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Energy availability (EA) is defined as the amount of dietary energy available to sustain physiological function after subtracting the energetic cost of exercise. Insufficient EA due to increased exercise, reduced energy intake, or a combination of both, is a potent disruptor of the endocrine milieu. As such, EA is conceived as a key etiological factor underlying a plethora of physiological dysregulations described in the female athlete triad, its male counterpart and the Relative Energy Deficiency in Sport models. Originally developed upon female-specific physiological responses, this concept has recently been extended to males, where experimental evidence is limited. The majority of data for all these models are from cross-sectional or observational studies where hypothesized chronic low energy availability (LEA) is linked to physiological maladaptation. However, the body of evidence determining causal effects of LEA on endocrine, and physiological function through prospective studies manipulating EA is comparatively small, with interventions typically lasting ≤ 5 days. Extending laboratory-based findings to the field requires recognition of the strengths and limitations of current knowledge. To aid this, this review will: (1) provide a brief historical overview of the origin of the concept in mammalian ecology through its evolution of algebraic calculations used in humans today, (2) Outline key differences from the ‘energy balance’ concept, (3) summarise and critically evaluate the effects of LEA on tissues/systems for which we now have evidence, namely: hormonal milieu, reproductive system endocrinology, bone metabolism and skeletal muscle; and finally (4) provide perspectives and suggestions for research upon identified knowledge gaps.

Background Skeletal muscle glycogen is an important energy source for muscle contraction and a key regulator of metabolic responses to exercise. Manipulation of muscle glycogen is therefore a strategy to improve performance in competitions and potentially adaptation to training. However, assessing muscle glycogen in the field is impractical, and there are no normative values for glycogen concentration at rest and during exercise. Objective The objective of this study was to meta-analyse the effects of fitness, acute dietary carbohydrate (CHO) availability and other factors on muscle glycogen concentration at rest and during exercise of different durations and intensities. Data Source and Study Selection PubMed was used to search for original articles in English published up until February 2018. Search terms included muscle glycogen and exercise, filtered for humans. The analysis incorporated 181 studies of continuous or intermittent cycling and running by healthy participants, with muscle glycogen at rest and during exercise determined by biochemical analysis of biopsies. Data Analysis Resting muscle glycogen was determined with a meta-regression mixed model that included fixed effects for fitness status [linear, as maximal oxygen uptake ( V ˙ O 2max ) in mL·kg −1 ·min −1 ] and CHO availability (three levels: high, ≥ 6 g·kg −1 of CHO per day for ≥ 3 days or ≥ 7 g·kg −1 CHO per day for ≥ 2 days; low, glycogen depletion and low-CHO diet; and normal, neither high nor low, or not specified in study). Muscle glycogen during exercise was determined with a meta-regression mixed model that included fixed effects for fitness status, resting glycogen [linear, in mmol·kg −1 of dry mass (DM)], exercise duration (five levels, with means of 5, 23, 53 and 116 min, and time to fatigue), and exercise intensity (linear, as percentage of V ˙ O 2max ); intensity, fitness and resting glycogen were interacted with duration, and there were also fixed effects for exercise modes, CHO ingestion, sex and muscle type. Random effects in both models accounted for between-study variance and within-study repeated measurement. Inferences about differences and changes in glycogen were based on acceptable uncertainty in standardised magnitudes, with thresholds for small, moderate, large and very large of 25, 75, 150 and 250 mmol·kg −1 of DM, respectively. Results The resting glycogen concentration in the vastus lateralis of males with normal CHO availability and V ˙ O 2max (mean ± standard deviation, 53 ± 8 mL·kg −1 ·min −1 ) was 462 ± 132 mmol·kg −1 . High CHO availability was associated with a moderate increase in resting glycogen (102, ± 47 mmol·kg −1 ; mean ± 90% confidence limits), whereas low availability was associated with a very large decrease (− 253, ± 30 mmol·kg −1 ). An increase in V ˙ O 2max of 10 mL·kg −1 ·min −1 had small effects with low and normal CHO availability (29, ± 44 and 67, ± 15 mmol·kg -1 , respectively) and a moderate effect with high CHO availability (80, ± 40 mmol·kg −1 ). There were small clear increases in females and the gastrocnemius muscle. Clear modifying effects on glycogen utilisation during exercise were as follows: a 30% V ˙ O 2max increase in intensity, small (41, ± 20 mmol·kg −1 ) at 5 min and moderate (87–134 mmol·kg −1 ) at all other timepoints; an increase in baseline glycogen of 200 mmol·kg −1 , small at 5–23 min (28–59 mmol·kg −1 ), moderate at 116 min (104, ± 15 mmol·kg −1 ) and moderate at fatigue (143, ± 33 mmol·kg −1 ); an increase in V ˙ O 2max of 10 mL·kg −1 ·min −1 , mainly clear trivial effects; exercise mode (intermittent vs. continuous) and CHO ingestion, clear trivial effects. Small decreases in utilisation were observed in females (vs. males: − 30, ± 29 mmol·kg −1 ), gastrocnemius muscle (vs. vastus lateralis: − 31, ± 46 mmol·kg −1 ) and running (vs. cycling: − 70, ± 32 mmol·kg −1 ). Conclusion Dietary CHO availability and fitness are important factors for resting muscle glycogen. Exercise intensity and baseline muscle glycogen are important factors determining glycogen use during exercise, especially with longer exercise duration. The meta-analysed effects may be useful normative values for prescription of endurance exercise.

