Journal Logo


Mild Hypohydration Decreases Cycling Performance in the Heat


Author Information
Medicine & Science in Sports & Exercise: September 2013 - Volume 45 - Issue 9 - p 1782-1789
doi: 10.1249/MSS.0b013e31828e1e77
  • Free


It is well documented that fluid deficit exceeding 2% of body mass (bm) can reduce exercise capacity (14) and increase thermoregulatory strain, especially in the heat (20). Even though heart rate increases during hypohydration (−4% bm)-induced hypovolemia, cardiac output cannot be maintained, especially when hyperthermia coexists (21). Thus, hypohydration might degrade aerobic performance more in hot than in temperate conditions (14). Similarly, skin temperature (Tsk) elevation will increase skin blood volume, sacrificing central blood volume (24). This combination of hypohydration and high Tsk can limit the cardiovascular system’s ability to support aerobic metabolism (28). Furthermore, hypohydration (−3% bm) can lower skin blood flow and sweat rate, increasing the risk of hyperthermia when exercise is performed in a hot environment (19). All these physiological responses to hypohydration can lead to the reduction of aerobic capacity (21,30,37) and power output (31), compromising exercise performance.

It is also known that the greater the hypohydration level, the greater the reduction in aerobic exercise performance. It has been demonstrated that levels of hypohydration of −1%, −2%, −3%, and −4% of bm are increasingly detrimental to cardiovascular and thermoregulatory function (28). Likewise, it has been shown that hypohydration at −2.5% of bm reduced exercise time to exhaustion, even in a temperate environment (29). In 1985, Armstrong et al. (1) examined hypohydrated (HYP) runners (−1.6% to −2.1% of bm) using diuretics. Time to completion in 1500, 5000, and 10,000 m increased in all three cases in comparison with their performance in the euhydrated (EUH) state. Ebert et al. (17) studied the effect of hypohydration on cycling hill climbing in the heat. Hypohydration was induced by a 2-h submaximal exercise, with low (0.4 L) or high (2.4 L) fluid intake, causing a −1.3% or −3.6% reduction in bm. After the 2-h exercise, subjects mounted their own bicycles and cycled on a treadmill set at an 8% grade and a speed of 88% of maximal aerobic power output. Time to exhaustion was 5.6 min shorter when subjects were HYP. Similarly, Cheuvront et al. (11) examined the effect of hypohydration (−3% bm) during 30-min cycling in a hot and cold environment. They concluded that work production was significantly lower (−8%) only in the hot environment.

It is evident that during high-intensity cycling in a hot environment, hypohydration greater than 2% reduces aerobic capacity (40). A reduction in aerobic performance has been frequently shown to occur in cases of modest hypohydration (<2% bm) and is exacerbated in hot environmental conditions (7,12). In 1994, Walsh et al. (40) examined cyclists in 32°C with a bm loss of −1.8%. They found the time to exhaustion at 90% of V˙O2max to be lower by 31%. On the other side, McConell et al. (27) noticed a little benefit of water intake during intense cycling exercise in 21°C. Furthermore, Robinson et al. (34) reported that during a 1-h test in which cyclists rode as far as possible in 20°C, fluid intake matching fluid loss offered no performance benefit. On a separate study, cyclists performed a work test of a fixed amount in a hot environment, either EUH or mildly HYP (less than −2% bm). Time to completion was 6.5% shorter in EUH subjects. The researchers reported that cyclists were able to self-select higher workload while EUH, probably because of lower esophageal temperature and RPE (8). Interestingly, though, most of these studies have tested cycling performance only through exercise-to-exhaustion or constant time protocol without using a simulated race-like course.

It is also well documented that a significant percentage of athletes start training or competing inadequately hydrated, based on high urine specific gravity (USG) values (32,38). Even though this technique cannot provide a precise level of hypohydration, we believe that their degree of hypohydration might be around the threshold of thirst. Thirst is usually activated when body water deficit exceeds 1% of bm (18). Thus, considering what was mentioned, we speculate that these HYP athletes might be HYP by approximately −1% of their bm.

