It is not uncommon for athletes to train or compete in a hypohydrated state, even showing chronic hypohydration before practices and games (9,28,34,39,43). Athletes in weight class sports such as boxing, wrestling, or mixed martial arts, often take extreme measures (saunas, hot water baths, or fluid restriction) to decrease body water to compete in lower weight classes (1,2,6,7). Significant changes in body mass through hypohydration can impair performance in training and competition (2,13,15,36).
Studies have reported anaerobic performance decrements associated with hypohydration (6,14,16,17,21,22,30,45), whereas others show no influence (6,7,14,17,18,44,45). A possible explanation for a portion of these equivocal results is the failure of some studies to achieve the level of body water loss (>3%) associated with diminished anaerobic performance (23,45). Other factors may also be influential. In a review, Kraft et al. (23) points out that it is difficult to determine the exact effects of hypohydration on anaerobic performance because of variations in exercise mode, mode of dehydration, and levels of hypohydration, among previous studies. Tests of anaerobic performance include one-repetition maximum weight lifting (14,30), full-body resistance exercise protocol (21), repeated back squats (18,21), unilateral leg extensions (14), vertical jump (7,14,18,44), 15-second Wingate tests (6,22), 30-second lower-body Wingate tests, and 30-second upper-body Wingate tests (16). In addition, various assessments of reaction time and skill (2,3,31,35,36) have been assessed. Of the 7 studies cited without diminished performance, 5 did not reach the critical (≥3%) level of hypohydration (6,14,17,44,45), and 3 were single bout, rather than repeated effort tests (6,44,45). Because the relative energy contribution from aerobic metabolic pathways systematically increases with each repeated anaerobic effort (8), there may be an increased likelihood to observe performance decrements with repeated (rather than single) effort protocols.
One mode that warrants further research is sprint performance, specifically, repeated sprint performance. In the only investigation addressing sprint performance, Watson et al. (44) found that hypohydration did not alter sprint performance when subjects completed simulated races at different distances (50, 200, and 400 m). The level of hypohydration (2.2–2.5%) and completion of only 2 repetitions per distance may explain the failure to observe impaired performance. Short distance (40-yd) sprinting is a common measure of anaerobic performance in football with repeated efforts used for conditioning simulated game play, and as a component for predicting success in American football (24). Furthermore, these athletes are subject to hypohydration particularly during practice and competition in extreme weather. The purpose of this study was to examine the effects of hypohydration to 3% body mass, on repeated 40-yd sprint performance, heart rate (HR) response, agility test (AT) performance, and perceptual measures.
Experimental Approach to the Problem
The current investigation was designed to isolate the effects of hypohydration on repeated sprint performance. Most previous studies which concluded that ≥3% loss of body mass impairs anaerobic performance, used exercise in heat (some in a heat chamber) to prompt body water loss (7,14,16,17,45). Kraft et al. (21,22) used submersion in hot water bath. All participants completed performance tests on the same day of dehydration. There is a potential connection between heat storage and fatigue, and fatigue may remain even after heat storage has dissipated (4). Similarly, as Kraft et al. (22) found, heat exposure alone could diminish same day performance even when fluids are replaced at the rate of loss. Kraft et al. (21,22) also included a recovery period allowing core temperature to return to near preheat exposure levels. Furthermore, residual effects of exercise-induced fatigue resulting from dehydration protocols may also impair subsequent performance. Consequently, previous designs make it difficult to conclude that hypohydration was fully responsible for diminished anaerobic performance. For these reasons, in this study, hypohydration was achieved using a nonexercise approach (hot water bath submersion) in the evening which allowed overnight recovery before completion of sprint trials the following morning. This approach helped isolate the independent effects of hypohydration on anaerobic performance while mitigating possible confounding effects of acute fatigue and same-day heat exposure.
Twelve anaerobically fit (participating in anaerobic exercise bouts at least 3 times a week for at least 3 weeks) current and former Division II male athletes (football, basketball, soccer, and track) participated in this investigation. Age range of subjects was 19–25 years. During an initial health screening and anthropometric assessment session, subjects completed a physical activity readiness questionnaire and were stratified according to American College of Sports Medicine (1) guidelines using known risk factors. Before data collection, subjects signed an informed consent describing the requirements. All procedures were approved by the local institutional review board for the protection of human subjects. Height to the nearest cm and mass to the nearest 0.1 kg were assessed with a stadiometer (Detecto, Webb City, MO, USA) and digital scale (Tanita Corp., Tokyo, Japan). Body fat percentage was estimated using Lange skinfold calipers (Cambridge, MD, USA) and a 3-site method (chest, abdomen, and thigh) (29).
