Rugby league is a physically demanding sport that necessitates considerable nutritional intake, focusing on quality and type, in order to optimize training and competition demands. However, rugby league athletes are reported to have inadequate nutrition intake to match these demands. Some factors that may determine an athlete's nutrition intake have been reported in other sports, including (but not limited to, knowledge, time, cooking skills, food costs, income, belief in the importance of nutrition, body composition goals, and family/cultural support). However, these potential factors are relatively unexplored in rugby league, where a range of personal (age, body composition) or social (ancestry) influences could affect nutritional intake. Further exploration of these factors is warranted to understand the knowledge, attitudes and behavior underlying rugby league athletes' nutritional intake that can provide practitioners with a more detailed understanding of how to approach nutrition behaviors and attitudes in rugby league athletes. The primary aim was to describe the nutrition behaviors and knowledge of rugby league athletes. A secondary aim was to compare nutrition knowledge and behavior based on age, body composition and self-identified ancestry. Fifty professional rugby league athletes anonymously completed a seventy-six-question online survey. The survey consisted of three sections : 1) sports nutrition knowledge, 2) attitudes toward nutrition on performance , and 3) nutrition behaviors. All participants completed the online survey without assistance using their own personal device, with data entered via REDCap during pre-season. Nutrition knowledge was compared based on age (years), body composition (body fat percentage (%)) and ancestral groups (Pasifika, Aboriginal and/or Torres Strait Islander (ATSI) and Anglo- European).Pearson correlation was used for the relationship between nutrition knowledge, age and body composition. An Analysis of Covariance (ANCOVA) was used to determine nutrition knowledge differences between ancestral groups with age and body composition as covariates. Attitudes and behaviors were compared based on age groups (<20, 20-24 and >25 y), ancestry and body composition. Attitudes and behaviors were analyzed by Pearson correlation for body composition, one-way ANOVA for age groups and ANCOVA for ancestry with covariates age and body composition. Overall athletes' nutrition knowledge score was reported as 40 ± 12% (overall rating "poor"). Nutritional behaviors were significant for body composition, as those with lower body fat percentage had higher intakes of vegetables and dairy products (p = 0.046, p = 0.009), and ate more in the afternoon (lunch p = 0.048, afternoon snack p = 0.036). For ancestry, after adjustment for both age and body composition, Pasifika athletes were more inclined to miss breakfast and lunch compared to their Anglo-European (p = 0.037, p = 0.012) and ATSI (p = 0.022, p = 0.006) counterparts and ate more fruit than Anglo-Europeans (p = 0.006, p = 0.016). After adjustment for body composition, ATSI athletes also viewed the impact of nutrition on mental health and well-being significantly lower than Pasifika (p = 0.044). These findings suggest differences exist within rugby league athletes based on ancestral backgrounds and body composition for nutrition attitudes, behaviors and knowledge. Such outcomes could be used when designing nutrition education interventions, with consideration given to these factors to optimize long-term positive behavior change.
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