Endurance athletes fail to meet carbohydrate (CHO) guidelines for competition, which may be due to limited knowledge. However, the relationship between knowledge and practice in this population is unknown. To investigate this, we assessed the dietary intake in 50 athletes (37 females) who completed endurance events ≥2.5 h in duration and compared CHO intake against the carbohydrates for endurance athletes in competition questionnaire validated nutrition knowledge questionnaire, with specific questions related to CHO loading, pre‐competition meal and during‐competition intake. CHO‐loading guidelines (10–12 g · kg−1 · day−1) were met in practice by n = 5 (10%), but there was no relationship between identified requirements (range 0–12 g · kg−1 · day−1) and actual intake (rs = 0.133, p = 0.358), with the n = 18 (36%) who correctly identified requirements, ingesting 6.1 ± 1.9 g · kg−1 · day−1. CHO intake for pre‐competition meal guidelines (1–4 g · kg−1) was met in practice by n = 40 (80%), but there was no relationship between identified requirements (range 0 to >4 g · kg−1) and actual intake (rs = 0.101, p = 0.487), with n = 19 (38%) who correctly identified guidelines requirements, ingesting 1.4 ± 0.6 g · kg−1. CHO intake during‐competition guidelines (60–90 g · h−1) was met in practice by n = 18 (36%), but there was no relationship between the amounts of CHO required (range 30 to >90 g/h) and actual intake (rs = 0.028, p = 0.849), with n = 32 (64%) who correctly identified guidelines requirements, ingesting 56 ± 20 g · h−1. Results show no relationship between the knowledge of CHO recommendations and practice, suggesting that theoretical knowledge does not guarantee the achievement of best practice and other important factors may ultimately determine practice. Highlights The carbohydrates for endurance athletes in competition questionnaire (CEAC‐Q) score did not show any association between theoretical knowledge and actual intake for carbohydrate (CHO) loading, pre‐competition, or during competition scenarios, indicating that athletes do not necessarily apply what they know. Despite 30% of athletes meeting the guidelines for CHO loading, and CHO intake during competition, there was no clear relationship between practice and their knowledge of these guidelines as measured by the CEAC‐Q. The discrepancy between theoretical knowledge and actual intake within real‐world competition highlights that other factors may be important barriers and facilitators to translate scientific knowledge and bridge the gap into optimal dietary practices of endurance athletes.

