympic Games; however current research has recently demonstrated that urinary analysis is an effective method for differentiating between the legal and illegal use of Gly in elite sport (Nelson et al, 2011; Koehler et al, 2011). This evidence strengthens the argument that Gly may be taken off WADA’s prohibited list in the future, subject to the urinary analysis testing of elite athletes. Nevertheless for recreational athletes, Gly hyper-hydration may still be a viable option to enhance performance.

Limitations of this Study

There are several limitations to this study in terms of equipment used and methods employed. The bio-electrical impedance machine, surprisingly, did not show a significant increase in %TBW between the fasting vs. pre-exercise states, suggesting that it may not have been sensitive enough to record this large fluid intake, questioning its use in future studies. Furthermore, there was not a bio-electrical impedance machine capable of differentiating between intracellular fluid (ICF) and extracellular fluid (ECF) composition. This would have been useful to assess whether Gly, which infiltrates the ECF and ICF, was more responsible than CM, which infiltrates the ICF, in causing the recorded changes hydration status. Responses to each solution may have been greater had the study used a rowing-specific VO2Max test to determine subjects’ individual exercise intensities, rather than the estimation formula. However, due to time restraints this was not possible. Taking simple, portable spirometry measurements, FVC, FEV1, would have added an extra dimension to the study, enabling the assessment of potential improvements in lung function with each solution, and over time. Skin temperature data would have been more accurate if multiple thermistors were attached to each subject and average skin temperatures derived at every 5 minute interval.

Historically, it was believed that when caffeine and CM are consumed in close succession, there is a significant molecular interaction that results in a decreased ergogenic effect of CM (Hespel et al, 2002). However further studies have counter-argued this perspective, demonstrating that the consumption of caffeine and CM together reduced RPE and is ergogenic to sports performance (Doherty et al, 2002). This has led to the formulation of powdered supplements, such as Assault™, which not only contain both caffeine and CM together, but have also been proven to reduce subjective fatigue in athletes (Spradley et al, 2012). Furthermore, any arguable interaction between caffeine and CM is ruled out by the fact that caffeine has a relatively short half-life (t- ½), of 1.77 hours, with a peak concentration (T-max), of 2.9 hours, occurring hours before the testing period began (Hammami et al, 2010). It is therefore not possible that caffeine can interact with CM, >8 hours following consumption. It is also important to recognise that neither exercise nor heat stress are factors capable of prolonging caffeine activity (Mclean et al, 2002).

Further Research

Further research should focus upon comparing Gly and αGCG solutions with sodium or caffeine-based hydration beverages that have been proven to have similar performance advantages (Carr et al, 2011; Gigou et al, 2012). Sweat rate could be recorded, in order to evaluate thermoregulatory efficiency and the potential differences in gAQP and AQP activity, with the different beverages. Potential gender differences should also be explored in order to make results relevant to a wider demographic. Potential improvements in lung function with each solution, and over time, should be assessed using portable spirometry. An increased sweat rate indicates enhanced thermoregulation and %TBW preservation indicates an enhanced hydration status. However these two indices are paradoxical as increased sweat rate reduces %TBW and %TBW preservation reduces sweat rate. Clarification is needed on this matter, in order to determine which mechanism is more beneficial to sports performance, the preservation of hydration status or an increased sweat rate?

Conclusion

The results of numerous studies have highlighted the various advantages and disadvantages of using a hyper-hydration strategy to enhance sports performance. Gly is still the most researched hyper-hydrating substance, despite being banned by WADA in 2010. It’s capability to increase ECF content has been proven to help preserve hydration status, by inducing renal reabsorption. Gly also improves thermoregulation, by activating molecular mechanisms, such as the gAQP system, which has the cumulative effect of improving sports performance in some studies. Discrepancies between positive results are likely due to methodological differences between studies. The αGCG solution contains numerous active ingredients which may also improve sports performance. α-lipoic acid interacts with GLUT receptors, enhancing CM uptake into the skeletal muscle, thereby catalysing maximal ICF retention. α-lipoic acid also induces the expression of HSF-1 and HSP synthesis, proteins capable of reducing thermoregulatory damage, during prolonged exercise.

