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SPORTSCIENCE |
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Original Research: Training |
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Effect of Training in the Heat on Cycling Performance at Normal Temperature
Joanna P
Morrisona, Will G Hopkinsb, Gordon G Sleivertc
Sportscience
6, sportsci.org/jour/0201/jpm.htm, 2002 (4278 words)
aExercise Science, University of Iowa, Iowa City, Iowa 5224; bSports
Studies, Auckland University of Technology, Auckland, New Zealand 1020. cKinesiology, University of New
Brunswick, Fredericton, New Brunswick, Canada E3B 5A3. Email. Reviewed by David T Martin, Physiology, Australian Institute of Sport,
Canberra ACT, Australia 2616.
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In a randomized crossover study of the effect of adaptation to exercise in the heat on endurance performance at room temperature, nine highly-trained male cyclists performed a simulated 40-km time trial at 20°C on an air-braked ergometer, preceded by 7 d of self-selected training on a cycle ergometer in the heat (90 min.d-1 at 37°C and 50% humidity) or 7 d of control training (90 min.d-1 at 20°C and 50% humidity) at similar perceived effort. A 2-wk washout period separated these acclimation periods, during which athletes replicated training recorded in the two weeks before their first acclimation period. The measures of acclimation were changes in heart rate, core temperature, whole-body sweat rate, and perceived exertion during a ride at fixed intensity on the first and last day of each acclimation period; an additional measure was the hematocrit on the day after each acclimation period. The observed mean effect of training in the heat on performance time in the 40-km time trial was 0.4% (95% confidence interval -1.5 to 2.2%). The chances that the true effect on performance is beneficial/trivial/harmful are 35/54/11%. Only one-third of the cyclists showed substantial changes in perceived exertion and heart rate consistent with heat acclimation, and the individual differences in heat acclimation did not relate consistently to performance in the time trial. In conclusion, moderately intense training in the heat produced only modest variable heat acclimation and only the possibility of a worthwhile enhancement of performance. Highly trained individuals probably need a more marked stimulus to achieve substantial heat adaptation and effects on performance. KEYWORDS: athlete, endurance, ergogenic, heat acclimation. Reprint pdf · Reprint doc · Reference list |
Individual
Differences in Acclimation and Performance
Training in the heat provides an opportunity to adapt to increased
environmental temperature before performing in a thermally stressful
environment. After heat acclimation
athletes have a lower core temperature at rest (Buono et al., 1998) and during exercise in the heat (Sawka et al., 1983; Armstrong and Kenney,
1993). An increase
in sweat rate (Nadel et al., 1974), a decrease in sodium content of sweat (Kirby and Convertino, 1986), a redistribution of sweating (Kirby and Convertino, 1986), and a lowering of the threshold temperature for
initiating the sweating response (Williams
et al., 1967) have also been observed after heat acclimation. There
is also an expansion of plasma volume (Senay
et al., 1976; Kirby and Convertino, 1986), which allows for increased blood flow to the skin to
dissipate heat without seriously compromising blood flow to muscles. Some of these adaptations probably account
for the enhancement of physical performance in the heat that occurs with heat
acclimation (Young et al., 1985;
Kirwan et al., 1987; Armstrong and Maresh, 1991). Whether
these adaptations enhance performance at normal temperature is unknown. The purpose of this study was therefore to
determine if adaptations gained through heat acclimation enhance 40-km cycle
performance in a thermoneutral environment.
Ten
highly-trained males volunteered for this study. The subjects were cyclists, triathletes, and duathletes who had
been racing in the top open men’s racing grade for the previous year. Age, height, and weight were 25 ± 6 y, 180 ± 5 cm, and 75 ± 7 kg respectively (mean ± SD). Maximum oxygen uptake (VO2max)
was 64.5 ± 3.1 ml·kg-1·min-1,
as determined in an incremental cycling test (150 W initial load, 50 W·min-1
increments) with respiratory equipment and end-point criteria as previously
described (Caird et al., 1999). The
University of Otago Ethics Committee gave ethical approval for this project,
and all subjects provided written informed consent. One subject’s data were discarded due to non-compliance with the
training requirements of the study.
