BMI (AUC=0.623) and SMI (AUC=0.608) best predicted musculoskeletal injury risk in physically active men, whereas MFR (AUC=0.628) and FMI (AUC=0.614) were the most reliable predictors for women.
Cross-Sectional (n=119)
No
Do body mass component indices predict the risk of musculoskeletal injuries in physically active young men and women?
BMI and SMI are better predictors of musculoskeletal injury risk in physically active men, while MFR and FMI are better predictors in women.
BACKGROUND: Body composition indices can be related to musculoskeletal injuries (MI), particularly in physically active groups. However, little is known about the accuracy of these diagnoses as potential predictors of musculoskeletal injuries. Therefore, this study aims to indicate the cut-off points of relative body mass (BMI), fat mass index (FMI), skeletal muscle mass (SMI), and muscle to fat ratio (MFR) and establish its reliability in injury prediction for physically active men and women. METHODS: The sample included 119 physically active individuals aged 23.72 ± 1.12 (66 men body height 1.79 ± 0.07 (m); body weight 80.51 ± 9.85 (kg) and 53 women body height 1.67 ± 0.08 (m); body weight 62 ± 10.72 (kg)), students at university of physical education in Poland. The participants' physical activity was measured with the International Physical Activity Questionnaire (IPAQ). The relevance of body mass index (BMI), fat mass index (FMI), skeletal muscle mass index (SMI), and muscle to fat ratio (MFR) in detecting injury risk was examined. Musculoskeletal injuries during 1 year before examination were registered using a self-reporting questionnaire. The areas under the curve (AUC) and Youden Index in the receiver operating characteristic curve (ROC) were calculated. RESULTS: The cut-off points used to classify the indices among men were BMI = 24.38; FMI = 3.74; SMI = 16.40; MFR = 3.70; and for women BMI = 20.90; FMI = 4.17; SMI = 8.96; MFR = 1.67. Results suggested the greatest reliability in the prediction of musculoskeletal injuries among men had BMI (AUC = 0.623; Youden = 0.30) and SMI (AUC = 0.608; Youden = 0.23) whereas among women, MFR (AUC = 0.628; Youden = 0.29) and FMI (AUC = 0.614; Youden = 0.32). CONCLUSION: BMI and SMI are the most appropriate indices to predict the risk of musculoskeletal injury in physically active men, whereas in women, MFR and FMI are more reliable. These results indicate that the indices with more muscle mass meaning are better in predicting injury among men. In contrast, indices with a higher contribution of fat are better for women. It indicates sex differentiation of injury risk conditions. Men should focus on developing muscle mass, whereas women should reduce body fat to decrease injury risk. However, widespread use seemed to be limited to the specific examined group. Therefore, cut-off points should be used with caution, and calculated values should be verified and confirmed in subsequent studies.
Domaradzki et al. (Wed,) conducted a cross-sectional in Musculoskeletal injuries (n=119). Body mass component indices (BMI, FMI, SMI, MFR) was evaluated on Prediction of musculoskeletal injuries. BMI (AUC=0.623) and SMI (AUC=0.608) best predicted musculoskeletal injury risk in physically active men, whereas MFR (AUC=0.628) and FMI (AUC=0.614) were the most reliable predictors for women.