Relationships and comparative reliability of ultrasound derived measures of upper and lower limb muscle thickness, and estimates of muscle area from anthropometric measures

Author:

Budzynski-Seymour EmilyORCID,Fisher James,Giessing Jürgen,Gentil Paulo,Steele JamesORCID

Abstract

Abstract: The gold standard measure for assessing muscular size currently is magnetic resonance imaging; however, it is expensive and not easily accessible. Both anthropometric techniques (AN) and ultrasound (UT) are commonly employed methods to measure muscle size. However, the degree to which these approaches offer similar information has not been examined. The aim of the study was to investigate the relationship between UT and AN measurements of muscle thickness in addition to their comparative reliability. Fifteen males (27±9 years) volunteered to take part in the study and underwent both AN and UT measures, taken to assess their upper arm and upper leg muscle size on separate days a week apart. Correlations between the two measures ranged from r=0.548-0.918 (p<0.05) suggesting a good relationship and thus comparable information. Results showed similar coefficient of variation (CV%) for the upper leg (AN 2.3%, UT 2.4%), but slightly greater reliability for UT results for the upper arm (AN 5.5%, UT 2.8%). It appears that both methods are reliable approaches to measurement of muscle size, though AN likely represents a lower cost and greater ease of use. Researchers should consider this when deciding upon which approach to use in the assessment of muscle size in the absence of gold standard approaches.

Publisher

Center for Open Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3