Objective: To examine the association between frailty and cognitive function in middle-aged and elderly populations using group-based trajectory model (GBTM), so as to provide insights into the prevention and intervention strategies for cognitive impairment in this population. Methods: From 2011 to 2018, data of demographic information and lifestyle behavior for individuals aged ≥45 years were collected from the China Health and Retirement Longitudinal Study. Frailty status was assessed using the frailty index, and cognitive function was evaluated using the Chinese version of the Mini-Mental State Examination. GBTM was applied to establish frailty trajectories based on the frailty index from 2011 to 2018 to analyze the trajectory of frailty changes. The association between frailty and cognitive function was analyzed using multiple linear regression model. Results: A total of 4 809 participants were included, with a mean age of (56.63±7.73) years. There were 2 621 males (54.50%) and 2 188 females (45.50%). The 2018 survey identified 574 individuals (11.94%) with cognitive function decline. GBTM identified four distinct frailty trajectories including the normal and stable group (69.27%), recovering frail group (9.32%), progressing pre-frail group (16.20%) and persistently frail group (5.22%). The mean cognitive funtion scores for these groups were (17.24±4.83) (16.38±5.53) (15.74±5.20) (15.02±5.11) points, respectively. The differences in cognitive funtion scores across groups were statistically significant (P<0.05). Multiple linear regression analysis showed, after adjusting for confounding factors such as gender, age, nighttime sleep duration, and smoking, compared with the normal and stable group, the cognitive function decline risk was higher in the frailty recovery group (β=-0.581), the pre-frail progression group (β=-0.583), and the persistently frail group (β=-0.662) compared with the non-frail stable group (all P<0.05). Conclusions There are four groups of changes in frailty among the middle-aged and elderly populations. Compared with the normal and stable group, the groups experiencing progression, persistence, and recovery of frailty exhibit a more pronounced risk of cognitive funtion decline.

ObjectiveTo explore the correlation between skeletal muscle mass and metabolic syndrome （MS） disease risk among middle-aged and elderly community residents in Urumqi， and to provide a theoretical basis for understanding the relationship between skeletal muscle mass and MS among middle-aged and elderly community residents in China. MethodsA total of 1 438 community residents ≥ 50 years old were selected as the research subjects from July 2018 to January 2019 in Urumqi. They were selected from a multi-ethnic natural population cohort in Xinjiang. Data were collected through questionnaires， physical examination， bioelectrical impedance analysis （BIA）， laboratory tests， etc. Skeletal muscle mass was evaluated using the limb skeletal muscle mass index （SMI） corrected for body weight； MS was defined as it at least includes three of the following： abdominal obesity， hypertension， hyperglycemia， high triglycerides and low high-density lipoprotein cholesterol. SMI was divided into four quantile arrays of Q₁‒Q₄. Trend χ² test was applied to explore whether there was a correlation between SMI changes and MS. A multivariate logistic regression model was used to analyze whether there is a difference in the risk of MS between the higher SMI group （Q₂， Q₃， Q₄） and the reference group Q₁. ResultA total of 560 MS patients were detected in this study， with a prevalence rate of 38.94%. Among them， the prevalence rate of MS was 39.16% in males and 38.80% in females. The increase in male SMI grading level is not correlated with the prevalence of MS （trend P>0.05）； After adjusting for confounding factors （model 4）， the increase in SMI was still not related to the prevalence of MS （P_trend=0.995）. There was no statistical difference in the risk of MS between the lowest quartile group Q₁ and the highest quartile group Q₄ （OR=1.01， 95%CI： 0.69‒1.78）. The prevalence of MS in women gradually decreased with the increase of SMI grading level （P_trend<0.001）； After adjusting for confounding factors （model 4）， there was still a correlation between the increase of SMI and the prevalence of MS （P_trend=0.005）. With the lowest quartile of SMI Q₁ as the reference group， the risk of MS in Q₂ （OR=0.63， 95%CI： 0.40‒1.00）， Q₃ （OR=0.56， 95%CI： 0.34‒0.94）， Q₄ （OR=0.42， 95%CI： 0.23‒0.76） decreased. ConclusionAn increase in skeletal muscle mass may be beneficial for preventing MS， especially among middle-aged and elderly female residents. Considering the intensification of aging in China and the close relationship between MS and related comorbidities， managing skeletal muscle mass may contribute to potential MS prevention.