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This study aimed to determine whether caffeine ingestion would increase the workload voluntarily chosen by athletes in a limited-sleep state. In a double-blind, crossover study, 16 professional rugby players ingested either a placebo or 4 mg/kg caffeine 1 hr before exercise. Athletes classified themselves into nondeprived (8 hr+) or sleep-deprived states (6 hr or less). Exercise comprised 4 sets of bench press, squats, and bent rows at 85% 1-repetition maximum. Athletes were asked to perform as many repetitions on each set as possible without failure. Saliva was collected before administration of placebo or caffeine and again before and immediately after exercise and assayed for testosterone and cortisol. Sleep deprivation produced a very large decrease in total load (p = 1.98 × 10(-7)). Caffeine ingestion in the nondeprived state resulted in a moderate increase in total load, with a larger effect in the sleep-deprived state, resulting in total load similar to those observed in the nondeprived placebo condition. Eight of the 16 athletes were identified as caffeine responders. Baseline testosterone was higher (p < .05) and cortisol trended lower in non-sleep-deprived athletes. Changes in hormones from predose to preexercise correlated to individual workload responses to caffeine. Testosterone response to exercise increased with caffeine compared with placebo, as did cortisol response. Caffeine increased voluntary workload in professional athletes, even more so under conditions of self-reported limited sleep. Caffeine may prove worthwhile when athletes are tired, especially in those identified as responders.
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International Journal of Sport Nutrition and Exercise Metabolism, 2012, 22, 157 -164
© 2012 Human Kinetics, Inc.
Cook and Drawer are with the United Kingdom Sports Coun-
cil, London, UK. Beaven is with the National Winter Sports
Research Center,Östersund, Sweden. Kilduff is with the
College of Engineering, Swansea University, Swansea, UK.
Acute Caffeine Ingestion’s Increase of Voluntarily
Chosen Resistance-Training Load After Limited Sleep
Christian Cook, C. Martyn Beaven, Liam P. Kilduff, and Scott Drawer
Introduction: This study aimed to determine whether caffeine ingestion would increase the workload voluntarily
chosen by athletes in a limited-sleep state. Methods: In a double-blind, crossover study, 16 professional rugby
players ingested either a placebo or 4 mg/kg caffeine 1 hr before exercise. Athletes classied themselves into
nondeprived (8 hr+) or sleep-deprived states (6 hr or less). Exercise comprised 4 sets of bench press, squats,
and bent rows at 85% 1-repetition maximum. Athletes were asked to perform as many repetitions on each set
as possible without failure. Saliva was collected before administration of placebo or caffeine and again before
and immediately after exercise and assayed for testosterone and cortisol. Results: Sleep deprivation produced
a very large decrease in total load (p = 1.98 × 10–7). Caffeine ingestion in the nondeprived state resulted in a
moderate increase in total load, with a larger effect in the sleep-deprived state, resulting in total load similar
to those observed in the nondeprived placebo condition. Eight of the 16 athletes were identied as caffeine
responders. Baseline testosterone was higher (p < .05) and cortisol trended lower in non-sleep-deprived
athletes. Changes in hormones from predose to preexercise correlated to individual workload responses to
caffeine. Testosterone response to exercise increased with caffeine compared with placebo, as did cortisol
response. Conclusions: Caffeine increased voluntary workload in professional athletes, even more so under
conditions of self-reported limited sleep. Caffeine may prove worthwhile when athletes are tired, especially
in those identied as responders.
Keywords: sleep deprivation, sleep poverty, testosterone, cortisol, individual responses
Original research
Caffeine has long been touted as an ergogenic aid.
With the lifting of the partial ban on its use by the Interna-
tional Olympic Committee in 2004, research on its effects
in relation to athletic performance has intensied. Indeed,
caffeine at appropriate doses appears able to improve
time to exhaustion and other indices of endurance in a
number of different physical activities including rowing,
swimming, cycling, and running and simulated rugby
and soccer performances (Carr, Gore, & Dawson, 2011;
Davis & Green, 2009; Paton, Lowe, & Irvine, 2010;
Stuart, Hopkins, Cook, & Cairns, 2005). Furthermore,
a position stand by the International Society of Sports
Nutrition has declared that the positive effects of caffeine
supplementation are not associated with negative effects
on uid balance that could negatively affect performance
(Goldstein et al., 2010).
In terms of the effects of caffeine on strength per-
formance, the existing literature is equivocal. It has been
suggested that caffeine can enhance contractile force at
submaximal loads (Tarnopolsky, 2008), and Jacobson,
Weber, Claypool, and Hunt (1992) observed that a dose
of 7 mg/kg body weight of caffeine had a benecial effect
on muscle strength. However, the same benets were not
seen in a similar study design by Bond, Gresham, McRae,
and Tearney (1986) using a 5-mg/kg body weight dose.
One study (Beck et al., 2006) suggested that upper body
strength is enhanced by caffeine consumption with no
effect on lower body strength, while others have seen
the opposite (Astorino, Martin, Schachtsiek, Wong, &
Ng, 2011) or have failed to see any evidence for strength
increases (Williams, Cribb, Cooke, & Hayes, 2008). Asto-
rino et al. (2011) concluded that caffeine had a limited
practical effect before workouts but conceded that this
was highly individual. Many fundamental resistance-
training programs progress by adding total load via
increased repetitions to set weights before increasing
the actual weight load itself (Kraemer & Ratamess,
2005), so motivation to perform additional repetitions,
as observed on the leg press by Astorino et al. (2011)
after caffeine ingestion, may in fact be an important
component in progressive training gain that has received
little focus.
Mild sleep deprivation is common across all aspects
of modern society (Bixler, 2009) and can affect physi-
cal performance and hormonal responses (Mougin et
al., 2001; Remes, Kuoppasalmi, & Adlercreutz, 1985;
Vgontzas et al., 2004). Indeed, increasing nightly sleep
hours by approximately 2 hr from 8 to 10 hr of sleep has
158 Cook et al.
been shown to improve physical-performance attributes
in college athletes (Mah, Mah, Kezirian, & Dement,
2011). Caffeine is commonly used to ameliorate the
effects of limited sleep, and caffeine consumption has
been associated with enhancements in mood, psycho-
motor performance, and vigilance (Dawkins, Shahzad,
Ahmed, & Edmonds, 2011; McLellan et al., 2005). In
terms of improving sporting performance, caffeine has
produced clear benets in cognitive tasks during exer-
cise (Hogervorst et al., 2008) and sport-specic skills in
team-sport players (Foskett, Ali, & Gant, 2009; Stuart et
al., 2005). Furthermore, our research team has reported
that caffeine improved passing skills in rugby during a
competitive test scenario while the athletes were sleep
deprived (Cook, Crewther, Kilduff, Drawer, & Gaviglio,
Caffeine ingestion also appears to be associated with
increases in free testosterone and cortisol concentrations
that may be important in mediating the adaptive benets
of resistance exercise. In professional athletes, caffeine
elicited small but signicant acute increases in salivary
testosterone across a workout accompanied by larger
increases in the cortisol response in a dose-responsive
manner (Beaven et al., 2008). Similar changes in these
hormones were seen across the combined physical and
mental stress of a simulated rugby skill (Cook et al.,
2011). In contrast, caffeinated chewing gum led to a
substantial increase in free testosterone not accompanied
by any change in cortisol in competitive cyclists (Paton
et al., 2010).
