[Effects of intermittent fasting and sports performance: a narrative review]

Introduction

Recently, fasted exercise has generated interest for its potential to stimulate metabolic and performance adaptations. The present study aims to analyze the effects of fasting and fasted training on performance and metabolism, acutely and chronically. The databases Medline (PubMed), Physiotherapy Evidence Database (PEDro), Cochrane, and Google Scholar were searched. In total, 767 studies were identified. Of those, 51 studies were finally included. Acutely, exercise on fasting promotes fat oxidation at low and moderate intensities, while protein catabolism is not increased. Performance is not affected in efforts lower than 1 hour. Chronically, fasting generates greater efficiency in fat metabolism and the ability to regulate blood glucose in the long term, although it has not been possible to determine whether these findings improve sports performance. More research is needed in elite athletes, with high training loads and with a periodized approach to fasting.

Protein Nutrition for Endurance Athletes: A Metabolic Focus on Promoting Recovery and Training Adaptation

The purpose of this narrative review is to provide an evidence-based update on the protein needs of endurance athletes with a focus on high-quality metabolic studies conducted on the topics of recovery and training adaptation over the past decade. We use the term 'protein needs' to delineate between the concepts of a daily protein requirement and per meal protein recommendations when devising scientific evidence-based protein guidelines for the endurance athlete to promote post-exercise recovery, enhance the adaptive response to endurance training and improve endurance performance. A habitual protein intake of 1.5 g/kg of body mass (BM)-1·day-1 is typical in male and female endurance athletes. Based on findings from a series of contemporary protein requirement studies, the evidence suggests a daily protein intake of ~ 1.8 g·kgBM-1·day-1 should be advocated for endurance athletes, with the caveat that the protein requirement may be further elevated in excess of 2.0 g·kgBM-1·day-1 during periods of carbohydrate-restricted training and on rest days. Regarding protein recommendations, the current lack of metabolic studies that determine the dose response of muscle protein synthesis to protein ingestion in relation to endurance exercise makes it difficult to present definitive guidelines on optimal per meal protein intakes for endurance athletes. Moreover, there remains no compelling evidence that co-ingesting protein with carbohydrate before or during endurance exercise confers any performance advantage, nor facilitates the resynthesis of liver or muscle glycogen stores during recovery, at least when carbohydrate recommendations are met. However, recent evidence suggests a role for protein nutrition in optimising the adaptive metabolic response to endurance training under conditions of low carbohydrate and/or energy availability that represent increasingly popular periodised strategies for endurance athletes.

The Efficacy of Nutritional Strategies and Ergogenic Aids on Acute Responses and Chronic Adaptations to Exertional-Heat Exposure: A Narrative Review

Global warming is attributed to an increased frequency of high ambient temperatures and humidity, elevating the prevalence of high-temperature-related illness and death. Evidence over recent decades highlights that tailored nutritional strategies are essential to improve performance and optimise health during acute and chronic exertional-heat exposure. Therefore, the purpose of this review is to discuss the efficacy of various nutritional strategies and ergogenic aids on responses during and following acute and chronic exertional-heat exposure. An outline is provided surrounding the application of various nutritional practices (e.g., carbohydrate loading, fluid replacement strategies) and ergogenic aids (e.g., caffeine, creatine, nitrate, tyrosine) to improve physiological, cognitive, and recovery responses to acute exertional-heat exposure. Additionally, this review will evaluate if the magnitude and time course of chronic heat adaptations can be modified with tailored supplementation practices. This review highlights that there is robust evidence for the use of certain ergogenic aids and nutritional strategies to improve performance and health outcomes during exertional-heat exposure. However, equivocal findings across studies appear dependent on factors such as exercise testing modality, duration, and intensity; outcome measures in relation to the ergogenic aid's proposed mechanism of action; and sex-specific responses. Collectively, this review provides evidence-based recommendations and highlights areas for future research that have the potential to assist with prescribing specific nutritional strategies and ergogenic aids in populations frequently exercising in the heat. Future research is required to establish dose-, sex-, and exercise-modality-specific responses to various nutritional practices and ergogenic aid use for acute and chronic exertional-heat exposure.

Predicting daily recovery during long-term endurance training using machine learning analysis

PURPOSE

The aim of this study was to determine if machine learning models could predict the perceived morning recovery status (AM PRS) and daily change in heart rate variability (HRV change) of endurance athletes based on training, dietary intake, sleep, HRV, and subjective well-being measures.