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Figure 1. Experimental design. Not shown is the standard exercise bout subjects performed on the first and last day of the heat and neutral acclimation periods. |
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The design was a randomized crossover.
Figure 1 shows the schedule of training and testing. Subjects completed a diary of their training
during the two weeks before acclimation.
This normal training was performed outdoors in cool spring weather. During the two-week wash-out between
acclimation periods subjects completed the same training from the first two
weeks of recorded training. This
training was also recorded and training diaries were evaluated qualitatively for any differences in
training between the two training periods.
Acclimation Training
Acclimation
training was conducted in an environmental chamber set at 37°C and 50% humidity for training in the heat, or
20°C and 50% humidity for training at normal
temperature. On Day 1 and Day 7 of each
acclimation period all athletes cycled on their own bicycles placed on an
air-braked ergometer (Kingcycle Ltd, High Wycombe, Buckinghamshire, UK) for 90
min at 45% of the subject’s maximum power output attained during the VO2max
test. For the remaining five days
subjects exercised on their own bicycles placed on an air-braked training
device (CS-1000 Cyclosimulator, Cateye, Osaka, Japan). Each exercise session consisted of 90 min of
self-selected cycle training. The
acclimation sessions replaced the athletes’ training during the seven-day
acclimation period. Heart rate was
recorded telemetrically every five minutes and at the end of every work
interval (Polar Electro, Kemplele, Finland).
Core temperature was measured using disposable thermisters (Model 400,
Mallinckrodt Medical, St Louis, MO) inserted 11 cm beyond the anal
sphincter. Rectal temperature was
sampled every 30 s on a data logger (1200 Series, Grant Instruments, Cambridge,
UK) and recorded manually every 5 min.
Perceived exertion rated on a 10 point scale (Noble et al., 1983) was recorded every 5 min and at the end of every work
interval. Whole body sweat rate (ml·h-1)
was calculated using measurements of pre- and post-exercise body mass accurate
to 0.01 kg (Wedderburn Scales, Teraoka Seiko, Tokyo, Japan). Body mass changes were corrected for fluid
consumption, but respiratory water loss and muscle glycogen loss were assumed
to be negligible. Subjects were
instructed to dry all sweat off their body and from their hair before
post-exercise mass was recorded. Work
to rest ratios during interval training were also recorded.
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Table 1. Descriptive statistics for the self-selected 90-min sessions of training in the heat and training at neutral temperature. |
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Heat |
Neutral |
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Overall session |
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Heart rate (min-1) |
133 ± 5 |
127 ± 7 |
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Core temperature (°C) |
38.1 ± 0.3 |
38.0 ± 0.4 |
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Perceived effort |
2.9 ± 0.5 |
3.0 ± 0.4 |
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Interval training within the session |
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Duration (min) |
15 ± 13 |
12 ± 11 |
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Heart rate |
174 ± 9 |
175 ± 10 |
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Perceived effort |
7.4 ± 1.0 |
7.3 ± 1.1 |
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Data are mean ± SD for all subjects for the self-selected training sessions on Days 2 to 6. The training bouts on Days 1 and 7 were performed at a fixed workload (see Figure 2). |
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To reproduce training sessions in the second acclimation period each athlete
was instructed to cycle at an intensity to maintain the same perceived exertion
for the same duration as that in the first acclimation period (Table 1). When intervals were performed the athlete
attempted to perform the same work and rest intervals at the same perceived
exertion as in the corresponding training session from the first acclimation
period. Subjects were encouraged to drink either water or a carbohydrate drink
ad libitum during all training sessions.
On the last day of acclimation subjects were instructed to drink enough
fluid so their urine was clear, and to avoid caffeine and alcohol between the
last training session and the hematocrit measurement. A fingerprick blood sample was collected from the subject's index
finger into heparinised capillary tubes the day after completion of acclimation
training for hematocrit determination to assess the effect of the training
intervention on plasma volume.
All
subjects completed three 40-km cycling time trials. The first time trial was for familiarization; the other two were
analyzed for the effect of heat acclimation.