The main aims of the current study, then, were to
observe whether caffeine ingestion inuenced the vol-
untary choice of workload and, if so, whether this effect
was exaggerated after self-reported poor sleep duration.
A secondary aim was to observe whether free concen-
trations of the hormones testosterone and cortisol varied
across these states.
Sixteen professional rugby players (age 20.9 ± 0.9 years,
height 1.85 ± 0.06 m, and body mass 97 ± 8 kg; M ± SD)
were recruited to participate in the study. The athletes
chosen were similar in strength level, with maximum lifts
of 170- to 210-kg squat, 130- to 170-kg bench press, and
110- to 130-kg barbell row. All participants were fully
informed of the nature and possible risks of the study
before giving written consent, and the protocol was
approved by the university ethics committee.
Experimental Protocol
All athletes completed a one-repetition maximum (1-RM)
test in the week preceding the start of the experiment for
back squat, bench press, and bent barbell row, and these
data were used to extrapolate each individual’s 85%
1-RM loading used in the four test sessions. Briey, the
1-RM test session consisted of 5 × 50%, 3 × 60%, 2 ×
70%, 1 × 80%, 1 × 90%, 1 × 95%, and then 1 × 100% of
each individual’s previous best effort. If athletes failed,
they had one more attempt, and if they still failed, the
weight was reduced by 2.5 kg until their best lift was
obtained. If they were successful at their 100% lift, the
weight was increased by 2.5 kg until two failed attempts
indicated they had reached their maximum weight. Three
minutes were allowed between efforts.
The study used a randomized, double-blind, placebo-
controlled, balanced trial. Each athlete was asked to
log his nightly sleep time and quality and to turn up for
testing on two occasions when he had obtained 8 hr or
more of good sleep and on two occasions when he had
slept for less than 6 hr (sleep-deprived state), under the
proviso that any two testing sessions be a minimum of
3 days apart. On arrival, the athletes ingested gelatin
capsules containing either lactose (placebo) or 4 mg/kg
body weight of caffeine 1 hr before exercise. Thus, all
participants completed four test sessions over a 4-week
period with caffeine or placebo ingested before exercise
in both a non-deprived and a sleep-deprived state. They
also completed a short questionnaire at the conclusion
of training to ascertain their perception of what they had
ingested and whether they thought it had had an effect
on their training.
All participants were instructed to refrain from
ingesting dietary caffeine before exercise on the test days.
A dietary log for the preceding 24 hr was collected to
assess caffeine, uid, and food intake, and reminders were
given to ensure dietary compliance. The athletes were by
their own admission light, occasional caffeine consum-
ers, and this was veried by food diaries that were kept
for 2 weeks before the study. The diaries indicated that
consumption of caffeine was equal to or less than 120 mg
caffeine per day, with most participants not consuming
caffeine on a daily basis.
Test Sessions
All exercises were performed at the gymnasium where the
participants were accustomed to training. All participants
were completely familiar with the training protocol and
had undertaken similar sessions over the last 12 months.
They all had a minimum of 2 years of fully recorded and
instructed resistance training. Resistance-training ses-
sions were performed at 11 a.m., with athletes reporting
to the gym at 9:30 a.m. after consuming breakfast and
at least 750 ml of uid. Water was available ad libitum
across the sessions.
The athletes performed a warm-up as follows: 5-min
warm-up on a stationary cycle, unloaded, at 60 rpm and
a nonstop circuit of one set of squats using a 20-kg bar
for 10 repetitions (reps), one set of bench press using a
20-kg for 10 reps, one set of barbell rows using a 20-kg
bar for 10 reps, and one set of squats, bench press, and
barbell row with a 60-kg weight for 10 reps (each with
30 s rest). The subjects then rested for 1 min and began
Caffeine’s Increase of Resistance-Training Load 159
Training consisted of four sets of back squat using
85% of their individually dened 1-RM, four sets of
bench press at 85% 1-RM, and four sets of bent row at
85% 1-RM. Athletes rested for 90 s between sets and
3 min between exercises. They were accompanied by
a trainer during the workout who verbally encouraged
them to perform as many repetitions on each set as they
felt they could without failure. No assistance was given,
and any failed repetitions were not counted. All sets were
attempted. The workload for each exercise was calculated
as the product of total repetitions and load lifted. The sum
of these workloads was dened as the total workload.
Saliva Samples
Whole saliva samples were obtained from each athlete
immediately before caffeine or placebo ingestion, then
again before starting and at the end of the resistance-
exercise session. For each sample, participants were
asked to expectorate 2 ml of saliva into a sterile container.
Saliva samples were stored at –20 °C until assay. Salivary
steroid samples were taken in this study because they are
minimally invasive and have the advantage of reecting
free-steroid concentrations, which are reported to be more
physiologically relevant than total blood levels (Obminski
& Stupnicki, 1997; Vining, McGinley, & Symons, 1983).
To prevent blood contamination of saliva, resulting in an
overestimation of hormone concentrations, subjects were
advised to avoid brushing their teeth, drinking hot uids,
or eating hard foods such as apples in the 2 hr before
providing their sample. Saliva samples were analyzed
in duplicate for testosterone and cortisol using ELISA
kits per manufacturer’s instructions (Salimetrics Ltd.).
Detection limits for the assays were 0.1 pg/ml and 0.01
ng/ml for testosterone and cortisol, respectively. The
intra- and interassay coefcients of variation were <9%
for cortisol and <8% for testosterone.
Statistical Analysis
Changes in the mean of each measure with and with-
out caffeine treatment were used to assess magnitudes
of effects by dividing the changes by the appropriate
between-participants SDs. Pairwise t-statistic compari-
sons were made between conditions, and differences were
interpreted in relation to the likelihood of exceeding the
smallest worthwhile effect with individual change thresh-
olds for each variable. Hormonal and load data were log-
transformed to reduce nonuniformity of error, with effects
derived by back-transformation as percentage changes.
Magnitudes of the standardized effects were interpreted
using thresholds of 0.2, 0.6, and 1.2 for small, moderate,
and large, respectively (Hopkins, Marshall, Batterham,
& Hanin, 2009). Standardized effects of –0.19 to 0.19
were termed trivial. To make inferences about the large-
sample value of an effect, the uncertainty in the effect
was expressed as 90% condence limits. An effect was
deemed unclear if the condence interval overlapped the
thresholds for both small positive and negative effects.
The signicance level was set at p .05.
None of the athletes were able to perceive beyond chance
whether they had actually received the placebo (which
they had been told was another supplement) or the 4-mg/
kg body weight caffeine dose. Caffeine administration in
the non-sleep-deprived state was associated with substan-
tial and signicant increases in bench press (effect size
[ES] 0.75, p = .039), back squat (ES 0.93, p = .0122),
bent row (ES 0.81, p = .0249), and total workload (ES
1.13, p = .003) compared with the non-sleep-deprived
placebo condition (Figure 1). Caffeine administration
in the sleep-deprived state also produced signicant
increases in bench press (ES 1.16, p = .0023), back squat
(ES 1.39, p = .0004), bent row (ES 1.07, p = .0043), and
total workload (ES 1.47, p = .0002) compared with pla-
cebo sleep-deprived state. With caffeine administration,
the total workload completed in the sleep-deprived state
was not signicantly different (p = .6402) than that seen
in the non-sleep-deprived state of the placebo condition
(Figure 1). Very large increases in the voluntarily chosen
workload were observed between the non-sleep-deprived
caffeine state and the sleep-deprived placebo state: bench
press 2,568 vs. 1,780 kg (p = 2.31 × 10–5), squat 3,316
vs. 2,327 kg (p = 2.20 × 10–5), bent row 1,997 vs. 1,524
kg (p = .0009), and total workload 7,881 vs. 5,631 kg (p
= 1.05 × 10–8). A lack of sleep was associated with sig-
nicant decreases in total workload in both the placebo
(ES 2.33, p = 1.98 × 10–7) and caffeine (ES 1.03, p =
.0058) condition.
