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Abstract
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OBJECTIVES: Digital gait biomarkers collected from body-worn devices can remotely and continuously collect movement types, quantity, and quality in real life. This study assessed whether digital gait biomarkers from a wrist-worn device could identify people with frailty in a large sample of middle-aged and older adults.
DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: A total of 5822 middle-aged (43-64 years) and 4344 older adults (65-81 years) who participated in the UK Biobank study. MEASURES: Frailty was assessed using a modified Fried's frailty assessment and was defined as having ≥3 of the 5 frailty criteria (weakness, low activity levels, slowness, exhaustion, and weight loss). Fourteen digital gait biomarkers were extracted from accelerometry data collected from wrist-worn sensors worn continuously by participants for up to 7 days.
RESULTS: A total of 238 (4.1%) of the middle-aged group and 196 (4.5%) of the older group were categorized as frail. Multivariable logistic regression analysis revealed that less daily walking (as assessed by step counts), slower maximum walking speed, and increased step time variability best-identified people with frailty in the middle-aged group (area under the curve [95% CI]: 0.70 [0.66-0.73]). Less daily walking, slower maximum walking speed, increased step time variability, and a lower proportion of walks undertaken with a manual task best-identified people with frailty in the older group (0.73 [0.69-0.76]).
CONCLUSIONS AND IMPLICATIONS: Our findings indicate that measures obtained from wrist-worn wearable devices worn in everyday life can identify individuals with frailty in both middle-aged and older people. These digital gait biomarkers may facilitate screening programs and the timely implementation of frailty-prevention interventions.
Language: en |