Real-world gait speed estimation, frailty and handgrip strength: a cohort-based study

Abstract

Gait speed is a reliable outcome measure across multiple diagnoses, recognized as the 6th vital sign. The focus of the present study was on assessment of gait speed in long-term real-life settings with the aim to: (1) demonstrate feasibility in large cohort studies, using data recorded with a wrist-worn accelerometer device; (2) investigate whether the walking speed assessed in the real-world is consistent with expected trends, and associated with clinical scores such as frailty/handgrip strength. This cross-sectional study included n = 2809 participants (1508 women, 1301 men, [45–75] years old), monitored with a wrist-worn device for 13 consecutive days. Validated algorithms were used to detect the gait bouts and estimate speed. A set of metrics were derived from the statistical distribution of speed of gait bouts categorized by duration (short, medium, long). The estimated usual gait speed (1–1.6 m/s) appears consistent with normative values and expected trends with age, gender, BMI and physical activity levels. Speed metrics significantly improved detection of frailty: AUC increase from 0.763 (no speed metrics) to 0.798, 0.800 and 0.793 for the 95th percentile of individual’s gait speed for bout durations < 30, 30–120 and > 120 s, respectively (all p < 0.001). Similarly, speed metrics also improved the prediction of handgrip strength: AUC increase from 0.669 (no speed metrics) to 0.696, 0.696 and 0.691 for the 95th percentile of individual’s gait speed for bout durations < 30, 30–120 and > 120 s, respectively (all p < 0.001). Forward stepwise regression showed that the 95th percentile speed of gait bouts with medium duration (30–120 s) to be the best predictor for both conditions. The study provides evidence that real-world gait speed can be estimated using a wrist-worn wearable system, and can be used as reliable indicator of age-related functional decline.

Monitoring Gait and Physical Activity of Elderly Frail Individuals in Free-Living Environment: A Feasibility Study

“…Nonetheless, when combined into a single, more robust endpoint, i.e., gait speed, it showed a decreasing trend toward frailty, and it resulted effective in distinguishing non-frail participants from both pre-frail and frail ones, confirming previous findings [38]. Also, the 95th percentile of gait speed, which estimates the upper-bound of the gait speed distribution, and hence it is more likely to reflect the physical reserve of the person, resulted significantly different across frailty groups, in agreement with previous findings [39].…”

Association between daily life walking speed and frailty measured by a smartphone application: a cross-sectional study

“…These studies, which recruited participants from a cohort study involving community-dwelling older adults and measured DWS using a smartphone application or an accelerometer, could not include frail participants because the participants were required to go to the survey venue or designated location for collecting and uploading the data, which may be difficult for frail participants. Soltani et al 17 recently reported the discriminability of DWS for frailty; however, the frailty definition included only the body mass index and handgrip strength and was limited to weight loss and weakness.…”

Predicting Slow Walking Speed From a Pooled Cohort Analysis: Sarcopenia Definitions, Agreement, and Prevalence in Australia and New Zealand

“…In concert with the SDOC, we selected walking speed <0.8 m/s as the primary outcome for numerous reasons. First, walking speed has been recognized as the “6th vital sign” ( 39 ) and is an established predictor of adverse outcomes across adulthood ( 18 , 34 ). Second, in recognition of its clinical significance, walking speed <0.8 m/s has been consistently used as the cut point in recent sarcopenia definitions ( 40 ).…”