The group data were biased by large responses
among 8 of the 16 athletes who were identied as high
caffeine responders. Those participants consistently noted
that they believed there was an effect when they were
administered the caffeine dose. Total workload in the
high caffeine responders was signicantly higher than in
nonresponders in the non-sleep-deprived (ES 3.46, p =
8.78 × 10–6) and sleep-deprived (ES 3.37, p = 1.13 × 10–5)
conditions (Figure 2). Indeed, there was no difference in
the voluntarily chosen workload of the nonresponders
between the caffeine and placebo conditions (p = .5329).
There was, however, a clear moderate positive effect of
the 4-mg/kg body weight caffeine dose on the workload
chosen by nonresponders in the fatigued state (ES 1.01,
p = .0533).
Baseline testosterone was clearly elevated in the
non-sleep-deprived groups compared with the groups
that reported a lack of sleep (ES 0.67–1.09; Table 1). The
4-mg/kg body weight caffeine dose produced an increase
in testosterone across the hour before the workout in
the sleep-deprived (5.8% ± 3.3%, p = .0083) and non-
sleep-deprived (3.4% ± 1.8%, p = .005) groups (Figure
3). In contrast, testosterone signicantly decreased over
the same period in both placebo groups (p < .01), with
a small but clear difference between the change in the
sleep-deprived (10.6% ± 3.6%, p = .0001) and non-sleep-
deprived conditions (10.9% ± 2.4%, p = 2.82 × 10–8). The
workout elicited signicant increases in testosterone in
each of the conditions, but the greatest increase was in the
Figure 1 — Workload for each exercise performed, M ± SD. NSD = non-sleep-deprived; SD = sleep-deprived; CAF = caffeine;
PLA = placebo; BP = bench press; SQT = back squat; BR = bent row. aSignicantly greater than NSD:PLA. bSignicantly greater
than SD:CAF. cSignicantly greater than SD:PLA. The threshold for signicance was p .05. Workload is dened as the product
of repetitions performed and load lifted.
Figure 2 — Total workload for responders and nonresponders with placebo and caffeine administration, M ± SD. RSP = caffeine
responders (n = 8); NR = nonresponders (n = 8); CAF = caffeine; PLA = placebo. *Signicantly greater than other conditions; #Clearly
greater than corresponding placebo condition. Caffeine dose was 4 mg/kg body weight. The threshold for signicance was p .01.
Caffeine’s Increase of Resistance-Training Load 161
non-sleep-deprived caffeine condition (30.1% ± 6.2%, p
= 2.14 × 10–11), which was greater than in any of the other
conditions (p £ .0104). The poorest testosterone response
was observed in the sleep-deprived placebo condition
(Figure 3), which was signicantly worse than in any of
the other conditions (p £ .0035).
Baseline cortisol was clearly elevated in the sleep-
deprived groups compared with the non-sleep-deprived
groups (ES 0.41–0.80; Table 1). Caffeine administration
produced an increase in cortisol across the hour before the
workout in the sleep-deprived (9.0% ± 5.3%, p = .0107)
and non-sleep-deprived (8.1% ± 2.5%, p = .0001) groups.
In contrast, cortisol signicantly decreased over the same
period in both placebo groups (p < .01), with a small but
clear difference between the change in the sleep-deprived
(13.7% ± 5.6%, p = .0007) and non-sleep-deprived
conditions (12.7% ± 2.7%, p = 3.67 × 10–7; Figure 3).
Exercise elicited signicant increases in cortisol in each
of the conditions, with the greatest increase in the non-
sleep-deprived caffeine condition (21.3% ± 8.4%, p =
1.56 × 10–7), which was greater than in any of the other
conditions (p £ .0898).
It was apparent that the increase in testosterone
across the hour before the workout was driven by the
previously identied caffeine responders, with increases
of 6.4% ± 1.6% (p = .0002) and 12.9% ± 2.8% (p = .0001)
in the non-sleep-deprived and sleep-deprived conditions,
respectively. The corresponding changes in testosterone
for the nonresponders were a trivial increase of 0.4%
± 2.1% in the non-sleep-deprived group and a trivial
decrease of 0.8% ± 1.7% in the sleep-deprived group.
These changes were signicantly less than those seen in
the caffeine responders (p = .0012 and 1.19 × 10–5, respec-
tively). Furthermore, among the 8 individuals identied
as caffeine responders, the change in testosterone from
time of caffeine ingestion to immediately before exercise
was strongly correlated with the subsequent increase in
voluntarily chosen workload (R2 = .67, p = .0002).
The main nding in this study was that caffeine ingestion
signicantly improved the total voluntary workload lifted
Table 1 Group Salivary Hormone Concentrations Across Treatment Groups
Predose Preworkout Postworkout
Testosterone Cortisol Testosterone Cortisol Testosterone Cortisol
NSD:CAF 136 ± 22b,c 2.07 ± 0.21 140 ± 20a,b,c 2.23 ± 0.21 183 ± 26a,b,c 2.71 ± 0.26a
NSD:PLA 134 ± 31b,c 2.22 ± 0.51 125 ± 30c2.13 ± 0.49 151 ± 32c2.44 ± 0.49
SD:CAF 113 ± 21 2.44 ± 0.54a,d 120 ± 24 2.64 ± 0.46a,c,d 143 ± 29c2.98 ± 0.50a,c
SD:PLA 115 ± 26 2.40 ± 0.53d110 ± 25 2.30 ± 0.51 123 ± 29 2.60 ± 0.49
Note. NSD = non-sleep-deprived; CAF = caffeine; PLA = placebo; SD = sleep-deprived. Testosterone and cortisol concentrations are in pg/ml and
ng/ml, respectively.
aSubstantially greater than NSD:PLA. bSubstantially greater than SD:CAF. cSubstantially greater than SD:PLA. dSubstantially greater than NSD:CAF.
Figure 3 — Salivary hormone responses to caffeine ingestion
and resistance exercise sessions, M ± SD. NSD = non-sleep-
deprived; SD = sleep-deprived; CAF = caffeine; PLA = placebo.
Caffeine dose was 4 mg/kg body weight. All preworkout tes-
tosterone and cortisol values are signicantly different from
the preceding predose value (p .01). All postworkout
testosterone and cortisol values are signicantly greater
than the preceding preworkout value (p < .01). aSubstantially
greater than corresponding sleep-deprived:caffeine value. bSub-
stantially greater than corresponding sleep-deprived:placebo
value. cSubstantially greater than corresponding non-sleep-
deprived:placebo value.
