Clinical Trials Logo

Clinical Trial Summary

Athletes in low energy availability (LEA) are at increased risk of developing the Relative Energy Deficiency in Sports (RED-S) syndrome (Mountjoy et al., 2018). LEA is a mismatch between dietary energy intake and exercise energy expenditure, leaving inadequate energy to support physiological functions, and the RED-S syndrome increases the risk of impaired health and performance (Drew et al., 2018, Sesbreno et al., 2022a, under review; Sesbreno et al., 2022b, in preparation; & VanHeest et al., 2014). Although athletes with eating disorders are at high risk, many more may be vulnerable due to uninformed practices for weight loss and/or failure to match energy intake to energy demands for exercise (Wells et al., 2020). Despite efforts to better detect athletes in LEA/RED-S;there is no research on the effectiveness of dietary interventions to influence energy intake in international elite/world-class athletes tomitigate risk of LEA (De Souza et al., 2021; Elliott-Sale et al., 2018; Heikura et al., 2021; Melin et al., 2014; Stellingwerf et al., 2021;Stenqvist et al., 2021 & Rogers et al., 2021). Therefore, it is important to investigate dietary interventions to influence eating habits to improve energy availability in elite athletes. Energy deficit associated with LEA in elite athletes may be accompanied by insufficient carbohydrate intake for training demands (Burke et al., 2011; Heikura et al., 2017; Sesbreno et al., 2021). Unfortunately, there is a paucity of information on the influence of sport nutrition education interventions on dietary intake in elite international (tier 4) and world-class (tier 5) athletes (McKay et al., 2022). However, recent findings suggest an association between nutrition knowledge and energy/carbohydrate availability in young female endurance athletes (Kettunen et al., 2021). This finding may offer a cost effective approach to lower the risk of LEA since education programs have shown to improve nutrition knowledge in athletes (Tam et al., 2019). However, an increase in nutrition knowledge may not always lead to a parallel increase in energy/carbohydrate intake (Heikkila et al., 2019). Indeed, the influence of nutrition education programs on improving dietary intake in athletes is reportedly equivocal (Boidin et al., 2021). However, the differences in intervention design with lack of guidelines on standardized and/or validated methods to assess sport nutrition knowledge and eating habits in elite athletes have made comparisons difficult for generalized interpretation. Fortunately, the new arrival of the Platform to Evaluate Athlete Knowledge of Sports Nutrition Questionnaire (PEAK-NQ) and the Athlete Diet Index (ADI) offer validated methods for assessing sport nutrition knowledge and eating habits in elite athletes (Capling et al., 2021 and Tam et al., 2021). Nevertheless, it is also important to appreciate that nutrition knowledge is not the sole influencing factors to athletes' dietary habits; and recognizing additional factors affecting athletes' decisions around nutrition is critical. A multitude of factors influence food choices in elite athletes (Thurecht et al., 2019). It ranges from sensory appeal, emotional influences, influence of others, weight control, performance among others (Thurecht et al, 2020). Interestingly, a moderate intercorrelation between nutritional attributes of the food and weight control, performance as well as food values and beliefs were reported (Thurecht et al., 2021). In fact, restraint eating behaviour have been associated with LEA, body weight and physique morphology (Jurov et al., 2021; Sesbreno et al., 2021; Sesbreno et al., 2022c in preparation; Sesbreno et al., 2022d, in preparation & Viner et al., 2015). Clearly, multiple factors influence dietary habits, and therefore, it is important to consider how education interventions are developed to influence dietary outcomes in elite athletes. The Capability, Opportunity, Motivation - Behaviour (COM-B) model describes the importance of influencing 3-sources of behaviour to consistently alter habits (Michie et al., 2011). This was reiterated by sport nutritionists who characterized enablers and barriers to nutrition adherence in high performance sports (Bentley et al., 2019). In a case study, dietary interventions that targeted all 3-source behaviours was associated with improvements in dietary intake, including energy availability as an elite rugby player prepared for his 1st professional season (Costello et al., 2018). Therefore, a sport nutrition education program that accounts for all source behaviours may be necessary to improve eating habits intake to lower the risk of LEA/RED-S in elite international and world-class athletes during the competitive season. Overall Aim: Investigate whether elite athletes' nutrition knowledge and dietary intake can improve through an education intervention to lower the risk of low energy availability.