Consumption of the αGCG solution resulted in the greatest %TBW preservation however this was not found to be statistically significant (0.008% increase p ≥ 0.05). Yet consumption of placebo resulted in statistically significantly greater %TBW preservation than Gly (0.003% vs. -1.123% TBW, p≤0.000). αGCG consumption resulted in lowest average skin temperature (30.19±0.9°C, p≤0.05), highest power output (108.38±6.29 watts, p≤0.05), and distance rowed (6082.13±120.2 meters), compared to Gly and placebo. However the lowest thirst sensation was associated with Gly consumption (4.5±0.5, p≤0.05). Furthermore, whilst there were no statistically significant RPE, TSS or heart rate results, data demonstrated that consumption of an αGCG solution, prior to prolonged submaximal exercise, is associated with greater improvements in thermoregulation and athletic performance than Gly or water-based placebo, during submaximal exercise on a rowing ergometer. However αGCG consumption is not associated with significant %TBW changes, suggesting that the discussed molecular mechanisms may be responsible for its ergogenic effect, rather than improvements in hydration status.

Figures and Tables:

Page Number

Figure 1. Schematic Diagram of Study Itinerary…………………………….………..……12

Figure 2. Schematic Diagram of Study Itinerary……………………………………..…….13

Figure 3. Boxplot highlighting average changes in %TBW for each solution consumed.....14

Figure 4. Line plot highlighting the average changes in skin temperature over time for glycerol, αGCG and placebo solutions. …………………….………………………....……15

Figure 5. Boxplot of variation in power output (watts) between glycerol, αGCG and placebo solutions.………………………………………..…………………………………….……..16

Figure 6. Boxplot showing the variation in distance covered for glycerol, αGCG and placebo solutions………………………………………………..……………………….………..….17

Figure 7. Scatterplot of the average distance covered (meters) for each week………..……18

Figure 8. Line plot demonstrating average changes in perceived thirst over time for glycerol, αGCG and placebo.…………………………………………………..…….……….....…..…19

Figure 9 Table with Variables Assessed for Each Solution with Averages, Standard Deviations and p-values…………………………………………………………………..19-20

Figure 10. Schematic Diagram of Study Itinerary Flow chart highlighting the proposed mechanisms by which glycerol supplementation induces enhanced fluid retention, increasing %TBW ……..……………………………………………………………………………..…23

Figure 11. Flow chart highlighting the mechanism by which α-lipoic acid supplementation induces increased CM uptake into the skeletal muscle………………………..…………….26

Figure 12. Flow chart highlighting the proposed mechanisms by which creatine monohydrate supplementation may influence thermoregulation ………………………………………….29

Figure 13. Diagrammatic representation of glycerol- mediated water transport, favouring thermoregulation, via aquaporin protein complexes. ……………………………………….31

Figure 14. Flow chart showing the cascade by which α-lipoic acid consumption enhances HSF-1 expression and HSP synthesis, enhancing thermoregulation and improving performance………………………………………………………………………………….32

Figure 15: Diagram Highlighting the Relationship between Distance Rowed, Caloric Expenditure and Power Output on Maximal Sports Performance…………………………..34

Abbreviations

Abbreviation

Full Word

Gly

Glycerol

CM

Creatine Monohydrate

αGCG

α-lipoic acid/ Glycerol/ Creatine Monohydrate/ Glucose Solution

TBW

Total Body Water

ICF

Intracellular Fluid

ECF

Extracellular Fluid

RPE

Rating of Perceived Exertion

TSS

Thermal Sensation Scale

TS

Thirst Scale

ANOVA

Analysis of Variance

HSP

Heat Shock Protein

CreaT1

Creatine Transporter 1 Protein

AQP

Aquaporin Channel

MET

Metabolic Equivalent

eMHR

Estimated Maximum Heart Rate

ADH

Anti Diruretic Hormone / Vasopressin

CHO

Carbohydrate

ROS

Reactive Oxygen Species

gAQP

Aquaglyceroporin Channel

HSF-1

Heat Stress Factor-1

BBB

Blood Brain Barrier

WADA

World Anti-Doping Agency

FVC

Forced Vital Capacity

FEV1

Forced Expiratory Volume at 1 Second

T-max

Maximum Concentration

T-½

Half Life