In the case of cyclists, even though they can carry their own bottle on the bike, they often neglect to rehydrate during races, that is, when it is essential to keep their hands on the handlebars and there is limited time for fluid intake, for example, cycling up steep hills, riding in an upright position, and fast cycling (4). Currently, there is limited research using true performance outcomes and not exercise time to exhaustion, so the effect of mild hypohydration on performance is not clear.

The aim of the present investigation was to determine the influence of mild (approximately 1% of the bm) hypohydration on both physiological and performance responses during a simulated-hill circuit course on a laboratory computerized cycle ergometer. We hypothesized that mild hypohydration would decrease cycling performance possibly via thermoregulatory and/or cardiovascular mechanisms.



Ten trained, heat-acclimated, male cyclists (age, 30 ± 7 yr; bm, 78.4 ± 9.5 kg; height, 1.80 ± 0.01 m; surface area, 1.97 ± 0.16 m2; V˙O2max, 52.4 ± 3.3 mL·min−1·kg−1; body fat, 12.1% ± 2%; Powermax, 355 ± 29 W) were recruited to participate in the study. All subjects raced in national cycling races for 9 ± 4 yr. The protocol was approved by the university review board, and each participant gave written informed consent. Eligibility criteria for participation in the study included a normal physical examination, as well as the absence of any metabolic, cardiovascular, and renal disease or history of heat stroke.

Preliminary Testing

Body composition

Anthropometric measurements were collected during the first visit to the laboratory. Bm was measured using an electronic scale (model 770; Seca, Hamburg, Germany) and standing height with a wall-mounted stadiometer (model 216, Seca). Subjects wore light clothing and no shoes, and measurements were recorded to the nearest 0.5 kg and 0.5 cm, respectively. Body composition was determined by dual-energy x-ray absorptiometry (model DPX; Lunar, Madison, WI).

Aerobic capacity

Peak oxygen uptake (V˙O2peak) was determined in a thermo-comfortable environment (22°C) using an incremental resistance exercise test on a mechanically braked cycle ergometer (Monark 839E, Sweden). After a 5-min warm-up, subjects cycled at 100 W for 1 min, at which point, cycling power increased by 20 W every minute until volitional exhaustion. During the test, expiratory gases were analyzed breath by breath via an online gas analyzer (MedGraphics Ultima Series, St. Paul, MN). Three of the four following criteria were used to verify the attainment of V˙O2peak: 1) V˙O2plateau with increased workload, 2) respiratory exchange ratio >1.1, 3) HR >90% of predicted maximal value (i.e., 220 − age), and 4) perceived exertion >17. The highest workload attained (Wmax) was defined as follows:

where Wout is the highest workload completed in 2 min, t is the number of seconds that remained in the final uncompleted workload, and ΔW is the increase of workload (3).

Experimental Protocol

All subjects performed, in counterbalanced mode, a simulated-hill circuit performance test with their bikes mounted on a computerized cycle ergometer (CompuTrainer Lab, Racer-Mate, Seattle, WA). The simulated-hill circuit consisted of three sets of 5 km at 50% of Wmax and 5 km of simulated hill (3% grade) at an all-out pace, with a 5-min rest every 5 km. Before the performance test, subjects cycled on a simulated flat course (0% grade) for 1 h with or without water intake to ensure that they started the performance test either EUH or HYP, by 0% ± 0% and −1.0% ± 0.0%, respectively. After each 5-km cycling bout, bm was measured and subjects were rehydrated with water to maintain desired hydration state. Each trial was separated by at least 1 wk but not more than 2 wk. Subjects were asked to abstain from alcohol, caffeine, and training for 24 h before each trial; to maintain the same training; and to abstain from racing between the two experimental trials. The simulated exercise trials were performed on an individual basis, in the morning, at the same time of the day on both visits to avoid diurnal variations (5). Urine samples were collected in dark 1-L containers so that subjects would not be able to get feedback on their urine color and volume. To confuse subjects regarding their hydration state, fluids were provided even in the hypohydration trial after each 5-km trial, whereas they were not able to see their bm during weighing. The day before each trial, all subjects were instructed to consume the same diet consisting of 75% carbohydrate, 15% proteins, and 10% fat and drink plenty of fluids to ensure optimal hydration state before experimental testing. To minimize differences in starting muscle glycogen concentrations, subjects were instructed to record their diet 24 h before their first visit. Their diet records were copied and returned to the participants with instructions to follow the same diet before each subsequent visit. On the day of the test, all volunteers consumed a standardized breakfast rich in carbohydrates (i.e., two slices of sliced bread with two tablespoons of honey).