The culture in many team sports involves consumption of large amounts of alcohol after training/competition. The effect of such a practice on recovery processes underlying protein turnover in human skeletal muscle are unknown. We determined the effect of alcohol intake on rates of myofibrillar protein synthesis (MPS) following strenuous exercise with carbohydrate (CHO) or protein ingestion. In a randomized cross-over design, 8 physically active males completed three experimental trials comprising resistance exercise (8×5 reps leg extension, 80% 1 repetition maximum) followed by continuous (30 min, 63% peak power output (PPO)) and high intensity interval (10×30 s, 110% PPO) cycling. Immediately, and 4 h post-exercise, subjects consumed either 500 mL of whey protein (25 g; PRO), alcohol (1.5 g·kg body mass⁻¹), 12±2 standard drinks) co-ingested with protein (ALC-PRO), or an energy-matched quantity of carbohydrate also with alcohol (25 g maltodextrin; ALC-CHO). Subjects also consumed a CHO meal (1.5 g CHO·kg body mass⁻¹) 2 h post-exercise. Muscle biopsies were taken at rest, 2 and 8 h post-exercise. Blood alcohol concentration was elevated above baseline with ALC-CHO and ALC-PRO throughout recovery (P<0.05). Phosphorylation of mTOR(Ser2448) 2 h after exercise was higher with PRO compared to ALC-PRO and ALC-CHO (P<0.05), while p70S6K phosphorylation was higher 2 h post-exercise with ALC-PRO and PRO compared to ALC-CHO (P<0.05). Rates of MPS increased above rest for all conditions (∼29-109%, P<0.05). However, compared to PRO, there was a hierarchical reduction in MPS with ALC-PRO (24%, P<0.05) and with ALC-CHO (37%, P<0.05). We provide novel data demonstrating that alcohol consumption reduces rates of MPS following a bout of concurrent exercise, even when co-ingested with protein. We conclude that alcohol ingestion suppresses the anabolic response in skeletal muscle and may therefore impair recovery and adaptation to training and/or subsequent performance.

Probing regional glycogen metabolism in humans non-invasively has been challenging due to a lack of sensitive approaches. Here we studied human muscle glycogen dynamics post-exercise with a spatial resolution of millimeters and temporal resolution of minutes, using relayed nuclear Overhauser effect (glycoNOE) MRI. Data at 5T showed a homogeneous distribution of glycogen in resting muscle, with an average concentration of 99 ± 13 mM. After plantar flexion exercise following fasting with recovery under fasting conditions, the calf muscle showed spatially heterogeneous glycogen depletion and repletion kinetics that correlated with the severity of this depletion. Three types of regional glycogen kinetics were observed: (i) single exponential repletion (type a); (ii) biphasic recovery of rapid repletion followed by additional depletion (type b); (iii) biphasic recovery where continued depletion is followed by an exponential recovery (type c). The study of the complex patterns of glycogen kinetics suggests that glycogen breakdown may be quantitatively important during the initial recovery. The non-invasive spatial measurement of glycogen in humans has been challenging due to a lack of sensitive approaches. Here, the authors characterize regional glycogen dynamics in human muscle under exercise using MRI, providing insights into the complex patterns of muscle energy consumption and recovery.

