Study of the significance of parameters and their interaction on assessing femoral fracture risk by quantitative statistical analysis

Early assessment of hip fracture helps develop therapeutic and preventive mechanisms that may reduce the occurrence of hip fracture. An accurate assessment of hip fracture risk requires proper consideration of the loads, the physiological and morphological parameters, and the interactions between these parameters. Hence, this study aims at analyzing the significance of parameters and their interactions by conducting a quantitative statistical analysis. A multiple regression model was developed considering different loading directions during a sideways fall (angle ( α) and ( β) on the coronal and transverse planes, respectively), age, gender, patient weight, height, and femur morphology as independent parameters and Fracture Risk Index (FRI) as a dependent parameter. Strain-based criteria were used for the calculation of FRI with the maximum principal strain obtained from quantitative computed tomography–based finite element analysis. The statistical result shows that β ( p < 0.0000) , age ( p < 0.0006) , true moment length ( p < 0.0006) , gender ( p < 0.0015) , FNA ( p < 0.0213) , height ( p < 0.0238) , and FSL ( p < 0.0315) significantly affect FRI where β is the most influential parameter. The significance of two-level interaction ( p < 0.05) and three-level interaction ( p < 0.05) shows that the effect of parameters is dissimilar and depends on other parameters suggesting the variability of FRI from person to person. Graphical abstract