Subjects cycled on their own bikes placed on the Kingcycle ergometer in
an environmental chamber. A
pre-exercise blood sample, taken from the subject's left index finger, was
collected into heparinised capillary tubes after the subject had rested quietly
on his bicycle for 5 min in his normal cycling position without cycling. Core temperature was also recorded at this
point via a rectal thermister. The
Kingcycle was then calibrated (Palmer
et al., 1996) and all participants performed a 10-min self-paced
warm-up before starting the time trial.
To mimic a competitive event, subjects were allowed to view a display of
speed, elapsed time, and distance covered.
Immediately upon finishing the time trial a post-exercise fingerprick
blood sample was obtained from the left index finger. Three to five capillary tubes of blood were collected for
determination of hematocrit; the mean hematocrit was used in the comparison of
pre- and post-exercise hematocrit to determine plasma volume shifts during the
time trial (Greenleaf et al., 1979). Subjects
were allowed to consume water ad libitum during the time trial. Whole body sweat rate (ml·h-1)
was calculated from body mass measured before and after the time trial
(accurate to 0.01kg) and corrected for fluid consumption as previously
described. Core temperature, arterial
oxygen saturation (Criticare Pulse Oximeter, Model 504US-504USP, Criticare
Systems, Milwaukee, WI), and heart rate were recorded at 5-km intervals during
the time trial. Mean power output for
the time trial was
obtained from the Kingcycle.
Statistical Analyses
Changes in
perceived exertion and physiological variables were used as measures of
acclimation. Changes in perceived
exertion and heart rate were calculated by subtracting the mean value over the
last 30 min of exercise during the standard exercise bout on Day 1 from that on
Day 7, then subtracting the resulting neutral acclimation value from the heat
acclimation value. Change in core
temperature was calculated in a similar fashion, but the subject's resting core
temperature (measured immediately before the standard exercise bout) was first
subtracted from the subject's mean value over the last 30 min of the bout. Change in sweat rate was calculated by subtracting
the sweat rate over the whole exercise bout on Day 1 from that on Day 7, then
subtracting the resulting neutral acclimation value from the heat acclimation
value. Change in hematocrit was the
value after heat acclimation minus the value after neutral acclimation. Pearson correlation coefficients between
measures of acclimation were used to determine which measures were mutually
most consistent.
To
determine if heat acclimation changed the physiology of the time trial
performance at room temperature, data from the performance trials were used to
create difference scores for the mean change in core temperature, arterial
oxygen saturation, plasma volume shifts, and heart rate between the heat
condition and the neutral condition. In
all cases data for the neutral condition were subtracted from those of the heat
condition.
We
quantified the effect of acclimation on time-trial performance with a
repeated-measures analysis using Proc Mixed in the Statistical Analysis System
(Version 6.12, SAS Institute, Cary NC); to account for learning effects we
included order of treatment as a within-subject effect. Analysis of log-transformed mean power
output and performance time yielded percentage changes. We also used repeated measures analyses of
covariance to quantify the effect of individual differences in acclimation
(change in heart rate, perceived exertion, and hematocrit) on performance.
Mean ±
standard deviation are used throughout for descriptive statistics. Precision of estimates of outcome statistics
is shown as the 95% confidence interval (CI), which defines the likely range of
the true value in the population. We used
a spreadsheet (Hopkins, 2002) to calculate probabilities of practical significance
for the change in performance following heat acclimation. The calculation requires a value for the
smallest worthwhile change in performance, which is ~0.5 of an elite athlete's
variation in performance time from race to race (Hopkins et al., 1999). For elite cyclists competing in time trials lasting
~1 h, this variation is 1.3% (CD Paton and WG Hopkins, unpublished
observations), so the smallest worthwhile performance change is ~0.6%.
Relative to
training at normal temperature, training in the heat caused substantial
reductions in perceived exertion (1.5 units on the 10-point scale, CI = 0.3 to
2.8), core temperature (0.50 °C, CI = -0.16 to 1.17 °C), and heart rate (8.5 min-1, CI =
-2.5 to 19.5 min-1) during the standard exercise bout in the heat
relative to the same exercise in the thermoneutral condition (Figure 2). Training in the heat also caused a slight
decrease in sweat rate (77 ml·h-1, CI = -120 to 280 ml·h-1)
in the standard exercise bout, a modest decrease in hematocrit the day before
the performance test (-0.8%, CI = -2.0 to 0.4%), and a slight increase in
resting core temperature before the performance test (0.24 °C, CI = -0.09 to 0.57 °C).
