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Nutrition and indoor cycling: A cross-sectional analysis of carbohydrate intake for online racing and training

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Cycling is a sport characterised by high training load and adequate nutrition is essential for training and race performance. With increased popularity of indoor trainers, cyclists have a unique opportunity to practice and implement key nutritional strategies. This study aimed to assess carbohydrate intake and nutrition knowledge of cyclists training or racing in this unique scenario for optimising exercise nutrition. A mixed-methods approach consisting of a multiple-pass self-report food recall and questionnaire was used to determine total carbohydrate intake pre, during and post training or racing using a stationary trainer and compared to current guidelines for endurance exercise. Sub-analyses were also made for higher ability cyclists (>4.W.kg ⁻¹ functional threshold power), races vs. non-races and ‘key’ training sessions. Mean CHO intake pre and post ride was 0.7±0.6 and 1.0±0.8 g.kgBM ⁻¹ and 39.3±27.5 g.h ⁻¹ during. Carbohydrate intake was not different for races (pre/during/post, p=0.31, 0.23, 0.18 respectively), ‘key sessions’ (p=0.26, 0.89, 0.98), or higher ability cyclists (p=0.26, 0.76, 0.45). The total proportion of cyclists who failed to meet CHO recommendations was higher than those who met guidelines (pre=79%, during=86%, post=89%). Cyclists training or racing indoors do not meet current CHO recommendations for cycling performance. Due to the short and frequently high-intensity nature of some sessions, opportunity for during exercise feeding may be limited or unnecessary.
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This peer-reviewed article has been accepted for publication but not yet copyedited or
typeset, and so may be subject to change during the production process. The article is
considered published and may be cited using its DOI
10.1017/S0007114521001860
The British Journal of Nutrition is published by Cambridge University Press on behalf of The
Nutrition Society
Nutrition and indoor cycling: A cross-sectional analysis of carbohydrate intake for
online racing and training
Andy J King1, Rebecca C Hall1,2,3
1Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne,
Australia
2Olympic Winter Institute of Australia, Docklands, Melbourne, Australia
3Victorian Institute of Sport, Albert Park, Melbourne, Australia
Corresponding Author: Andy J King, Mary Mackillop Institute for Health Research, 215
Spring Street, Melbourne, Victoria, 3000, Australia, Email: andy.king@acu.edu.au
Short Title
Carbohydrate intake during indoor cycling
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Abstract
Cycling is a sport characterised by high training load and adequate nutrition is essential for
training and race performance. With increased popularity of indoor trainers, cyclists have a
unique opportunity to practice and implement key nutritional strategies. This study aimed to
assess carbohydrate intake and nutrition knowledge of cyclists training or racing in this
unique scenario for optimising exercise nutrition. A mixed-methods approach consisting of a
multiple-pass self-report food recall and questionnaire was used to determine total
carbohydrate intake pre, during and post training or racing using a stationary trainer and
compared to current guidelines for endurance exercise. Sub-analyses were also made for
higher ability cyclists (>4.W.kg-1 functional threshold power), races vs. non-races and ‘key’
training sessions. Mean CHO intake pre and post ride was 0.7±0.6 and 1.0±0.8 g.kgBM-1 and
39.3±27.5 g.h-1 during. Carbohydrate intake was not different for races (pre/during/post,
p=0.31, 0.23, 0.18 respectively), ‘key sessions’ (p=0.26, 0.89, 0.98), or higher ability cyclists
(p=0.26, 0.76, 0.45). The total proportion of cyclists who failed to meet CHO
recommendations was higher than those who met guidelines (pre=79%, during=86%,
post=89%). Cyclists training or racing indoors do not meet current CHO recommendations
for cycling performance. Due to the short and frequently high-intensity nature of some
sessions, opportunity for during exercise feeding may be limited or unnecessary.
Keywords: Exercise, food, diet, metabolism, stationary cycling, cycling
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Background
Endurance cycling (road, mountain, gravel) is a sport characterised by prolonged periods of
steady-state power output with stochastic efforts in the heavy and severe intensity domains
[1], requiring adequate CHO consumption from exogenous and endogenous (liver and muscle
glycogen) sources. Recent evidence for withholding CHO from certain sessions, i.e.
periodised nutrition for endurance adaptations shows promise [2], but athletes have
historically recognised the value of ‘key’ sessions within the training cycle, where high
intensity performance and/or practice of race intensities are needed. Therefore adequate CHO
consumption is suggested [3, 4] signifying the important role of sports nutrition. In recent
years, rapid improvement in ‘turbo-trainer’ technology and increased popularity in amateur
cycling has led to the advent of online racing and training platforms, such as ‘Zwift’,
‘Sufferfest’ and ‘TrainerRoad’, gaining substantial subscribers in the previous 2-3 years [5].
On-bike nutrition can be challenging due to tactical and bike-handling requirements of racing
not allowing suitable feeding opportunity, and long training rides limiting the ability to carry
sufficient fuel. CHO consumption during training can also enhance gut tolerance and
intestinal absorption capacity [6, 7].
