Citation

Hilliard MJ, Martinez KM, Janssen I, Edwards B, Mille ML, Zhang Y, Rogers MW. Arch. Phys. Med. Rehabil. 2008; 89(9): 1708-1713.

Affiliation

Department of Physical Therapy, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.

Copyright

(Copyright © 2008, Elsevier Publishing)

DOI

10.1016/j.apmr.2008.01.023

PMID

18760155

PMCID

PMC2953551

Abstract

OBJECTIVE: To prospectively determine the capacity of measures of mediolateral (ML) protective stepping performance, maximum hip abduction torque, and trunk mobility, in order to predict the risk of falls among community-living older people. DESIGN: Cross-sectional study. SETTING: A balance and falls research laboratory. PARTICIPANTS: Medically screened and functionally independent community-living older adult volunteers (N=51). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Measures included: (1) protective stepping responses: percentage of trials with multiple balance recovery steps and sidestep/crossover step recovery patterns, and first step length following motor-driven waist-pull perturbations of ML standing balance; (2) hip abduction strength and axial mobility: (3) peak isokinetic hip abduction joint torque and trunk functional axial rotation (FAR) range of motion; and (4) fall incidence: monthly mail-in reporting of fall occurrences with follow-up contact for 1 year post-testing. One- and 2-variable logistic regression analysis models determined which single and combined measures optimally predicted fall status. RESULTS: The single variable model with the strongest predictive value for falls was the use of multiple steps in all trials (100% multiple steps) (odds ratio, 6.2; P=.005). Two-variable models, including 100% multiple steps and either hip abduction torque or FAR variables, significantly improved fall prediction over 100% multiple steps alone. The hip abduction and FAR logistic regression optimally predicted fall status. CONCLUSIONS: The findings identify new predictor variables for risk of falling that underscore the importance of dynamic balance recovery performance through ML stepping in relation to neuromusculoskeletal factors contributing to lateral balance stability. The results also highlight focused risk factors for falling that are amenable to clinical interventions for enhancing lateral balance function and preventing falls.

Language: en