Subjects arrived at the laboratory at approximately 0600 hours to perform a baseline trial (BT), which allowed the subjects to familiarize themselves with testing protocol. Subjects were instructed to hydrate themselves throughout the day before their initial baseline trial to help ensure euhydration. Upon arrival, subjects consumed a standardized breakfast (sports drink and protein bar). Before BT, urine specific gravity (USG) was assessed with a manual refractometer (Atago, Tokyo, Japan) to assess hydration status. According to National Athletic Trainers' Association recommendations, participants whose USG was ≤1.020 were considered euhydrated (5). Subjects also provided subjective ratings for sleep quality during the previous night, and acute thirst sensation. Both were assessed by subjects, marking on a 10-cm line (containing verbal descriptors) according to subjective feelings. Following descriptive, and perceptual data, subjects performed a 5-minute, self-directed warm-up. During warm-up, subjects were allowed to familiarize themselves with the timing equipment. After warm-up, subjects completed a bout of 10 × 40-yd sprints. A 60-second active recovery period followed each sprint, during which time subjects walked from the finish of the previous sprint back to the starting line. Following a 5-minute recovery period, subjects completed a second bout of 10 × 40-yd sprints exactly as the first. All sprint sessions took place in a climate controlled environment in an indoor court with a hardwood floor. Sprints were timed with a photogate timing system (TC System, Brower Timing Systems, Draper, UT, USA). Photogates were placed at start line, 10-yd line, and finish line. A 5-minute recovery period followed completion of 40-yd sprints, after which, subjects completed 2 trials of an agility test (AT). Agility test consisted of a modified “T-test” (26), where instead of shuffling between cones, subjects sprinted from cone to cone. Time for each sprint and agility test was recorded to the nearest hundredth of a second using the photogate system, and used as a baseline measurement. Heart rate, recorded continuously throughout the trial, was obtained using a Polar team 2 heart rate monitoring system (Polar Electro Oy, Kempele, Finland). Peak heart rate (overall peak for each 10 sprint bout) (HRpk) and average heart rate (average for entirety of each 10 sprint bout, including recovery) (HRavg) were identified using graphic plots from the team 2 System. Ratings of perceived exertion (RPE) was recorded immediately after each of the 20 sprints. Ratings of perceived exertion relative to each 10 sprint bout (RPEb1, RPEb2) was recorded 3 minutes after the final sprint of each bout. Session rating of perceived exertion (SRPE) was assessed 10 minutes after completion of the entire session. All RPE were estimated using a 0–10 scale (41) in view of participants during testing.
Following BT, subjects returned to complete the experimental trials (described below). Experimental trials were counterbalanced in a randomized cross-over design to control for ordering. Each trial was separated by a minimum of 3 days.
Subjects were instructed to abstain from alcohol and caffeine for 24 hours before reporting to the laboratory, hydrate aggressively throughout the day, and consume a 500 ml bottle of water in the hour before arrival. Subjects were also instructed to eat a light meal 2–3 hours before each evening session and record food items and amount for replication in their second trial.
Subjects reported to the laboratory at 1,800 hours to begin treatments. Dehydration was achieved by submersion in a hot (39° C) water bath to elicit a ∼3.5% loss of body mass. Core temperature was continually monitored using a Physitemp RET-1 rectal thermocouple (Physitemp Instruments, Inc., Clifton, NJ, USA) inserted 8 cm beyond rectal sphincter. If core temperature reached or exceeded 38.9° C, or if adverse symptoms occurred, subjects were removed from the hot water bath and allowed to cool for safety before returning to the water. Subjects exited the water and were toweled off and weighed every 30 minutes. Subjects replaced 75% of their fluid losses (water) after each weight measurement (30 minute intervals) before returning to the hot bath. After treatment, subjects were given an additional volume of water to result in a total of 125% fluid replacement of sweat loss. Subjects were given fluids in excess of what was lost to attempt to account for obligatory urine production. A prepackaged standardized evening meal was also provided to participants to control nutritional variability. Subjects were instructed to consume fluid in a metered fashion before returning to the laboratory the following morning, consuming no fluids or food other than what was provided. Subjects collected all urine voids between evening and morning testing sessions. Subjects returned at 0600 hours the following morning and their hydration status was assessed via body mass and USG. Subjects then completed performance trials identical to BT, with the lone exception being that, following warm-up, the subjects estimated their level of recovery using a perceived recovery scale (PRS). The PRS scale was developed by Laurent et al. (25) for subjective estimations of feelings of recovery before exercise.
