The predictive value of gait speed and maximum step length for falling in community-dwelling older persons

Abstract

Background: Falling is a major health problem.

Objective: To investigate the predictive value for falls of the maximum step length and gait speed.

Design: A prospective cohort study.

Setting: Geriatric outpatient clinic.

Subjects: Three hundred and fifty-two community-dwelling older persons screened by their general practitioner.

Methods: Maximum step length and gait speed were recorded as part of a comprehensive geriatric assessment. One-year follow-up was performed using the fall telephone system.

Results: One hundred and thirty-six (39%) of all subjects (mean age: 76.2 years, standard deviation: 4.3, 55% female), fell at least once, of whom 96 were injured. Predictive values for any falls of both maximum step length and gait speed were low (area under the curve (AUC): 0.53 and 0.50) and slightly better for recurrent falls (maximum step length AUC: 0.64 and gait speed AUC: 0.59). After adding age, gender and fall history to the prediction model, the AUC was 0.63 for maximum step length and 0.64 for gait speed, and for recurrent falls, the AUC was 0.69 both for maximum step length and gait speed. The prediction of fall-related injuries showed similar results. A higher maximum step length score indicated a lower likelihood for falls (hazards ratio 0.36; 95% confidence interval 0.17-0.78).

Conclusions: Maximum step length and gait speed as single-item tools do not have sufficient power to predict future falls in community-dwelling older persons.

Keywords: fall prediction; gait speed; maximum step length; mobility; older people.