Predicting Changes in Adolescent Muscle Mass with Field Testing

Abstract

With physical training and normal adolescent growth, gains in lean muscle mass can be seen among the healthy adolescent population. Assessing these gains is crucial to monitoring and adjusting training protocols and helping with client motivation and investment. However, the ability of common field tests to accurately predict changes in muscle mass among this population has yet to be proven. PURPOSE: The purpose of this study was to assess the ability of the standing long jump (SLJ) and 90° push-up (PU) test to accurately predict changes in lean mass (ΔLM) among healthy adolescents aged 12-18 years. METHODS: Forty-five healthy adolescents completed the standing long jump, 90° push-up test, and a full-body dual energy x-ray absorptiometry (DEXA) scan twice with 7-10 months between test sessions. The difference in each outcome was calculated and used to indicate change. Field test predictive ability was evaluated using multiple regression and accounted for age (yrs), sex (female = 0, male = 1), height (cm), body mass, and pubertal stage using the Pubertal Development Scale (PDS). RESULTS: A mean change of 2198.82 g of lean mass (range = -1193.60, 7307.70; SD = 1816.67) was shown using DEXA. The SLJ and PU had a mean change of 5.11 cm (range = -36.00, 35.70; SD = 16.40) and 0 repetitions (range = -13, 11; SD = 5.30) respectively. Both ΔSLJ (r = .340, p = .011) and ΔPU (r = .315, p = .018) had significant moderate relationships to ΔLM. The inclusion of ΔSLJ and ΔPU in the model accounted for an additional 8.8% of the variability (R2= .551 from .463) and 4.2% (R2= .593) respectively. The overall model explained 59.3% of the variability in lean mass change and resulted in the following predictive equation: ΔLM = 1237.59 + (-630.44 x age) + (-169.34 x PDS) + (847.31 x gender) + (33.89 x height) + (199.04 x BMI) + (29.07 x ΔSLJ) + (73.13 x ΔPU) CONCLUSIONS: Along with anthropometric developmental factors, the SLJ and PU tests can be used to estimate changes in lean muscle mass. However, these factors only account for approximately 60% of the change in lean muscle mass leaving the remaining 40% attributable to other (neural, mechanical, motivational) factors. Nevertheless, this prediction equation can assist in monitoring changes in lean muscle mass during adolescence.