DO UNIQUE SIGNATURES OF MOBILITY PREDICT DISTINCT ADVERSE HEALTH OUTCOMES IN OLDER ADULTS? PROSPECTIVE FINDINGS. (11th November 2018) - Hausdorff, J; Dawe, R; Leurgans, S; Yu, L; Barnes, L; Giladi, N; Bennett, D; Buchman, A
Abstract: Accumulating evidence has shown that mobility is a multi-dimensional construct. In this prospective study, we examined if previously validated body-fixed sensor derived mobility metrics extracted from an inertial measurement unit worn on the lower back (e.g., gait speed, angular velocity during turning, stride regularity, sway amplitude during standing) are associated with diverse health outcomes among older adults in the Rush Memory and Aging Project. Then we examined if different combinations of these metrics predict distinct outcomes. Mobility metrics were extracted from 1, 249 community-dwelling older adults (mean age 81.2 years, 78% female) who were followed on average for 3.6 years. Cox proportional hazards models controlling for age, sex, education and race with backward elimination determined the final combination of the specific metrics that best predicted six outcomes: mortality, disability in activities of daily living (ADL), mobility disability, multiple falls, mild cognitive impairment (MCI), and Alzheimer's dementia (AD). Different combinations of mobility metrics independently predicted these six outcomes. For example, sway was one of the independent predictors of ADL disability, but was not included in the final models of other outcomes. Stride regularity independently predicted mortality, MCI and AD, but not ADL or mobility disability. Interestingly, gait speed was included as an independent predictor of mortality and ADL disability, but not of falls, mobility disability, MCI or AD. Mobility metrics extracted from a wearable sensor complement gait speed metrics. Quantifying multiple facets of mobility facilitates the identification of mobility signatures that enhance risk stratification for distinct adverse health outcomes among older adults.