Subjects reported to the lab at 1,800 hours to begin treatments. Dehydration was achieved by submersion in a hot (39° C) water bath to elicit a ∼3.5% loss of body mass. Subjects were weighed every 30 minutes, and returned to hot water bath until dehydration of ∼3.5% loss of body mass was achieved. Safety precautions for dehydrated trial (DT) were exactly as described for hydrated trial (HT). Subjects were given a standardized meal and a 500 ml bottle of water with instructions to consume it in a metered fashion before returning to the laboratory the following morning, with further instructions to consume no fluids or food other than what was provided. Subjects returned at 0600 hours the following morning and completed performance trials identical to HT.
From pilot work, achieving 3.5% of body loss followed by fluid intake in the prescribed manner was found to elicit 3% hypohydration. Further, this approach allowed a certain amount of fluid to be consumed following dehydration, without 100% fluid restriction, which would be an unlikely approach by athletes. Consideration was given to obligatory urine production.
Mean values for sprint time session 1, sprint time session 2, RPE session 1, and RPE session 2 were compared between DT and HT trials using a 2 (trial) × 10 (sprint) repeated measures analysis of variance. Paired t-tests were used for follow-up analysis per sprint. Mean values for dependent measures including peak heart rate response bout 1 (HRpkb1) and bout 2 (HRpkb2), mean heart rate response (HRavgb1, HRavgb2), AT (agility test) (average of 2 trials), SRPE, RPEb1, RPEb2, perceived recovery status (PRS), USG, thirst rating, and sleep rating were compared between DT and HT trials using t-tests for paired samples. Statistical significance was set at p ≤ 0.05.
Descriptive characteristics for subjects include height 178 ± 6 cm, body mass 87.4 ± 11.6 kg, age 21.9 ± 1.8 years, body fat 7.9 ± 2.6%. Mean times for 40-yd sprints are displayed in Figure 1. Results indicated that the main effect for the first bout of 10 sprints approached significance (p = 0.10) and the main effect for the second bout of 10 sprints was significant (p = 0.03). No significant interactions were found for bout 1 (p = 0.14) or bout 2 (p = 0.17). Follow-up t-tests for the second bout of 10 sprints showed that sprint times were significantly slower for DT (sprints 2, 5, and 6). No significant difference was found for mean AT performance (p = 0.12) (DT = 8.77 ± 0.52 seconds, HT = 8.68 ± 0.56 seconds). Means for HRpk and HRavg are displayed in Table 1. Means for HRpkb1 (p = 0.02), and HRavgb1 (p = 0.05) for DT were significantly higher than HT. Significance between DT and HT for HRpkb2 was p = 0.12 and was p = 0.06 for HRavgb2.
Perceptual and Hydration Measures
Mean RPE for 40-yd sprints are displayed in Figure 2. A main effect was found for RPE for set 1 (p = 0.0001), and follow up t-tests found RPE for DT to be significantly higher for all 10 sprints. The main effect for the second set of 10 sprints approached significance (p = 0.07). No significant interactions were found for bout 1 (p = 0.14) or bout 2 (p = 0.15). Follow up t-tests indicated that DT was significantly higher for sprints 1 and 2, with no significant difference for sprints 3–10. Ratings of perceived exertion RPEb1 (p = 0.01) and RPEb2 (p = 0.04) (Table 1) were significantly higher for DT. Session ratings of perceived exertion (Table 1) approached significance (p = 0.07) for DT. Perceived recovery scale (Table 1) was significantly lower (p = 0.004) for DT than HT, reflecting greater subjective feelings of recovery for HT. Thirst sensation rating was significantly higher (p = 0.0001) for DT (8.33 ± 1.36) than HT (4.20 ± 1.70) (indicative of greater thirst). Although mean values showed greater quality of sleep after HT (vs. DT) the difference was not significant for sleep rating (p = 0.35) (DT: 3.60 ± 1.58, HT: 4.38 ± 1.71). Urine specific gravity was significantly higher (p = 0.0001) for DT (1.028 ± 0.002) than HT (1.014 ± 0.006). Each subject's pre-trial USG for HT was ≤1.020, indicating all subjects were adequately rehydrated. Subjects' pretrial body mass loss percentage was significantly lower (p ≤ 0.0001) for DT (2.9 ± 0.5) than HT (0.73 ± 0.57).