Hydration state

To achieve the desired initial hydration state, subjects exercised at an intensity eliciting a heart rate of 70%–75% of maximum heart rate (approximately 135 beats·min−1). The simulated exercise was performed indoors, with their bikes mounted on the computerized cycle ergometer, in the heat (31.8°C ± 0.7°C). A fan was placed directly in front of the subjects to provide air flow of 3.2 m·s−1. All participants performed 1 h of exercise (i.e., two sets of 25-min cycling followed by a 5-min rest) with or without drinking water to achieve the desired preexercise hydration status. During the 5-min rest, subjects towel dried themselves, urinated if they had to, and were weighed wearing their cycling shorts only. In the EUH trial, bm loss was replenished by an equal amount of water during the 5-min rest. In the HYP trial, at the end of the 1-h exercise protocol, total bm loss was calculated. Whenever hypohydration exceeded −1%, researchers provided additional water to achieve the desired loss. During the 5-min rest, on both the EUH and HYP trials, subjects ingested water based on their bm loss to avoid greater dehydration. For the both experimental trials, Volvic bottled water (Danone, France) was used.

Performance test

Upon achievement of the desired initial hydration state, blood and urine samples were collected immediately. Subjects had a 20-min rest before the performance test. In both trials, all cyclists used their own bikes, as well as their cycling shoes with cleats and cycling clothes. In both trials, tires were inflated at 110 psi and bikes were checked to ensure proper functioning. No cycling computer was allowed. During the EUH and HYP trials, ambient temperature (Ta) was 32.9°C ± 0.3°C and 33.0°C ± 0.5°C, respectively.

Thermoregulatory measurements

To record gastrointestinal temperature (TGI), subjects were asked to ingest a thermosensitive pill (HQ, Inc., Palmetto, FL) 8–10 h before the test. Skin temperature was also measured using skin thermistors (4000 A; YSI, Dayton, OH) in four locations: 1) the lateral upper arm (TForearm), 2) the chest at a point midway between the acromion process and the nipple (Tchest), 3) midway up the lateral side of the thigh (Tthigh), and 4) the lateral side of the upper calf (Tcalf). Mean weighted skin temperature (Tsk) was calculated using the Ramanathan equation (33):

TGI and Tsk were measured before starting the baseline hydration state, as well as before (Pre), during, and immediately after (Post) the performance bouts. Mean body temperature (Tb) was calculated according to the following equation (13):

Tb was graphed against time (39), allowing computation of the area under the heating curve (the integral °C·min). Total body sweat rate was also calculated from bm loss adjusted for drinking water and urine output (16). In addition, sweat sensitivity (g·°C−1·min−1) was calculated by dividing sweat loss (g) by the area under the heating curve for mean body temperature (°C·min) (2).

Cardiovascular and performance variables

Heart rate data were recorded via a T6c wireless heart rate monitor (Suunto T6c, Oy, Finland) mounted underneath the bike saddle, where subjects were not able to get any feedback. Blood pressure was measured before and after each 5-km climb with an aneroid sphygmomanometer and a stethoscope by an experienced technician. The mean blood pressure (MBP) was defined as follows:

where DP is the diastolic pressure and SP the systolic pressure (22).

Cycling cadence, distance, time, and power data were recorded by the computerized cycle ergometer. Cyclists were able to view on-screen the course profile and distance covered, but they could not get any feedback on their cycling performance. Subjects were also asked to rate both their perceived exertion using a 6–20 Borg scale (RPE) (9) and their thirst using a visual analog scale (35) before and after each 5-km bout. In addition, subjects completed an Environmental Symptoms Questionnaire (ESQ) immediately after the performance tests, but still on their bikes (36).