Female soccer players have been identified as presenting with low energy availability (LEA), though the prevalence of LEA may be overestimated given inaccuracies associated with self‐reporting dietary intakes. Accordingly, we aimed to quantify total daily energy expenditure (TDEE) via the doubly labelled water (DLW) method, energy intake (EI) and energy availability (EA). Adolescent female soccer players (n = 45; 16 ± 1 years) completed a 9–10 day ‘training camp’ representing their national team. Absolute and relative TDEE was 2683 ± 324 and 60 ± 7 kcal kg−1 fat free mass (FFM), respectively. Mean daily EI was lower (P < 0.01) when players self‐reported using the remote food photography method (RFPM) (2047 ± 383 kcal day−1) over a 3‐day period versus DLW derived EI estimates accounting for body mass (BM) changes (2545 ± 518 kcal day−1) over 7–8 days, representing a mean daily Δ of 499 ± 526 kcal day−1 and 22% error when using the RFPM. Estimated EA was different (P < 0.01) between methods (DLW: 48 ± 14 kcal kg−1 FFM, range: 22–82; RFPM: 37 ± 8 kcal kg−1 FFM, range: 22–54), such that prevalence of LEA (<30 kcal kg−1 FFM) was lower in DLW compared with RFPM (5% vs. 15%, respectively). Data demonstrate the potential to significantly underestimate EI when using self‐report methods. This approach can therefore cause a misrepresentation and an over‐prevalence of LEA, which is the underlying aetiology of ‘relative energy deficiency in sport’ (REDs). What is the central question of this study? Do self‐reported dietary intakes (via remote food photography method, RFPM) overestimate low energy availability (LEA) prevalence in female soccer players compared with energy intake evaluation from the doubly labelled water (DLW) method? What is the main finding and its importance? Estimated energy availability is greater with the DLW method compared with RFPM, such that the prevalence of LEA is greater when self‐reporting dietary intakes. Accordingly, data demonstrate the potential to misrepresent the prevalence of LEA, an underlying factor in the aetiology of ‘relative energy deficiency in sport’ (REDs).

Previous studies demonstrate that “under-fuelling” (i.e., reduced carbohydrate (CHO) and energy intake (EI) in relation to recommended guidelines) is prevalent within adult female soccer players, the consequence of which may have acute performance and chronic health implications. However, the dietary practices of adolescent female soccer players, a population who may be particularly at risk for the negative aspects of low energy availability (LEA), are not well documented. Accordingly, we aimed to quantify EI and CHO intake, physical loading and estimated energy availability (EA) in elite national team adolescent female soccer players (n = twenty-three; age, 17.9 ± 0.5 years) during a 10-day training and game schedule comprising two match days on day six (MDa) and nine (MDb). The players self-reported their EI via the remote food photography method, whilst the physical loading and associated exercise energy expenditure were assessed via GPS technology. The relative CHO intake was significantly greater (all p < 0.05) on the day before the first match (MD-1a) (4.1 ± 0.8 g·kg−1), on the day before the second match (MD-1b) (4.3 ± 1.1 g·kg−1), MDa (4.8 ± 1.2 g·kg−1) and MDb (4.8 ± 1.4 g·kg−1) in comparison to most other days (<4 g·kg−1). The mean daily measured EA over the 10-day period was 34 ± 12 kcal·kg FFM−1·day−1 (with six players, i.e., 34%, presenting LEA), though, when adjusting the energy intake for potential under-reporting, these values changed substantially (44 ± 14 kcal·kg FFM−1·day−1, only one player was classed as presenting LEA). Such data suggest that the prevalence of LEA amongst female team sport athletes may be over-estimated. Nonetheless, players are still likely under-fuelling for the work required in relation to the daily CHO recommendations (i.e., >6 g·kg−1) for intensive training and game schedules. These data provide further evidence for the requirement to create and deliver targeted player and stakeholder education and behaviour change interventions (especially for younger athletes) that aim to promote increased daily CHO intake in female soccer players.

To determine if a 4 d period of high carbohydrate intake can supercompensate muscle glycogen and exercise work capacity on back-to-back occasions. Seven trained cyclists (6 male, VO2peak: 57 ± 4 mL kg−1 min−1) completed a 9-d experimental period, consisting of three intermittent exhaustive cycling trials on days 1 (trial 1), 5 (trial 2) and 9 (trial 3). Following trial 1 cyclists were fed a high carbohydrate diet (˜10 g kg−1 day−1) for eight days to assess their capacity to repeatedly supercompensate muscle glycogen with 4 d recovery. A resting muscle biopsy was obtained prior to each trial consisting of 2 min work intervals (90–60% peak power output) interspersed with 2 min recovery (40% peak power output) repeated until exhaustion. Each 72-h period between trial days included two days of low volume cycling and a rest day. Resting muscle glycogen and total work completed was determined for each trial day. Baseline muscle glycogen on day 1 (583.6 ± 111.0 mmol kg−1 dry mass) was supercompensated on day 5 (835.1 ± 112.8 mmol kg−1 dry mass; p = 0.04, d = 2.25) and again on day 9 (848.3 ± 111.4 mmol kg−1 dry mass; p = 0.01, d = 2.38). Total cycling work capacity increased from trial 1 to trial 2 (+8.7 ± 5.4 kJ kg−1; p = 0.01; d = 1.41); a large effect was observed in trial 3 compared to trial 1 (+6.4 ± 6.8 kJ kg−1; p = 0.10; d = 1.10). A 4 d high carbohydrate feeding strategy is sufficient to repeatedly supercompensate muscle glycogen content following exhaustive exercise and results in enhanced work capacity.