Previous research examined hypohydration effects on sprint race performance, finding no significant effect (44). In that study, level of hypohydration (<3%) and lack of repeated efforts are plausible explanations for no significant difference being found. Although this paradigm is ecologically valid for single bout sports, such as track and field, it does not fully examine the potential deleterious effects of hypohydration on performance during intermittent sprinting sports, such as football. To our knowledge, this study is the first to assess the effects of hypohydration on repeated 40-yd sprint performance.
Frequent practice and competition in extreme weather conditions subject athletes to performing repeated short distance maximal efforts such as sprints in a hypohydrated state. This study attempted to replicate anaerobic performance in such conditions. Though it is unlikely that an athlete, other than those in weight-class sports, would intentionally dehydrate themselves, it is plausible that an athlete would not properly rehydrate between practice sessions, and consequently return for their next practice or competition hypohydrated. Professional, collegiate, and youth athletes have all been shown to frequently arrive for practices and games hypohydrated (9,28,34,39,43).
The foremost variable in the current investigation was 40-yd sprint performance (Mean DT bout 1 = 5.38 ± 0.37, bout 2 = 5.47 ± 0.39; Mean HT bout 1 = 5.35 ± 0.34, bout 2 = 5.42 ± 0.39). As seen in Figure 1, only 3 of 20 (15%) sprints were significantly slower for DT (vs. HT). Based on aggregate analysis, hypohydration had little effect on repeated sprint performance, which agrees with previous research showing no influence of hypohydration on anaerobic performance (6,7,14,17,18,44,45). In the only previous study that used sprint performance as a performance variable, Watson et al. (44) found that diuretic induced dehydration (2.2–2.5%) did not significantly affect single bout sprint performance (50, 200, 400 m). Though both dehydration and sprint protocols differed, statistical analysis based on aggregate data in the current study agrees with the findings of Watson, suggesting that hypohydration has little effect on sprint performance.
However, using only an analysis of aggregate data, de-emphasizes the effect experienced by individual subjects whose sprint capacity was considerably affected. It is plausible that because of interindividual variability, the group means disguise the effects observed in many of the participants (20). That is, if a portion of subjects improve, a portion do not change, and a portion incur impaired performance, to conclude “no effect” based on analysis of means is inaccurate in more cases than not. King et al. (20) validated the efficacy of this theory by demonstrating that after a 12-week exercise program, individual changes in weight were masked when compiled as group means. If only group means were considered, misinterpretation of the results could occur. Consequently, we have opted to provide a more in-depth assessment with emphasis not only on group means but also individual performance (Table 2). Although statistical analysis fails to reflect an overwhelming effect of hypohydration on sprint time based on mean data, further consideration is warranted, particularly regarding individual responses and practical (vs. statistical) significance.