Blood and urine analysis

Samples were collected upon arrival, as well as before and immediately after each trial. All blood samples were drawn without stasis, after subjects sat for at least 20 min in the heat. Blood samples were analyzed immediately for hematocrit and hemoglobin. The remaining quantities were transferred to serum and plasma tubes and span at 1800g for 12 min at 4°C. Hematocrit was determined in triplicate from whole blood using the microcapillary technique, after centrifugation for 5 min at 9500g. Hemoglobin was measured in duplicate from whole blood with the cyanmethemoglobin technique, using a commercially available kit (Drabkin reagent; Sigma, Saint Louis, MO). Percent change in plasma volume (ΔPV) was calculated using the Dill and Costill equation (15). Whole blood lactate was measured immediately at the end of each 5 km using an Accutrend lactate analyzer (Roche Diagnostics, Mannheim, Germany). USG and total plasma proteins (TPP) were measured using a refractometer (Atago SUR-NE, Tokyo, Japan). The urine color was estimated immediately using the eight-level color scale in a well-lit room, whereas the sample was in a glass tube against a plain white background (23). Urine and plasma osmolality were measured in duplicate via freezing point depression in fresh samples (3D3 Osmometer; Advanced Instruments Inc., Norwood, MA). Serum potassium (K+) and sodium (Na+) concentrations were determined in duplicate from fresh samples (ILyte, Na/K/Li analyzer; Instrumentation Laboratory, Milan, Italy).

Statistical Analysis

Normality of data was graphically explored using percentile plots. All variables are presented as mean ± SD, because they were normally distributed. Differences in the mean values or the distributions of sweat rate, sweat sensitivity, and ESQ between EUH and HYP were assessed using Student’s paired t-tests. Generalized estimating equations were fitted to evaluate differences between the two experimental trials (EUH and HYP), as well as across time points. For the dependent variables (i.e., cycling speed, power output, cycling cadence, heart rate, MBP, lactate, thirst, RPE, Tc, Tb, Tsk, bm, ΔBW, Osmu, USG, urine color, Osmp [Na+]p, [K+]p, TPP, and ΔPV), the normal distribution was used to fit generalized estimating equation, with the identity as the link function. The unstructured formation of the correlation matrix was used after comparing various scenarios, using the corresponding QIC (quasi-likelihood under the independence criterion for model’s goodness of fit). Independent variables were time (baseline, Pre, Post) and trial (EUH, HYP) or distance (1–5) and trial (EUH, HYP). First-order interactions between time and trial or between distance and trial were also applied. Post hoc analysis for comparing mean values between trials across time points, as well as different time points, was applied by using the sequential Bonferroni correction rule adjusting for the inflation of type I error due to multiple comparisons. All statistical analyses were carried out with SPSS 19 for Windows (IBM SPSS, Chicago, IL). A value of P ≤ 0.05 was regarded as statistically significant.



In the HYP trial, subjects started the simulated-hill cycling test with a water deficit of −0.8 ± 0.1 kg (−1.0% ± 0.0% bm), whereas in the EUH trial, they started without any water deficit (0.0% ± 0.0%). As a response to the exercise, subjects finished the exercise trial HYP by −0.5 ± 0.2 kg (−0.6% ± 0.1% bm) and −1.4 ± 0.2 kg (−1.7% ± 0.1% bm) for the EUH and HYP trial, respectively (P < 0.001, Table 1).

Blood and urine parameters during the experiment (N = 10).

Cycling performance

Cycling speed during the first, second, and third bout of the 5 km at an all-out pace was greater in the EUH (28.1 ± 3.1, 27.7 ± 3.3, and 27 ± 3.6 km·h−1) than that in the HYP trial (27 ± 2.9, 26.1 ± 3.7, and 25.9 ± 3.6 km·h−1), by +3.9% ± 2.8%, +5.7% ± 6.3%, and +4.2% ± 4.2%; respectively (P < 0.05). Mean speed was faster by +4.6 %± 4.6% in the EUH (27.6 ± 3.2 km·h−1) than that in the HYP trial (26.3 ± 3.4 km·h−1, P < 0.05, Fig. 1), whereas all subjects performed better in EUH versus HYP (range, +0.1 to +2.3 km·h−1, Fig. 2). The cycling speed during the simulated-hill sessions for the EUH and HYP trials is depicted in Figure 1. The higher speed was the result of greater power output during the first, second, and third bout of each 5 km at an all-out pace during the EUH trial (284 ± 55, 266 ± 53, and 254 ± 58 W) versus the HYP trial (271 ± 56, 250 ± 61, and 240 ± 57 W; P < 0.05, Fig. 3). Cycling cadence at the first, second, and third 5 km at an all-out pace was not different between the EUH (87 ± 8, 85 ± 8, and 86 ± 8 rpm) and the HYP trial (88 ± 9, 84 ± 10, and 83 ± 10 rpm).

