Original article
Dynamic Gait Stability, Clinical Correlates, and Prognosis of Falls Among Community-Dwelling Older Adults

https://doi.org/10.1016/j.apmr.2010.12.032Get rights and content

Abstract

Bhatt T, Espy D, Yang F, Pai Y-C. Dynamic gait stability, clinical correlates, and prognosis of falls among community-dwelling older adults.

Objective

To establish an accurate measure for prognostic assessment of fall risk in community-dwelling older adults, this study examined the prediction accuracy of a dynamic gait stability measure and common clinical tests for slip-related falls among these adults.

Design

Participants were tested for their fall-risk likelihood on a slip-test.

Setting

Biomechanics research laboratory.

Participants

Community-dwelling older adults (N=119; ≥65y).

Interventions

Not applicable.

Main Outcome Measures

Participants performed a battery of clinical tests, including Berg Balance Scale, Timed Up & Go (TUG) test, static posturography, isometric muscle strength, and bone density. They were then exposed to an unannounced slip during gait. The dynamic stability during unperturbed gait was measured based on the center of mass position and velocity relative to the limits of stability against backward falling. Accuracy of each measure was examined for prediction of slip outcome (fall or recovery).

Results

On the slip, 59 participants fell, 56 recovered their balance, and 4 were harness-assisted. Dynamic stability predicted fall outcome with 69% accuracy. Except for TUG and bone density, no other measure could differentiate fallers from nonfallers; TUG predicted 56% of fall outcomes.

Conclusions

Reproduction of actual falls provides a new benchmark for evaluating the prognostic power of different performance-based assessment tools. The TUG was able to better predict fall outcome than other clinical measures; however, the new dynamic gait stability measure was more sensitive than TUG in its prediction of falls. Ultrasound bone scan could be used to screen older adults for fall risk.

Section snippets

Participants

This study included 119 ambulatory, community-dwelling older adults (75 women; mean age ± SD, 71±6y; range, 65–90y), who were free of serious musculoskeletal, neurologic, cognitive, or other systemic disorders, as assessed by a health questionnaire. Those classified as osteopenic or osteoporotic through a calcaneal ultrasound scan (Lunar Achilles Insighta) were excluded (T score<–1.516), as were those with a score below 25 on the Folstein Mini Mental Status Exam. Participants' past history of

Results

All 115 older adults with an unambiguous outcome experienced a loss of balance; 59 fell and 56 recovered successfully. There was no effect of age or sex on fall incidence (table 1). TUG was the only functional status measure found to be significantly different between fallers and nonfallers: individuals who fell had higher TUG scores (slower) than those who did not (see table 1). The T score obtained from the ultrasound heel scan was also significantly different between fallers and nonfallers (P

Discussion

The reproduction of actual falls resulting from an unannounced slip has provided a benchmark for comparing the prognostic power of each measure considered. Our results indicated that the time-based TUG test was able to predict immediate fall risk significantly better than the BBS, posturographic balance assessment under varied sensory conditions, or isometric muscle strength testing. The results suggest that dynamic gait stability identified overall slip outcome significantly better than other

Conclusions

These results further verified the power of the TUG as a fall-risk prediction tool. The findings indicate that simultaneous measurement of the COM position and velocity relative to the BOS can also provide important prognostic power, such that the quantitative assessment of regular dynamic gait stability can indeed provide fall-risk assessment in a safe and possibly cost-effective manner among older adults. A simple ultrasound bone scan can be used as a screening tool for fall risk. We conclude

Acknowledgments

The authors thank Ting-yun Wang for assisting in data collection and processing.

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    Supported by the National Institutes of Health (grant nos. 2R01-AG16727 and R01-AG029616).

    No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated.

    Reprints will not be available from the author.

    Espy is currently located at the School of Health Sciences, Cleveland State University, Cleveland, OH.

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