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成人健康受试者中低肌肉量及与肥胖相关的低肌肉量筛查中的原始生物电阻抗参数与矢量分析

Raw bioelectrical impedance parameters and vector analysis in the screening of low muscle mass and low muscle mass associated with obesity in adult healthy subjects.

作者信息

Bennouar Salam, Bachir Cherif Abdelghani, Raaf Nabil, Hani Hadda Meroua, Kessira Amel, Abdi Samia

机构信息

Central Laboratory of Clinical Biology, Frantz Fanon Hospital, University Hospital Center of Blida, 9000, Blida, Algeria.

Department of Internal Medicine, University Hospital Center of Blida, 9000, Blida, Algeria.

出版信息

Intern Emerg Med. 2025 Apr;20(3):709-722. doi: 10.1007/s11739-025-03857-y. Epub 2025 Jan 15.

Abstract

The aim was to estimate the prevalence of low muscle mass (LMM) and low muscle mass associated with obesity (LMM-O) in healthy adult, and to verify the performance of raw bioelectrical impedance parameters (BIA) and vector analysis (BIVA) in the screening of this tow conditions. This is a cross-sectional study including 1025 healthy adults. Body composition was assessed by the BIA technique. The appendicular skeletal muscle mass index (ASMMI) and body fat percentage (BF%) were used for the screening of LMM and LMM-O. The raw BIA parameters were: resistance (R), reactance (X), phase angle (PhA), and impedance (Z). The vectors, R and X, were adjusted for height and projected on the RX graph. Associations were checked by the correlation test, binary logistic regression, adjusted for age and body water, and ROC curve. LMM was found in 30.8% of the subjects, and 20.9 and 21.4% of the men and women were with LMM-O. PhA and R/H were the most powerful discriminators of LMM with a sensitivity of 62-100% and a specificity of 71-90%. Cutoff values of PhA ranged between 4.95° and 5.75° for women and men. The RX graph was able to identify LMM subjects, with clustering on the right side: area of low cellularity, high R/H and low-phase angle. Traditional anthropometric indices were the least effective in identifying LMM-O. The BIVA approach, PhA, R and R/H are effective in the screening of LMM and LMM-O, irrespective of age, gender, intra- and extracellular hydration status.

摘要

目的是估计健康成年人中低肌肉量(LMM)和与肥胖相关的低肌肉量(LMM-O)的患病率,并验证原始生物电阻抗参数(BIA)和矢量分析(BIVA)在筛查这两种情况时的性能。这是一项横断面研究,纳入了1025名健康成年人。采用BIA技术评估身体成分。用四肢骨骼肌质量指数(ASMMI)和体脂百分比(BF%)筛查LMM和LMM-O。原始BIA参数包括:电阻(R)、电抗(X)、相角(PhA)和阻抗(Z)。将矢量R和X根据身高进行调整,并投影到RX图上。通过相关性检验、二元逻辑回归(校正年龄和身体水分)以及ROC曲线来检查相关性。30.8%的受试者存在LMM,20.9%的男性和21.4%的女性患有LMM-O。PhA和R/H是LMM最有力的判别指标,敏感性为62%-100%,特异性为71%-90%。女性和男性的PhA截断值在4.95°至5.75°之间。RX图能够识别LMM受试者,在右侧聚集:低细胞密度、高R/H和低相角区域。传统人体测量指标在识别LMM-O方面效果最差。BIVA方法、PhA、R和R/H在筛查LMM和LMM-O方面有效,不受年龄、性别、细胞内和细胞外水合状态的影响。

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