As seen in Table 2, 7 of 12 (58%) subjects had a slower mean sprint time for DT in either the first or second bout of 10 sprints. Conversely, 7 subjects (58%) had a faster mean sprint time for DT in either the first or second bout of 10 sprints. Further, 42% (5 of 12) had a slower mean sprint time of ≥0.1 seconds for at least 1 bout of 10 sprints during DT, and 33% (4 of 12) had a faster sprint time of ≥0.1 seconds, which is of great practical significance (32). In total, 10 of 12 (83%) participants experienced a change (either positive or negative) of ≥0.1 seconds in at least 1 bout of 10 sprints (DT vs. HT). Likewise, while no significant difference was found for AT (DT = 8.77 ± 0.52, HT = 8.68 ± 0.56), 9 of the 12 subjects (75%) experienced differences of ≥0.1 seconds. Further emphasizing the importance of considering individual responses, the subject experiencing the lowest level of hypohydration (2%) experienced the greatest detrimental effects on sprint performance (DT: bout 1 = 5.55, bout 2 = 5.68, HT: bout 1 = 5.25, bout 2 = 5.36 seconds), while the subject experiencing the highest level of hypohydration (3.6%) experienced the greatest beneficial effects on sprint performance (DT: bout 1 = 4.96, bout 2 = 5.06, HT: bout 1 = 5.10, bout 2 = 5.18 seconds). The subjects that experienced slower sprint times are in agreement with previous research showing adverse effects of hypohydration on anaerobic performance (6,14,16,17,21,22,30,45). It has been postulated that hypohydration could potentially improve anaerobic performance in which the subject must accelerate his or her own body mass (i.e., sprints, vertical jump) due to having less mass to propel (7,42,44). Viitasalo et al. (42) found that subjects were able to improve vertical jump height after diuretic-induced weight loss, suggesting this to be an efficacious concept. This theory is a plausible explanation for the improved performance experienced by some subjects in this investigation. This highlights the importance of considering interindividual sensitivity to hypohydration by showing that some individuals were greatly affected by hypohydration, both positively and negatively, whereas others experienced less of an effect. From this investigation, there is clear evidence that some individuals experience meaningful impairment in anaerobic performance after dehydration whereas others appear more tolerant to the effects of hypohydration, during repeated maximal anaerobic efforts, with some benefiting from hypohydration. It cannot be overemphasized that, allowing aggregate analyses to entirely dictate discussion has considerable potential for leading to erroneous conclusions. In the current example, concluding that hypohydration had no impact on sprint performance would be a false statement (83% of observations) more often than it is true. Future work is warranted to identify what individual factors influence tolerance to hypohydration as demonstrated in the current paradigm.
It was hypothesized that any possible negative effects of hypohydration on repeated sprint performance would possibly be seen in the first 10-yd of a 40-yd sprint. Analysis found that 33% (4 of 12) of subjects recorded decreases of ≥0.03 seconds for mean 10-yd time for either the first or second bout of sprints during DT. When mean times for all participants for each of the 20 sprints were examined, only sprint 5 of the first bout, and sprint 2 of the second bout recorded decreases of ≥0.03 seconds. Therefore, hypohydration seems to have had little effect on the first 10-yd of repeated 40-yd sprints.
Ratings of perceived exertion was significantly higher for DT (vs. HT) for all sprints during the first bout of 10 sprints, and the first 2 sprints of the second bout of 10 (Figure 2). Further, RPEb1 and RPEb2 were significantly higher for DT (vs. HT) (Table 1). Elevated RPE during DT further emphasizes the impact of hypohydration on repeated sprint performance for those individuals experiencing slower sprint times, and those who experienced no differences in sprint time. Elevated RPE for those subjects whose sprint times were not faster in DT suggests that the sprints were perceived as more difficult than HT, whereas performance was the same or worse. If performance and RPE do not change concurrently (i.e., faster sprint time = increased RPE and vice versa), it can be concluded that hypohydration affected the perceived feelings of exertion even if minimal changes in performance occurred. Watson et al. (44) found RPE was not significantly different for sprints at 50, 200, and 400 m during a control (50/200: 17 ± 2, 400: 19 ± 1) compared with diuretic-induced dehydration (50/200: 16 ± 2, 400: 19 ± 1) with no significant differences in time. The differences in RPE response between Watson et al. (44) and the current investigation can possibly be explained by the lower level of hypohydration (2.2%) and the use of a single sprint bout used by Watson et al. The observation in the current study, however, is similar to previous studies that used a similar protocol. In 2010, Kraft et al. (21) found that hypohydration increased RPE across a full-body resistance exercise protocol. Subjects performed 6 exercises (3 sets to failure) and completed significantly fewer total repetitions hypohydrated (144.1 ± 26.63) vs. hydrated (169.4 ± 29.1), whereas postset RPE remained unchanged. That is, hypohydration resulted in significantly fewer repetitions, yet this lower volume of work was perceived as equally taxing. A similar study by Kraft et al. (22) found significantly higher RPE during repeated 15-second Wingate tests after a dehydration protocol vs. euhydrated and control trials. Kraft et al. (21,22) used passive (water bath submersion) dehydration, eliminating confounding effects of exercise-induced fatigue (to achieve dehydration). However, the passive dehydration used in these studies was administered on the same day as the performance trials. This approach allows possible residual effects of heat exposure in addition to hypohydration to negatively impact performance during testing. With the potential for heat exposure as well as hypohydration to impact performance, it is difficult to differentiate the independent impact of each. The current study used previous night passive dehydration to allow overnight recovery to lessen the possible effects of acute heat exposure and more effectively isolate the effects of hypohydration. Although sprint performance in a hypohydrated state in the current study reached statistical significance in 3 of 20 sprints (DT vs. HT) and practical significance in other instances, there was a clear negative impact on perceived difficulty across all of the first bout of 10 sprints and the first 2 sprints during the second bout (Figure 2) and perceived difficulty (RPE) relative to each bout of sprints (Table 1).
