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Research Reports |
LK Boulgarides, PT, MS, is Lecturer, Kinesiology and Health Science Department, California State University, Sacramento, 6000 J St, Sacramento, CA 95819-6073 (USA) (boulgarides{at}csus.edu), and Faculty Director, CSUS LIFE Center for Senior Fitness and Wellness.
SM McGinty, PT, EdD, is Chair, Department of Physical Therapy, California State University, Sacramento
JA Willett, PhD, ATC, is Associate Professor, Kinesiology and Health Science Department, California State University, Sacramento
CW Barnes, PhD, is Professor, Department of Sociology, California State University, Sacramento, and Director, CSUS Institute for Social Research
Address all correspondence to Ms Boulgarides
Background and Purpose. Few tests have been found to be strongly predictive of falls in community-dwelling older adults. The purpose of this study was to determine whether data from 5 balance tests—combined with data regarding fall history, number of medications, dizziness, visual problems, use of an assistive device, physical activity level, sex, and age—could predict falls in community-dwelling older adults who were independent. Subjects. Ninety-nine community-dwelling older adults aged 65 to 90 years (
= 74.02, SD=5.64) were tested. Methods. Subjects were tracked for falls over a 1-year period following testing. Impairment-based tests, which are tests that attempt to specifically identify which sensory systems are impaired or how motor control is impaired (eg, speed, accuracy of movement), were the Modified Clinical Tests of Sensory Interaction for Balance (Modified CTSIB) and the 100% Limits of Stability Test, both of which were done on the Balance Master 6.1. Performance-based tests, which are functional tests that identify functional limitations without necessarily identifying their causes, were the Berg Balance Scale, the Timed "Up & Go" Test, and the Dynamic Gait Index. Demographic and health data included age, sex, number of medications, physical activity level, presence of dizziness, vision problems, and history of falls over the previous year. Logistic regression was used to determine which combinations of data from balance tests, demographics, and health factors were predictive of falls. Results. Two models—(1) the "standing on a firm surface with eyes closed" (FEC) condition of the Modified CTSIB and (2) the FEC combined with age and sex—were predictive of falls, but predicted only 1 and 2 subjects who were at risk for falling, respectively, out of 20 people who were at risk for falling. Discussion and Conclusion. Five balance tests combined with health and demographic factors did not predict falls in a sample of community-dwelling older adults who were active and independent.
Key Words: Balance tests • Fall prediction • Older adults
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