FALL RISK ASSESSMENT & PREDICTION IN COMMUNITY-DWELLING OLDER ADULTS

Abstract

Background: Falls in older adulthood can lead to serious consequences, including disability and death. Although falls are preventable, current fall risk assessments lack evidence specific to community-dwelling older adults. The aim of this thesis, comprising four studies, was to advance the understanding of fall risk assessment in community-dwelling older adults.

Methods: The first study was an umbrella review synthesizing prospective evidence on fall risk factors among community-dwelling older adults. Second, we developed standardized protocols for virtual balance and mobility tests and evaluated their feasibility and psychometric properties. Third, we described baseline data from a prospective cohort study (the INITIATE study) and examined associations between performance on 7 balance and mobility tests and 12-month fall history. Last, we evaluated the validity of these tests for predicting falls over 12-months and examined their utility within the World Falls Guidelines (WFG) algorithm for stratifying older adults into low, intermediate, and high-risk groups.

Results: The umbrella review identified 29 unique risk factors across 57 systematic reviews, with mobility-related measures most frequently assessed; where clinical tests of balance, physical function, gait, and dual task ability were most consistently associated with falls. Frailty and chronic conditions were also consistently associated with falls. In study 2, virtual test administration was feasible and the tests demonstrated good to excellent psychometric properties. Study 3 described the baseline sample and found significant differences in test performance between individuals with and without a history of falls. Prospective analyses demonstrated poor predictive ability (all AUCs < 0.70), and incorporating these tests into the WFG algorithm did not improve fall risk stratification.

Discussion: Balance and mobility tests offer limited value for fall prediction. Adding these tests to the WFG algorithm provides little additional utility. Future research is needed to identify the most effective strategies for fall risk screening in community-dwelling older adults.