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Heather R. Clark, Margo E. Barker and Bernard M. Corfe

Mountain marathons are 2-d, self-supported adventure races, during which competitors must carry all nutritional requirements to sustain athletic effort. This requires a compromise between the energy required to perform and the weight penalty of carrying it. We have undertaken a nutritional survey of event competitors in the UK using a questionnaire-based approach and have monitored dehydration during the event. We found that competitors in longer-distance classes (> 50 km) carry significantly less mass of food, which is more energy dense, but that the calorific value is lower than that of competitors in shorter classes. Carbohydrate and protein consumption both positively associated with performance. Competitors became progressively dehydrated throughout the event. Counterintuitively, the better-performing subjects became the most dehydrated. Competitors at all distances should make more effort to rehydrate during breaks in the event. Competitors at shorter distances could choose more energy-dense foods to reduce weight penalty.

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John Cairney, Heather Clark, Dean Dudley and Dean Kriellaars

Purpose: Physical literacy (PL) has been proposed as a key construct for understanding participation in physical activity. However, the lack of an agreed-upon definition and measure has hindered research on the topic. The current study proposed and analyzed the construct validity of a PL model comprised of motor competence, perceived competence, motivation, and enjoyment. Method: The authors tested three different models in two samples: Grade 5 (N = 1,448) and Grade 7 students (N = 698). Results: The PL construct was best represented as a hierarchical model in both the Grade 5, X2(295) = 791.90, p < .001; root mean square error of approximation = .035; and comparative-fit index = .97, and the Grade 7 samples, X2(295) = 557.21, p < .001; root mean square error of approximation = .036; and comparative-fit index = .98, samples. Discussion: Future work is needed to design and evaluate a PL measure consistent with our model. Such work will help generate further research and understanding of PL.