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Abstract

Background: Socioeconomic factors significantly influence health outcomes in older adults, yet their impact on specific aspects of mobility remains unclear. This study investigates the relationship between area-level socioeconomic disadvantage and mobility health in older adults.

Methods: We conducted a cross-sectional study of 110 community-dwelling older adults recruited and collected using voluntary response sampling at eight health fairs across rural Southeast Alabama in 2022–2024 (60 ± 16 years, 80% female). Area-level socioeconomic status was measured using the Area Deprivation Index (ADI), a validated composite measure of neighborhood disadvantage. Mobility was assessed using the Instrumented Timed Up and Go (iTUG) test and the Instrumented Five Times Sit-to-Stand (i5TSTS) test. Kruskal–Wallis tests and general linear models in SAS 9.4 analyzed the relationship between ADI and mobility measures.

Results: Higher ADI scores were significantly associated with poorer performance on the i5TSTS test (p = 0.0004). While overall iTUG duration did not differ significantly across ADI groups, the sit-to-stand phase of the iTUG showed a significant relationship with ADI (p = 0.0026). These associations remained significant after adjusting for age, weight, race, and education level.

Conclusions: These findings suggest that neighborhood context plays a crucial role in mobility health, particularly in functions related to postural transitions. Clinicians should consider area-level disadvantage when screening for mobility limitations and may need to prioritize sit-to-stand interventions for patients living in high-deprivation areas.

Document Type

Article

Publication Date

2026

Notes/Citation Information

© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.

Digital Object Identifier (DOI)

https://doi.org/10.3390/healthcare14010111

Funding Information

Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number T32TR004767. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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