162 Cook et al.
by professional rugby athletes in a self-reported state of
sleep poverty. There was a similar, although smaller, ben-
ecial effect on total workload in a non-sleep-deprived
state. As loads were kept constant throughout the testing,
the increases in total workload were a direct result of an
increase in the number of voluntarily selected repetitions
in each set. It is important to state, then, that given the
voluntary nature of the repetitions (not forced by coach
or lifting partner), this is likely more about motivation to
perform than an actual physical-performance increase. As
training progression is often based around such increases,
caffeine ingestion appears to be a valuable intervention
when an athlete is tired. The results also demonstrate
that it is important for athletes to avoid states of sleep
poverty due to the negative physical and hormonal effects
Previously published work has focused on acute
improvements in maximal strength measures in non-
sleep-deprived conditions, where a small effect of caf-
feine was observed (Astorino, Rohmann, & Firth, 2008;
Beck et al., 2006). University of California researchers
have reported that while caffeine did produce signicant
effects on repetitions performed on the leg press, it was
of limited practical value to the training environment
(Astorino et al., 2011). Part of their argument was based
on the importance of progression in extrapolated 1-RM
strength, which clearly is important, rather than main-
tenance of repetitions performed across sequential sets.
However, herein we focus more on a higher maintenance
of repetitions per set at a standard weight, which we
suggest is a valid training gain. Indeed, the ingestion of
caffeine in the non-sleep-deprived state was associated
with an increase in total workload of 2,250 kg in a single
session compared with the sleep-deprived placebo con-
dition. This voluntary increase in workload represents a
superior adaptive stimulus as a result of caffeine ingestion
without an increase in maximal load.
To a large extent our data agree with the ndings of
Astorino et al. (2011), as we found moderate effects of
caffeine ingestion on repetitions performed while non-
sleep-deprived, with the largest effect observable on
squats rather than bench press or bent row. After sleep
deprivation, however, we saw larger effects of caffeine
ingestion, potentially offering more practical signicance
to athletes when programs progress based on added
repetitions, especially given that sleep deprivation is not
uncommon in many athletic groups. Indeed, high train-
ing loads have been associated with sleep disruption in
competitive swimmers (Taylor, Rogers, & Driver, 1997).
It should be noted that ours results demonstrated
large variability, and individual responses in caffeine sus-
ceptibility were apparent. Indeed, some athletes showed
clear changes in voluntary load volume with caffeine
ingestion compared with placebo, while others were not
affected at all. These data were used to identify the high
caffeine responders in the current study along with their
associated distinctive hormonal proles. Astorino et al.
(2011) also clearly reported an individual responsive-
ness, with heavier caffeine consumers tending to respond
positively to caffeine ingestion. A number of studies
now suggest that heavy caffeine consumers are more
responsive to caffeine ingestion and that this may in fact
simply represent amelioration of caffeine-withdrawal
effects induced by the restrictions on caffeine intake that
studies demand before testing (James & Keane, 2007;
Yeomans, Ripley, Davies, Rusted, & Rogers, 2002). We
intentionally chose low consumers of caffeine to avoid
any potential confounding effects of withdrawal rever-
sal. We have previously suggested that in low caffeine
consumers a much lower dose of caffeine may be more
ergogenic than a higher dose (Cook et al., 2011).
In both placebo groups (sleep-deprived and non-
sleep-deprived) salivary testosterone and cortisol tended
(p < .08) to decline from predose to immediately before
exercise. This observation is consistent with other data
showing a circadian fall across the morning hours (Bird &
Tarpenning, 2004; Gachon, Nagoshi, Brown, Ripperger,
& Schibler, 2004). However, the expected circadian
decrease was absent in the caffeine groups, with notable
increases in individuals identied as caffeine responders.
The observation that the caffeine-induced increase in
testosterone was specic to the athletes who responded
positively in terms of increased workload volume sug-
gests that the dose of caffeine sufcient to elicit meaning-
ful training-volume improvements is related to changes
in preworkout hormones. Alternatively, our research
group has demonstrated a role of testosterone in training
gains that may relate to motivation to perform (Cook et
al., 2011; Crewther & Cook, 2010). The current study
provides some support for this hypothesis, which may be
worthy of further exploration in a competitive environ-
ment where caffeine may have more signicant effects.
Caffeine ingestion was also associated with signi-
cant increases in free testosterone and cortisol after the
workout compared with the placebo condition. This phe-
nomenon does not appear to have been well studied. How-
ever, in professional rugby league players we also saw
a small but signicant increase in both the testosterone
and the cortisol response across the workout after caffeine
ingestion (Beaven, Hopkins, et al., 2008). One other study
has reported similar, but larger, effects in testosterone but
did not observe a marked change in cortisol (Paton et
al., 2010). That study in competitive cyclists employed
a chewing-gum delivery method, which may account for
the differences in hormone response observed. It is also
possible that the differential hormonal responses across
the workout are a simple reection of the increased
workload, facilitated through other mechanisms by caf-
feine, as hormone change is known to be inuenced by
intensity of workout (Kraemer et al., 1990; Kraemer &
Ratamess, 2005).
The actual outcome of this caffeine-augmented
increase in hormones across the workout remains equivo-
cal. Indeed, it has been suggested that typical changes in
testosterone concentration are unlikely to have any real
anabolic effect (West et al., 2010). In contrast, others
have suggested that testosterone can both directly and
indirectly inuence muscle and strength gains (Beaven,
Caffeine’s Increase of Resistance-Training Load 163
Cook, & Gill, 2008; Kvorning, Anderson, Brixen, &
Madsen, 2006; Rønnestad, Nygaard, & Raastad, 2011).
Furthermore, the importance of a functional androgen
receptor has been demonstrated (Inoue, Yamasaki,
Fushiki, Okada, & Sugimoto, 1994), suggesting at least
a permissive role for testosterone in muscle adaptation.
In addition, testosterone has been demonstrated to be
dose responsive in priming for a workout, with short-term
effects on the neuromuscular system that have the poten-
tial to mediate adaptation (Crewther, Cook, Cardinale,
Weatherby, & Lowe, 2011).
In conclusion, we found signicant positive effects
of caffeine ingestion on voluntary workload volume in
a resistance-exercise session performed by professional
rugby players. We found large benecial effects of caf-
feine in athletes who reported a poor sleep duration that
could have practical implications in certain responsive
individuals. In these individuals, salivary testosterone
and cortisol were inuenced by caffeine and may in part
be linked to the increase in voluntary workload.
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... Some studies included in this meta-analysis assessed the influence of sleep loss on more than one performance task, either belonging to the same category [40,41,53,58,59,63,64,[75][76][77][78][79][80][81][82][83][84], or different categories [41, 43, 44, 56-59, 61, 62, 64, 65, 75, 77-81, 85-102]. For example, Souissi et al. [78] measured anaerobic power in two separate tasks (i.e., squat jump and Wingate test). ...
... The overall weighted mean effect estimate (Table 2) indicated a negative influence of sleep loss on strength-endurance (mean % Δ = − 9.85%, 95% CI − 19.6 to − 0.13, p = 0.048, Fig. S7]. However, the magnitude and statistical significance of the effect was unstable during one-out analyses (mean % Δ range = − 11.2 to − 8.71% and 95% CIs did not include zero except when outcome measures from six trials were sequentially removed [60,75,84,86]). Findings were comparable with alternative correlation coefficients (ESM Table S14). ...
... Subgroup analyses showed that strength-endurance was negatively affected by sleep restriction, but not sleep deprivation (Table 2). Note, however, that the three outcome measures analysed for sleep restriction were derived from one study [84]. There were no outcome measures to conduct analysis for either early-or late-restriction sleep protocols. ...