METHODS

Self-selected nutrition intake, exercise training, sleep habits, HRV, and subjective well-being of 43 endurance athletes ranging from professional to recreationally trained were monitored daily for 12 weeks (3572 days of tracking). Global and individualized models were constructed using machine learning techniques, with the single best algorithm chosen for each model. The model performance was compared with a baseline intercept-only model.

RESULTS

Prediction error (root mean square error [RMSE]) was lower than baseline for the group models (11.8 vs. 14.1 and 0.22 vs. 0.29 for AM PRS and HRV change, respectively). At the individual level, prediction accuracy outperformed the baseline model but varied greatly across participants (RMSE range 5.5-23.6 and 0.05-0.44 for AM PRS and HRV change, respectively).

CONCLUSION

At the group level, daily recovery measures can be predicted based on commonly measured variables, with a small subset of variables providing most of the predictive power. However, at the individual level, the key variables may vary, and additional data may be needed to improve the prediction accuracy.

The Influence of Dietary Carbohydrate on Perceived Recovery Status Differs at the Group and Individual Level—Evidence of Nonergodicity Among Endurance Athletes

Purpose

Research findings are typically reported at the group level but applied to individuals. However, an emerging issue in sports science concerns nonergodicity—whereby group-level data cannot be generalized to individuals. The purpose of this study was to determine if the relationship between daily carbohydrate intake and perceived recovery status displays nonergodicity.

Methods

Fifty-five endurance athletes recorded daily measures of self-selected dietary intake, training, sleep, and subjective wellbeing for 12 weeks. We constructed linear models to measure the influence of daily carbohydrate intake on perceived recovery status while accounting for training load, sleep duration, sleep quality, and muscle soreness. Using linear model coefficients for carbohydrate intake we tested whether the distributions (mean and SD) differed at the group and individual levels (indicating nonergodicity). Additionally, a decision tree was created to explore factors that could provide an indication of an individual athlete’s relationship between carbohydrate intake and perceived recovery status.

Results

Mean values were not different between group- and individual-level analyses, but SDs at the individual level were ~2.4 times larger than at the group level, indicating nonergodicity. Model coefficients for carbohydrate intake were negative for three participants, positive for four participants, and non-significant for 37 participants. The κ value measuring accuracy of the decision tree was 0.52, indicating moderate prediction accuracy.

Conclusion

For most individuals, carbohydrate intake did not influence recovery status. However, the influence of dietary carbohydrate intake on daily recovery differs at the group and individual level. Therefore, practical recommendations should be based on individual-level analysis.

What if gastrointestinal complications in endurance athletes were gut injuries in response to a high consumption of ultra-processed foods? Please take care of your bugs if you want to improve endurance performance: a narrative review

To improve performance and recovery faster, athletes are advised to eat more often than usual and consume higher doses of simple carbohydrates, during and after exercise. Sports energetic supplements contain food additives, such as artificial sweeteners, emulsifiers, acidity regulators, preservatives, and salts, which could be harmful to the gut microbiota and impair the intestinal barrier function. The intestinal barrier plays a critical function in bidirectionally regulation of the selective transfer of nutrients, water, and electrolytes, while preventing at the same time, the entrance of harmful substances (selective permeability). The gut microbiota helps to the host to regulate intestinal homeostasis through metabolic, protective, and immune functions. Globally, the gut health is essential to maintain systemic homeostasis in athletes, and to ensure proper digestion, metabolization, and substrate absorption. Gastrointestinal complaints are an important cause of underperformance and dropout during endurance events. These complications are directly related to the loss of gut equilibrium, mainly linked to microbiota dysbiosis and leaky gut. In summary, athletes must be cautious with the elevated intake of ultra-processed foods and specifically those contained on sports nutrition supplements. This review points out the specific nutritional interventions that should be implemented and/or discontinued depending on individual gut functionality.

The effect of pre-exercise protein intake on substrate metabolism, energy expenditure, and energy intake: a dose-response study

BACKGROUND

Pre-exercise protein consumption does not seem to influence substrate metabolism during exercise compared to fasted exercise, however it is unclear if the protein dose impacts on this effect.

METHODS

In a randomized, double-blinded within-subject design trial, healthy, active males and females (n = 15, 25 ± 5 yrs, O2peak: 47.5 ± 8.8 ml/kg/min) completed 1 h of cycling exercise at 60% peak power output 30 min after having consumed either 0, 20, or 40 g of whey protein. Indirect calorimetry was used to measure substrate oxidation during exercise and baseline and post-exercise resting energy expenditure. Blood samples were taken throughout the trials to measure metabolic responses. Free-living food intake post-trial was collected using food diaries.

