Predicting population level-hip fracture risk: a novel probabilistic modeling approach incorporating factor-of-risk principles

Fall related injuries are a serious concern for older adults, specifically for hip fractures (fx), where 95% are due to falls [1]. In Canada alone, there are ~25000 hip fx/year [2], accounting for over one third of all fall-related hospitalizations, costing $650 million annually [3]. While models are available for predicting an individual’s risk of hip fx, there exists no model to predict risk on a population level, which would be valuable in the development of prevention and intervention policies. Accordingly, the goal of this study was to develop and validate a mechanistic, probabilistic model to predict population-level hip fracture risk for older adults.