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Factors Influencing Mobility During the COVID-19 Pandemic in Community-Dwelling Older Adults
OBJECTIVE: To describe and identify factors influencing mobility among older adults during the first 5 months of the COVID-19 pandemic. DESIGN: A cross-sectional telesurvey. SETTING: Community dwelling older adults, situated within the first 5 months of the COVID-19 pandemic, in Hamilton, Canada. PA...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
by the American Congress of Rehabilitation Medicine.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9424116/ https://www.ncbi.nlm.nih.gov/pubmed/36055379 http://dx.doi.org/10.1016/j.apmr.2022.08.009 |
Sumario: | OBJECTIVE: To describe and identify factors influencing mobility among older adults during the first 5 months of the COVID-19 pandemic. DESIGN: A cross-sectional telesurvey. SETTING: Community dwelling older adults, situated within the first 5 months of the COVID-19 pandemic, in Hamilton, Canada. PARTICIPANTS: A random sample of 2343 older adults were approached to be in the study, of which 247 completed the survey (N=247). Eligible participants were aged ≥65 years. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Mobility was measured using global rating of change items and the Late Life Function Instrument (LLFI). Multivariate linear regression models were used to examine the association between mobility and related factors based on Webber's model. RESULTS: 247 older adults (29% male, mean age 78 [Formula: see text] 7.3 years) completed surveys between May and August 2020. Respectively, 26%, 10%, and 9%, rated their ability to engage in physical activity, housework, and move around their home as worse compared with the start of the pandemic. The mean LLFI score was 60.9 [Formula: see text] 13.4. In the model, walking volume (β=0.03 95% confidence interval 0.013, 0.047), fall history (β=-0.04, 95% confidence interval -0.08, -0.04), male sex (β=0.06, 95% confidence interval 0.02, 0.09), unpleasant neighborhood (β=-0.06, 95% confidence interval -0.11, -0.02), musculoskeletal pain (β=-0.07, 95% confidence interval -0.11, -0.03), and self-reported health (β=0.08, 95% confidence interval 0.03, 0.13) had the strongest associations with LLFI scores and explained 64% of the variance in the LLFI score. CONCLUSIONS: Physical and environmental factors may help explain poorer mobility during lockdowns. Future research should examine these associations longitudinally to see if factors remain consistent over time and could be targeted for rehabilitation. |
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