(49) THE UTILITY OF FAT-FREE MASS INDEX TO SCREEN FOR LOW BONE MINERAL DENSITY IN MEN AND WOMEN COLLEGIATE ATHLETES

Purpose: Fat-free mass (FFM) index (FFMI) is a measure of FFM, normalized to height, and is calculated by dividing FFM (in kg) by height (m²). FFMI has found new applications in sports, helping to interpret measures of FFM and better evaluate athletic potential, tailor training and nutrition, support athlete recruitment, and gauge an individual’s capacity for further FFM development. Low FFMI values may indicate athletes at risk of low energy availability, and thus may potentially serve as a non-invasive and easy screening tool for low bone mineral density (BMD). However, this relationship has yet to be explored. Thus, the purpose of this study is to determine the relationship between FFMI and whole-body BMD z-score in a diverse sample of NCAA Division I athletes. Methods: Body composition and whole-body BMD z-scores were assessed using dual-energy x-ray absorptiometry (DEXA) during a single study visit. Athletes from the following NCAA men’s (n=937) and women’s (n=730) sports participated: baseball (n=190), basketball (n=300), lacrosse (n=277), rowing (n=18), soccer (n=439), softball (n=43), swim (n=23), track and field (n=21), volleyball (n=125), wresting (n=13), and football (n=218). Athletes were instructed to refrain from exercise, eating, and drinking for at least 2 hours prior to testing. Separate Pearson correlations were used to determine associations between body composition (FFM, FFMI) and BMD z-score in men’s and women’s sports. Linear regression analyses were conducted using FFMI and FFM to predict BMD z-score, adjusting for sex and sport-type (p< 0.05). Results: For men’s sports, there was a positive, moderate relationship between FFM and BMD z-score (r=0.414, p< 0.001), and a positive, very weak relationship between FFMI and BMD z-score (r=0.091, p=0.009). For women’s sports, there a positive, strong relationship between FFM and BMD z-score (r=0.600, p< 0.001), and a positive, weak correlation between FFMI and BMD z-score (r=0.255, p< 0.001). After accounting for both sport (p < 0.001, t = 9.1) and sex (p < 0.001, t = 5.3), FFMI was not a significant predictor of BMD z-score (p = 0.852, R² = 0.080). When the model was adjusted for FFM, FFM emerged as the strongest predictor of BMD z-score (p < 0.001, t = 13.8, R² = 0.201). Sport (p < 0.001, t = 6.4) and sex (p < 0.001, t = 5.7) remained significant predictors, though FFM had the greatest influence within the model. Conclusions: BMD z-score is most influenced by FFM, followed by sport and sex. An athlete with greater FFM likely places more force on their skeleton, stimulating greater bone formation. In contrast, FFMI removes the effect of height, potentially diminishing its predictive power for BMD. Practical Applications: It is recommended that practitioners prioritize strategies that enhance FFM to support bone adaptation and sport performance. Additionally, sport-specific and sex-based differences suggest an individualized approach to training and nutritional interventions. Acknowledgements: None