ScholarWorks@경상국립대학교

초록

We aimed to identify patterns of sedentary behaviors among older adults in residential care homes in China and characterize older adults in each identified pattern. We used data from 283 older adults who lived in 11 care homes in northeastern China. Patterns of sedentary behaviors were identified using latent profile analysis. We further verified the clinical relevance of the identified patterns by associating them with depressive symptoms using a regression model. The LPA results showed that the four-profile model was the most appropriate based on the fitting metrics of AIC, BIC, ABIC, LMR, BLRT, and Entropy, which we named the sedentism group, the balanced group, the mentally-active group, and the mentally-passive group. Compared to residents in the mentally-active group, those in the sedentism group (coefficient = 3.98, 95% CI = 2.18 – 5.78, p < 0.001) and mentally-passive group (coefficient = 1.96, 95% CI = 0.13 – 3.78, p = 0.036) had higher levels of depressive symptoms, supporting the clinical relevance of the identified patterns. Our findings suggest targeted interventions for residents with different sedentary patterns. © 2025 Elsevier Inc.

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