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在进行上肢重复运动任务时,性别是否可以作为机械变量的代理?性别和人体测量负荷对肌肉疲劳影响的研究。

Is sex a proxy for mechanical variables during an upper limb repetitive movement task? An investigation of the effects of sex and of anthropometric load on muscle fatigue.

机构信息

Department of Kinesiology and Physical Education, McGill University, 475 Pine Ave W, Montreal, Quebec, H2W 1S4, Canada.

CINBIOSE Research Centre, Université du Québec à Montréal (UQAM), 8888, Succ. Centre-ville, Montreal, Quebec, H3C 3P8, Canada.

出版信息

Biol Sex Differ. 2020 Oct 30;11(1):60. doi: 10.1186/s13293-020-00336-1.

DOI:10.1186/s13293-020-00336-1
PMID:33126920
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7596960/
Abstract

BACKGROUND

Women report more work-related pain and neck/shoulder musculoskeletal disorders than men. For the same absolute workload, due to lower strength, females generally work at a higher relative intensity, which could induce more fatigue. However, the arm's anthropometric load (AL) of men is higher. Therefore, simply lifting their arm could be more fatiguing. Sex as a variable is formed of many constructs, and analyses can become muddied by their differing responses to fatigue. No studies have considered AL, when comparing how fatigue affects men and women. The purpose was to determine if including the arm's AL in the statistical analysis would impact findings of sex-specific effects of shoulder fatigue on muscle EMG.

METHODS

Fifty-five (29m/26f) participants completed a repetitive pointing task (RPT) at shoulder height until they reported fatigue of 8+ on the BORG CR-10 scale. Muscle activities were measured using surface electrodes placed over the anterior deltoid (AD) and upper trapezius (UT) muscles. Muscle activity amplitude was quantified using root mean square (RMS). First- and last-minute data were used to assess change from no-fatigue (NF) to fatigue-terminal (FT) conditions. AL was calculated using sex-specific body parameter equations. General estimating equations (GEE) were used to determine the effects of sex and fatigue on RMS values, while including AL in the GEE.

RESULTS

There was no sex difference in time to reach fatigue. A significant main effect of sex on RMS was observed (χ(1) = 4.17, p = 0.04) when including AL as a covariate. Females displayed a significantly higher percentage change in AD RMS from NF to FT, compared to males (p = 0.03), when AL was included in the GEE. No sex differences in UT were observed.

CONCLUSIONS

This sex difference emerged when AL was included as a covariate, suggesting that sex-associated anthropometric differences may contribute to sex differences in the fatigue response. Differences in the impact of AL on AD compared to UT could be explained by differences in their respective mechanical roles or muscle fiber content. Anthropometrics may be useful to include as covariates in future research to separate individual anthropometric differences from sex differences.

摘要

背景

女性比男性报告更多与工作相关的疼痛和颈部/肩部肌肉骨骼疾病。由于力量较弱,对于相同的绝对工作量,女性通常以更高的相对强度工作,这可能会导致更多疲劳。然而,男性的手臂人体工程学负荷(AL)更高。因此,仅仅抬起手臂可能会更疲劳。性别作为一个变量由许多结构组成,由于它们对疲劳的反应不同,分析可能会变得混乱。没有研究在比较疲劳对男性和女性的影响时考虑到 AL。目的是确定在统计分析中包括手臂的 AL 是否会影响肩部疲劳对肌肉肌电图的性别特异性影响的研究结果。

方法

55 名参与者(29 名男性/26 名女性)完成了一个重复性指向任务(RPT),直到他们在 BORG CR-10 量表上报告疲劳程度为 8+。使用放置在前三角肌(AD)和上斜方肌(UT)上的表面电极测量肌肉活动。使用均方根(RMS)量化肌肉活动幅度。使用第一分钟和最后一分钟的数据评估从无疲劳(NF)到疲劳终末(FT)条件的变化。使用特定性别的身体参数方程计算 AL。使用广义估计方程(GEE)确定性别和疲劳对 RMS 值的影响,同时在 GEE 中包含 AL。

结果

达到疲劳的时间没有性别差异。当包括 AL 作为协变量时,观察到性别对 RMS 值有显著的主效应(χ(1) = 4.17,p = 0.04)。当包括 GEE 中的 AL 时,女性从 NF 到 FT 时 AD RMS 的百分比变化明显高于男性(p = 0.03)。UT 中未观察到性别差异。

结论

当包括 AL 作为协变量时,出现了这种性别差异,这表明与性别相关的人体工程学差异可能导致疲劳反应中的性别差异。AD 与 UT 相比,AL 对 AD 的影响不同,这可能是由于它们各自的机械作用或肌肉纤维含量不同所致。人体测量学可能是有用的协变量,可用于未来的研究,以将个体人体测量学差异与性别差异分开。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/e1e8da8db4b2/13293_2020_336_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/1c85a4a6fadc/13293_2020_336_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/fbdb94bf09f2/13293_2020_336_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/03f1604b9571/13293_2020_336_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/e1e8da8db4b2/13293_2020_336_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/1c85a4a6fadc/13293_2020_336_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/336483df6626/13293_2020_336_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/af0b94226ff2/13293_2020_336_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/fbdb94bf09f2/13293_2020_336_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/03f1604b9571/13293_2020_336_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a57/7596960/e1e8da8db4b2/13293_2020_336_Fig6_HTML.jpg

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