Comparison of a functional obstacle course with an index of clinical gait and balance and postural sway.
BACKGROUND
Older adults commonly experience falls because of balance and mobility problems. Better assessment methods are needed to understand and correct balance and mobility disorders.


METHODS
We used a low technology, functional obstacle course (FOC) to measure balance and mobility in 352 community-dwelling elderly participants. To establish concurrent validity of the FOC, we compared performance on the FOC with two established measures of balance and mobility: performance on the Tinetti Index (TI) and postural sway area measured on a force platform.


RESULTS
Bivariate correlation analyses revealed significant inverse correlations between FOC completion time, the TI balance and gait subscores, and the TI total score (r = -.73 to -.78). The FOC quality scores and TI balance and subscores gait and TI total scores (r = .76 to .82) were significantly positively correlated. FOC time had significant, but small, positive correlations with sway area with eyes open (r = .18) and closed (r = .17) and nonsignificant correlation with sway area with visual feedback. FOC quality also had significant, but smaller, inverse correlations with sway area with eyes open (r = -.024) and closed (r = -.015), and nonsignificant correlation with sway area with visual feedback. Regression analysis showed that TI gait and balance measures accounted for most of the variance found in FOC performance.


CONCLUSIONS
Our findings support the position that the FOC and the TI measure dynamic balance, whereas postural sway measures a different aspect of balance. Advantages of the FOC include the evaluation of environmentally influenced falls and balance problems.
Means
K M
KM
Department of Physical Medicine and Rehabilitation, College of Nursing, University of Arkansas for Medical Sciences, Little Rock, USA. kmmeans@Life.UAMS.EDU
Rodell
D E
DE
O'Sullivan
P S
PS
Winger
R M
RM
D000058:Accidental Falls; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005684:Gait; D006801:Humans; D008297:Male; D011187:Posture; D012044:Regression Analysis