Abstract

Prior research has suggested that measurements of brain functioning and performance on dual tasks (tasks which require simultaneous performance) are promising candidate predictors of fall risk among older adults. However, no prior study has investigated whether brain function measurements during dual task performance could improve prediction of fall risks and whether the type of subtasks used in the dual task paradigm affects the strength of the association between fall characteristics and dual task performance. In this study, 31 cognitively normal, community-dwelling older adults provided a self-reported fall profile (number of falls and fear of falling), completed a gait dual task (spell a word backward while walking on a GaitRite mat), and completed a supine dual task (rhythmic finger tapping with one hand while completing the AX continuous performance task (AX-CPT) with the other hand) during functional magnetic resonance imaging (fMRI). Gait performance, AX-CPT reaction time and accuracy, finger tapping cadence, and brain functioning in finger-tapping-related and AX-CPT-related brain regions all showed declines in the dual task condition compared to the single task condition. Dual-task gait, AX-CPT and finger tapping performance, and brain functioning were all independent predictors of fall profile. No particular measurement domain stood out as being the most strongly associated measure with fall variables. Fall characteristics are determined by multiple factors; brain functioning, motor task, and cognitive task performance in challenging dual-task conditions all contribute to the risk of falling.

Highlights

  • Falls affect more than 30% of older adults

  • Multiple predictors, spanning multiple measurement domains, were significantly associated with each of the four fall profile variables in single-predictor regression models

  • No gait dual-task hit variables were correlated with falls

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Summary

Introduction

Falls affect more than 30% of older adults. It is not surprising that falls in this population are the leading cause of non-fatal injury in this population (Centers for Disease Control and Prevention, 2014), while a major cause of fatal injury. Falls are associated with declines in functional status and social activity (Stel et al, 2004), as well as significant financial burdens due to consequent health care utilization (Alexander et al, 1992; Hoffman et al, 2017). Identifying older adults at increased risk of falling is especially challenging. A large set of studies have assessed fall risk using a variety of different predictors.

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