Mean cycling speed of each simulated-hill session (mean ± SD). *Statistically significant differences, P ≤ 0.05 between trials at same time point.
Individual performance data in EUH and HYP trials. Each line represents a different individual subject.
Mean power output of each kilometer during simulated-hill bouts (mean ± SD). *Statistically significant differences, P ≤ 0.05 between trials at same time point.

Thermoregulatory markers

TGI, Tsk, and Tb immediately after the last simulated-hill session were greater in the HYP than that in the EUH trial (P < 0.05, Fig. 4). TGI at the end of the first, second, and third 5-km all-out-pace bouts were greater in the HYP than that in the EUH trial, indicating a greater thermal load (P < 0.05, Fig. 5). Whole body sweat rate was similar in both trials (HYP, 0.29 ± 0.1 mg·m−2·s−1 or 2.23 ± 0.52 L·h−1; EUH, 0.26 ± 0.1 mg·m−2·s−1 or 2.01 ± 0.76 L·h−1, P > 0.05). Sweat sensitivity during the circuit was lower in the HYP (67 ± 19 g·°C−1·min−1) than that in the EUH trial (115 ± 58 g·°C−1·min−1, P = 0.011).

Gastrointestinal temperature (T GI), mean body temperature (T b), and skin temperature (T sk) at baseline, precircuit, and immediately postcircuit course. *Statistically significant differences, P ≤ 0.05 between trials at same time point.
Gastrointestinal temperature (T GI) of each kilometer during simulated-hill bouts (mean ± SD). *Statistically significant differences, P ≤ 0.05 between trials at same time point.

MBP, lactate, and heart rate

MBP at the end of the first, second, and third of the three at an all-out-pace bouts was 126 ± 20, 122 ± 24, and 131 ± 22 mm Hg in the HYP trial, whereas in the EUH trial, it was 117 ± 14, 120 ± 14, and 122 ± 8 mm Hg (P > 0.05). At the end of each simulated-hill bout, blood lactate accumulation in the HYP trial was 4.6 ± 0.6, 4.2 ± 0.8, and 4.7 ± 1.1 mmol·L−1, whereas in the EUH trial, it was 5.4 ± 1.6, 5.0 ± 1.3, and 5.1 ± 1.5 mmol·L−1 (P > 0.05). Heart rate during the three at an all-out-pace bouts was near maximal (90% ± 8%) and did not differ significantly between trials (HYP: 169 ± 15, 169 ± 15, and 170 ± 15 beats·min−1; EUH: 167 ± 15, 167 ± 15, and 169 ± 15 beats·min−1, P > 0.05).

Thirst, ESQ, and RPE

At the end of each simulated-hill bout, thirst did not differ between the HYP (76 ± 18, 67 ± 23, and 78 ± 18 mm) and the EUH (56 ± 24, 45 ± 22, and 49 ± 27 mm) trial (P > 0.05). Similarly, no differences were found between the trials for the cumulative score on the Environmental Symptom Questionnaire (EUH, 27 ± 6; HYP, 29 ± 2; P > 0.05). Lastly, at the end of each simulated-hill bout, RPE was similar and near maximal in both the HYP (17.0 ± 1.0, 17.0 ± 1.0, and 19.0 ± 1.0) and the EUH trial (17.0 ± 1.0, 17.0 ± 1.0, and 18.0 ± 1.0; P > 0.05).