Clinical Trial Description

Study Design The duration of the study will be 3-weeks and 30 participants will be recruited. Participants will complete the EDE-Q 6.0 to examine inclusion and exclusion criteria to participate in the study. When enrollment to participate is confirmed and informed consent is received, participants will complete the platform to evaluate athlete knowledge of sports nutrition questionnaire (PEAK-NQ) and three factor eating questionnaire (TFEQ)-R18 (cognitive restraint eating subscale only), Low energy availability male or female questionnaire (LEAM- or LEAF-Q) on day 1, a 5-day food intake journal from day 2 to 6 and the food management questionnaire, athlete diet index questionnaire (ADI), athlete food choice questionnaire (AFCQ)and surface anthropometry on day 7. Participants will be randomly assigned to a group nutrition education treatment program. The programs will be in a classroom setting (60min for treatment group and 45min for the control group) at the end of the first week (day 8). Post assessment will be scheduled over week 3 and will include the completion of the 5-day food intake journal from day 15 to day 20 and EDE-6.0 (weight and shape concern subscales only), TFEQ-R18 (cognitive restraint eating subscale only), ADI questionnaire, PEAK-NQ, AFCQ, and surface anthropometry on day 21. The investigator will be onsite on day 1, 7, 8 and 21. This will allow the investigator to clarify any missing or incomplete items with the participant in person at INS Québec and/or the Volleyball Canada national training centre. Randomization The randomization procedure will occur via blocked randomization with stratification for high and low PEAK-NQ score (separated with the median score of a similar reference group (Tam et al., 2021). In the case of chance imbalances between groups a minimization design will be applied (Vickers, 2006). The process of randomization will be completed by the investigator. The project will be staged at Volleyball Canada's National training centre and/or the Institut National du Sport du Québec (INS Québec). INS Québec is a national multisport training and sport science/medical service institute for more than 10 national elite sport programs. Despite disruptions related to the COVID 19 pandemic, INS Québec (Montreal) and Volleyball Canada national training centre (Gatineau) has been allowed under provincial government permission to adapt operations to accommodate training requirements for elite amateur athletes preparing for the upcoming international events such as the Summer/Winter Olympics and Paralympic games, World Championships and among others. As long as recommendations to manage COVID-19 transmission are strictly implemented as per respective management documents , the investigation will be able to operate as scheduled. MEASUREMENTS AND STUDY INSTRUMENTS Surface Anthropometry Anthropometric profiles, including body mass, standing height, bone breadths at two sites, limb girths at two sites and skinfolds at eight sites will be measured by a level III accredited anthropometrist from the International Society for the Advancement of Kinanthropometry (ISAK) with a technical error of measurement of ≤ 2.0% for sum of eight skinfolds and ≤ 1.0% for all other measures. All measurements will be made on the right side of the body using ISAK techniques previously described (Stewart et al., 2011). Standing height will be measured using a stadiometer (Rosscraft, Surrey, BC, Canada), body mass on a calibrated digital scale with a precision of ± 0.1 kg (BWB-800S Tanita, Illinois, USA), girths with a flexible steel measuring tape (Rosscraft, Surey, BC, Canada), bone breadth with small bone caliper (Rosscraft, Surrey, BC, Canada) and skinfolds with a Harpenden calipers (Baty International, Burgess Hill, England). The calculations of lean mass index and anthropometric somatotype will be performed as previously described (Norton and Olds, 1996 & Slater et al., 2006). Platform to Evaluate Athlete Knowledge of Sports Nutrition Questionnaire (PEAK-NQ) Athlete knowledge on sport nutrition will be assessed through a validated 50-item electronic questionnaire (Tam et al., 2021). It is based on a total score of 75 across two sections: General Nutrition and Sports Nutrition. Correct answers are given one mark. Incorrect and "not sure" responses are given a