The Relationship of Hedonic Hunger, Macronutrient Balance, Nutrition Knowledge, and Body Image and Weight Control with Dietary Intake in Student Athletes and Exercisers.

Dietary intake is known to impact athletic performance. The factors that influence dietary intake have been investigated widely, but their collective effect has not been examined. The primary aim of this cross-sectional study was to assess the relationship between dietary intake and nutrition knowledge, body image, weight control, macronutrient balance, and hedonic hunger. Forty-two student athletes or active individuals were recruited through contact with sporting organisations and course coordinators, advertising via twitter, and flyers posted within university buildings. Nutrition knowledge, body image, weight control, macronutrient balance, and hedonic hunger were measured using the Abridged Nutrition for Sport Knowledge Questionnaire, Body Image Disturbance Questionnaire and Contour Drawing Rating Scale, a Weight Fluctuation Measure, Australian Eating Score, and Power of Food Scale, respectively. Hierarchical regression analysis, correlation testing, and mean difference testing were applied. Carbohydrate intake, body image disturbance scores, weight fluctuation, and hedonic hunger for food tasted had a significant relationship (R2 = 64.6%, Adj R2 = 0.608%, p < 0.001) with dietary energy intake. Student athletes' dietary intakes are influenced by multiple potentially modifiable factors. Future studies should use larger sample sizes, with interventions focusing on individual modifiable factors to determine how dietary intake can be most significantly impacted.

A systematic review of interventions targeting modifiable factors that impact dietary intake in athletes.

Appropriate dietary intake has been found to positively impact athletes' performance, body composition and recovery from exercise. Strategies to optimise dietary intake often involve targeting one or more of the many factors that are known to influence dietary intake. This review aims to investigate the types and effectiveness of interventions used to impact modifiable factors of dietary intake in athletes. MEDLINE, CINAHL, SPORTDiscus and Web of Science were searched from inception to May 2022 for intervention studies that measured dietary intake with a quantitative tool and explored at least one factor thought to influence the dietary intake of adult athletes. Study quality was assessed using the ADA Quality Criteria Checklist: Primary Research. Twenty-four studies were included. The most common interventions focused on nutrition education (n 10), macronutrient adjustment (n 7) and physical activity (n 5). The three most common factors thought to influence dietary intake addressed were nutrition knowledge (n 12), hunger and appetite (n 8), and body composition (n 4). Significant changes in dietary intake were found in sixteen studies, with nutrition education interventions returning significant results in the largest proportion of studies (n 8). Study quality within this review was mostly average (n 4 < 50 %, n 19 50-80 %, n 1 > 80 %). As studies included were published between 1992 and 2021, interventions and factors explored in older studies may require up-to-date research to investigate possible differences in results due to time-related confounders.

A systematic review update of athletes' nutrition knowledge and association with dietary intake.

Athletes' dietary intakes sometimes do not meet sports nutrition guidelines. Nutrition knowledge (NK) is one factor that may influence dietary intake, but NK measurement tools are often outdated or unvalidated, and results regarding athletes' NK are equivocal. The aims of this systematic review were to update previous systematic reviews by examining athletes' NK and to assess the relationship between athletes' general NK, sport NK and dietary intake. MEDLINE, CINAHL, Scopus, SPORTDiscus, Web of Science and Cochrane were searched for studies published between November 2015 and November 2020 that provided a quantitative measure of NK and described the NK tool used. Twenty-eight studies were included, study quality was assessed using JBI checklists and data on NK score and diet intake was extracted. Eight studies utilised validated, up-to-date NK measurement tools. Mean general and sport NK% scores varied between 40·2% ± 12·4 and 70 % ± 9. Mean protein and carbohydrate consumption was 1·1-3·4 g/kg.bw/d and 2·4-4·6 g/kg.bw/d, respectively. Weak-to-moderate, positive associations were found between NK and positive dietary behaviours. Due to a wide variety of NK measurement tools used, it is difficult to synthesise results to determine overall NK in athletes. Overall, there appears to be a low standard of knowledge. Quality of measurement tools for NK has improved but remains an issue. Future studies should use relevant, current validated NK tools or validate tools in their study population. More research is needed into the relationship between NK and other modifiable factors influencing dietary intake.