In order to maximise performance and mitigate exercise induced disturbances to energy
balance, current nutrition guidelines [16] for endurance exercise recommend athletes
consume 1-4 g of CHO per kilogram of body mass (referred to as g.kg-1 from hereon)
between 1 and 4 hours prior to exercise. For rides lasting between one and two hours, it is
recommended athletes consume up to 60 g.h-1 CHO during exercise [17], but up to 90 g.h-1,
consisting of multiple transportable CHO is advised for longer duration exercise [18] where
optimal performance is desired, rather than training where duration (<1 hour) and intensity
are low, or where metabolic fat adaptation is specifically sought. For optimal recovery, CHO
recommendations are to aim for 1.0-1.2 g.kg-1 CHO within the hour following exercise, with
repetition of this every hour for the first 4 hours in the instance of a second key session or
race <8 hours [8]. However, amateur athletes training in their usual environments do not
meet nutrition recommendations pre or post-exercise [19], and the discrepancy between
recommendations and actual CHO intake during exercise is apparent in both elite and sub-
elite athletes [9]. The unique environment created by indoor cycling presents an opportunity
for athletes to successfully meet nutritional requirements due to the ability to source food and
fluid at home.
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The aim of this study was to determine if athletes racing and training indoors with online
platforms meet current CHO recommendations for exercise performance. It was hypothesised
that cyclists would not meet overall current CHO recommendations but would meet during
exercise targets, planned session intensity would relate to higher CHO intake, cyclists of
higher ability would achieve better pre, during and post-ride CHO intake, and cyclists
identifying as well-trained and identifying the session as a ‘key’ session or race would be
more likely to meet CHO recommendations.
Methods
Participants and Study Design
This cross-sectional, observational study assessed food intake pre, during and post a cycling
based training session conducted using an indoor trainer by using a mixed-methods
(qualitative and quantitative) questionnaire. The study was available to cyclists of any ability
who had completed an indoor training ride or online race in the preceding 24 hours (to reduce
recall bias). Study recruitment was through professional networks, word-of-mouth, and social
media platforms (Twitter/Facebook). The study was conducted in accordance with the
Declaration of Helsinki and approved by the Australian Catholic University Human Research
Ethics Committee (HREC-2020-125E). Participants provided informed consent, their main
cycling discipline, typical duration of indoor training sessions, if they considered themselves
competitive (defined by either online or traditional races), highest level of competition, and
years of competitive experience. Session specific information included self-reported current
body mass, functional threshold power (FTP), if the session was a race, perceived session
intensity (‘moderate’, ‘high’ or ‘very high’), session duration and average power output (if
using a smart trainer or power meter), and if the session was considered a ‘key’ session,
defined as where training quality, high-intensity performance, and/or practice of race
conditions is required [4]. FTP was provided by participants from a known 20-minute time
trial test or calculated by a cycling software program if it had been conducted within the
previous 2 weeks.
Online Questionnaire Design
The questionnaire was in English and consisted of 81 questions encompassing demographics,
ride details, food recall, fluid and supplements consumed in 3 distinct time periods around the
session; hours prior (pre), during and following (post). The questionnaire was built and run
using specialised software (REDCap, Tennessee, USA). Detailed instructions were provided
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at the start of each sub-section to reiterate the detail required; quantities in known units,
brands and specified food types to be provided. The multi-pass method for food recall [8]
was used, with focused, prompting questions to enhance diet recall. Questions were also
included to determine the time of the session and food and drink intake, including what meal
(including ‘snack’) participants considered pre and post-ride intake. Qualitative, open-ended
questions were used to allow participants to expand on ‘anything missed’ for each period of
food intake as well as to qualify their decisions around food timing and composition. Also to
ask if time of day affected food choice.
Data Analysis and Statistics
Demographic and ride detail data were checked for completeness and relative FTP calculated
[reported FTP (W) / body mass (kg)]. Analyses performed to differentiate effects of ‘trained
cyclists’ were made using an FTP >4.0 W.kg-1. Diet recall data was quantified by an
Accredited Practising Dietitian using FoodWorks-10 (Xyris, Australia). Quantified data were
then compared to CHO guidelines for cycling in the context of ride intensity and duration [3,
9]. If a diet recall for pre, during or post was provided without specified quantity or detail,
that record was excluded from analysis for the given intake period. Responses were labelled
to note food composition, fluid and supplement choices including ‘CHO’, ‘protein’, ‘high
fat’, ‘supplements’, ‘sports foods’ and ‘caffeine’. Open-ended questions were analysed using
thematic analysis, with coded responses combined after independent analysis by two
researchers. Where applicable, responses and themes were tallied to allow both a quantitative
and qualitative representation of responses.
Responses were counted for the number of participants who met pre, during or post-exercise
CHO intake recommendations and are presented as a total number and percentage of the total
number of responses for each subsection. Comparisons for CHO intake between ‘key
sessions’, ‘trained cyclists’ and all sessions were conducted by one-way ANOVA with Tukey
post hoc adjustment where applicable (alpha level: 5%). Cohen’s D effect sizes were
calculated for comparisons where relevant. Box and whisker plots are presented for pre,
during and post-exercise CHO intake.
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Results
A total of 106 responses were collated between 26/06/2020 and 19/08/2020. Figure 1
outlines where sufficient data was present to report nutritional intake for each stage of the
sessions, i.e. pre-ride, during and post-ride. 76 responses were identified as providing detailed
information about of at least pre-ride, during or post-ride session nutritional intake.
Breakdown of participant information is contained in table 1.
