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Association of Gait Quality With Daily-Life Mobility: An Actigraphy and Global Positioning System Based Analysis in Older Adults.

Authors :
Suri A
VanSwearingen J
Baillargeon EM
Crane BM
Moored KD
Carlson MC
Dunlap PM
Donahue PT
Redfern MS
Brach JS
Sejdic E
Rosso AL
Source :
IEEE transactions on bio-medical engineering [IEEE Trans Biomed Eng] 2024 Jan; Vol. 71 (1), pp. 130-138. Date of Electronic Publication: 2023 Dec 22.
Publication Year :
2024

Abstract

Objective: Walking is a key component of daily-life mobility. We examined associations between laboratory-measured gait quality and daily-life mobility through Actigraphy and Global Positioning System (GPS). We also assessed the relationship between two modalities of daily-life mobility i.e., Actigraphy and GPS.<br />Methods: In community-dwelling older adults (N = 121, age = 77±5 years, 70% female, 90% white), we obtained gait quality from a 4-m instrumented walkway (gait speed, walk-ratio, variability) and accelerometry during 6-Minute Walk (adaptability, similarity, smoothness, power, and regularity). Physical activity measures of step-count and intensity were captured from an Actigraph. Time out-of-home, vehicular time, activity-space, and circularity were quantified using GPS. Partial Spearman correlations between laboratory gait quality and daily-life mobility were calculated. Linear regression was used to model step-count as a function of gait quality. ANCOVA and Tukey analysis compared GPS measures across activity groups [high, medium, low] based on step-count. Age, BMI, and sex were used as covariates.<br />Results: Greater gait speed, adaptability, smoothness, power, and lower regularity were associated with higher step-counts (0.20<|ρ <subscript>p</subscript> | < 0.26, p < .05). Age(β = -0.37), BMI(β = -0.30), speed(β = 0.14), adaptability(β = 0.20), and power(β = 0.18), explained 41.2% variance in step-count. Gait characteristics were not related to GPS measures. Participants with high (>4800 steps) compared to low activity (steps<3100) spent more time out-of-home (23 vs 15%), more vehicular travel (66 vs 38 minutes), and larger activity-space (5.18 vs 1.88 km <superscript>2</superscript> ), all p < .05.<br />Conclusions: Gait quality beyond speed contributes to physical activity. Physical activity and GPS-derived measures capture distinct aspects of daily-life mobility. Wearable-derived measures should be considered in gait and mobility-related interventions.

Details

Language :
English
ISSN :
1558-2531
Volume :
71
Issue :
1
Database :
MEDLINE
Journal :
IEEE transactions on bio-medical engineering
Publication Type :
Academic Journal
Accession number :
37428666
Full Text :
https://doi.org/10.1109/TBME.2023.3293752