In the present study, we examined the effect of mild hypohydration (−1% of bm) in a simulated-hill circuit race trial on a laboratory cycling ergometer in the heat. Our data indicated that cyclists during the EUH trial performed better in all three bouts of 5-km hill cycling, as indicated by both time to completion and power output. We found that by the end of the race, gastrointestinal temperature, mean body temperature, and skin temperature in the HYP trial were greater than that in the EUH trial, thus indicating that even a small degree of hypohydration could induce greater thermoregulatory strain. The fact that sweating responses were similar between the trials, even though internal and skin temperatures were greater in the HYP trial, indicated that sweat sensitivity deteriorated due to water deficit. Our data indicated that even −1% hypohydration induced significantly lower sweat sensitivity and emphasized the critical modulatory role of even mild hypohydration on thermoregulatory responses. That is, even though EUH athletes were able to sustain higher power output and speed, they did not experience greater hyperthermia due to greater metabolic heat production, as expected on the basis of the literature (26).

Walsh et al. (40) found that the cycling performance in 32°C to exhaustion at 90% of V˙O2max decreased 31% when subjects started cycling HYP by −1.8%. Similarly, Below et al. (8) showed that cycling performance declined 6.5% when subjects were HYP less than −2%. Likewise, in 2010, Casa et al. (10) found that during trail running in the heat, subjects in the HYP trial had 0.22°C greater gastrointestinal temperature for every 1% of bm lost, when compared with the EUH trial. Furthermore, it has been suggested that hypohydration can play a modulating role on the degree of exercise-induced hyperthermia (28).

Armstrong et al. (2) examined thermoregulatory responses during a fixed 90-min treadmill walk in the heat where subjects were EUH or HYP by −3.9%, with or without ad libitum water intake during exercise. They found that both sweating and sweat sensitivity were reduced in the HYP trial when subjects did not drink fluids during exercise, thus showing that hypohydration amplifies thermoregulatory responses. Their data indicated that lower sweat sensitivity was associated with the degree of hypohydration and changes in plasma osmolality.

Recent studies have suggested that increased skin temperature could independently influence the hypohydration-related decrement of exercise performance in the heat. In this regard, Kenefick et al. (24) examined the interaction between four different environmental and hypohydration conditions during a 30-min (50% V˙O2max) cycling exercise, followed by a 15-min time trial. They found that hypohydration and hyperthermia significantly contribute to impaired performance, whereas Tsk can play a modulating role in the decline of exercise performance. In our study, although the difference in core temperature between the EUH and HYP trials was small, skin temperature was more than 1.5°C greater in the HYP trial, supporting the notion that skin hyperthermia might modulate the decline in performance.

In a recent study, Bardis et al. (6) examined the effects of mild hypohydration (−1% bm) during an outdoor cycling climbing trial. Their data indicated that mild hypohydration decreased cycling performance in the 5-km outdoor hill climbing course, probably because of greater heat strain and perceived exertion. Similar to the present study, greater Tc and lower sweat sensitivity were evident during mild hypohydration.

Heart rate responses during the 5-km cycling test did not differ between trials, even though exercise induced near maximal heart rate in both trials. Although we did not measure cardiac output during exercise, we speculated that both stroke volume and cardiac output might have been compromised as a response to hypohydration. This response has been well documented with a greater degree of hypohydration by others (21). For instance, Logan-Sprenger et al. (25) studied nine females during 120-min cycling exercise, with or without fluid replacement to match losses. They concluded that 1% of bm hypohydration induced considerable cardiovascular, thermoregulatory, and metabolic strain toward greater carbohydrate oxidation. More specifically, the observed increase in muscle glycogenolysis appeared to be primarily the result of a rise in core and muscle temperature.

Another potential factor that could explain the performance improvement observed in the present study during the EUH trial could have been the psychological effect of drinking during the preliminary 1-h exercise. Moreover, pharyngeal receptor activation via drinking (3) could have influenced motivation and/or performance outcome. However, the researchers made an effort to confuse the subjects by drinking during the performance test, not being able to see their bm or urine color and volume. Lastly, the similar thirst rating in the two trials was indicative that the subjects were not clear about whether their hydration state had been altered.