Training Sessions
Forty sessions were reported as ‘key’ and 21 as races. Of these, 15 were identified as both
‘key’ and race, with 31 neither of these. Nutrition data are reported for all sessions, and
subgroup analyses reported with sessions removed meeting the following criteria for not
being a ‘key session’. Relative session intensity was reported by 57 participants and were
(%FTP): >100%=6, 90-100%=11, 80-90%=20, 70-80%=8, 60-70%=8, 50-60%=3 and 40-
50%=1. Qualitative self-reported intensity was given by 74 participants and included: ‘very
high’=12, ‘high’=25 and ‘moderate’=37. Session duration was predominantly between 45
and 120 minutes (45-60 minute=32 and 60-120 minutes=27), with 8 sessions reported as
being >120 minutes, and 7 sessions <45 minutes. 2 were not reported. The time of day
sessions were completed was 0000-0600=5, 0600-1200=30, 1200-1800=22, 1800-2359=19.
Pre-ride Nutrition
To the question “did you eat or drink anything in the 4 hours before this ride or race (a meal
and or a snack or something to drink)?”, 89% of participants responded that they consumed
something prior to their session, of which 9% did not consume any CHO. For sessions of all
duration, 73% of all participants consumed <1 g.kg-1 of CHO in the 4 hours pre-ride (Table
2), with 20% of these consuming zero CHO. Data for each session duration are presented in
Table 2, with the highest proportion of participants meeting pre-exercise CHO intake
recommendations for sessions lasting 60-120 minutes and sessions >120 minutes. Overall,
26% of participants consumed 1-4 g.kg-1 of CHO, which was higher among ‘trained’ cyclists
(39%) and for ‘key sessions’ (35% of all ‘key sessions’). Figure 2 shows the distribution of
intakes for all sessions, however, mean intake did not differ between all sessions, ‘key
sessions’ and ‘trained cyclists’ (0.7±0.6 vs. 0.8±0.6 vs. 0.9±0.8 g.kg-1, p=0.26). However,
average CHO intake for participants that consumed some pre-exercise CHO was slightly
higher in ‘trained’ cyclists at 1.2±0.7 g.kg-1 (ES=0.33, p=0.06). Average CHO intakes for
each session duration are in Table 2, being highest for sessions lasting >120 minutes. Total
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pre-ride CHO intake did not differ between sessions identified as races or non-races for total
CHO (55.9±40.5 vs. 45.337.4 g; ES=0.27, p=0.31) or relative CHO intake (0.68±0.61 vs.
0.81±0.62 g.kg-1, ES=0.29, p=0.42).
Data relating to timing and type of food intake pre-ride is presented in Figure 4. 89% of
participants reported eating pre-ride food as either part of a regular meal, most commonly
breakfast, or a snack. The time prior to exercise that participants consumed food or drink was
between 0 (n=4) and 4 hours (7, 9.2%), with 28% of participants consuming food or drink <1
hour pre-ride, and 34% between 1-3 hours prior. The distribution of eating time prior to
exercise was similar for all ride durations (p = 0.07). 53% of participants stated that the time
of day they ate affected the quantity of food/drink they consumed. This was qualified by
asking “If yes, then how did it affect how much you ate?”. Accordingly, 11 participants
reported eating less than usual, 2 reported eating more, and 1 the same amount. Seven
participants deliberately ate nothing due to the time of day, 1 person reported eating an
“additional snack” and 2 people “ate enough to feel full but avoid GI issues”. However, 13
participants also reported food timing as a consideration; 9 stating the session was too early
to eat, and 3 adjusted food timing to account for an early training session. Two participants
noted the session intensity being “hard” influenced their food intake. Considering types of
food and drink consumed pre-ride, 70% of participants specifically listed fluid intake , 75%
consumed some CHO, 45% used caffeine containing foods/drinks, 5% took supplements
(5%), 11% ate high fat foods, 5% used sports specific foods/products, and 2.5% chose gluten
free foods.
During Ride Nutrition
A total of 78% of participants reported consuming some food or drink during their ride.
However, of these, 54% did not consume any food/drink with energy content, recording
water, zero-calorie electrolyte drinks or coffee/caffeine supplements as ‘fuel’. Together with
participants who reported not fuelling during their ride, 74% did not consume any CHO
during exercise. The number of participants who fuelled during ‘key’ sessions did not differ
for all sessions types; 78% of participants reported food/drink intake but 50% did not
consume any CHO. Mean CHO intake was 9.4±21.3 g.h-1 for all sessions and was not
different between non-races and races (6.5±16.5 g.h-1 vs. 13.6±23.2 g.h-1, ES=0.35, p=0.23)
or to ‘key sessions’ (10.2±20.9 g.h-1, p=0.84) or ‘trained cyclists’ (9.5±20.9 g.h-1, p=1.00).
Where participants did consume CHO during-ride, the average intake was 39.3±27.5 g.h-1
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and not significantly different for ‘key sessions’ (36.9±26.3 g.h-1, ES=0.08, p=0.89) or
‘trained cyclists’ (43.6±27.7 g.h-1, ES=0.15, p=0.76). Intakes were identical between races
and non-races (p=0.95). Data for each duration are presented in Table 3 and with no
differences for session time. Sources of during-ride food and drink are shown in Figure 3,
largely being comprised of commercially available drinks, gels and solid foods. Responses to
the question “If no, please state why you did not consume or drink anything during your
recent ride?”, are also presented in Figure 3.