Significantly elevated HR responses for DT (Table 1) suggest potentially greater physiological strain and impaired recovery between sprints. Although stored adenosine triphospate and the phospho creatine (PCr) system are the primary sources of energy during anaerobic exercise bouts, it is reasonable to suggest that cardiovascular function becomes increasingly more important over a longer duration, as in repeated sprints (10–12,19). A 1-minute active recovery between each sprint would not have allowed enough time for full recovery of the PCr system. This suggests that the aerobic component would increase throughout the duration of sprint bouts, increasing the importance of cardiovascular function (10–12,19). Watson et al. (44) found no difference in HR response (dehydrated vs. control) following sprints at 50, 200, and 400 m. This is possibly explained by the difference in paradigms used by Watson (single bout) and in the current investigation (repeated effort). Kraft et al. (22), who used a similar protocol to the current investigation, found elevated HR response with hypohydration during a full-body resistance exercise protocol. A higher RPE and increased HR response suggest that the performance trials were more difficult for subjects during DT (vs. HT) even in cases when sprint times failed to reach statistical significance based on pre-established alpha level.
Recovery plays an integral role in subsequent athletic performance (4). Previous research has established a close association between perceptual feelings of recovery and sprint performance (8,25). Laurent et al. (25) determined that subjects were able to accurately assess recovery following fatiguing exercise, based on subsequent sprint performance 80% of the time using the PRS scale. In the current study, subjects provided lower PRS scores (reflecting poorer subjective feelings of recovery) for DT and also had impaired subsequent sprint performance 56% of the time. When verbal and numeral markers from the PRS scale (expect weak performance: 0–3, expect average performance: 4–7, expect optimal performance: 8–10) were taken into account, subjects' PRS scores were accurate in predicting performance 50% of the time. The current study was unable to duplicate the accuracy of assessing recovery demonstrated by Laurent et al. (25). However, mean PRS estimations were significantly lower for DT, meaning subjects expected diminished performance (vs. HT). Although sprint times were not significantly different for each sprint (DT vs. HT), RPE and HR responses suggest greater difficulty for DT. That subjects were at times able to accurately predict diminished performance during DT using a subjectively based scale, indicates subjects were sensitive to hypohydration and feel less well-prepared for exercise while failing to replenish adequate fluids after dehydration. This is particularly important in the current paradigm where hypohydration was achieved via hot water bath. This approach eliminated prior exercise as a confounder. Subjective estimations of recovery (PRS values-Table 1) therefore were accounted for principally by hypohydration. The greater thirst sensations for DT (8.33 ± 1.36), HT (4.20 ± 1.70) further indicate subjects were sensitive to fluid imbalances. It is worth noting however, that a myriad of factors tend to mediate perceptual measures with mediating factors themselves often not being mutually exclusive. Previous research suggests the PRS scale is a valid means of assessing perceptual feelings of recovery following repeated sprint bouts (25) and resistance exercise (33). However, to the author's knowledge, the current study is the first to investigate the effectiveness of the PRS scale in predicting performance following hypohydration, and while not definitive, current results offer introductory support to the idea that the PRS scale is sensitive to hypohydration. Additional research is needed to further examine the PRS scale's sensitivity to hypohydration and the potential interindividual variability in perceptual responses relative to recovery.
In a similar way, the possible effects of sleep disturbance may have influenced current results. Whereas no significant difference was found (p = 0.35), subjects provided lower ratings of sleep during DT vs. HT (DT: 3.60 ± 1.58, HT: 4.38 ± 1.71) possibly suggesting that hypohydration disrupts normal sleep patterns, and thus hindered recovery. This notion is supported by Souissi et al. (37), who found that 4 hours of partial sleep deprivation resulted in decreases in anaerobic power during repeated sprints on a cycle ergometer when sleep deprivation occurred at the end of the night but not at the beginning of the night. While it is unknown to what extent sleep was altered in the current study, it is plausible that some subjects possibly experienced significant sleep impairment. If, in fact, sleep disturbances interfered with recovery, this could at least partially account for lower PRS and slower sprint times for DT.
