Lower extremity function and subsequent disability: Consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery

Background. Although it has been demonstrated that physical performance measures predict incident disability in previously nondisabled older persons, the available data have not been fully developed to create usable methods for determining risk profiles in community-dwelling populations. Using several populations and different follow-up periods, this study replicates previous findings by using the Established Populations for the Epidemiologic Study of the Elderly (EPESE) performance battery and provides equations for the prediction of disability risk according to age, sex, and level of performance. Methods. Tests of balance, time to walk 8 ft, and time to rise from a chair 5 times were administered to 4,588 initially nondisabled persons in the four sites of the EPESE and to 1,946 initially nondisabled persons in the Hispanic EPESE. Follow-up assessment for activity of daily living (ADL) and mobility-related disability occurred from 1 to 6 years later. Results. In the EPESE, compared with those with the best performance (EPESE summary performance score of 1012), the relative risks of mobility-related disability for those with scores of 4-6 ranged from 2.9 to 4.9 and the relative risk of disability for those with scores of 7-9 ranged from 1.5 to 2.1, with similar consistent results for ADL disability. The observed rates of incident disability according to performance level in the Hispanic EPESE agreed closely with rates predicted from models developed from the EPESE sites. Receiver operating characteristic curves showed that gait speed alone performed almost as well as the full battery in predicting incident disability. Conclusions. Performance tests of lower extremity function accurately predict disability across diverse populations. Equations derived from models using both the summary score and the gait speed alone allow for the estimation of risk of disability in community-dwelling populations and provide valuable information for estimating sample size for clinical trials of disability prevention.