RESULTS

Fat oxidation rates during exercise did not differ between the three conditions (p = 0.19) with small effect sizes between conditions (Cohen's dz: 0 vs. 20 g = 0.22, 0 vs. 40 g = 0.47, 20 vs. 40 g = 0.27). Serum insulin was higher in the protein groups vs. 0 g (p < 0.05), whereas non-esterified fatty acids were higher in the 0 g compared to 20 and 40 g (p < 0.05). Glucose was significantly lower after 15 min of exercise in 20 and 40 g vs. 0 g (p = 0.01). Resting energy expenditure was elevated post-exercise (p < 0.001), without an interaction for protein dose (p = 0.90). Post-trial free-living energy intake was not different between conditions (p = 0.31), but 24-h energy intake was significantly higher in 40 vs. 0 g (p = 0.04).

CONCLUSION

Protein doses up to 40 g do not seem to impair fat oxidation rates during exercise compared to fasted exercise and could be considered as a nutritional strategy for exercising individuals who struggle to include fasted exercise in their training.

Environmental heat stress offsets adaptation associated with carbohydrate periodization in trained male triathletes

PURPOSE

Carbohydrate (CHO) intake periodization via the sleep low train low (SL-TL) diet-exercise model increases fat oxidation during exercise and may enhance endurance-training adaptation and performance. Conversely, training under environmental heat stress increases CHO oxidation, but the potential of combined SL-TL and heat stress to enhance metabolic and performance outcomes is unknown.

METHODS

Twenty-three endurance-trained males were randomly assigned to either control (n = 7, CON), SL-TL (n = 8, SLTemp ) or SL-TL + heat stress (n = 8, SLHeat ) groups and prescribed identical 2-week cycling training interventions. CON and SLTemp completed all sessions at 20°C, but SLHeat at 35°C. All groups consumed matched CHO intake (6 g·kg-1 ·day-1 ) but timed differently to promote low CHO availability overnight and during morning exercise in both SL groups. Submaximal substrate utilization was assessed (at 20°C), and 30-min performance tests (at 20 and 35°C) were performed Pre-, Post-, and 1-week post-intervention (Post+1).

RESULTS

SLTemp improved fat oxidation rates at 60% MAP (~66% VO2peak ) at Post+1 compared with CON (p < 0.01). Compared with SLTemp , fat oxidation rates were significantly lower in SLHeat at Post (p = 0.02) and Post+1 (p < 0.05). Compared with CON, performance was improved at Post in SLTemp in temperate conditions. Performance was not different between any groups or time points in hot conditions.

CONCLUSION

SL-TL enhanced metabolic adaptation and performance compared with CON and combined SL-TL and heat stress. Additional environmental heat stress may impair positive adaptations associated with SL-TL.

Interaction of exercise and meal timing on blood glucose concentrations

PURPOSE OF REVIEW

Exercise and diet are among the most studied behaviors that can affect blood glucose concentrations. Despite multiple studies examining these interventions in different populations and contexts, inconsistencies across studies have led to variable expectations. The purpose of this review is to more specifically examine how the timing of when exercise is performed in relation to meals can modify changes in glucose concentrations or insulin sensitivity. When possible, studies in type 2 diabetes are emphasized, but recent research in type 1 diabetes, obesity, and athletes is also considered.

RECENT FINDINGS

The effect of a single bout of exercise performed after an overnight fast is often comparable to that of postprandial exercise on 24 h mean glucose concentrations. However, there is recent evidence to suggest that in some situations, but not all, longer term metabolic adaptations can be more favorable when exercise is regularly performed in the fasted state.

SUMMARY

Exercise after an overnight fast can have different effects on glucose metabolism compared with postprandial exercise. The shorter term and longer term changes following fasting exercise can be relevant to those who are seeking greater glucoregulatory benefit from their exercise sessions, such as people with diabetes.

Factors Influencing Substrate Oxidation During Submaximal Cycling: A Modelling Analysis

BACKGROUND

Multiple factors influence substrate oxidation during exercise including exercise duration and intensity, sex, and dietary intake before and during exercise. However, the relative influence and interaction between these factors is unclear.

OBJECTIVES

Our aim was to investigate factors influencing the respiratory exchange ratio (RER) during continuous exercise and formulate multivariable regression models to determine which factors best explain RER during exercise, as well as their relative influence.

