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MUSCLE COMPOSITION AND PERFORMANCE IN MALE AND FEMALE PREPUBESCENT YOUTH

Abstract

Rosemary Sisillo1, Makenzie E. Kerans1, Jackson R. Dinsmore2, Trent J. Herda2, and Ashley A. Herda1 1University of Kansas-Edwards Campus, Overland Park, KS; 2University of Kansas-Lawrence Campus, Lawrence, KS

PURPOSE: The purpose of this study is to identify the relationships among thigh muscle composition and sprint speed in young males and females. METHODS: Fourteen young (range: 5-11 years) males (n=9) and females (n=5) were measured for height, weight, and seated height to determine leg length and maturation. Skinfold thickness of the right tricep and subscapular regions were measured to estimate body fat percentage. Additionally, an ultrasound image of the right quadriceps vastus lateralis (VL) muscle was recorded and analyzed for VL thickness (VLTHK), cross-sectional area (VLCSA), and subcutaneous fat (VLFAT). Participants performed a 10-meter sprint on a 25m marked turf course. The first 10mwere dedicated to acceleration, timing gates were set at the 10m and 20m marks and the final 5m was used for deceleration. Stepwise linear regression was used to determine prediction of the 10m sprint using anthropometric and muscle composition data. Additionally, Pearson correlation coefficients were determined between sprint speed and muscle composition. RESULTS: The results of the linear regression analysis indicated age, leg length, and VLFAT were the primary predictors of 10-meter sprint time (R2=0.916; p<0.05). Cross-validation with a second group of individuals(5-11 years; n=7) resulted in a strong correlation between the actual 10m sprint time and predicted time (r=0.87, p=0.01) and a paired t-test indicated no difference between the predicted and actual 10m sprint time (mean diff=0.02s, p=0.70). Top speed (m/s) during the 10m sprint speed was correlated to VL thickness (r=0.56, p=0.04) and leg length (r=0.56, p=0.04) whereas the 10m sprint time was correlated with VLCSA (r=0.621, p=0.02). CONCLUSION: Application of anthropometric and muscle composition data to predict performance would be simple and non-exertive during recovery if a young athlete were injured and undergoing a rehabilitation protocol. These measurements also assist in determining sport specificity as they mature and begin to specialize in endurance, speed, or strength-based activities. Caution for this prediction should be exercised as this study used a relatively small sample to estimate the 10m sprint. Body composition should not be the primary focus at such a young age, rather skill development to optimize performance and reduce injury.

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