Change in
heart rate and change in perceived exertion were the most closely related of
the measures of acclimation (r = 0.93, CI = 0.70 to 0.99). Only three subjects
showed substantial changes in both these variables consistent with acclimation
(Figure 3). Change in core temperature
had only weak correlations with changes in heart rate (r = 0.15, CI = -0.57 to
0.74), perceived exertion (r = -0.30, CI = -0.80 to 0.45), and sweat rate (r =
0.33, CI = -0.43 to 0.82). There was
little relationship between change in sweat rate and changes in resting core
temperature, heart rate and perceived exertion (r = -0.36, -0.15, -0.01). Change in hematocrit had a strong
correlation with change in sweat rate (r = -0.81, CI = -0.96 to -0.32) but
small-moderate correlations with change in perceived exertion, heart rate, and
core temperature (r = -0.14, -0.32, -0.53).
Training in
the heat resulted in a slight enhancement of time-trial time from 54:36 ± 2:50 (min:s) before to 54:20 ± 3:30 after heat acclimation. After adjustment
for learning effects the enhancement was 0.4% (CI = -1.5 to 2.2%). The chances that the true effect on
performance is beneficial/trivial/harmful are 35/54/11%. Mean power output in
the time trial was 310 ± 40 W before heat acclimation and
315 ± 50 W after heat, an increase of
0.7% (CI = -4.0 to 5.3%).
Training in
the heat had minimal effects on plasma-volume shift, heart rate, core
temperature, and sweat rate in the time trial (data not shown). There was also a minimal effect on arterial
oxygen saturation, but change in this variable correlated strongly with change
in hematocrit before the time trials (r
= 0.87, CI = 0.49 to 0.97) and change in sweat rate during the acclimation
rides (r = -0.81, CI = 0.32 to 0.96). Changes in other variables measured during
the time trial had generally trivial correlations with measures of acclimation
(data not shown).
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Figure 2. Heart rate, change in core temperature, and perceived exertion during 90 min of cycling at 45% of VO2max in the heat on Day 1 and Day 7 of the heat acclimation period. Data are means; error bars are representative standard deviations. |
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A
substantial learning effect between the first and second time trials was
evident in performance time (1.7%, CI = -3.5 to 0.2%) and mean power output
(4.3%, CI = -0.3 to 8.9%). The residual
coefficient of variation in performance time was 1.6%, after learning and
treatment effects were accounted for in the statistical model.
Individual Differences in Acclimation and Performance
Changes in heart rate, perceived exertion, and hematocrit were included
in separate analyses of covariance to determine the extent to which individual
differences in acclimation predicted individual differences in
performance. For every 10 min-1
drop in heart rate after training in the heat, mean power declined by
1.3% (CI = -3.0% to 5.9%). Similarly,
for every unit decrease in perceived exertion, mean power also declined by 1.1%
(CI = -2.7 to 5.0%). Figure 3 shows
graphically how acclimation of heart rate and perceived exertion were
associated with these trends towards impairment of performance. In contrast, for every percent decrease in
hematocrit mean power improved by 1.0% (CI = -2.5% to 4.8%).
DISCUSSION
Changes in
heart rate, sweat rate, core temperature, perceived exertion, and plasma volume
have been used extensively to monitor heat acclimation in previous studies (Armstrong and Maresh, 1991). In the present study there were substantial
changes in perceived exertion but only modest changes in heart rate, core
temperature, and sweat rate as a result of training in the heat. The 0.8% reduction in hematocrit with heat
acclimation is consistent with a modest
expansion of plasma volume.