Post-ride Nutrition
For all sessions 49% of participants consumed <1 g.kg-1 of CHO post-ride (Table 4), with
13% of these consuming no food/drink and 7% consuming food/drink containing no CHO. In
total 70% of participants consumed <1.0 g.kg-1, 13% consumed 1-1.2 g.kg-1, 11% consumed
1.2-2.0 g.kg-1 and 6% consumed >2 g.kg-1 (Figure 2). For long sessions (60-240 minutes)
12% consumed 1-1.2 g.kg-1 post-ride, 25% consumed between 1.2-2.0 g.kg-1 and 4%
consumed 2.0-4.0 g.kg-1. For sessions <1 hour, 66% of participants consumed <1.0 g.kg-1,
19% participants consumed 1-1.2 g.kg-1, 6% consumed 1.2-2.0 g.kg-1 and 9% consumed >2.0
g.kg-1. For ‘key sessions’ 50% of participants consumed <1 g.kg-1, including 23% of
participants who ate no CHO. Of the ‘trained cyclists’ none reported eating zero CHO, but
the 58% consumed <1.0 g.kg-1 8% consuming 1.2-2.0 g.kg-1.
Mean CHO consumption post-ride was 55.9±42.8 g across all sessions. Mean CHO intakes
for each session duration are in Table 4 and were highest for sessions lasting <45 minutes,
but similar to pre-ride, the smaller sample is noted. Total post-ride CHO intake did not differ
between sessions identified as races or non-races for total (76.5±64.3 vs. 55.9±42.8 g;
ES=0.29, p=0.22) or relative CHO (0.9±0.7 vs. 1.1±1.0 g.kg-1, ES=0.18, p=0.55, Table 4).
Mean post-ride intake in ‘trained cyclists’ was not different compared to all participants
(1.0±0.8 g.kg-1, ES=0.20, p=0.45).
Seventy-five percent of participants reported post-exercise food intake was part of a meal;
dinner (36%), breakfast (20%) and 25% reported post-ride intake as a snack (Figure 4). Post-
ride intake occurred <10 minutes for 2 participants, however the majority (32, 46%)
consumed their post-ride intake within the recommended one hour, with 17 (25%) eating 1-2
hours post-exercise. Ten participants consumed some food or drink in multiple sittings in the
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4 hours post-ride. The mean intake time in minutes post-ride for each ride duration was: <45
minutes; 78±70, 45-60 minutes; 31±15, 60-120 minutes; 52±32, 120-240 minutes; 32±30.
The number of participants that stated the time of day they ate affected the quantity of
food/drink they consumed was similar (45% “yes”/55% “no”). As for pre-ride this was
qualitatively assessed. Responses from the 4 participants who did not eat anything in the 4
hours post-ride included “I went to bed”, “waited for dinner/was an intense session” and
“didn’t need to”. Three participants reported eating less than usual, one stating “ate enough to
fuel but not puke”, a participant who consumed their post-ride intake within 40 minutes and
one who “didn’t want to overeat before going to bed”. Two participants specifically noted
eating the same, based on the usual meal at that time of day, but six participants reported
eating more than usual due to the session. Three of these noted “hunger” driving this
decision. Nine responses noted food timing was affected by the ride, the time to bedtime was
noted on two occasions, and the timing of the session in relation to usual meal patterns was
noted by 5 participants. Eight participants also responded with statements to the effect of
“watching food intake”. For example, “I ate because I was hungry and to refuel after the
session”, “having milk-based snack to aid sleep”, “I felt like I ate a fair bit before ride so
didn't feel like I needed a huge amount after ride”, “I am not hungry after training and it's
difficult to eat because I am working” and “ate a lot of carbs and some protein immediately
after for recovery” highlight sports nutrition considerations by participants. Of food/drink
types consumed post-ride, 64% specifically listed fluid intake, 80% consumed some CHO,
23% used caffeine, 65% consumed some protein, 7% took supplements and 7% drank
alcohol.
Discussion
This is the first study to investigate the nutrition practice of cyclists undertaking indoor,
stationary training or competition. The primary outcome of this cross-sectional analysis of
athletes’ food intake is that cyclists do not implement CHO recommendations for endurance
performance despite the ideal environment of riding indoors. Data for pre, during and post-
ride indicate significantly suboptimal CHO intake for ‘key’ training sessions or races at all
three important time points for exercise nutrition, meaning cyclists are not adequately
fuelling sessions leading to likely under performance [10, 11]. A significant proportion (75%)
of cyclists also consumed no CHO during sessions where CHO fuelling is known to be
beneficial, which was not hypothesised given the advantageous scenario of practicing optimal
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race day nutrition compared to outdoor cycling. This study also demonstrates that although
CHO intake was suboptimal, cyclists training or competing indoors have adequate nutrition
knowledge relating to exercise CHO intake. Despite being seemingly well aware of the
requirements of appropriate fuelling, this has not translated to practice and was unaffected by
session duration, intensity, or training status.
