Predicting Population Level Hip Fracture Risk: A Novel Hierarchical Model Incorporating Probabilistic Approaches And Factor Of Risk Principles

Fall-related hip fractures are a major public health issue. While individual-level risk assessment tools exist, population-level predictive models could catalyze innovation in large-scale interventions. This study presents a hierarchical probabilistic model that predicts population-level hip fracture risk based on Factor of Risk (FOR) principles. Model validation demonstrated thatFORoutput aligned with a published dataset categorized by sex and hip fracture status. The model predicted normalizedFORfor 100000 individuals simulating the Canadian older-adult population. Predicted hip fracture risk was higher for females (by an average of 38%), and increased with age (by15% per decade). Potential applications are discussed.