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DOI 10.1111/ggi.70050

Медицинская библиотека · Geriatrics & gerontology international · 2025

Association between sarcopenia and healthy aging patterns among Chinese older adults: A latent class analysis approach.

Chen Weichao, Zheng Caiqi

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Аннотация

BACKGROUND

From the perspective of active aging, understanding the relationship between sarcopenia and multidimensional health status among older adults is crucial for developing targeted interventions and health policies.

METHODS

Data were derived from the China Health and Retirement Longitudinal Study (CHARLS) 2018 survey. In total, 3392 older adults (aged ≥60 years) were included in the analysis. Healthy aging was assessed using 38 items across seven domains: cognition, psychological symptoms, vitality, sensory function, mobility, activities of daily living (ADLs), and instrumental activities of daily living (IADLs). Sarcopenia was evaluated following the AWGS 2019 criteria. Latent class analysis was performed to identify distinct patterns of healthy aging, and logistic regression models were used to explore the relationship between sarcopenia and healthy aging patterns.

RESULTS

Latent class analysis identified two distinct healthy aging classes: higher healthy aging (Class 1, 65.0%) and lower healthy aging (Class 2, 35.0%). Older adults with different types of sarcopenia were negatively associated with healthy aging compared with those without sarcopenia. Heterogeneity analyses revealed that older adults (aged ≥70), females and rural residents were more vulnerable to the negative impacts of sarcopenia on healthy aging.

CONCLUSION

Healthcare providers and policymakers should develop strategies to prevent and manage sarcopenia while promoting healthy aging among older adults. Different strategies should be implemented depending on sex and place of residence to prevent sarcopenia. Geriatr Gerontol Int 2025; 25: 864-870.

Для цитирования: Chen Weichao, Zheng Caiqi. Association between sarcopenia and healthy aging patterns among Chinese older adults: A latent class analysis approach.. Geriatrics & gerontology international. 2025. DOI: 10.1111/ggi.70050.

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