Applying the International Classification of Functioning, Disability and Health framework to determine the predictors of falls and fractures in people with osteoarthritis or at high risk of developing osteoarthritis: data from the Osteoarthritis Initiative

Background

Falls are a major cause of injury and death among older people. Evidence suggests that people with osteoarthritis (OA) are at a higher risk of falls and fall-related injuries including fractures. While studies demonstrate a link between OA and falls, little is known about the pathways that link falls with demographic factors, OA impairments, activity limitations and participation restrictions. The aim of this study was to identify risk factors for falls and fractures among people with OA or at high risk of developing OA using the International Classification of Functioning, Disability and Health (ICF) framework.

Methods

A longitudinal analysis of data from the Osteoarthritis Initiative (OAI) dataset was undertaken. Participants were considered to have OA if they reported they had been diagnosed with knee or hip OA by a medical practitioner. Outcomes were self-reported falls and fractures. Potential predictors were classified using the ICF framework. Poisson regression models were used to determine the risk factors for falls and fractures.

Results

Of the 4796 participants, 2270 (47%) were diagnosed with knee and/or hip OA. A higher proportion of participants with OA reported having had falls (72% vs 63%; p < 0.0001) and fractures (17% vs 14%; p = 0.012) than those without OA. Personal factors were found to be stronger predictors of falls and fractures compared to OA impairments, activity limitations and participation restrictions in this sample of participants. After adjusting for potential covariates, self-reported history of falls was a significant predictor of both increased falls (incidence rate ratio [IRR] 1.50; 95% confidence interval [CI] 1.40, 4.60) and fracture risk (IRR 1.38; 95% CI 1.13, 1.69).

Conclusions

By applying the ICF framework, we have shown that personal factors were more likely to predict falls and fractures rather than OA impairments, environmental factors, activity limitations and participation restrictions in people with OA or at high risk of developing OA. This highlights the importance of questioning patients about their previous falls and past medical history, and using this information to focus our assessment and clinical decision-making processes.