Cyclists undertaking ‘key’ training sessions should consume adequate CHO around the
session, in order to provide optimal fuel for exercise power output and to support recovery
and glycogen resynthesis [12]. Here cyclists did not consume sufficient CHO as measured by
either the number meeting recommendations or mean intake. Critically we observed that a
high proportion of cyclists do not consume any CHO during indoor sessions, and this is not
differentiated during ‘key’ sessions or races. The term fuelling is currently used in sports
nutrition to refer to a food or fluid option that contributes energy to intake. Interestingly there
were a number of individuals (38) in this study who answered “yes” to fuelling during their
ride but subsequently only reported non-calorie or very low-calorie beverage consumption.
The wording of the question could perhaps have been improved with a definition of fuelling,
but the number of similar responses suggest this term is not well understood or appropriate
when used in isolation. Due to the combination of high intensity and duration often present in
‘key’ sessions CHO intake supports sustained power output where sessions are longer than
~45 minutes [13]. Where cyclists did consume CHO during exercise, mean intakes were ~35-
40 g.h-1 which although conferring some metabolic and performance advantage over zero
CHO consumption [14, 15], also suggests reasons exist preventing higher consumption. CHO
intakes of 80-90g.h-1 may be beneficial for longer sessions with combined glucose:fructose
composition [10, 16-18].
Consuming CHO during training can enhance gut tolerance and intestinal absorption capacity
[19]. Although mechanisms to this effect are not fully determined [20], the unique indoor
environment allows athletes to have sufficient CHO within reach to achieve higher intake
without the demands of carrying it on the bike. Indoor training also allows athletes to practice
on-bike feeding within the relative comfort of their own home or gym, whereby immediately
terminating training due to GI distress is possible. Therefore, we hypothesised that cyclists
training indoors would consume CHO during exercise in sufficient quantity to meet
recommendations, which was not observed. Unfortunately, too few participants reported
qualitative data on their decision making for during exercise CHO intake and firm
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explanations for this under fuelling are therefore not possible. However, the responses
received noted the lack of need to fuel due to perceived session demands. This is despite only
8 of the 76 total responses in the study dealing with sessions <45 minutes, where CHO intake
is not required [21], or mouth-rinse strategies can provide ergogenic benefits during race
conditions [22], especially if fasted [23]. On-bike nutrition can be met through the use of
homemade solutions, or commercially available products, including hydrogels, which have
anecdotal support to mitigate GI issues [24]. In light of this finding, it is suggested that
cyclists consider the role of indoor training to practice and optimise individual CHO intake
while heeding nutrition recommendations, with the understanding that self-made CHO
supplementation is a suitable strategy if required [21, 25]. Where cyclists consumed some
CHO during exercise, consumption in the present study is in line with professional cyclists’
intake during a stage of the Vuelta A Espana [26], that is, notably lower than current
guidelines. However, data from the 1989 Tour de France indicate professional cyclists can
and do meet 90 g.h-1 targets if required to [27]. However, comparisons to elite bike racing are
made with caution due to anticipated differences in habitual practice and CHO consumption
knowledge to the current cohort, as well as the fact the current study assessed CHO intake in
a novel environment. As such future research is required to fully elucidate if CHO intake
differs between indoor racing and training and outdoor cycling.
Pre and post-ride CHO intake were also substantially below suggested ranges, further
compromising performance during races or ‘key’ sessions. Whilst shorter sessions may not
benefit from pre-exercise CHO, sessions lasting >/=60 minutes benefit from replenishing
liver glycogen stores following overnight fasts or periods between meals [28, 29]. Therefore,
the target of consuming 1-4 g.kg-1 in the 1-4 hours prior to exercise is broad, and we
speculate this may cause some confusion as to specific, individualised approaches needed for
different athletes and sessions. However, this was not highlighted by participants, but due to
constraints of questionnaire length this could be further investigated in future. Post-ride CHO
intake was similarly under consumed, meaning participants were likely compromising
recovery energy intake as CHO plays a significant role in exercise adaptation [30, 31] and
immune system health [32]. Mean CHO intake post-ride was 0.84 g.kg-1, but was higher
following sessions lasting 60-120 minutes (1.13 g.kg-1) indicating the possibility that
participants were either aware of the need to replenish CHO stores, or appetite was
sufficiently stimulated, leading to increased CHO consumption. We were unable to directly
test these effects. Despite this, CHO intake was substantially below requirements and is in
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agreement with season long data from Viner et al. [33]. The data for sessions lasting >120
minutes in the current study are reported with the caveat that several of the food records were
insufficiently complete to determine accurate CHO intake. Similarly, memory-based food
recall methods have limitations to their accuracy of actual food intake [34], although the
multiple-pass method mitigates some reporting error [8]. Despite a higher prevalence of
insufficient food intake data in the post-ride period, the majority of participants under
consumed CHO, reflecting a possible limitation in the length of the questionnaire.
Furthermore, due to the much narrower CHO intake target for immediate post-exercise intake
(1-1.2 g.kg-1), mean intakes post-ride are less likely to be ‘on target’ despite the fact that
small deviations either way, particularly with higher intakes in this cohort, are unlikely to be
harmful. Considering the context of a single session in an athlete’s training program is
essential, but despite this, few athletes reported the need to recover or prepare for their next
session when reflecting on their post-session food intake.
