Force magnitude and distribution during impacts to the hip are affected differentially by body size and body...

Hip fractures are a severe health concern among older adults. While anthropometric factors have been shown to influence hip fracture risk, the low fidelity of common body composition metrics (e.g. body mass index) reduces our ability to infer underlying mechanisms. While simulation approaches can be used to explore how body composition influences impact dynamics, there is value in experimental data with human volunteers to support the advancement of computational modeling efforts. Accordingly, the goal of this study was to use a novel combination of subject-specific clinical imaging and laboratory-based impact paradigms to assess potential relationships between high-fidelity body composition and impact dynamics metrics (including load magnitude and distribution and pelvis deflection) during sideways falls on the hip in human volunteers. Nineteen females (<35 years) participated. Body composition was assessed via DXA and ultrasound. Participants underwent low-energy (but clinically relevant) sideways falls on the hip during which impact kinetics (total peak force, contract area, peak pressure) and pelvis deformation were measured. Pearson correlations assessed potential relationships between body composition and impact characteristics. Peak force was more strongly correlated with total mass (r = 0.712) and lean mass indices (r = 0.510-0.713) than fat mass indices (r = 0.401-0.592). Peak deflection was positively correlated with indices of adiposity (all r > 0.7), but not of lean mass. Contact area and peak pressure were positively and negatively associated, respectively, with indices of adiposity (all r > 0.49). Trochanteric soft tissue thickness predicted 59 % of the variance in both variables, and was the single strongest correlate with peak pressure. In five-of-eight comparisons, hip-local (vs. whole body) anthropometrics were more highly associated with impact dynamics. In summary, fall-related impact dynamics were strongly associated with body composition, providing support for subject-specific lateral pelvis load prediction models that incorporate soft tissue characteristics. Integrating soft and skeletal tissue properties may have important implications for improving the biomechanical effectiveness of engineering-based protective products.