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Background Sleep loss may influence subsequent physical performance. Quantifying the impact of sleep loss on physical performance is critical for individuals involved in athletic pursuits. Design Systematic review and meta-analysis. Search and Inclusion Studies were identified via the Web of Science, Scopus, and PsycINFO online databases. Investigations measuring exercise performance under ‘control’ (i.e., normal sleep, > 6 h in any 24 h period) and ‘intervention’ (i.e., sleep loss, ≤ 6 h sleep in any 24 h period) conditions were included. Performance tasks were classified into different exercise categories (anaerobic power, speed/power endurance, high-intensity interval exercise (HIIE), strength, endurance, strength-endurance, and skill). Multi-level random-effects meta-analyses and meta-regression analyses were conducted, including subgroup analyses to explore the influence of sleep-loss protocol (e.g., deprivation, restriction, early [delayed sleep onset] and late restriction [earlier than normal waking]), time of day the exercise task was performed (AM vs. PM) and body limb strength (upper vs. lower body). Results Overall, 227 outcome measures (anaerobic power: n = 58; speed/power endurance: n = 32; HIIE: n = 27; strength: n = 66; endurance: n = 22; strength-endurance: n = 9; skill: n = 13) derived from 69 publications were included. Results indicated a negative impact of sleep loss on the percentage change (%Δ) in exercise performance (n = 959 [89%] male; mean %Δ = − 7.56%, 95% CI − 11.9 to − 3.13, p = 0.001, I² = 98.1%). Effects were significant for all exercise categories. Subgroup analyses indicated that the pattern of sleep loss (i.e., deprivation, early and late restriction) preceding exercise is an important factor, with consistent negative effects only observed with deprivation and late-restriction protocols. A significant positive relationship was observed between time awake prior to the exercise task and %Δ in performance for both deprivation and late-restriction protocols (~ 0.4% decrease for every hour awake prior to exercise). The negative effects of sleep loss on different exercise tasks performed in the PM were consistent, while tasks performed in the AM were largely unaffected. Conclusions Sleep loss appears to have a negative impact on exercise performance. If sleep loss is anticipated and unavoidable, individuals should avoid situations that lead to experiencing deprivation or late restriction, and prioritise morning exercise in an effort to maintain performance.
... Age ↑ Cortisol, ↓ amylase in elliptical and cycle ergo meter in young males [2] ↓ cortisol, amylase in treadmill sessions in young males [2] ↑ salivary cortisol post resistance in middle-aged man [20] in superset strength training protocol Gender ↑ amylase activity post exercise in females in cycling [1] ↑ 1.5× amylase activity in males at rest, but similar cortisol levels in high intensity interval training [21] ↑ amylase and cortisol in females in the Ecomotion/ProAdventure Race World [22] -basal amylase levels higher in females in 5000 m race [23] Caffeine ↑ post-triathlon cortisol levels-microencalsulated caffeine [24] ↓ testosterone:cortisol ratio in resistance exercise [25] -caffeine gum-no changes in salivary cortisol after simulated half time by professional academy rugby union [26] ↓ salivary cortisol in repeated, high-intensity sprint exercise in competitive cyclists [26] ↑ adrenaline and cortisol levels after recovery leading to increased levels of IL-6 and IL-10 after treadmill exercise [27] -acute coffee consumption activates salivary amylase, but not salivary cortisol [28] -consumption of green tea after a taekwondo training session ↑ salivary amylase activity [29] -caffeine consumed as a cereal bar during exhaustive cycling ↑ endurance and salivary cortisol, but did not affect the salivary amylase increase post-exercise [30] ↑ salivary cortisol after caffeine administration in acute sleep deprived athletes and altered performance [31,32] -performance improved in endurance athletes [24,33] -significant performance improvement in competitive intermittent-sprint [34,35], tennis performance [36], women's rugby seven competition [37]. ...
... A variety of studies have started to shift their attention on sleep importance and influence on performance especially in prolonged activities. Two studies have reported elevated salivary cortisol after caffeine administration in acute sleep deprived athletes and altered performance [31,32]. Interestingly, one study has reported that even the bitter taste of caffeine has an impact on the level of salivary amylase as they have observed that in the case of hypersensitive subjects the levels of amylase fragments were much higher [84]. ...
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Athletes are exposed to a tremendous amount of stress, both physically and mentally, when performing high intensity sports with frequent practices, pushing numerous athletes into choose to use ergogenic aids such as caffeine or β-alanine to significantly improve their performance and ease the stress and pressure that is put onto the body. The beneficial or even detrimental effects of these so-called ergogenic aids can be appreciated through the use of numerous diagnostic tools that can analyze various body fluids. In the recent years, saliva samples are gaining more ground in the field of diagnostic as it is a non-invasive procedure, contains a tremendous amount of analytes that are subject to pathophysiological changes caused by diseases, exercises, fatigue as well as nutrition and hydration. Thus, we describe here the current progress regarding potential novel biomarkers for stress and physical activity, salivary α-amylase and salivary cortisol, as well as their use and measurement in combination with different already-known or new ergogenic aids.
... Prior research has shown that sleep duration can be compromised during periods of high training demands, such as those experienced during preseason training [6][7][8][9]. Decreased sleep duration can have detrimental effects on athletic performance through impaired cognitive performance, endocrine, mood and metabolic function [10,11]. However, to date, there has been limited research investigating the relationship between sleep and changes in physical performance markers during periods of increased training demands in team sport athletes. ...
... A reduction in sleep efficiency and duration seen during intensified training periods may be detrimental to maximising physiological adaptation and muscle recovery [19]. Researchers have suggested that reductions in sleep duration may inhibit muscle growth and recovery [19] and lead to a catabolic environment [20,21] with the potential to attenuate muscular adaptation associated with resistance training [10,20,22]. Reductions in sleep duration are also known to lead to an imbalance in hormones (i.e., Leptin and Grehlin) necessary for the control of appetite, satiety, which has been associated with decreases in resting metabolic rate and increased hunger, and caloric consumption and weight gain [19,21,23], which may impact individual athletes depending on the body composition requirements of the sport and or playing position. ...
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Background: Preseason training optimises adaptations in the physical qualities required in rugby union athletes. Sleep can be compromised during periods of intensified training. Therefore, we investigated the relationship between sleep quantity and changes in physical performance over a preseason phase in professional rugby union athletes. Methods: Twenty-nine professional rugby union athletes (Mean ± SD, age: 23 ± 3 years) had their sleep duration monitored for 3 weeks using wrist actigraphy. Strength and speed were assessed at baseline and at week 3. Aerobic capacity and body composition were assessed at baseline, at week 3 and at week 5. Participants were stratified into 2 groups for analysis: <7 h 30 min sleep per night (LOW, n = 15) and >7 h 30 min sleep per night (HIGH, n = 14). Results: A significant group x time interaction was determined for aerobic capacity (p = 0.02, d = 1.25) at week 3 and for skinfolds at week 3 (p < 0.01, d = 0.58) and at week 5 (p = 0.02, d = 0.92), in favour of the HIGH sleep group. No differences were evident between groups for strength or speed measures (p ≥ 0.05). Conclusion: This study highlights that longer sleep duration during the preseason may assist in enhancing physical qualities including aerobic capacity and body composition in elite rugby union athletes.
... Short sleep duration and decreased sleep efficiency as a result of variability in sleep-wake time, can also have negative ramifications for mood and mental wellbeing (Chellappa, Morris, & Scheer, 2020). With respect to physical performance, longer sleep durations have demonstrated improved training capacity (Cook, Beaven, Kilduff, & Drawer, 2012), and improved aerobic adaptations in athletes (Teece et al., 2021). Similarly, when stratifying military trainees into two quantile groups based on sleep duration, small benefits in aerobic fitness were observed in those who averaged only a modest 36 minutes longer sleep duration than a short sleeping cohort (Edgar, Gill, Beaven, Zaslona, & Driller, 2021). ...
