目的·探讨慢性非传染性疾病（慢性病）共病、相位角与老年人肌少症相关的肌肉质量减少的相关性，以及慢性病共病、相位角对老年人肌肉质量减少的预测价值。方法·对2018年8月1日—2019年7月31日入住上海交通大学医学院附属仁济医院老年科，年龄≥60岁的患者进行回顾性筛查。收集患者基本情况（性别、年龄、用药数、共病数、有无骨质疏松症、有无吸烟史等），以及实验室检查指标（血红蛋白、白蛋白、血肌酐、血尿酸、铁蛋白、维生素D、三酰甘油、总胆固醇、高密度脂蛋白、低密度脂蛋白等）结果。计算年龄调整后查尔森合并症指数（age-adjusted Charlson comorbidity index，aCCI）。采用InBody S10生物电阻抗身体成分检测仪进行人体成分测试，记录身体质量指数（body mass index，BMI）、骨骼肌质量指数（skeletal muscle mass index，SMI）、相位角（phase angle，PhA）。部分患者接受握力测量。肌肉质量减少采用2019年亚洲肌肉减少症工作组（Asian Working Group for Sarcopenia，AWGS）推荐的SMI值（男性≤7.0 kg/m²、女性≤5.7 kg/m²）进行诊断。根据测定的SMI值将患者分为肌肉质量正常组与肌肉质量减少组。采用单因素和多因素Logistic分析老年患者发生肌少症相关的肌肉质量减少的危险因素。并进一步运用受试者操作特征曲线（receiver operator characteristic curve，ROC曲线）及曲线下面积评估相关因素预测肌肉质量减少的价值。结果·共入组慢性病共病患者359例，其中男性226例，女性133例；肌肉质量正常组241例，肌肉质量减少组118例，老年人肌少症相关的肌肉质量减少发生率为32.9%。单因素Logistic回归分析提示年龄（OR=1.036，95%CI 1.013~1.060）、共病数（OR=1.117，95%CI 1.025~1.217）、aCCI（OR=1.123，95%CI 1.031~1.222）、高密度脂蛋白（OR=3.688，95%CI 2.065~6.622）与老年人肌肉质量减少的风险呈正相关，BMI（OR=0.514，95%CI 0.443~0.597）、PhA（OR=0.195，95%CI 0.126~0.303）、血红蛋白（OR=0.984，95%CI 0.972~0.996）、三酰甘油（OR=0.606，95%CI 0.424~0.866）与老年人肌肉质量减少的风险呈负相关。多因素Logistic回归模型提示PhA（OR=0.338，95%CI 0.119~0.959）、BMI（OR=0.634，95%CI 0.476~0.844）与老年人肌肉质量减少的风险呈负相关。BMI、PhA预测老年人肌少症相关的肌肉质量减少的ROC曲线下面积分别为0.893（95%CI 0.855~0.931）和0.786（95%CI 0.736~0.837），敏感度分别为0.724和0.676，特异度分别为0.916和0.762；BMI联合PhA预测老年人肌肉质量减少的ROC曲线下面积为0.917（95%CI 0.883~0.951），敏感度为0.867，特异度为0.860。结论·aCCI与老年人肌少症相关的肌肉质量减少具有相关性。随着BMI、PhA的下降，老年人肌肉质量减少的风险升高。BMI联合PhA具有较高的老年人肌少症相关的肌肉质量减少的预测价值。未发现慢性病共病对其的预测价值。

Objective ·To explore the correlation between comorbidities of chronic non-communicable diseases (chronic diseases), phase angle (PhA), and muscle mass decline associated with sarcopenia in the elderly, and the predictive value of chronic disease comorbidities and PhA in muscle mass decline in the elderly. Methods ·By retrospectively screening inpatients aged ≥60 years who were admitted to the Department of Geriatrics, Renji Hospital, Shanghai Jiao Tong University School of Medicine from August 1, 2018 to July 31, 2019, basic information and medical history of the patients (gender, age, number of medications used, number of comorbidities, presence of osteoporosis, smoking history, etc.) were collected, as well as laboratory examination indicators (hemoglobin, albumin, serum creatinine, serum uric acid, ferritin, vitamin D, triacylglycerol, total cholesterol, high-density lipoprotein, low-density lipoprotein, etc.). The age-adjusted Charlson comorbidity index (aCCI) was calculated. The InBody S10 bioelectrical impedance body composition detector was used to test the body composition. Body mass index (BMI), skeletal muscle mass index (SMI), and PhA were collected. Some patients underwent measurement of grip strength. Muscle mass decline was diagnosed by using the SMI values recommended by the 2019 Asian Working Group for Sarcopenia (AWGS) (≤7.0 kg/m² for males and ≤5.7 kg/m² for females). According to the measured SMI values, patients were divided into a group with normal muscle mass and a group with muscle mass decline. Univariate and multivariate Logistic analyses were employed to investigate the risk factors associated with muscle mass decline related to sarcopenia in the elderly. Additionally, the receiver operator characteristic (ROC) curve and the area under the curve were utilized to predict the significance of these factors in muscle mass decline. Results ·A total of 359 chronic disease patients were enrolled, including 226 males and 133 females. There were 241 cases in the normal muscle mass group and 118 cases in the muscle mass decline group. The incidence of muscle mass decline related to sarcopenia in the elderly was 32.9%. The univariate Logistic regression analysis showed that age (OR=1.036, 95%CI 1.013?1.060), comorbidities (OR=1.117, 95%CI 1.025?1.217), aCCI (OR=1.123, 95%CI 1.031?1.222), and high-density lipoprotein (OR=3.688, 95%CI 2.065?6.622) were positively correlated with the risk of muscle mass decline in the elderly. BMI (OR=0.514, 95%CI 0.443?0.597), PhA (OR=0.195, 95%CI 0.126?0.303), hemoglobin (OR=0.984, 95%CI 0.972?0.996) and triacylglycerol (OR=0.606, 95%CI 0.424?0.866) were negatively correlated with the risk of muscle mass decline in the elderly. Multivariate Logistic regression model indicated that PhA (OR=0.338, 95%CI 0.119?0.959) and BMI (OR=0.634, 95%CI 0.476?0.844) were negatively correlated with the risk of muscle mass decline in elderly. The area under the ROC curve for predicting muscle mass decline related to sarcopenia in elderly by using BMI and PhA was 0.893 (95%CI 0.855?0.931) and 0.786 (95%CI 0.736?0.837), respectively. The sensitivity was 0.724 and 0.676, respectively. The specificity was 0.916 and 0.762, respectively. When BMI combined with PhA predicted muscle mass decline in the elderly, the area under the ROC curve was 0.917 (95%CI 0.883?0.951). The sensitivity was 0.867, and the specificity was 0.860. Conclusion ·aCCI is correlated with muscle mass decline associated with sarcopenia in the elderly. As BMI and PhA decrease, the risk of muscle mass decline in the elderly increases. The combination of BMI and PhA has a high predictive value in muscle mass decline in the elderly.No predictive value of chronic diseases comorbidities in muscle mass decline related to sarcopenia in the elderly is found.