The Combined Additive Effect of Inter-Limb Muscle Mass Asymmetries and Body Composition Indices on Lower Limb Injuries in Physically Active Young Adults

Biological measurements that predict injury risk are crucial diagnostic tools. Yet, research on improving diagnostic accuracy in detecting accidents is insufficient. Combining multiple predictors and assessing them via ROC curves can enhance this accuracy. This study aimed to (1) evaluate the importance of lower limb muscle mass asymmetry and body composition (BMI and FMI) as predictors of injuries, (2) explore the role of the most effective body composition index in the relationship between muscle asymmetry and injury, and (3) assess the prognostic potential of combined predictors. Cross-sectional sampling was used to select students from a university. The sample included 237 physically active young adults (44% males). The independent variables were inter-limb muscle mass asymmetry (absolute asymmetry, AA), BMI, and FMI; the dependent variable was the number of injuries in the past year. Using zero-inflated Poisson regression, we examined the relationships, including a moderation analysis (moderated multiple ZIP regression). The mediation by body composition was tested using ZIP and logistic regression. The predictive power was assessed via ROC curves. The significance level was set at an alpha-value of 0.05. No significant difference in injury incidence between males and females was found (chi 2 = 2.12, p = 0.145), though the injury types varied. Males had more muscle strains, while females had more bone fractures (chi 2 = 6.02, p = 0.014). In males, the inter-limb asymmetry and FMI predicted injuries; in females, the BMI and FMI did, but not asymmetry. No moderating or mediating effects of body composition were found. In males, combined asymmetry and the FMI better predicted injuries (AUC = 0.686) than separate predictors (AA: AUC = 0.650, FMI: AUC = 0.458). For females, the FMI was the best predictor (AUC = 0.662). The most predictive factors for injuries in males were both muscle asymmetry and the FMI (as combined predictors), while in females, it was the single FMI. The hypothesis regarding the mediating role of body composition indicators was rejected, as no moderation or mediation by the FMI was detected in the relationship between absolute asymmetry (AA) and injuries. For clinical practice, the findings suggest that practitioners should incorporate assessments of both muscle asymmetry and body composition into routine screenings for physically active individuals. Identifying those with both high asymmetry and an elevated FMI can help target preventative interventions more effectively. Tailored strength training and conditioning programs aimed at reducing asymmetry and managing body composition may reduce the risk of injury, particularly in populations identified as high-risk.