zero mark. The items with multiple correct answers score one mark per correct answer and are deducted one mark per incorrect option. Negative scores resulting from multiple incorrect answers are adjusted to zero. Athlete Food Choice Questionnaire (AFCQ) To account for factors that reportedly influence food choices in elite athletes will be assessed by the AFCQ. It is a validated 32-items questionnaire to assess 9-factors influencing food choices in elite athletes (Thurecht et al., 2021). Items are presented as neutral statements and participants rank each on a frequency scale from 1 (never) to 5 (always). Food choice will be referred to foods and beverages. Athlete Diet Index (ADI) The participants eating habits will be assess with the ADI questionnaire. It is a food frequency questionnaire based on reported habits over the last 7 days and was validated in elite athletes across multiple sport disciplines (Capling et al, 2021). A total score (out of a possible 125) is calculated from the sum of the individual sub-scores; with a higher score indicating greater compliance with dietary recommendations for healthy and sport performance/recovery. The total ADI score, sub-scores, and non-scored information (ie: 7 day training log, dietary supplement use) are used in combination to provide an indication of overall diet quality and dietary patterns of the athletes. Although the sub-score for healthy eating are based on the Australian guidelines to healthy eating, the principals are similar to the Canadian Food Guide and will therefore be included in the group analysis (Government of Canada, n.d. & and Australian Government, n.d.). Non scored data is also collected such as medical illness, injuries, weight goals, training schedule, education level as descriptive data to help contextualize the dietary trends and scores. Dietary Intake Journal Each athlete will complete a 5-consecutive day dietary intake report within the week while using the Keenoa (Montréal, Québec, Canada) phone application (Ji et al, 2020). The intake assessment will include a day of rest, and 4 days of coach directed training. Athletes will receive detailed online instructions on how to record all food, fluid and dietary supplement intake. During this investigation, the researcher will use the participant's email to send an invitation to download the app on their smartphone, which will connect the user to the investigator. Participants will be asked to weigh and take pictures of each food item with their smartphone prior to consumption. A food scale will be provided to facilitate data capture. If the app recognizes the food item(s), it will display selected options for the users to confirm the right identity of the food. Items could range from a single item (ie: apple) to composite items (ie: lasagna). Alternatively, participants could search and record food items manually from a database linked to the Canadian Nutrient File (2015). If the athlete ate out, or is unable to find a suitable food match among the available choices on the app, they will be instructed to provide the name of the restaurant food, and fluid orders with size; or name of the food with brand and portion size, respectively, to enable cross-checking. The investigator will review all dietary records and analysis reports for consistency. Food Management Questionnaire This non-validated questionnaire will be used to describe some basic factors associated with the athlete's capability based on the COM-B model to manage food and fluid availability and preparation for oral consumption during the training week. It is divided into 3 main subcategories such as culinary environment at his/her place of residence, food availability and food preparation. Low Energy Availability in Females Questionnaire (LEAF-Q) Female participants will complete a 25-item questionnaire to screen for self-reported physiological symptoms related to low energy availability (Melin et al., 2014). Participants will be subsequently categorized as being at risk for the RED-S if their total score is ≥8. Low energy availability male questionnaire (LEAM-Q) Participants will complete a 42-item questionnaire to screen for self-reported physiological symptoms related to low energy availability (Lundy et al., 2022). Higher total scores indicate a higher relative risk of low energy availability, but with a lower