In summary, mild hypohydration induced greater skin and gastrointestinal and body temperature but a similar sweating response to the EUH state while exercising at lower intensities. Simulated cycling all-out performance was impaired by mild hypohydration potentially via increased thermoregulatory strain and reduced stroke volume and cardiac output (not measured in the present study) as supported by other studies (20,21) during similar performance trials in hot environments. Thus, it is likely that thermal and cardiovascular strain acted jointly to reduce total power output during HYP. Further research is required to determine the effect of mild hypohydration on cycling performance in the field (i.e., during actual competition).

No funding was received for this study. No author conflict of interest exists.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.


1. Armstrong LE, Costill DL, Fink WJ. Influence of diuretic-induced dehydration on competitive running performance. Med Sci Sports Exerc. 1985; 17 (4): 456–61.
2. Armstrong LE, Maresh CM, Gabaree CV, et al. Thermal and circulatory responses during exercise: effects of hypohydration, dehydration, and water intake. J Appl Physiol. 1997; 82 (6): 2028–35.
3. Arnaoutis G, Kavouras SA, Christaki I, Sidossis LS. Water ingestion improves performance compared with mouth rinse in dehydrated subjects. Med Sci Sports Exerc. 2012; 44 (1): 175–9.
4. Atkinson G, Davison R, Jeukendrup A, Passfield L. Science and cycling: current knowledge and future directions for research. J Sports Sci. 2003; 21 (9): 767–87.
5. Atkinson G, Todd C, Reilly T, Waterhouse J. Diurnal variation in cycling performance: influence of warm-up. J Sports Sci. 2005; 23 (3): 321–9.
6. Bardis C, Arnaoutis G, Panagiotakos D, Sidossis L, Kavouras SA. Mild dehydration decreases cycling performance during 5 km hill climbing. J Athl Train. 2013 (in press).
7. Barr SI. Effects of dehydration on exercise performance. Can J Appl Physiol. 1999; 24 (2): 164–72.
8. Below PR, Mora-Rodriguez R, Gonzalez-Alonso J, Coyle EF. Fluid and carbohydrate ingestion independently improve performance during 1 h of intense exercise. Med Sci Sports Exerc. 1995; 27 (2): 200–10.
9. Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982; 14 (5): 377–81.
10. Casa DJ, Stearns RL, Lopez RM, et al. Influence of hydration on physiological function and performance during trail running in the heat. J Athl Train. 2010; 45 (2): 147–56.
11. Cheuvront SN, Carter R 3rd, Castellani JW, Sawka MN. Hypohydration impairs endurance exercise performance in temperate but not cold air. J Appl Physiol. 2005; 99 (5): 1972–6.
12. Cheuvront SN, Carter R 3rd, Sawka MN. Fluid balance and endurance exercise performance. Curr Sports Med Rep. 2003; 2 (4): 202–8.
13. Colin J, Timbal J, Houdas Y, Boutelier C, Guieu JD. Computation of mean body temperature from rectal and skin temperatures. J Appl Physiol. 1971; 31 (3): 484–9.
14. Coyle EF. Fluid and fuel intake during exercise. J Sports Sci. 2004; 22 (1): 39–55.
15. Dill DB, Costill DL. Calculation of percentage changes in volumes of blood, plasma, and red cells in dehydration. J Appl Physiol. 1974; 37 (2): 247–8.
16. Bois Du D, Bois Du E. A formula to estimate the approximate surface area if height and weight be known. Arch Intern Med. 1916; 17: 863–71.
17. Ebert TR, Martin DT, Bullock N, et al. Influence of hydration status on thermoregulation and cycling hill climbing. Med Sci Sports Exerc. 2007; 39 (2): 323–9.
18. Fitzsimons JT. The physiological basis of thirst. Kidney Int. 1976; 10 (1): 3–11.
19. Fortney SM, Wenger CB, Bove JR, Nadel ER. Effect of hyperosmolality on control of blood flow and sweating. J Appl Physiol. 1984; 57 (6): 1688–95.