The manipulation of light exposure in the evening has been shown to modulate sleep, and may be beneficial in a military setting where sleep is reported to be problematic. This study investigated the efficacy of low‐temperature lighting on objective sleep measures and physical performance in military trainees. Sixty‐four officer‐trainees (52 male/12 female, mean ± SD age: 25 ± 5 years) wore wrist‐actigraphs for 6 weeks during military training to quantify sleep metrics. Trainee 2.4‐km run time and upper‐body muscular‐endurance were assessed before and after the training course. Participants were randomly assigned to either: low‐temperature lighting (LOW, n = 19), standard‐temperature lighting with a placebo “sleep‐enhancing” device (PLA, n = 17), or standard‐temperature lighting (CON, n = 28) groups in their military barracks for the duration of the course. Repeated‐measures ANOVAs were run to identify significant differences with post hoc analyses and effect size calculations performed where indicated. No significant interaction effect was observed for the sleep metrics; however, there was a significant effect of time for average sleep duration, and small benefits of LOW when compared with CON (d = 0.41–0.44). A significant interaction was observed for the 2.4‐km run, with the improvement in LOW (Δ92.3 s) associated with a large improvement when compared with CON (Δ35.9 s; p = 0.003; d = 0.95 ± 0.60), but not PLA (Δ68.6 s). Similarly, curl‐up improvement resulted in a moderate effect in favour of LOW (Δ14 repetitions) compared with CON (Δ6; p = 0.063; d = 0.68 ± 0.72). Chronic exposure to low‐temperature lighting was associated with benefits to aerobic fitness across a 6‐week training period, with minimal effects on sleep measures.
Athletes display differing sleep habits to non-athletic populations; similarly, differences occur in sleep habits between athletes from different sports. There is currently limited research investigating the differences in sleep habits and behaviors between different levels of competition within the same sport. A total of 224 rugby union athletes (109 academy, 38 semi-professional, 84 professional) completed the Athlete Sleep Behavior Questionnaire and the Pittsburgh Sleep Quality Index. Professional athletes displayed a significantly longer self-reported sleep duration compared to semi-professional and academy athletes (7 h 52 min ± 51 min vs. 7 h 16 min ± 1 h 15 min vs. 7 h 19 min ± 1 h 12 min, p < 0.01). Pittsburgh Sleep Quality Index global scores revealed a significantly lower ( p = 0.04, d = 0.3) score for professional athletes (5.2 ± 2.5 AU) than academy athletes (6.0 ± 2.7 AU). Individual components of the Pittsburgh Sleep Quality Index revealed significant differences ( p < 0.05) between groups for sleep duration and daytime dysfunction. No significant differences ( p > 0.05) were observed between levels of competition for the Athlete Sleep Behavior Questionnaire global score; however, significant differences ( p < 0.05) were observed for 6 of the 18 items. This study was the first to investigate sleep behaviors across multiple levels of competition in rugby union athletes. Professional athletes displayed longer sleep duration compared to semi-professional and academy level athletes. Additionally, results highlighted that differences exist between levels of competition for specific sleep behaviors. This study identified that sleep behaviors could be improved for all levels of rugby union athletes.
Introduction: Female athletes sleep less and report more sleep problems than males. Inadequate sleep reduces maximal strength in males; however, little is known about the impact of sleep restriction on the quantity and quality of resistance exercise performed by females. This study investigated the effect of nine nights of moderate sleep restriction on repeated resistance exercise performance, hormonal responses and perceived fatigue in females. Methods: Ten healthy, resistance-trained, eumenorrheic females aged 18-35 years underwent nine nights of sleep restriction (SR; 5-h time in bed) and normal sleep (NS; ≥7 h time in bed), in a randomised, cross-over fashion with a minimum 6-week washout. Participants completed four resistance exercise sessions per trial, with blood samples collected pre- and post-exercise. Exercise performance was assessed using volume-load, reactive strength index and mean concentric velocity with rating of perceived exertion recorded post-exercise. Participants completed awakening saliva sampling and the multi-component training distress scale daily. Results: Volume-load decreased trivially (<1%, p < 0.05) with SR. Mean concentric velocity per set was slower during SR for lower body (up to 15%, p < 0.05), but not upper body, compound lifts. Intra-set velocity loss was up to 7% greater during SR for back squats (p < 0.05). SR increased salivary cortisol area under the curve (by 42%), total training distress (by 84%) and session perceived exertion (by 11%). Conclusions: Sustained SR reduces markers of resistance exercise quality (bar velocity) more than quantity (volume-load), and increases perceived effort at the same relative intensity in resistance-trained females. Markers of exercise quality and internal load may be more sensitive than volume-load, to advise coaches to the decline in lifting performance for females experiencing sleep restriction.
Background Daytime napping on match-day is a strategy used by athletes to alleviate sleep debt or to avoid boredom. However, the utilization of pre-match napping and its effect on self-rated performance has not been evaluated in professional Rugby athletes. Methods Over a 17-match season, 30 professional Rugby Union athletes (mean ± SD: 23 ± 3 y) completed a weekly questionnaire on their daytime napping practices on match day. Questions included whether they took a nap, the duration of nap, their mood state upon waking and, their perceived performance during the subsequent match. Additionally, three team coaches evaluated the match performance of each participant. Finally, each participant was asked a questionnaire focusing on their napping preferences and individual habits of match-day napping at the conclusion of the season. Results Pre-match naps were used by 86% of athletes, with an average nap duration of 32 ± 19 min. A significantly greater number of naps were taken during away matches compared to home matches (60% vs. 40%, p < 0.01). Of the athletes who napped, 86% chose to nap less than 4 h before kick-off. Furthermore, 87% of athletes who napped on match day reported believing naps helped their match performance. Additionally, the odds of an athlete rating their performance as “good” was increased 6.7 times if they napped and won the match. Conclusion This study highlights that match-day naps are commonly used amongst professional Rugby Union athletes. The results suggest that taking naps before away matches may support self-rated performance amongst Rugby Union athletes.
Sleep is very important for the proper functioning of the human body and consists of several stages. This text will address the concepts of biological rhythms, the circadian rhythm and body temperature, which is considered the main biological marker of the circadian rhythm. Their disorders have an influence on the athlete’s performance, with jet lag being approached. The diagnosis of these disorders can be made through various subjective and objective methods. Finally, adaptation strategies will be mentioned, addressing physical exercise, diet, and medication, among others.
