Gait parameters and falling in the elderly : a prospective study Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/jh343w434

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  • The incidence of falls is common in older adults and becomes more frequent with advancing age. Falls and injuries associated with falls are among the most debilitating and traumatic medical problems encountered by the elderly. There is evidence that indicates there may be a cause and effect relationship between specific gait parameters and falling. If a simple gait test can predict fallers, it could become a valuable tool for identifying individuals at high risk of falling. The purposes of this study were 1) to determine whether performance on the Functional Ambulation Profile (FAP) could accurately predict fallers and non-fallers in a prospective manner and 2) to identify gait parameters within the FAP that would best classify fallers. My hypothesis for this study include 1) the Functional Ambulation Profile (FAP) will accurately predict subjects as fallers and non-fallers and 2) of the five variables that comprise the FAP walking velocity, right and left step length:leg length ratio, step width will be the most powerful predictors of fall status. Two hundred twenty six subjects were evaluated using the GAITRite electronic walkway. Falls surveillance was conducted for 8 months after each participant's specific GAITRite testing date. Average height, weight and BMI were 161.9 ± 8.7 cm, 68.1 ± 16.7 kg, and 25.9 ± 4.1 kg/m², respectively. Men and women were analyzed separately using analysis of variance, logistic regression and relative operating characteristic curves. There was no difference between fallers and non-fallers for any of the FAP variables for both the men and women. Regression results indicated the overall model for FAP to predict fallers was not statistically significant for either men or women, (p=0.706 and p=0.543, respectively). In addition, none of the five variables that make up the FAP was significant enough to be included in a stepwise logistic model, thus we were unable to develop an alternative model for predicting fallers based on gait variables. A secondary analysis found that the FAP was unable to distinguish multiple fallers (3 or more) from occasional and non-fallers in this same study population. The results of this study indicate that the FAP does not predict falls in independently living men and women over the age of 70. Further, none of the five gait variables that compose the FAP was a significant independent predictor of falls in this same population. Based on the results of this study we conclude that the FAP alone is not sufficient to predict risk of falling among older adults. Because of the complexity of all the physical, psychological and environmental elements that can lead to falling, tests based on only spatial and temporal gait characteristics do not appear to be good fall predictors for independent older adults.
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