One
explanation for the apparently modest degree of heat acclimation could be that
most of our measures of heat acclimation were unreliable or otherwise
invalid. This explanation is not
consistent with the high correlation between some of these measures. The highest correlation, between changes in
heart rate and perceived exertion during the standard exercise bout, indicates
that both measures were probably tracking individual differences in the extent
of heat acclimation. Similarly, the
strong negative correlation between change in sweat rate during the standard
exercise bout and change in hematocrit is the expected finding if there were
individual differences in heat acclimation.
Curiously, these two pairs of measures did not correlate well between
each other, suggesting that there may have been two largely independent
adaptation processes in our subjects.
It is also possible that changes in hematocrit were due to factors other
than heat acclimation, such as effects of diet or environment on hydration,
which would also affect sweat rate (Montain
et al., 1995). The one
measure that probably was unreliable in our hands was change in core
temperature, which did not correlate well with any other measure. The problem appears to have been movement of
the rectal thermister while the athletes were cycling.
If we make
the reasonable assumption that changes in heart rate and perceived exertion
were valid and reliable measures of heat adaptation in our study, we need to
find explanations for the fact that the adaptation was only modest. In most heat-acclimation studies the
subjects have been soldiers, mineworkers, or moderately trained student
volunteers (Maughan, 1997). In contrast,
our subjects were highly trained athletes.
We therefore suspect that, for some of our subjects, adaptations induced
by hard training prior to the study resulted in little or no thermoregulatory
adaptation to the training performed in the heat. The lack of adaptation might have been due to high core
temperature experienced during hard training (Davies
and Thompson, 1986) or a circulatory adaptation to hard training, such as
expanded blood volume (Convertino,
1991). An important consequence for future studies
of heat adaptation is that researchers should use higher temperatures or more
intense exercise regimes when the subjects are highly trained athletes.
The
observed effect of heat acclimation on performance time at normal temperature
was a little less than the smallest worthwhile improvement in performance, so
it is almost equally possible that the true effect is trivial or beneficial.
Although the true effect is unlikely to be harmful, further research with a
large sample or a more reliable measure of performance is needed for more
definitive conclusions.
The
individual differences in heat acclimation had small inconsistent effects on
mean power in the time trial: there were tendencies for small negative effects
on performance for acclimation of heart rate and perceived exertion, and a
tendency towards a small positive effect for acclimation of hematocrit. Again, there was considerable uncertainty in
the true values of these effects, but the lack of consistency argues for little
overall true effect of acclimation on performance. A greater degree of acclimation than we achieved might reveal a
more marked effect on performance. A stronger and more consistent relationship
between performance and objective measures of acclimation would also increase
confidence that any enhancement of performance is not a placebo effect, which
can be ~1% for the performance test with cyclists similar to those in the
present study (Clark et al., 2000). We would
expect to see enhancement of performance with more acclimation, but it is
possible that the extra heat stress will induce some kind of neural fatigue
that counteracts beneficial physiological adaptations.
In
principle, the observed small effect of acclimation on performance could be a
consequence of low validity or reliability of the measure of performance. We are reasonably confident about the
validity, inasmuch as cyclists used their own bikes on the Kingcycle ergometer,
rode at a steady pace for most of the time trial, and reached maximal or near
maximal effort at the finish. The reliability
of the measure (1.6% for performance time) is somewhat larger than the 1.1%
found by Palmer et al. (Palmer et
al., 1996) in a reliability study of the 40-km time trial on the
Kingcycle. This difference is probably
due to the learning effect between the first and second time trial in our
study. The learning effect was large,
probably because subjects were able to see elapsed time and distance during the
time trials and tried to improve their performance in the second time trial. Learning effects can reduce the reliability
of performance tests, because any individual differences in the learning effect
add to within-subject variability (Hopkins,
2000). In future studies of endurance performance we intend
to use a constant-load test to exhaustion, which appears to be substantially
more reliable than any other tests (Hopkins
et al., 2001). We will also
blind the subjects to their times to exhaustion, to reduce learning effects.
In
conclusion, well-trained cyclists show only small adaptations to a moderate
heat-acclimation program. These
adaptations probably have little impact on performance at normal environmental
temperatures, but more research is needed to clarify this issue.
The authors
thank Diana Wilson and Frances Van Eerten for their valuable technical
assistance.
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