Dynamic sarcopenia transitions in older Chinese: physical activity and cognitive insights

作者：Yutao Li, Yuxin Tang, Wei Pan, Song Heng-guo · 发表于：BMC Geriatrics · 年份：2025 · DOI：10.1186/s12877-025-06752-5 · 被引用次数：1 · 研究领域：Nutrition and Health in Aging、Frailty in Older Adults、Balance, Gait, and Falls Prevention

OBJECTIVES: To investigate sarcopenia state transitions (non-sarcopenia, possible sarcopenia, and sarcopenia) and their determinants among older Chinese adults, emphasizing the roles of physical activity, cognitive status, and other risk factors. METHODS: A longitudinal study utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011–2015, integrating Multi-State Markov (MSM) models and Transformer-based deep learning approaches. We examined 5,756 participants (including 3,373 for deep learning) across three waves, with a mean age of 67.9 years (SD = 6.5). MSM models estimated transition intensities and probabilities between sarcopenia states. Deep learning with SHAP analysis identified key determinants of transitions and mortality. Covariates included age, sex, BMI, smoking, physical activity, mild cognitive impairment (MCI), and functional disability. RESULTS: MSM models indicated a high transition rate from non-sarcopenia to possible sarcopenia (intensity: 0.383, 95% CI: 0.355–0.411) and a 38.6% five-year recovery probability from possible sarcopenia to non-sarcopenia. Physical activity reduced deterioration risk (HR: 0.916, 95% CI: 0.842–0.997) and mortality in possible sarcopenia (HR: 0.565, 95% CI: 0.339–0.944). MCI increased deterioration risk (HR: 1.724, 95% CI: 1.268–2.346). Age > 80 significantly elevated deterioration (HR: 3.007, 95% CI: 1.992–4.538) and mortality risks (HR: 7.400, 95% CI: 2.542–21.544). Sex, BMI, smoking, and fun...