Tea consumption has been extensively shown to be closely related to physical health and cognitive abilities. However, there are no definite conclusions on the relationship between tea consumption and convergent thinking. Convergent thinking requires top-down cognitive processing, which focuses on searching for an appropriate idea based on well-defined criteria. It is a necessary part of the creative process and is inextricably linked to divergent thinking that requires people to search for many different ideas with less defined criteria within a wider search span. It has been found that tea consumption is beneficial to divergent thinking in creativity. Given that convergent thinking is related to divergent thinking, we hypothesized that drinking tea may also promote convergent thinking. This research was to investigate the enhancing effects of tea on convergent thinking and test its possible mediating mechanism (i.e., the role of positive emotions) and marginal conditions (e.g., the moderating roles of intelligence and tea preference). In Experiment 1, participants completed the Remote Associates Test (RAT) which requires the solver to create a meaningful link (word association) that mediates three seemingly unrelated cues (e.g., Same–Tennis–Head is mediated by Match) after drinking tea or water. The results showed that the type of drinks and tea consumption habits had a significant interaction effect on RAT scores. The participants who drank tea (v.s. water) performed best in the RAT. A “split half effect” was found. That is, participants' performance in different groups was significantly different in the second half of the RAT, suggesting that drinking tea leads to persistent problem-solving convergent thinking. Experiment 2 aimed to replicate the findings in Experiment 1 using a different convergent thinking task, namely, riddle tasks, where participants needed to solve riddles with different levels of difficulty. The results revealed that performance in the tea group on the difficult tasks was significantly higher than that in the water group; after controlling for knowledge level and intelligence, the differences in the performance in the medium- and high-difficulty riddle tasks between the two groups were significant. Although no experiments found a mediating effect of positive emotions, Experiment 2 showed that the participants in the tea group were happier and more interested in the task than those in the water group. To conclude, the positive effects of tea drinking on convergent thinking was demonstrated, and the moderating effects of knowledge level, intelligence, and tea drinking habits were elaborated. The results have important practical significance for those who are engaged in creative work or those who are prone to fatigue.
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The aim of this review is to highlight two emerging concepts for the elite athlete using the resistance-training model: (i) the short-term effects of testosterone (T) and cortisol (C) on the neuromuscular system; and (ii) the dose-response training role of these endogenous hormones. Exogenous evidence confirms that T and C can regulate long-term changes in muscle growth and performance, especially with resistance training. This evidence also confirms that changes in T or C concentrations can moderate or support neuromuscular performance through various short-term mechanisms (e.g. second messengers, lipid/protein pathways, neuronal activity, behaviour, cognition, motor-system function, muscle properties and energy metabolism). The possibility of dual T and C effects on the neuromuscular system offers a new paradigm for understanding resistance-training performance and adaptations. Endogenous evidence supports the short-term T and C effects on human performance. Several factors (e.g. workout design, nutrition, genetics, training status and type) can acutely modify T and/or C concentrations and thereby potentially influence resistance-training performance and the adaptive outcomes. This novel short-term pathway appears to be more prominent in athletes (vs non-athletes), possibly due to the training of the neuromuscular and endocrine systems. However, the exact contribution of these endogenous hormones to the training process is still unclear. Research also confirms a dose-response training role for basal changes in endogenous T and C, again, especially for elite athletes. Although full proof within the physiological range is lacking, this athlete model reconciles a proposed permissive role for endogenous hormones in untrained individuals. It is also clear that the steroid receptors (cell bound) mediate target tissue effects by adapting to exercise and training, but the response patterns of the membrane-bound receptors remain highly speculative. This information provides a new perspective for examining, interpreting and utilizing T and C within the elite sporting environment. For example, individual hormonal data may be used to better prescribe resistance exercise and training programmes or to assess the trainability of elite athletes. Possible strategies for acutely modifying the hormonal milieu and, thereafter, the performance/training outcomes were also identified (see above). The limitations and challenges associated with the analysis and interpretation of hormonal research in sport (e.g. procedural issues, analytical methods, research design) were another discussion point. Finally, this review highlights the need for more experimental research on humans, in particular athletes, to specifically address the concept of dual steroid effects on the neuromuscular system.
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The effect caffeine elicits on endurance performance is well founded. However, comparatively less research has been conducted on the ergogenic potential of anaerobic performance. Some studies showing no effect of caffeine on performance used untrained subjects and designs often not conducive to observing an ergogenic effect. Recent studies incorporating trained subjects and paradigms specific to intermittent sports activity support the notion that caffeine is ergogenic to an extent with anaerobic exercise. Caffeine seems highly ergogenic for speed endurance exercise ranging in duration from 60 to 180 seconds. However, other traditional models examining power output (i.e. 30-second Wingate test) have shown minimal effect of caffeine on performance. Conversely, studies employing sport-specific methodologies (i.e. hockey, rugby, soccer) with shorter duration (i.e. 4–6 seconds) show caffeine to be ergogenic during high-intensity intermittent exercise. Recent studies show caffeine affects isometric maximal force and offers introductory evidence for enhanced muscle endurance for lower body musculature. However, isokinetic peak torque, one-repetition maximum and muscular endurance for upper body musculature are less clear. Since relatively few studies exist with resistance training, a definite conclusion cannot be reached on the extent caffeine affects performance. It was previously thought that caffeine mechanisms were associated with adrenaline (epinephrine)-induced enhanced free-fatty acid oxidation and consequent glycogen sparing, which is the leading hypothesis for the ergogenic effect. It would seem unlikely that the proposed theory would result in improved anaerobic performance, since exercise is dominated by oxygen-independent metabolic pathways. Other mechanisms for caffeine have been suggested, such as enhanced calcium mobilization and phosphodiesterase inhibition. However, a normal physiological dose of caffeine in vivo does not indicate this mechanism plays a large role. Additionally, enhanced Na+/K+ pump activity has been proposed to potentially enhance excitation contraction coupling with caffeine. A more favourable hypothesis seems to be that caffeine stimulates the CNS. Caffeine acts antagonistically on adenosine receptors, thereby inhibiting the negative effects adenosine induces on neurotransmission, arousal and pain perception. The hypoalgesic effects of caffeine have resulted in dampened pain perception and blunted perceived exertion during exercise. This could potentially have favourable effects on negating decreased firing rates of motor units and possibly produce a more sustainable and forceful muscle contraction. The exact mechanisms behind caffeine’s action remain to be elucidated.
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To investigate the effects of sleep extension over multiple weeks on specific measures of athletic performance as well as reaction time, mood, and daytime sleepiness. Stanford Sleep Disorders Clinic and Research Laboratory and Maples Pavilion, Stanford University, Stanford, CA. Eleven healthy students on the Stanford University men's varsity basketball team (mean age 19.4 ± 1.4 years). Subjects maintained their habitual sleep-wake schedule for a 2-4 week baseline followed by a 5-7 week sleep extension period. Subjects obtained as much nocturnal sleep as possible during sleep extension with a minimum goal of 10 h in bed each night. Measures of athletic performance specific to basketball were recorded after every practice including a timed sprint and shooting accuracy. Reaction time, levels of daytime sleepiness, and mood were monitored via the Psychomotor Vigilance Task (PVT), Epworth Sleepiness Scale (ESS), and Profile of Mood States (POMS), respectively. Total objective nightly sleep time increased during sleep extension compared to baseline by 110.9 ± 79.7 min (P < 0.001). Subjects demonstrated a faster timed sprint following sleep extension (16.2 ± 0.61 sec at baseline vs. 15.5 ± 0.54 sec at end of sleep extension, P < 0.001). Shooting accuracy improved, with free throw percentage increasing by 9% and 3-point field goal percentage increasing by 9.2% (P < 0.001). Mean PVT reaction time and Epworth Sleepiness Scale scores decreased following sleep extension (P < 0.01). POMS scores improved with increased vigor and decreased fatigue subscales (P < 0.001). Subjects also reported improved overall ratings of physical and mental well-being during practices and games. Improvements in specific measures of basketball performance after sleep extension indicate that optimal sleep is likely beneficial in reaching peak athletic performance.