METHODS

Data were extracted from 434 studies reporting RER during continuous cycling exercise. General linear mixed-effect models were used to determine relationships between RER and factors purported to influence RER (e.g., exercise duration and intensity, muscle glycogen, dietary intake, age, and sex), and to examine which factors influenced RER, with standardized coefficients used to assess their relative influence.

RESULTS

The RER decreases with exercise duration, dietary fat intake, age, VO2max, and percentage of type I muscle fibers, and increases with dietary carbohydrate intake, exercise intensity, male sex, and carbohydrate intake before and during exercise. The modelling could explain up to 59% of the variation in RER, and a model using exclusively easily modified factors (exercise duration and intensity, and dietary intake before and during exercise) could only explain 36% of the variation in RER. Variables with the largest effect on RER were sex, dietary intake, and exercise duration. Among the diet-related factors, daily fat and carbohydrate intake have a larger influence than carbohydrate ingestion during exercise.

CONCLUSION

Variability in RER during exercise cannot be fully accounted for by models incorporating a range of participant, diet, exercise, and physiological characteristics. To better understand what influences substrate oxidation during exercise further research is required on older subjects and females, and on other factors that could explain additional variability in RER.

Factors Influencing AMPK Activation During Cycling Exercise: A Pooled Analysis and Meta-Regression

BACKGROUND

The 5' adenosine monophosphate (AMP)-activated protein kinase (AMPK) is a cellular energy sensor that is activated by increases in the cellular AMP/adenosine diphosphate:adenosine triphosphate (ADP:ATP) ratios and plays a key role in metabolic adaptations to endurance training. The degree of AMPK activation during exercise can be influenced by many factors that impact on cellular energetics, including exercise intensity, exercise duration, muscle glycogen, fitness level, and nutrient availability. However, the relative importance of these factors for inducing AMPK activation remains unclear, and robust relationships between exercise-related variables and indices of AMPK activation have not been established.

OBJECTIVES

The purpose of this analysis was to (1) investigate correlations between factors influencing AMPK activation and the magnitude of change in AMPK activity during cycling exercise, (2) investigate correlations between commonly reported measures of AMPK activation (AMPK-α2 activity, phosphorylated (p)-AMPK, and p-acetyl coenzyme A carboxylase (p-ACC), and (3) formulate linear regression models to determine the most important factors for AMPK activation during exercise.

METHODS

Data were pooled from 89 studies, including 982 participants (93.8% male, maximal oxygen consumption [[Formula: see text]] 51.9 ± 7.8 mL kg-1 min-1). Pearson's correlation analysis was performed to determine relationships between effect sizes for each of the primary outcome markers (AMPK-α2 activity, p-AMPK, p-ACC) and factors purported to influence AMPK signaling (muscle glycogen, carbohydrate ingestion, exercise duration and intensity, fitness level, and muscle metabolites). General linear mixed-effect models were used to examine which factors influenced AMPK activation.

RESULTS

Significant correlations (r = 0.19-0.55, p < .05) with AMPK activity were found between end-exercise muscle glycogen, exercise intensity, and muscle metabolites phosphocreatine, creatine, and free ADP. All markers of AMPK activation were significantly correlated, with the strongest relationship between AMPK-α2 activity and p-AMPK (r = 0.56, p < 0.001). The most important predictors of AMPK activation were the muscle metabolites and exercise intensity.

CONCLUSION

Muscle glycogen, fitness level, exercise intensity, and exercise duration each influence AMPK activity during exercise when all other factors are held constant. However, disrupting cellular energy charge is the most influential factor for AMPK activation during endurance exercise.

Divergent serum metabolomic, skeletal muscle signaling, transcriptomic, and performance adaptations to fasted versus whey protein-fed sprint interval training

