PurposeTo identify the risk factors for training-related lower extremity muscle injuries in young males by a non-invasive method of body composition analysis. MethodsA total of 282 healthy young male volunteers aged 18 – 20 years participated in this cohort study. Injury location, degree, and injury rate were adjusted by a questionnaire based on the overuse injury assessment methods used in epidemiological studies of sports injuries. The occurrence of training injuries is monitored and diagnosed by physicians and treated accordingly. The body composition was measured using the BodyStat QuadScan 4000 multifrequency Bio-impedance system at 5, 50, 100 and 200 kHz to obtain 4 impedance values. The Shapiro-Wilk test was used to check whether the data conformed to a normal distribution. Data of normal distribution were shown as mean ± SD and analyzed by t-test, while those of non-normal distribution were shown as median (Q1, Q3) and analyzed by Wilcoxon rank sum test. The receiver operator characteristic curve and logistic regression analysis were performed to investigate risk factors for developing training-related lower extremity injuries and accuracy. ResultsAmong the 282 subjects, 78 (27.7%) developed training injuries. Lower extremity training injuries revealed the highest incidence, accounting for 23.4% (66 cases). These patients showed higher percentages of lean body mass (p = 0.001), total body water (TBW, p = 0.006), extracellular water (p = 0.020) and intracellular water (p = 0.010) as well as a larger ratio of basal metabolic rate/total weight (p = 0.006), compared with those without lower extremity muscle injuries. On the contrary, the percentage of body fat (p = 0.001) and body fat mass index (p = 0.002) were lower. Logistic regression analysis showed that TBW percentage > 65.35% (p = 0.050, odds ratio = 3.114) and 3rd space water > 0.95% (p = 0.045, odds ratio = 2.342) were independent risk factors for lower extremity muscle injuries. ConclusionTBW percentage and 3rd space water measured with bio-impedance method are potential risk factors for predicting the incidence of lower extremity muscle injuries in young males following training.
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