Objective : To investigate the factors affecting concurrent sarcopenia among patients with cardiovascular diseases, so as to provide insights into early identification and prevention of cardiovascular diseases complicated with sarcopenia. Methods: A total of 250 inpatients with cardiovascular diseases in the Sixth Division Hospital of Xinjiang Production and Construction Corps were recruited and divided into the sarcopenia and non-sarcopenia groups according to the diagnostic criteria of sarcopenia. Subjects' basic characteristics, body mass index, blood biochemical indicators and human body composition parameters were collected using questionnaire surveys, and factors affecting concurrent sarcopenia among patients with cardiovascular diseases using a multivariable logistic regression model. Results: Among the 250 patients with cardiovascular diseases, there were 149 males (59.60%) and 101 females (40.40%). The overall prevalence of sarcopenia was 8.40% among the study subjects. The mean age and body mass index were (75.19±9.74) and (20.77±2.19) kg/m2 in the sarcopenia group and (65.24±11.50) years and (25.85±2.87) kg/m2 in the non-sarcopenia group. Multivariable logistic regression analysis identified age (OR=1.115, 95%CI: 1.030-1.207) and body mass index (OR=0.582, 95%CI: 0.445-0.761) were as factors affecting concurrent sarcopenia among patients with cardiovascular diseases. Conclusion Advanced age and low body mass index may increase the risk of concurrent sarcopenia among patients with cardiovascular diseases.

ObjectiveTo obtain the prevalence of sarcopenia in middle-aged and elderly people in Urumqi based on the 2020 updated based on the 2020 updated Consensus Report 2019 of Asian Working Group for Sarcopenia （AWGS2019）， and to further explore the association between sarcopenia and metabolic syndrome （MS）. MethodsA total of 1 438 middle-aged and elderly people （aged≥50 years） in Urumqi from July 2018 to January 2019 were selected as the research subjects. Data were collected by questionnaire survey， physical examination and laboratory test. Skeletal muscle mass，grip strength and 4 m walking speed were used to represent muscle mass， muscle strength and body function， respectively. Bioelectrical impedance analysis （BIA） was used to measure human body components. Based on the diagnostic criteria of sarcopenia recommended by AWGS2019， the prevalence of sarcopenia in people over 50 years old was obtained. Multivariate logistic regression model was used to explore the correlation between sarcopenia and MS in middle-aged and elderly people of different genders. ResultsThere were 194 patients with sarcopenia， with a prevalence of 13.49%. The prevalence was 15.56% in males and 12.12% in females. There was no significant difference in the prevalence of MS between male sarcopenia group （40.45%） and non-sarcopenia group （38.92%）， while the prevalence of MS in female sarcopenia group （39.04%） was higher than that in non-sarcopenia group （27.56%）. Multivariate logistic regression analysis showed that sarcopenia was a related factor of MS. Compared with non-sarcopenia， the risk of MS in male sarcopenia group was higher （OR=2.11，95%CI： 1.15‒3.88 ）. ConclusionSarcopenia increases the risk of MS in middle-aged and elderly people， with a greater risk in men. Fully understanding of sarcopenia is helpful to early identify high-risk groups of MS and prevent the occurrence of MS.

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.