sex-drive being a more sensitive indicator. Low sex drive is identified when 2 or more score on A1 or 2 or more is scored on B1 and 1 or more on B2. Eating Disorder Examination Questionnaire (EDE-Q 6.0) All participants will complete a 28-item questionnaire derived from the semi-structured interview Eating Disorder Examination to assess the range and severity of features associated with a diagnosis of eating disorder using 4 subscales (Restraint, Eating Concern, Shape Concern and Weight Concern) and a global score (Fairburn et al, 2008). It focuses on the past 28 days and uses a seven-point rating scale (0-6). Total score > 2.5 to ensure vulnerable subgroups are not subjected to mental health triggers that may encourage problems with eating (Kuikman et al., 2021). The 2 subscales related to shape and weight concerns will be used at each time point to assess change in self reported concerns with physique. Three Factor Eating Questionnaire R18 (TFEQ-R18) The TFEQ-R18 refers to current dietary practice and measures 3 different aspects of eating behavior: restrained eating (conscious restriction of food intake to control body weight or to promote weight loss), uncontrolled eating (tendency to eat more than usual due to a loss of control over intake accompanied by subjective feelings of hunger), and emotional eating (inability to resist emotional cues) (de Lauzon et al., 2004). The questionnaire consists of 18 items on a 4-point response scale and items are scored, summated and transformed into a 0-100 scale for each behaviour as previously described. Higher scores in the respective scales indicate greater cognitive restraint, uncontrolled, or emotional eating. For the purpose of this investigation, the questions for calculating the cognitive restraint eating behaviours score will only be used at each testing time point to characterize restraint eating. The TFEQ-R18 restraint eating score (questions 2, 11, 12, 15, 16 and 18) was selected over EDE-Q 6.0 restraint eating score because it has been associated with athletes at risk of LEA/RED-S as well as surrogate markers of LEA in the athletic population (Jurov et al., 2021, Viner et al., 2015 and Sesbreno et al., 2022, in preparation). Intervention Treatment Participants randomized in the intervention group will undertake a classroom group education session (60min) to cover a variety of sub-themes aimed to increase caloric intake (primarily via protein and carbohydrate intake) over the national team training camp. The content will be administered via power point by the investigator. The session will be recorded to examine content delivery for the assessment of fidelity. The content is design to deliver interventions related to 3 source behaviours associated with the COM-B model of behaviour change. Educational content will be independently coded by two registered dietitians on the research team based on the Behaviour Change Taxonomy code (http://www.bct-taxonomy.com/). Agreement between raters is required to confirm the coding. If failure to agree after three attempts, a third dietitian on the research team will independently code. The coding results by popular vote will confirm the coding. Topics covered will include: 1. Food knowledge (Capability - Psychological) - Macronutrients for energy (protein, carbs, fat) - Foods/fluids rich in protein, carbs, fats - Key nutrients iron, calcium, and water 2. Sport Nutrition Knowledge (Capability - Psychological) - Energy requirements between rest, single and double training days - Daily protein requirements for recovery and training response - Carbohydrate requirements for pre-practices and post practices - Fluid requirements over the day, during training and immediately after practice 3. Culinary and menu planning knowledge (Opportunity - Psychological/Physical) • Basic menu planning guidelines 4. Low energy availability and association on health and performance outcomes (Motivational - Reflective - Education and persuasion) - Link between restrain eating and physique traits - What is LEA and RED-S and prevalence in Olympic level athletes - Link between restrain eating and LEA risk in elite athletes - Link between LEA and risk of poor health in elite athletes - Link between LEA and risk of poor jumping performance and reaction time in elite athletes - Athlete testimonials on consequences to health outcomes