Medication Status and Gait Mechanics in Older Adults: A Multivariate Analysis. Issue 2 (April 2020) - Gabaldon, Josi; Wood, Robert; Murphy, Eryn; Keeley, David W.
Abstract : Background and Purpose: Falls are the leading cause of unintentional deaths in older adults, with nearly one-third of adults older than 65 years falling annually. Previous work reveals that both medication status and gait changes are contributing factors to falls in older adults; however, it is unknown how these factors interact. Thus, the purpose of this investigation was to examine differences between gait biomechanics as a function of medication status in individuals older than 60 years with a self-reported history of falling. It was hypothesized that differences in gait mechanics would be observed as a function of the number of medications in these individuals. Methods: A total of 384 participants, age, mean (SD) = 73.2 (4.2) years; height, mean (SD) = 173.09 (16.4) cm; mass, mean (SD) = 65.45 (5.78) kg, were recruited from across the Southwest United States (Texas, New Mexico, Arizona, Nevada, and California) by the Electronic Caregiver Mobile Fall Risk Assessment Laboratory. Data for cadence, gait velocity, stride length, swing time, and double-support time were collected using a Walkway gait analysis system. Factor analysis was employed to determine whether the gait characteristics were similar to those observed in previous studies. A multivariate analysis with a follow-up univariate analysis was employed to determine group differences in gait factors and variables according to medication number (≥4 medications, n = 262 vs ⩽3 medications, n = 122). Results: Results of the factor analysis reveal that the data analyzed in the current study are similar to those observed in previous studies, with cadence (factor loading coefficient [FLC] = 0.745), gait velocity (FLC = 0.922), stride length (FLC = 0.789 for left and 0.790 for right) loading positively on a "pace" factor, swing time (FLC = 0.728 for right and 0.683 for left), and double-support time (FLC= 0.723) loading positively on a "rhythm" factor. The results of the multivariate analysis of variance revealed differences in gait factors across groups according to medication status. Univariate follow-up tests reveal that double-support time is longer and stride length is shorter in persons taking 4 or more medications as compared with those on 3 or fewer medications. Conclusion: The findings of this study indicate that certain abnormal gait parameters in participants with a history of falls are associated with taking 4 or more medications. Future studies should examine the extent to which gait changes and medications interact to predict falls.