APTA Annual Conference Abstracts
APTA NEXT 2017 Conference, June 21 - 24, 2017
Influences of Age, Obesity and Adverse Drug Effects on Gait Speed in Community-dwelling Older Adults
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INFLUENCES OF AGE, OBESITY AND ADVERSE DRUG EFFECTS ON GAIT SPEED IN COMMUNITY-DWELLING OLDER ADULTS
Peter C. Panus*1, Courtney D. Hall3, Zachary F. Walls1, Brian L. Odle2
PURPOSE: Examine whether age, obesity and adverse drug effects influence the determination of fall risk based on preferred gait speed.
BACKGROUNDS/SIGNIFICANCE: Age, obesity and adverse effects of drugs may all influence fall risk in the elderly. Different balance and mobility tests are used to assess future fall risk in this same population. External variables may influence test performance, but are not incorporated into the test nor are test scores adjusted for these variables. We hypothesize that age, obesity (as determined by body mass index (BMI)) and adverse drug effects (Quantitative Drug Index, QDI) influence preferred gait speed. Additionally, these variables may assist in separating repeated fallers from non-fallers based on this test.
SUBJECTS: This is a secondary analysis of 70 adults, between the ages of 51 and 88, recruited for a rehabilitation study of dizziness and balance. Patient demographics including age, height and weight were self-reported upon entry into the study. A list of current medications was recorded at initial evaluation. The number of stated falls for each patient in the last twelve months was also recorded.
METHODS AND MATERIALS: Gait speed was assessed by having participants walk at their preferred speed over a level indoor surface without an assistive device. The time to walk the middle 6 m of a 9-m path was recorded using a stopwatch. Gait speed has excellent test--retest reliability (r = .90). The BMI for each participant was calculated from their weight and height. The QDI, based on fall-related drug adverse effects, was derived from the drug list for each patient. Adverse effects for each drug were compiled from LexiComp. The adverse effects related to fall risk were determined by two authors, and each adverse effect was weighted equally. The fall-associated adverse effects were summed to provide each drug with an overall score, which was used throughout the analysis. Individual drug scores were summed for all drugs a participant was taking at the time of enrollment for their QDI score.
ANALYSES: Multiple linear regression was conducted using age, BMI and QDI as independent variables and preferred gait speed as the dependent variable. Participants were subsequently divided into either recurrent fallers (> 1 fall in the previous twelve months) or non-fallers. Analysis of Covariance (ANCOVA) was conducted with fall category as the independent variable, preferred gait speed as the dependent variable and age, BMI and QDI as covariates. All analyses were conducted with SPSS (Version 22). Data is presented as average + standard error of the mean.
RESULTS: The overall multiple regression function for preferred gait speed was significant (p=0.001, R2 = 0.272) with age, BMI and QDI as the independent variables. Each independent variable was significant within the model with the standardized betas demonstrating the highest weighting to QDI (p < 0.001, β= -0.359) followed by age (p=0.005, β= -0.315) and BMI (p = 0.011, β= -0.279). The negative standardized betas demonstrate that as age, BMI or QDI increased, preferred gait speed decreased. Positive autocorrelation of the residuals was minimal (Durbin Watson = 1.907), and there was minimal multicollinearity for the independent variables with the variance inflation factors equal to 1.058, 1.047 and 1.030, respectively. Comparison of recurrent fallers versus non-fallers was significant (p = 0.051) with the gait speed for the non-fallers (0.942 + 0.034 m/s, n=32) being faster than that of the recurrent fallers (0.851 + 0.031 m/s, n=38). The covariates of age (p=0.005), BMI (p=0.009) and QDI (p=0.002) were all significant within the model.
CONCLUSIONS: Age, BMI and QDI are all predictors that contribute to preferred gait speed in community-dwelling older adults. Only 27 percent of the variance in preferred gait speed was accounted for by these three variables, suggesting that other factors also contribute to gait speed. Additionally, these same three variables (age, BMI, QDI) are all significant covariates when comparing preferred gait speed of recurrent fallers to non-fallers. The clinical relevance of these findings is that these three variables may be used as an easy fall risk screening tool to identify individuals at risk of future falls who may benefit from comprehensive balance and mobility testing. Age and BMI, would be easily incorporated into current electronic medical records. In contrast, adverse effects of drugs associated with fall risk are not currently quantified; thus, the inclusion of QDI would require revision of current electronic medical records. The role of age, BMI and QDI in other balance and mobility testing will require additional examination.
FUNDING SOURCE: Veterans Affairs Merit Review (E7613R)
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KEYWORDS: falls, adverse drug effects, risk
*First author
