Stair falls, especially during stair descent, are a major problem for older people. Stair fall risk has typically been assessed by quantifying mean differences between subject groups (e.g. older vs. younger individuals) for a number of biomechanical parameters individually indicative of risk, e.g., a reduced foot clearance with respect to the stair edge, which increases the chances of a trip. This approach neglects that individuals within a particular group may also exhibit other concurrent conservative strategies that could reduce the overall risk for a fall, e.g. a decreased variance in foot clearance. The purpose of the present study was to establish a multivariate approach that characterises the overall stepping behaviour of an individual. Twenty-five younger adults (age: 24.5±3.3 y) and 70 older adults (age: 71.1±4.1 y) descended a custom-built instrumented seven-step staircase at their self-selected pace in a step-over-step manner without using the handrails. Measured biomechanical parameters included: 1) Maximal centre of mass angular acceleration, 2) Foot clearance, 3) Proportion of foot length in contact with stair, 4) Required coefficient of friction, 5) Cadence, 6) Variance of these parameters. As a conventional analysis, a one-way ANOVA followed by Bonferroni post-hoc testing was used to identify differences between younger adults, older fallers and non-fallers. To examine differences in overall biomechanical stair descent behaviours between individuals, k-means clustering was used. The conventional grouping approach showed an effect of age and fall history on several single risk factors. The multivariate approach identified four clusters. Three clusters differed from the overall mean by showing both risky and conservative strategies on the biomechanical outcome measures, whereas the fourth cluster did not display any particularly risky or conservative strategies. In contrast to the conventional approach, the multivariate approach showed the stepping behaviours identified did not contain only older adults or previous fallers. This highlights the limited predictive power for stair fall risk of approaches based on single-parameter comparisons between predetermined groups. Establishing the predictive power of the current approach for future stair falls in older people is imperative for its implementation as a falls prevention tool.

Background Stair falls are a major health problem for older people, but presently there are no specific screening tools for stair fall prediction. The purpose of the present study was to investigate whether stair fallers could be differentiated from non-fallers by biomechanical risk factors or physical/psychological parameters and to establish the biomechanical stepping profile posing the greatest risk for a stair fall. Methods Eighty-seven older adults (age: 72.1±5.2 y) negotiated an instrumented seven-step staircase and performed a range of physical/psychological tasks. K-means clustering was used to profile the overall stair negotiation behaviour with biomechanical parameters indicative of fall risk as input. Falls and events of balance perturbation (combined “hazardous events”) were then monitored during a 12-month follow-up. Cox-regression analysis was performed to examine if physical/psychological parameters or biomechanical outcome measures could predict future hazardous events. Kaplan-Meier survival curves were obtained to identify the stepping strategy posing a risk for a hazardous event. Results Physical/psychological parameters did not predict hazardous events and the commonly used Fall Risk Assessment Tool (FRAT) classified only 1/17 stair fallers at risk for a fall. Single biomechanical risk factors could not predict hazardous events on stairs either. On the contrary, two particular clusters identified by the stepping profiling method in stair ascent were linked with hazardous events. Conclusion This highlights the potential of the stepping profiling method to predict stair fall risk in older adults against the limited predictability of single parameter approaches currently used as screening tools.

Declarations of Interest: Mike Roys is an independent consultant working as a sole trader under the name of Rise and Going Consultancy. There is no conflict of interest with how this study was run nor the outcome measures reported. No other competing interests exist.

No abstract

The version presented here may differ from the published version or from the version of the record. Please see the repository URL above for details on accessing the published version and note that access may require a subscription.