Models to Predict Fall History and Fall Risk for Community-Dwelling Elderly

ABSTRACT

The objective of this study was to compare fall-risk models for the prediction of 1-year fall history in community-dwelling elderly persons. The study design was a descriptive analysis of factors associated with retrospective fall history for individuals living in community-based independent living facilities. Thirty-three older adults (10 men and 23 women, mean age ± standard deviation, 82.6 ± 5.5 years) volunteered to participate. The main outcome measure was multivariate logistic regression models using a minimal set of predictor variables for predicting 1-year fall history and fall-risk status. The results showed that a fall history prediction model using age, gait velocity, and time to complete Trails Making Test Part B yielded 76% of overall predictive accuracy (75% sensitivity, 76% specificity). A second logistic regression with gait speed eliminated was used to identify fall-risk status (fall history plus a positive score on the Timed Up and Go test) with similar results. These findings suggest that these variables are critical for identifying elderly fallers and those at risk for falls.

KEYWORDS. :

• Elderly
• falls
• risk factors for falls
• visually guided stepping
• cognition