An important facet of sports nutrition is understanding athlete behaviour, beliefs and diet
education [35]. We attempted to qualify cyclists’ practice by including open questions to
determine if, and how, any factors influenced the time of day and type of food that was
consumed pre and post-ride. Despite choosing to compare to the gold standard of nutrition
recommendations for elite cyclists, all sports nutrition advice should, and is typically,
individualised to the athlete and further periodised to their training goals. We acknowledge
limitations in the study design not allowing thorough and in depth interrogation of all
elements of food intake around the sessions or the days prior and following, but the
constraints of time for the quantitative element of the study questionnaire did not allow such
investigation. However, cyclists reported the time of day and/or session timing significantly
influenced their pre-ride food intake (timing and quantity), especially where sessions were in
the early morning. Given that participants significantly under consumed CHO prior to their
session, consuming on average only 0.67 g.kgBM-1, it would be interesting to know with
those who opted for a snack whether this was additional to normal intake or a regular snack
incorporated in daily meal pattern irrespective of training. In this way, snacking or
consuming extra meals would present an immediate solution to increasing CHO intake,
especially given only 30% of elite endurance athletes consume CHO based foods, gels or
drinks prior to ‘key sessions’ [4]. Future research may wish to focus on athletes’ awareness
and practitioner measurement of [low] energy availability (LEA) which is widely recognised
to impair numerous physiological functions critical to exercise performance and adaptation
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Accepted manuscript
[36]. However, assessment of LEA requires access to the athlete and a laboratory, which was
beyond the remit of this study. Future research would ideally explore the reasons behind this
observed sub-optimal fuelling and closely examine the prospect of poor within-day energy
availability.
This study has limitations, including the cross-sectional study design. However, the
opportunity to capture nutritional practice of cyclists engaging in this type of training was
unique during 2020. Due to this being the first study to investigate sports nutrition practice in
this environment, the design provides novel and applicable data to the field in a timely
manner. A prospective study in a similar cohort would allow further depth regarding precise
food intake on a training day, but also capture the nutritional context of food intake and
training. It would also be interesting to investigate and qualify the behavioural and habitual
practice of cyclists racing and training indoors, but this was beyond the remit of the current
study. Due to the intensive nature of capturing accurate food intake, our goal was to
maximise recruitment and engagement to provide a preliminary report without overly
compromising session related food intake data, where the multi-pass method used increases
food recall. The mixed-methods design provides a useful perspective of some of the decision
making around CHO intake but due to concerns of questionnaire length, the study was not
able to fully elucidate participant behaviour or context in relation to food intake. In terms of
the qualitative component of the study, this could be enhanced and further investigated in
future work, and some concerns exist as to the inferential power of the current design for the
qualitative component [37]. Comparisons to previous studies are also difficult as no
investigations of athletes training in this environment have been conducted. However,
understanding practice of athletes in their usual training environments is crucial and can be
overlooked in sports nutrition, as food intake and the relation to energy expenditure are
complex bio-psycho-social structures [35, 38, 39]. Limitations also exist around the self-
report nature of key physiological variables such as FTP and body mass, as well as food
recall. ‘Digital doping’ is prevalent in online racing, whereby athletes under report body mass
or modify equipment to provide higher power output values. We anticipate such effects were
small, if not entirely absent due to research being anonymous and with little or no extrinsic,
competitive element. However, this cannot be entirely ruled out.
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Accepted manuscript
Conclusion
In conclusion, cyclists conducting training sessions using indoor means, do not meet sports
nutrition guidelines for CHO intake pre, during or post-ride. Therefore cyclists using indoor
training to achieve training targets should be mindful of appropriately fuelling these sessions.
Coaches and practitioners should also be aware that athletes may not achieve suggested CHO
intakes around ‘key’ training sessions requiring high CHO availability despite good
knowledge of session demands. Athletes should focus on consuming sufficient CHO before
& during sessions to increase glycogen storage and exercising CHO oxidation where
maximum performance outcomes involving prolonged high intensity or high quality outputs
are required.
List of Abbreviations
CHO carbohydrate
ES effect size
FTP functional threshold power
LEA low energy availability
SD standard deviation
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Accepted manuscript
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Accepted manuscript
Declarations
Ethics approval and consent to participate
This study was approved by the Australian Catholic University Human Research Ethics
Committee (number; HREC-2020-125E) and were in agreement with the Declaration of
Helsinki.
Financial Support
There are no funders to report for this submission
Consent for publication
n/a
Availability of data and materials
The datasets used and/or analysed during the current study are available from the
corresponding author on reasonable request.
Competing interests
Author AK declares to have no competing interests. RH works with VIS cycling, but no
contribution was made by this body to the study.
Authors' contributions
AK & RH were responsible for study conception, data collection, analysis and preparing and
reviewing the manuscript.
Acknowledgements
The authors thank each participant who took the time to complete the survey during a
difficult year.
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Accepted manuscript
Table 1: Participant demographics
Body Mass (kg)*
71.3±14.3
FTP (W)*
(W.kg-1)*
261.7 ± 71.9
3.81 ± 0.83
Age
<18
18-24
25-29
30-34
35-39
40-44
45-49
50-54
55-59
60-64
not reported
1
8
7
12
12
11
9
9
2
1
4
Sex
Male
Female
not reported
34
23
19
Country of residence
Australia
UK
South Africa
Netherlands
Canada
New Zealand
USA
Spain
Portugal
Belgium
not reported
39
16
6
3
2
2
1
1
1
1
4
Cycling Discipline#
Road
Cyclocross
Endurance/ultra
MTB
45
3
7
6
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Accepted manuscript
not reported
1
Education
High school
(Advanced) diploma
Bachelor’s degree
Post grad cert/dip
Master’s degree
Doctorate
not reported
12
2
19
7
21
11
4
*self-reported data
#participants could identify >1 category
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Accepted manuscript
Table 2: Carbohydrate consumption pre-ride
Fuelled Pre-Ride?
