Predictors of Falls Among Elderly People

Abstract

A study was performed to identify and rank risk factors for falling among populations of institutionalized (fallers, N = 79, nonfallers, N = 70) and noninstitutionalized (fallers, N = 34, nonfallers, N = 34) elderly persons. Fallers were matched by age, sex, and living location to nonfaller control subjects. A nurse practitioner performed a comprehensive physical assessment in all subjects using a standardized protocol and physician consultation. Fallers in both populations were significantly more physically and functionally impaired than control subjects. Logistic regression identified hip weakness, poor balance, and number of prescribed medications as factors most strongly associated with falling among institutionalized subjects. A fall prediction model was developed from these findings yielding 76% overall predictive accuracy (89% sensitivity, 60% specificity). Using the model, the predicted 1-year risk of falling ranged from 12% for persons with none of the three risk factors to 100% for persons with all three risk factors. Findings among noninstitutionalized subjects were similar. These data support the concept of performing focused fall risk assessments to identify elderly patients at high risk for falling.