Upper and Lower Limb Muscle Thickness Measurements in Older Women: Analysis of Variability and Development of Prediction Equations

IF 0.5 Q4 ORTHOPEDICS MLTJ-Muscles Ligaments and Tendons Journal Pub Date : 2023-03-01 DOI:10.32098/mltj.01.2023.08
Rafael Pereira, Claudineia Matos de Araujo, J. Carneiro, Raildo da, Silva Coqueiro, L. Schettino, M. Fernandes, A. I. O. L. C. arneiro
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Abstract

Purpose. The present study aimed to describe the variability of muscle thickness measures (MT) of arm and thigh muscles, obtained by ultrasound (USD) from community-dwelling healthy older women; and to obtain a predictive equation model for arm, thigh and leg MT based on upper and lower limb circumference measures using a frequentist and Bayesian approach. Methods. Sixty-two older women (74.5 ± 8.5 years) volunteered and were submitted to MT measures. Assessments of the Brachial (Br), Biceps Brachii (BB), Vastus Lateralis (VL), Rectus Femoris (RF) were obtained and grouped to infer elbow flexors (EF), and knee extensors (KE) muscles. Thigh (TC) and arm (AC) circumference were also measured. Variability of MT and circumference measures were inferred by the coefficient of variation (CV) and Huber’s M-estimator. Age-adjusted linear regression models were generated to predict MT. The magnitude of evidence was obtained using Bayesian inference, determining posterior probabilities based on our data. Results. The MT measure of the EF presented lower CV (15.9%). The CV of limb circumference measures was 10.8% (TC) and 12.5% (AC) and Huber’s M-estimator varied 0.18 cm (AC). Circumference measurements were significantly associated with MT with age-adjusted coefficients of determination (R 2 ) of 0.268 and 0.173 (p < 0.05), and standard error of the estimate of 0.36 cm and 0.56 cm for EF and KE, respectively. Bayesian inference confirmed the good posterior probability of the model. Conclusions. Measure of MT of the EF presented lower between-subject variability, and a better predictive equation model for MT based on AC.
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老年妇女上肢和下肢肌肉厚度测量:变异性分析和预测方程的发展
目的。本研究旨在描述社区居住的健康老年妇女通过超声(USD)获得的手臂和大腿肌肉厚度测量(MT)的变异性;基于上肢和下肢围度测量,采用频率分析和贝叶斯方法,获得手臂、大腿和腿部MT的预测方程模型。方法。62名老年妇女(74.5±8.5岁)自愿接受MT测量。对肱(Br)、肱二头肌(BB)、股外侧肌(VL)、股直肌(RF)进行评估,并分组推断肘屈肌(EF)和膝关节伸肌(KE)。同时测量大腿(TC)和手臂(AC)围度。通过变异系数(CV)和Huber 's m -估计量推断MT和周长的变异性。生成年龄调整的线性回归模型来预测MT。使用贝叶斯推理获得证据的大小,根据我们的数据确定后验概率。结果。MT测量EF的CV值较低(15.9%)。肢体围度CV分别为10.8% (TC)和12.5% (AC), Huber 's M-estimator变化0.18 cm (AC)。周长测量与MT显著相关,经年龄调整的决定系数(r2)分别为0.268和0.173 (p < 0.05), EF和KE的估计标准误差分别为0.36 cm和0.56 cm。贝叶斯推理证实了该模型具有良好的后验概率。结论。EF的MT测量具有较低的受试者间变异性,基于AC的MT预测方程模型具有较好的预测效果。
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来源期刊
CiteScore
1.30
自引率
0.00%
发文量
51
期刊介绍: MLTJ (Muscle, Ligaments and Tendons Journal) is an open access, peer-reviewed online journal that encompasses all aspects of clinical and basic research studies related to musculoskeletal, ligament, tendon, public health, exercise physiology and kinesiology issues. Muscle, Ligaments and Tendons Journal (MLTJ) provides the platform for exchange of new clinical and scientific information in the most precise and expeditious way to achieve timely dissemination of information and cross-fertilization of ideas. It is the official journal of the Italian Society of Muscles, Ligaments and Tendons (I.S.Mu.L.T.), Società Italiana Terapia con Onde D’urto (S.I.T.O.D.) and Società Italiana Studio Piede e Caviglia (S.I.S.P.E.C)
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