(n)
CHO guidelines met?
CHO consumption
Session
duration
(min)
YE
S
NO
‘yes’*
YES
NO
n/a
(g)
(g)
[when
CHO
consumed]
(g.kgBM-1)
[when
CHO
consumed]
ALL
61
8
7
16
45
15
48.1 ± 38.3
60.1 ± 33.3
0.92 ± 0.56
< 45
7
0
0
1
5
1
51.6 ± 22.4
51.6 ± 22.4
0.74 ± 0.42
45-60
26
4
2
3
20
9
43.8 ± 40.2
55.8 ± 38.7
0.84 ± 0.64
60-120
21
2
4
8
15
4
51.0 ± 38.9
66.2 ± 30.7
0.97 ± 0.49
>120
7
2
1
4
5
1
52.1 ± 48.3
74.4 ± 29.5
1.17 ± 0.56
Data are total number of participants (column 2-4) and mean ± sd consumption (column 5-7).
n/a indicates where insufficient dietary information reported to quantify CHO intake.
* indicates participants answering YES to question “Did you eat or drink anything in the 4
hours before this ride or race (a meal and or a snack or something to drink)?” but who
consumed zero carbohydrate.
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Accepted manuscript
Table 3: Carbohydrate consumption during-ride
Fuelled During-Ride?
(n)
CHO consumption
Session
duration
YES
NO
YES (no
CHO
consumed)
(g)
(g/h)
[when CHO
consumed]
ALL
18
15
41
62.0 ± 52.8
39.3 ± 27.5
< 45 min
3
1
3
37.3 ± 38.2
49.8 ± 51.0
45-60 min
3
8
20
36.7 ± 7.3
36.7 ± 7.6
60-120 min
6
5
15
56.4 ± 33.7
37.6 ± 22.5
>120 min
6
1
3
92.5 ± 76.3
37.0 ± 30.5
Data are total number of participants (column 2-4) and mean ± sd consumption (column 5-7)
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Accepted manuscript
Table 4: Carbohydrate consumption post-ride
Ate/Drank Post-
Ride?
(n)
CHO guidelines
met?
CHO consumption
Session
duration
(min
YES
NO
‘yes’*
YES
NO
n/a
(g)
(g)
[when
CHO
consumed]
(g.kgBM-1)
ALL
65
4
2
7
40
24
57.1 ± 42.4
67.3 ± 42.4
0.84 ± 0.73
< 45
5
0
0
1
1
3
83.8 ± 54.0
83.8 ± 54.0
1.73 ± 0.98
45-60
27
2
0
3
17
9
50.2 ± 37.0
59.0 ± 37.0
0.72 ± 0.55
60-120
23
2
1
3
17
6
62.4 ± 47.7
74.1 ± 47.7
1.13 ± 0.80
>120
10
0
1
0
5
6
46.5 ± 37.8
62.0 ± 37.8
0.85 ± 0.42
Data are total number of participants (column 2-4) and mean ± sd consumption (column 5-7).
n/a indicates where insufficient dietary information reported to quantify CHO intake.
* indicates participants answering YES to question “Did you eat a meal or snack in the hours
after this ride or race?” but who consumed zero carbohydrate.
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Figure Titles
Figure 1: Flowchart of responses and data screening for pre, during and post session data
Figure Legend: NO LEGEND
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Figure 2: Total CHO intake pre, during and post ride and relative CHO intake
Figure Legend: post ride (panel A) and relative (per kg body mass) CHO intake (panel B).
Boxes represents median with 1st and 3rd quartile range, and whiskers maximum and
minimum values, excluding outliers (open circles; 1.5 x IQ range). X represents mean CHO
intake.
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Figure 3: CHO intake during sessions of all durations
Figure Legends: Circles represent individual CHO intakes; bars represent recommended
CHO targets for session duration.
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Figure 4: Response breakdown to questions “did you fuel” pre, during and post session
Figure Legends: Qualitative responses are represented as total numbers of a response
provided and grouped within themes. Qualitative responses are also presented as quotes from
participants where these highlight specific individual considerations.
