Prediction of muscle fiber composition using multiple repetition testing

使用多次重复测试预测肌纤维组成

阅读:6
作者:Elliott C R Hall, Evgeny A Lysenko, Ekaterina A Semenova, Oleg V Borisov, Oleg N Andryushchenko, Liliya B Andryushchenko, Tatiana F Vepkhvadze, Egor M Lednev, Piotr Zmijewski, Daniil V Popov, Edward V Generozov, Ildus I Ahmetov0

Abstract

Direct determination of muscle fiber composition is invasive and expensive, with indirect methods also requiring specialist resources and expertise. Performing resistance exercises at 80% 1RM is suggested as a means of indirectly estimating muscle fiber composition, though this hypothesis has never been validated against a direct method. The aim of the study was to investigate the relationship between the number of completed repetitions at 80% 1RM of back squat exercise and muscle fiber composition. Thirty recreationally active participants' (10 females, 20 males) 1RM back squat load was determined, before the number of consecutive repetitions at 80% 1RM was recorded. The relationship between the number of repetitions and the percentage of fast-twitch fibers from vastus lateralis was investigated. The number of completed repetitions ranged from 5 to 15 and was independent of sex, age, 1RM, training frequency, training type, training experience, BMI or muscle fiber cross-sectional area. The percentage of fast-twitch muscle fibers was inversely correlated with the number of repetitions completed (r = -0.38, P = 0.039). Participants achieving 5 to 8 repetitions (n = 10) had significantly more fast-twitch muscle fibers (57.5 ± 9.5 vs 44.4 ± 11.9%, P = 0.013) than those achieving 11-15 repetitions (n = 11). The remaining participants achieved 9 or 10 repetitions (n = 9) and on average had equal proportion of fast- and slow-twitch muscle fibers. In conclusion, the number of completed repetitions at 80% of 1RM is moderately correlated with muscle fiber composition.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。