Control Treatment Participants randomized in the control group will undertake a classroom group education session (45min) to cover a variety of sub-themes aimed to increase caloric intake (primarily via protein and carbohydrate intake) over the national team training camp. The content will be administered via power point by the investigator. The session will be recorded to examine content delivery for the assessment of fidelity. The content is design to deliver interventions related to 2 source behaviours associated with the COM-B model of behaviour change. Topics covered will include: 1. Food knowledge (Capability - Psychological) - Macronutrients for energy (protein, carbs, fat) - Foods/fluids rich in protein, carbs, fats - Key nutrients iron, calcium, and water 2. Sport Nutrition Knowledge (Capability - Psychological) - Energy requirements between rest, single and double training days - Daily protein requirements for recovery and training response - Carbohydrate requirements for pre-practices and post practices - Fluid requirements over the day, during training and immediately after practice 3. Culinary and menu planning knowledge (Opportunity - Psychological/Physical) • Basic menu planning guidelines 4. Low energy availability and association on health and performance outcomes (Motivational - Reflective - Education (only)) - Link between restrain eating and physique traits - What is LEA and RED-S and prevalence in Olympic level athletes - Link between restrain eating and LEA risk in elite athletes - Link between LEA and risk of poor health in elite athletes - Link between LEA and risk of poor jumping performance and reaction time in elite athletes Both groups will receive a copy of the power-point slides to review sections: 1. Food knowledge 2. Sport Nutrition Knowledge 3. Culinary and menu planning knowledge ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05709678
Study type Interventional
Source McGill University
Contact Erik Sesbreno, MSc
Phone 514-291-4830
Email erik.sesbreno@mail.mcgill.ca
Status Recruiting
Phase N/A
Start date August 22, 2022
Completion date April 30, 2024

See also
  Status Clinical Trial Phase
Completed NCT03117374 - Impact of Web-based School Nutrition Intervention to Increase Fruits, Vegetables and Dairy N/A
Completed NCT04025099 - Internal Cues Versus External Cues for Eating and Activity N/A
Recruiting NCT06111040 - Nurturing Needs Study: Parenting Food Motivated Children N/A
Completed NCT05485168 - Combined Effects of Sequential Variety and Portion Size on Meal Intake of Women N/A
Completed NCT03241121 - Study of Eating Patterns With a Smartphone App and the Effects of Time Restricted Feeding in the Metabolic Syndrome N/A
Completed NCT03850990 - Effect of Gut-Cued Eating on BMI and Efficacy of Open-Label Placebo to Augment Weight Loss N/A
Completed NCT02470949 - Influence of a Monopoly Game on Subtle Behaviors N/A
Recruiting NCT01863212 - The Role of the FTO Gene in Reward System Activation in Obese and Healthy Subjects N/A
Completed NCT02729675 - Innovative Approaches to Increase F&V Intake Thru Worksites Phase 2
Completed NCT05405244 - Examination of Bromocriptine on Homeostatic and Hedonic Mechanisms of Food Intake in Individuals at High Risk for T2DM Phase 3
Completed NCT04971811 - Effects of Energy Density on Self-served Snacks in Preschool Children N/A
Completed NCT05019872 - Al Dente or Well Done? The Eating Rate of a Pasta Meal Modified by Texture N/A
Completed NCT04605224 - Effectiveness of a Culinary Class on Food Literacy and Eating Behaviours of Francophone High School Students
Recruiting NCT04526743 - Eating Behavior and Weight Trajectory After Bariatric Surgery
Active, not recruiting NCT05026411 - Food Reward Circuit Change by Orthodontics N/A
Completed NCT05173311 - Pilot Study: The Effectiveness of a Mobile Application in Increasing Vegetable Acceptance N/A
Completed NCT05149066 - #KindGirlsInACTion: A Programme for the Promotion of Mental Health of Female Adolescents N/A
Completed NCT03779321 - Effect of Food Acceptability on Appetite Hormones' Response in Normal Weight vs. Obese Male Subjects N/A
Recruiting NCT06108128 - Food for Thought: Executive Functioning Around Eating Among Children N/A
Completed NCT05085041 - Healthy Online Parental Education Project to Increase Fruit and Vegetable Intake and Active Playtime Among Toddlers N/A