Sprint interval training (SIT) is a time-efficient alternative to endurance exercise, conferring beneficial skeletal muscle metabolic adaptations. Current literature has investigated the nutritional regulation of acute and chronic exercise-induced metabolic adaptations in muscle following endurance exercise, principally comparing the impact of training in fasted and carbohydrate-fed (CHO) conditions. Alternative strategies such as exercising in low CHO, protein-fed conditions remain poorly characterized, specifically pertaining to adaptations associated with SIT. Thus, this study aimed to compare the metabolic and performance adaptations to acute and short-term SIT in the fasted state with preexercise hydrolyzed (WPH) or concentrated (WPC) whey protein supplementation. In healthy males, preexercise protein ingestion did not alter exercise-induced increases in PGC-1α, PDK4, SIRT1, and PPAR-δ mRNA expression following acute SIT. However, supplementation of WPH beneficially altered acute exercise-induced CD36 mRNA expression. Preexercise protein ingestion attenuated acute exercise-induced increases in muscle pan-acetylation and PARP1 protein content compared with fasted SIT. Acute serum metabolomic differences confirmed greater preexercise amino acid delivery in protein-fed compared with fasted conditions. Following 3 wk of SIT, training-induced increases in mitochondrial enzymatic activity and exercise performance were similar across nutritional groups. Interestingly, resting muscle acetylation status was downregulated in WPH conditions following training. Such findings suggest preexercise WPC and WPH ingestion positively influences metabolic adaptations to SIT compared with fasted training, resulting in either similar or enhanced performance adaptations. Future studies investigating nutritional modulation of metabolic adaptations to exercise are warranted to build upon these novel findings.NEW & NOTEWORTHY These are the first data to show the influence of preexercise protein on serum and skeletal muscle metabolic adaptations to acute and short-term sprint interval training (SIT). Preexercise whey protein concentrate (WPC) or hydrolysate (WPH) feeding acutely affected the serum metabolome, which differentially influenced acute and chronic changes in mitochondrial gene expression, intracellular signaling (acetylation and PARylation) resulting in either similar or enhanced performance outcomes when compared with fasted training.

Fuelling the female athlete: Carbohydrate and protein recommendations

Optimal carbohydrate and protein intakes are vital for modulating training adaptation, recovery, and exercise performance. However, the research base underpinning contemporary sport nutrition guidelines has largely been conducted in male populations with a lack of consensus on whether the menstrual phase and associated changes in sex hormones allow broad application of these principles to female athletes. The present review will summarise our current understanding of carbohydrate and protein requirements in female athletes across the menstrual cycle and provide a critical analysis on how they compare to male athletes. On the basis of current evidence, we consider it premature to conclude that female athletes require sex specific guidelines in relation to CHO or protein requirements provided energy needs are met. However, there is a need for further research using sport-specific competition and training related exercise protocols that rigorously control for prior exercise, CHO/energy intake, contraceptive use and phase of menstrual cycle. Our overarching recommendation is to use current recommendations as a basis for adopting an individualised approach that takes into account athlete specific training and competition goals whilst also considering personal symptoms associated with the menstrual cycle.

Pre-Exercise Carbohydrate or Protein Ingestion Influences Substrate Oxidation but Not Performance or Hunger Compared with Cycling in the Fasted State

Nutritional intake can influence exercise metabolism and performance, but there is a lack of research comparing protein-rich pre-exercise meals with endurance exercise performed both in the fasted state and following a carbohydrate-rich breakfast. The purpose of this study was to determine the effects of three pre-exercise nutrition strategies on metabolism and exercise capacity during cycling. On three occasions, seventeen trained male cyclists (VO_2peak 62.2 ± 5.8 mL·kg⁻¹·min⁻¹, 31.2 ± 12.4 years, 74.8 ± 9.6 kg) performed twenty minutes of submaximal cycling (4 × 5 min stages at 60%, 80%, and 100% of ventilatory threshold (VT), and 20% of the difference between power at the VT and peak power), followed by 3 × 3 min intervals at 80% peak aerobic power and 3 × 3 min intervals at maximal effort, 30 min after consuming a carbohydrate-rich meal (CARB; 1 g/kg CHO), a protein-rich meal (PROTEIN; 0.45 g/kg protein + 0.24 g/kg fat), or water (FASTED), in a randomized and counter-balanced order. Fat oxidation was lower for CARB compared with FASTED at and below the VT, and compared with PROTEIN at 60% VT. There were no differences between trials for average power during high-intensity intervals (367 ± 51 W, p = 0.516). Oxidative stress (F₂-Isoprostanes), perceived exertion, and hunger were not different between trials. Overall, exercising in the overnight-fasted state increased fat oxidation during submaximal exercise compared with exercise following a CHO-rich breakfast, and pre-exercise protein ingestion allowed similarly high levels of fat oxidation. There were no differences in perceived exertion, hunger, or performance, and we provide novel data showing no influence of pre-exercise nutrition ingestion on exercise-induced oxidative stress.

Effect of low- and high-carbohydrate diets on swimming economy: a crossover study

Background

Swimming economy refers to the rate of energy expenditure relative to swimming speed of movement, is inversely related to the energetic cost of swimming, and is as a key factor influencing endurance swimming performance. The objective of this study was to determine if high-carbohydrate, low-fat (HCLF) and low-carbohydrate, high-fat (LCHF) diets affect energetic cost of submaximal swimming.