Furthermore, it is notable that the current design evaluated athletes following only a single dehydration session which did not involve exercise. It is entirely plausible that, across a week of practice sessions, hydration status would get progressively worse if day to day efforts toward rehydration are inadequate. Feelings of recovery-PRS would be expected to parallel insufficient fluid replenishment. Because negative impacts of hypohydration were observed where only a single exposure to fluid loss was involved, it is likely that progressive dehydration would result in progressively greater mitigations in anaerobic performance. Similarly, environmental conditions could have potentially played a part in the outcomes. Sprints in the current study took place in a climate controlled indoor court. It is plausible that had sprints taken place in a hot or humid environment, the negative effects of hypohydration may have been amplified. These concepts deserve attention in future investigations.
Though only speculative, a possible explanation for lack of statistical difference in sprint times among some subjects is the possibility of the subjects “pacing” themselves during repeated efforts to offset cumulative fatigue. Pacing is best viewed as an attempt at optimal performance by an individual in which there is a “negotiation” of effort expended based on multiple factors, primarily reaching the end point of exercise without incurring excessive fatigue (27,40). Because fatigue is also a multifactorial issue the negotiation takes into account all factors (many of which may as yet be poorly understood) contributing to fatigue. Because hypohydration is linked to fatigue, subjects possibly negotiated less effort in situations where performance was worse. Hypohydration has been shown to impair pacing ability. Although this took place during aerobic exercise, it is plausible that a similar effect could occur during anaerobic exercise (38). It is also noteworthy that pacing and the central governor theory of fatigue are tightly coupled and this model of fatigue is proposed to have a large subconscious component (27,40). Therefore it is not necessarily proposed that any pacing that potentially occurred was altogether intentional or calculated. It is only proposed as a possibility. Furthermore, other than the direct performance variable, the concept of pacing, particularly if occurring on a subconscious level, is difficult to measure. Subjects were instructed to provide a maximal effort for each sprint, and the number of sprints completed was not revealed to subjects during each trial. Although pacing is a possibility, it would be expected that, if hypohydration impairs anaerobic sprint performance, the “paced” effort would result in systematically slower efforts in a hypohydrated state. Future studies should seek to include a provision to guard against paced efforts in repeated high-intensity efforts.
In conclusion, loss of 3% body mass seems to have little effect on repeated 40-yd sprint performance when only group mean analyses are considered. However, when individual responses were considered, there is clear evidence that most subjects (83%) experienced considerable effects, both positive and negative, from hypohydration during repeated anaerobic efforts. This is further supported by HR response and evaluation of subjective estimations of difficulty-RPE and feelings of recovery-PRS. A limitation of the current study was restriction to a single session with no exercise involved in dehydration. However, it is plausible that with exercise-induced dehydration and progressive hypohydration across several days, the impact of hypohydration on anaerobic exercise would be even more apparent. These concepts warrant further attention.
It is unlikely that athletes, other than those in weight class sports, would intentionally dehydrate themselves. It is highly possible, however, that athletes do not adequately rehydrate between sequential practice sessions and before competition. This especially applies to athletes participating in hot and humid conditions and completing multiple practice sessions in a given day, a paradigm characterized by high risk of heat illness. The current investigation found adverse effects (slower sprint times for some subjects, elevated RPE, elevated HR responses, and diminished feelings of recovery) after only 1 bout of dehydration. It is plausible that these negative effects could be intensified if progressively greater levels of hypohydration were realized over the course of several days because of excessive sweat losses, insufficient fluid replacement or a combination thereof (i.e., preseason football camp). Given the significant detrimental effects on certain individual subjects after an acute bout of dehydration, if prolonged over the course of a week or weeks, these effects could be greatly expounded. Further, the negative effects of hypohydration could potentially be more pronounced when exercising in hot and humid conditions as opposed to the temperate conditions in the present study. Closely monitoring hydration levels by assessing fluid losses during practice and competition by means of pre- and post-weight measurements of athletes is a possible method to be employed by coaches to help ensure proper rehydration. Results from the current study could also be implemented by coaches as part of a tutorial on the importance of hydration for athletes. Information gained from this investigation can be used by coaches and athletes to improve hydration procedures and to avoid diminished performance associated with hypohydration.
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