20. Gonzalez-Alonso J, Mora-Rodriguez R, Below PR, Coyle EF. Dehydration reduces cardiac output and increases systemic and cutaneous vascular resistance during exercise. J Appl Physiol. 1995; 79 (5): 1487–96.
21. Gonzalez-Alonso J, Mora-Rodriguez R, Below PR, Coyle EF. Dehydration markedly impairs cardiovascular function in hyperthermic endurance athletes during exercise. J Appl Physiol. 1997; 82 (4): 1229–36.
22. Gonzalez-Alonso J, Mora-Rodriguez R, Coyle EF. Supine exercise restores arterial blood pressure and skin blood flow despite dehydration and hyperthermia. Am J Physiol. 1999; 277 (2 Pt 2): H576–83.
23. Kavouras SA. Assessing hydration status. Curr Opin Clin Nutr Metab Care. 2002; 5 (5): 519–24.
24. Kenefick RW, Cheuvront SN, Palombo LJ, Ely BR, Sawka MN. Skin temperature modifies the impact of hypohydration on aerobic performance. J Appl Physiol. 2010; 109 (1): 79–86.
25. Logan-Sprenger HM, Heigenhauser GJ, Killian KJ, Spriet LL. Effects of dehydration during cycling on skeletal muscle metabolism in females. Med Sci Sports Exerc. 2012; 44 (10): 1949–57.
26. Maughan RJ, Leiper JB, Thompson J. Rectal temperature after marathon running. Br J Sports Med. 1985; 19 (4): 192–5.
27. McConell GK, Stephens TJ, Canny BJ. Fluid ingestion does not influence intense 1-h exercise performance in a mild environment. Med Sci Sports Exerc. 1999; 31 (3): 386–92.
28. Montain SJ, Coyle EF. Influence of graded dehydration on hyperthermia and cardiovascular drift during exercise. J Appl Physiol. 1992; 73 (4): 1340–50.
29. Nielsen B, Kubica A, Bonnesen A, Rasmussen I, Stoklosa J, Wilk B. Physical work capacity after dehydration and hyperthermia. Scand J Sports Sci. 1981; 3 (1): 2–10.
30. Nybo L, Jensen T, Nielsen B, Gonzalez-Alonso J. Effects of marked hyperthermia with and without dehydration on VO(2) kinetics during intense exercise. J Appl Physiol. 2001; 90 (3): 1057–64.
31. Nybo L, Nielsen B. Hyperthermia and central fatigue during prolonged exercise in humans. J Appl Physiol. 2001; 91 (3): 1055–60.
32. Osterberg KL, Horswill CA, Baker LB. Pregame urine specific gravity and fluid intake by National Basketball Association players during competition. J Athl Train. 2009; 44 (1): 53–7.
33. Ramanathan NL. A new weighting system for mean surface temperature of the human body. J Appl Physiol. 1964; 19: 531–3.
34. Robinson TA, Hawley JA, Palmer GS, et al. Water ingestion does not improve 1-h cycling performance in moderate ambient temperatures. Eur J Appl Physiol Occup Physiol. 1995; 71 (2–3): 153–60.
35. Rolls BJ, Wood RJ, Rolls ET, Lind H, Lind W, Ledingham JG. Thirst following water deprivation in humans. Am J Physiol. 1980; 239 (5): R476–82.
36. Sampson JB, Kobrick JL. The environmental symptoms questionnaire: revisions and new filed data. Aviat Space Environ Med. 1980; 51 (9 pt 1): 872–7.
37. Sawka MN, Burke LM, Eichner ER, Maughan RJ, Montain SJ, Stachenfeld NS. American College of Sports Medicine Position Stand: exercise and fluid replacement. Med Sci Sports Exerc. 2007; 39 (2): 377–90.
38. Stover EA, Petrie HJ, Passe D, Horswill CA, Murray B, Wildman R. Urine specific gravity in exercisers prior to physical training. Appl Physiol Nutr Metab. 2006; 31 (3): 320–7.
39. Takamata A, Mack GW, Gillen CM, Jozsi AC, Nadel ER. Osmoregulatory modulation of thermal sweating in humans: reflex effects of drinking. Am J Physiol. 1995; 268 (2 pt 2): R414–22.
40. Walsh RM, Noakes TD, Hawley JA, Dennis SC. Impaired high-intensity cycling performance time at low levels of dehydration. Int J Sports Med. 1994; 15 (7): 392–8.


© 2013 American College of Sports Medicine