Methods

Eight recreational swimmers consumed two 3-day isoenergetic diets in a crossover design. Diets were tailored to individual food preferences, and macronutrient consumption was 69–16-16% and 16–67-18% carbohydrate-fat-protein for the HCLF and LCHF diets, respectively. Following each 3-day dietary intervention, participants swam in a flume at velocities associated with 50, 60, and 70% of their maximal aerobic capacity (VO_2max). Expired breath was collected and analyzed while they swam which enabled calculation of the energetic cost of swimming. A paired t-test compared macronutrient distribution between HCLF and LCHF diets, while repeated-measures ANOVA determined effects of diet and exercise intensity on physiological endpoints.

Results

Respiratory exchange ratio was significantly higher in HCLF compared to LCHF (p = 0.003), but there were no significant differences in the rate of oxygen consumption (p = 0.499) or energetic cost of swimming (p = 0.324) between diets. Heart rate did not differ between diets (p = 0.712), but oxygen pulse, a non-invasive surrogate for stroke volume, was greater following the HCLF diet (p = 0.029).

Conclusions

A 3-day high-carbohydrate diet increased carbohydrate utilization but did not affect swimming economy at 50–70% VO_2max. As these intensities are applicable to ultramarathon swims, future studies should use higher intensities that would be more relevant to shorter duration events.

What Should I Eat before Exercise? Pre-Exercise Nutrition and the Response to Endurance Exercise: Current Prospective and Future Directions

The primary variables influencing the adaptive response to a bout of endurance training are exercise duration and exercise intensity. However, altering the availability of nutrients before and during exercise can also impact the training response by modulating the exercise stimulus and/or the physiological and molecular responses to the exercise-induced perturbations. The purpose of this review is to highlight the current knowledge of the influence of pre-exercise nutrition ingestion on the metabolic, physiological, and performance responses to endurance training and suggest directions for future research. Acutely, carbohydrate ingestion reduces fat oxidation, but there is little evidence showing enhanced fat burning capacity following long-term fasted-state training. Performance is improved following pre-exercise carbohydrate ingestion for longer but not shorter duration exercise, while training-induced performance improvements following nutrition strategies that modulate carbohydrate availability vary based on the type of nutrition protocol used. Contrasting findings related to the influence of acute carbohydrate ingestion on mitochondrial signaling may be related to the amount of carbohydrate consumed and the intensity of exercise. This review can help to guide athletes, coaches, and nutritionists in personalizing pre-exercise nutrition strategies, and for designing research studies to further elucidate the role of nutrition in endurance training adaptations.

Pre-Exercise Nutrition Habits and Beliefs of Endurance Athletes Vary by Sex, Competitive Level, and Diet

OBJECTIVE

The purpose of this study was to determine the self-reported beliefs and practices relating to pre-exercise nutrition intake among endurance athletes of varying ages and competitive levels and examine differences based on sex, competitive level, and habitual dietary pattern.

METHOD

An anonymous online survey was circulated internationally in English and completed by 1950 athletes of varying competitive levels (51.0% female, mean age 40.9 years [range 18:78]). Survey questions included training background, determinants of pre-exercise nutrition intake and composition, and timing relative to exercise.

RESULTS

Prior to morning exercise, 36.4%, 36.0%, and 27.6% of athletes consumed carbohydrate-containing food/drinks before almost every workout, some of the time, and never/rarely, respectively, with significant effects of sex (p < 0.001, Cramer's V (ϕ_c) = 0.15) and competitive level (p < 0.001, ϕ_c = 0.09). Nutritional intake before exercise varied based on workout duration for 47.6% of athletes, with significant effects of sex (ϕ_c = 0.15) and habitual diet (ϕ_c = 0.19), and based on workout intensity for 39.1% of athletes, with significant effects of sex (ϕ_c = 0.13) and habitual diet (ϕ_c = 0.17, all p < 0.001). Additionally, 89.0% of athletes reported using at least some type of dietary supplement (including caffeine from coffee/tea) within 1 hour before exercise.

CONCLUSIONS

Overall, nearly all factors measured relating to pre-exercise nutrition intake varied by sex, competitive level, habitual dietary pattern, and/or intensity/duration of the training session and suggest a large number of athletes may not be following current recommendations for optimizing endurance training adaptations.