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Article
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Key points: Reduced carbohydrate (CHO) availability before and after exercise may augment endurance training-induced adaptations of human skeletal muscle, as mediated via modulation of cell signalling pathways. However, it is not known whether such responses are mediated by CHO restriction, energy restriction or a combination of both. In recovery from a twice per day training protocol where muscle glycogen concentration is maintained within 200-350 mmol.kg-1 dw, we demonstrate acute post-exercise CHO and energy restriction (i.e. <24 hours) does not potentiate potent cell signalling pathways that regulate hallmark adaptations associated with endurance training. In contrast, consuming CHO before, during and after an acute training session attenuated markers of bone resorption, effects that are independent of energy availability. Whilst the enhanced muscle adaptations associated with CHO restriction may be regulated by absolute muscle glycogen concentration, the acute within day fluctuations in CHO availability inherent to twice per day training may have chronic implications for bone turnover. Abstract: We examined the effects of post-exercise carbohydrate (CHO) and energy availability (EA) on potent skeletal muscle cell signalling pathways (regulating mitochondrial biogenesis and lipid metabolism) and indicators of bone metabolism. In a repeated measures design, nine males completed a morning (AM) and afternoon (PM) high-intensity interval (HIT) (8 × 5-min at 85% VO2peak ) running protocol (interspersed by 3.5 hours) under dietary conditions of 1) high CHO availability (HCHO: CHO ∼12 g.kg-1 , EA∼ 60 kcal.kg-1 FFM), 2) reduced CHO but high fat availability (LCHF: CHO ∼3 g.kg-1 , EA∼ 60 kcal.kg-1 FFM) or 3), reduced CHO and reduced energy availability (LCAL: CHO ∼3 g.kg-1 , EA∼ 20 kcal.kg-1 FFM). Muscle glycogen was reduced to ∼200 mmol.kg-1 dw in all trials immediately post PM-HIT (P < 0.01) and remained lower at 17-h (171, 194 and 316 mmol.kg-1 dw) post PM-HIT in LCHF and LCAL (P < 0.001) compared to HCHO. Exercise induced comparable p38MAPK phosphorylation (P < 0.05) immediately-post PM-HIT and similar mRNA expression (all P < 0.05) of PGC-1α, p53 and CPT1 mRNA in HCHO, LCHF and LCAL. Post-exercise circulating βCTX was lower in HCHO (P < 0.05) compared to LCHF and LCAL, whereas exercise-induced increases in IL-6 were larger in LCAL (P < 0.05) compared to LCHF and HCHO. In conditions where glycogen concentration is maintained within 200-350 mmol.kg-1 dw, we conclude post-exercise CHO and energy restriction (i.e. < 24 hours) does not potentiate cell signalling pathways that regulate hallmark adaptations associated with endurance training. In contrast, consuming CHO before, during and after HIT running attenuates bone resorption, effects that are independent of energy availability and circulating IL-6. This article is protected by copyright. All rights reserved.
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Strong evidence during the last few decades has highlighted the importance of nutrition for sport performance, the role of carbohydrates (CHO) being of special interest. Glycogen is currently not only considered an energy substrate but also a regulator of the signaling pathways that regulate exercise-induced adaptations. Thus, low or high CHO availabilities can result in both beneficial or negative results depending on the purpose. On the one hand, the depletion of glycogen levels is a limiting factor of performance during sessions in which high exercise intensities are required; therefore ensuring a high CHO availability before and during exercise is of major importance. A high CHO availability has also been positively related to the exercise-induced adaptations to resistance training. By contrast, a low CHO availability seems to promote endurance-exercise-induced adaptations such as mitochondrial biogenesis and enhanced lipolysis. In the present narrative review, we aim to provide a holistic overview of how CHO availability impacts physical performance as well as to provide practical recommendations on how training and nutrition might be combined to maximize performance. Attending to the existing evidence, no universal recommendations regarding CHO intake can be given to athletes as nutrition should be periodized according to training loads and objectives.
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Purpose This study investigated the effect of small manipulations in carbohydrate (CHO) dose on exogenous and endogenous (liver and muscle) fuel selection during exercise. Method Eleven trained males cycled in a double-blind randomised order on 4 occasions at 60% \(\dot {V}{{\text{O}}_{2\;\hbox{max} }}\) for 3 h, followed by a 30-min time-trial whilst ingesting either 80 g h⁻¹ or 90 g h⁻¹ or 100 g h−1 13C-glucose-¹³C-fructose [2:1] or placebo. CHO doses met, were marginally lower, or above previously reported intestinal saturation for glucose–fructose (90 g h⁻¹). Indirect calorimetry and stable mass isotope [¹³C] techniques were utilised to determine fuel use. Result Time-trial performance was 86.5 to 93%, ‘likely, probable’ improved with 90 g h⁻¹ compared 80 and 100 g h⁻¹. Exogenous CHO oxidation in the final hour was 9.8–10.0% higher with 100 g h⁻¹ compared with 80 and 90 g h⁻¹ (ES = 0.64–0.70, 95% CI 9.6, 1.4 to 17.7 and 8.2, 2.1 to 18.6). However, increasing CHO dose (100 g h⁻¹) increased muscle glycogen use (101.6 ± 16.6 g, ES = 0.60, 16.1, 0.9 to 31.4) and its relative contribution to energy expenditure (5.6 ± 8.4%, ES = 0.72, 5.6, 1.5 to 9.8 g) compared with 90 g h⁻¹. Absolute and relative muscle glycogen oxidation between 80 and 90 g h⁻¹ were similar (ES = 0.23 and 0.38) though a small absolute (85.4 ± 29.3 g, 6.2, − 23.5 to 11.1) and relative (34.9 ± 9.1 g, − 3.5, − 9.6 to 2.6) reduction was seen in 90 g h⁻¹ compared with 100 g h⁻¹. Liver glycogen oxidation was not significantly different between conditions (ES < 0.42). Total fat oxidation during the 3-h ride was similar in CHO conditions (ES < 0.28) but suppressed compared with placebo (ES = 1.05–1.51). Conclusion ‘Overdosing’ intestinal transport for glucose–fructose appears to increase muscle glycogen reliance and negatively impact subsequent TT performance.
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