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. 2023 May 11;78(5):811-820.
doi: 10.1093/gerona/glac185.

Using GPS Technologies to Examine Community Mobility in Older Adults

Breanna M Crane  1 , Kyle D Moored  2 , Andrea L Rosso  2 , Michelle C Carlson  1
Affiliations

Using GPS Technologies to Examine Community Mobility in Older Adults

Breanna M Crane et al. J Gerontol A Biol Sci Med Sci. .

Abstract

Background: Objective measures of community mobility are advantageous for capturing movement outside the home. Compared with subjective, self-reported techniques, global positioning system (GPS) technologies leverage passive, real-time location data to reduce recall bias and increase measurement precision. We developed methods to quantify community mobility among community-dwelling older adults and assessed how GPS-derived indicators relate to clinical measures of physical and cognitive performance.

Methods: Participants (n = 149; M ± standard deviation [SD] = 77.1 ± 6.5 years) from the program to improve mobility in aging (PRIMA) study, a physical therapy intervention to improve walking ability, carried a GPS device for 7 days. Community mobility was characterized by assessing activity space, shape, duration, and distance. Associations between GPS-derived indicators and cognition and physical function were evaluated using Spearman correlations.

Results: In adjusted models, a larger activity space, greater duration (eg, time out-of-home), and greater distance traveled from home were correlated with better 6-Minute Walk Test performance (ρ = 0.17-0.23, p's < .05). A more circular activity shape was related to poorer performance on the Trail Making Test, Part A (ρ = 0.18, p < .05). More time out-of-home and a larger activity space were correlated with faster times on the Trail Making Test, Part B (ρ = -0.18 to -0.24, p's < .05). Community mobility measures were not associated with global cognition, skilled walking, or usual gait speed.

Conclusion: GPS-derived community mobility indicators capture real-world activity among older adults and were correlated with clinical measures of executive function and walking endurance. These findings will guide the design of future interventions to promote community mobility.

Keywords: Cognition; Life-space activity; Physical performance; Public health.

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Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
GPS data processing pipeline. GPS = global positioning system; CSV = comma-separated values; UTC = Coordinated Universal Time; DST = daylight savings time; GCS = geographic coordinate system; PCS = projected coordinate system; SDE = standard deviational ellipse.
Figure 2.
Figure 2.
Community mobility measures derived from global positioning system (GPS) devices (test data).
See this image and copyright information in PMC

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