Purpose We determined the effect of suppressing lipolysis via administration of Nicotinic acid (NA) and pre-exercise feeding on rates of whole-body substrate utilisation and cycling time trial (TT) performance. Methods In a randomised, single-blind, crossover design, eight trained male cyclists/triathletes completed two series of TTs in which they performed a predetermined amount of work calculated to last ~60, 90 and 120 min. TTs were undertaken after a standardised breakfast (2 g kg −1 BM of carbohydrate (CHO)) and ingestion of capsules containing either NA or placebo (PL). Results Plasma [free fatty acids] were suppressed with NA, but increased in the later stages of TT90 and TT120 with PL ( p  < 0.05). There was no treatment effect on time to complete TT60 (60.4 ± 4.1 vs. 59.3 ± 3.4 min) or TT90 (90.4 ± 9.1 vs. 89.5 ± 6.6 min) for NA and PL, respectively. However, TT120 was slower with NA (123.1 ± 5.7 vs. 120.1 ± 8.7 min, p  < 0.001), which coincided with a decline in plasma [glucose] during the later stages of this ride ( p  < 0.05). For TTs of the same duration, the rates of whole-body CHO oxidation were unaffected by NA, but decreased with increasing TT time ( p  < 0.05). CHO was the predominant substrate for all TTs contributing between 83 and 94 % to total energy expenditure, although there was a small use of lipid-based fuels for all rides. Conclusion (1) NA impaired cycling TT performance lasting 120 min, (2) cycling TTs lasting from 60 to 120 min are CHO dependent, and (3) there is an obligatory use of lipid-based fuels in TTs lasting 1–2 h.

Despite the well-documented role of carbohydrate (CHO) in promoting endurance exercise performance, endurance athletes typically fail to meet current recommendations in competition. Adequate nutrition knowledge is key to drive athletes’ behaviour, but the current level of knowledge in this population is not known. The present study assessed knowledge of CHO for competition in an international cohort of endurance athletes using the Carbohydrates for Endurance Athletes in Competition Questionnaire (CEAC-Q). The CEAC-Q was completed by 1016 individuals (45 % female), from the United Kingdom (40 %), Australia/New Zealand (22 %), the United States of America/Canada (18 %) and other countries (21 %). Total CEAC-Q scores were 50 ± 20 % (mean ± sd), with no differences in scores between the five subsections (10 ± 5 points, P < 0⋅001). Based on typical knowledge and frequency of correct answers, we defined questions with low (0–39 %), moderate (40–69 %) and high (70–100 %) knowledge at a population level. Knowledge deficiencies were identified in questions related to CHO metabolism (Low: 2 out of 5 questions (2/5), Moderate: 3/5), CHO-loading (Low: 2/5, Moderate: 1/5), pre-event CHO (Low: 2/5, Moderate: 2/5), CHO during exercise (Moderate: 4/5) and CHO for recovery (Low: 3/5, Moderate: 1/5). Current CHO amounts recommendations were identified correctly for CHO-loading, pre-competition meal, during competition >2⋅5 h) and post-competition recovery by 28% (Low), 45 % (Moderate), 48 % (Moderate), and 29 % (Low), respectively. Our findings indicate that endurance athletes typically have limited knowledge of carbohydrate guidelines for competition, and we identify specific knowledge gaps that can guide targeted nutrition education to improve knowledge as an initial step towards optimal dietary practice.