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The purpose of this study was to determine the influence of transiently elevated endogenous hormone concentrations during exercise on strength training adaptations. Nine subjects performed four unilateral strength training session per week on the elbow flexors for 11 weeks. During two of the weekly sessions, leg exercises were performed to acutely increase the systemic anabolic hormone concentration immediately before the exercises for one of the elbow flexors (L + A). On the two other weekly training sessions, the contralateral elbow flexors were trained without prior leg exercises (A). By randomizing one arm of the subjects to serve as a control and the other as experimental, both conditions have the same nutritional and genetic environment. Serum testosterone and growth hormone was significantly increased during the L - A training session, while no hormonal changes occurred in the A session. Both A and L + A increased 1RM in biceps curl, peak power in elbow flexors at 30 and 60% of 1RM, and muscle volume of the elbow flexors (p < 0.05). However, only L + A achieved increase in CSA at the part of the arm flexors with largest cross sectional area (p < 0.001), while no changes occurred in A. L + A had superior relative improvement in 1RM biceps curl and favorable muscle adaptations in elbow flexors compared to A (p < 0.05). In conclusion, performing leg exercises prior to arm exercises, and thereby increasing the levels of serum testosterone and growth hormone, induced superior strength training adaptations compared to arm training without acute elevation of hormones.
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We investigated the effects of sleep deprivation with or without acute supplementation of caffeine or creatine on the execution of a repeated rugby passing skill. Ten elite rugby players completed 10 trials on a simple rugby passing skill test (20 repeats per trial), following a period of familiarisation. The players had between 7-9 h sleep on 5 of these trials and between 3-5 h sleep (deprivation) on the other 5. At a time of 1.5 h before each trial, they undertook administration of either: placebo tablets, 50 or 100 mg/kg creatine, 1 or 5 mg/kg caffeine. Saliva was collected before each trial and assayed for salivary free cortisol and testosterone. Sleep deprivation with placebo application resulted in a significant fall in skill performance accuracy on both the dominant and non-dominant passing sides (p < 0.001). No fall in skill performance was seen with caffeine doses of 1 or 5 mg/kg, and the two doses were not significantly different in effect. Similarly, no deficit was seen with creatine administration at 50 or 100 mg/kg and the performance effects were not significantly different. Salivary testosterone was not affected by sleep deprivation, but trended higher with the 100 mg/kg creatine dose, compared to the placebo treatment (p = 0.067). Salivary cortisol was elevated (p = 0.001) with the 5 mg/kg dose of caffeine (vs. placebo). Acute sleep deprivation affects performance of a simple repeat skill in elite athletes and this was ameliorated by a single dose of either caffeine or creatine. Acute creatine use may help to alleviate decrements in skill performance in situations of sleep deprivation, such as transmeridian travel, and caffeine at low doses appears as efficacious as higher doses, at alleviating sleep deprivation deficits in athletes with a history of low caffeine use. Both options are without the side effects of higher dose caffeine use.
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This study examined the relationships between salivary testosterone (Sal-T) and cortisol (Sal-C) concentrations and training performance in Olympic weightlifters. Four male and four female Olympic weightlifters each provided saliva samples before and after four workouts during a four-week training period. Training involved the same three exercises; snatch, clean and jerk, and front squat with the one repetition maximum (1RM) calculated for each exercise during each workout. Significant (P < 0.05-0.01) training improvements in 1RM performance (4.0-5.2%) were noted during the snatch and clean and jerk exercises, along with the Olympic total lift. For male participants only, the pre-workout concentrations of Sal T were significantly (P < 0.05-0.01) correlated with the snatch (r = 0.70) and clean and jerk 1RM (r = 0.62), and the Olympic total lift (r = 0.66). A short period of training improved the 1RM performance of Olympic weightlifters in two exercises (snatch and clean and jerk) and the Olympic total. For male participants, their Sal-T concentrations before each workout was also related to 1RM performance during these exercises, thereby highlighting one possible short-term causative mechanism. Limitations of this study include the short duration of hormonal monitoring, the limited number of workouts assessed and the small number of participants recruited. Also, correlations between the outcome variables still only reflect casual associations.
We explored whether caffeine, and expectation of having consumed caffeine, affects attention, reward responsivity and mood using double-blinded methodology. 88 participants were randomly allocated to 'drink-type' (caffeinated/decaffeinated coffee) and 'expectancy' (told caffeinated/told decaffeinated coffee) manipulations. Both caffeine and expectation of having consumed caffeine improved attention and psychomotor speed. Expectation enhanced self-reported vigour and reward responsivity. Self-reported depression increased at post-drink for all participants, but less in those receiving or expecting caffeine. These results suggest caffeine expectation can affect mood and performance but do not support a synergistic effect.
The purpose of this investigation was to determine the effect of ingested caffeine, sodium bicarbonate, and their combination on 2,000-m rowing performance, as well as on induced alkalosis (blood and urine pH and blood bicarbonate concentration [HCO3-]), blood lactate concentration ([La-]), gastrointestinal symptoms, and rating of perceived exertion (RPE). In a double-blind, crossover study, 8 well-trained rowers performed 2 baseline tests and 4 × 2,000-m rowing-ergometer tests after ingesting 6 mg/kg caffeine, 0.3 g/kg body mass (BM) sodium bicarbonate, both supplements combined, or a placebo. Capillary blood samples were collected at preingestion, pretest, and posttest time points. Pairwise comparisons were made between protocols, and differences were interpreted in relation to the likelihood of exceeding the smallest worthwhile-change thresholds for each variable. A likelihood of >75% was considered a substantial change. Caffeine supplementation elicited a substantial improvement in 2,000-m mean power, with mean (± SD) values of 354 ± 67 W vs. placebo with 346 ± 61 W. Pretest [HCO3-] reached 29.2 ± 2.9 mmol/L with caffeine + bicarbonate and 29.1 ± 1.9 mmol/L with bicarbonate. There were substantial increases in pretest [HCO3-] and pH and posttest urine pH after bicarbonate and caffeine + bicarbonate supplementation compared with placebo, but unclear performance effects. Rowers' performance in 2,000-m efforts can improve by ~2% with 6 mg/kg BM caffeine supplementation. When caffeine is combined with sodium bicarbonate, gastrointestinal symptoms may prevent performance enhancement, so further investigation of ingestion protocols that minimize side effects is required.
The primary aim of the study was to determine the efficacy of acute caffeine intake to enhance intense resistance training performance. Fourteen resistance-trained men (age and body mass = 23.1 ± 1.1 years and 83.4 ± 13.2 kg, respectively) who regularly consumed caffeine ingested caffeine (6 mg · kg(-1)) or placebo 1 hour before completion of 4 sets of barbell bench press, leg press, bilateral row, and barbell shoulder press to fatigue at 70-80% 1-repetition maximum. Two minutes of rest was allotted between sets. Saliva samples were obtained to assess caffeine concentration. The number of repetitions completed per set and total weight lifted were recorded as indices of performance. Two-way analysis of variance with repeated measures was used to examine differences in performance across treatment and sets. Compared to placebo, there was a small but significant effect (p < 0.05) of acute caffeine intake on repetitions completed for the leg press but not for upper-body exercise (p > 0.05). Total weight lifted across sets was similar (p > 0.05) with caffeine (22,409.5 ± 3,773.2 kg) vs. placebo (21,185.7 ± 4,655.4 kg), yet there were 9 'responders' to caffeine, represented by a meaningful increase in total weight lifted with caffeine vs. placebo. Any ergogenic effect of caffeine on performance of fatiguing, total-body resistance training appears to be of limited practical significance. Additional research is merited to elucidate interindividual differences in caffeine-mediated improvements in performance.