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使用人体测量学数据、DASH 问卷和手腕活动范围预测握力和关键捏力。

Predicting grip strength and key pinch using anthropometric data, DASH questionnaire and wrist range of motion.

机构信息

Department of Handsurgery, Vulpius Klinik, Bad Rappenau Vulpiusstrasse 29, 74906 Bad Rappenau, Germany.

出版信息

Arch Orthop Trauma Surg. 2012 Dec;132(12):1807-11. doi: 10.1007/s00402-012-1602-8. Epub 2012 Sep 16.

Abstract

PURPOSE

The objective of this study was to examine the influence of anthropometric data, occupational manual strain, DASH (disability of arm, shoulder and hand) score and range of motion (ROM) on grip strength and key pinch. An additional goal was to develop models that enable the prediction of hand strength using the aforementioned parameters.

METHODS

Normative data generated from a healthy working population (n = 750) served as basis for the statistical analysis. Prediction models for hand strength were developed using multivariate regression analysis.

RESULTS

Gender, body weight and height, BMI and extension ROM correlate positively, age and DASH score, however, correlate negatively with grip strength and key pinch. Occupational manual strain has no influence on hand strength. The predictive power of the developed models was 68.4 % for grip strength and 57.1 % for key pinch.

CONCLUSIONS

The developed models enable the prediction of hand strength using easily obtainable data points. The models will have application in clinical practice, physiological studies, medical evidence and rehab decisions.

摘要

目的

本研究旨在探讨人体测量数据、职业体力劳动负荷、手臂、肩部和手部功能障碍(DASH)评分和活动范围(ROM)对握力和捏力的影响。本研究的另一个目的是开发使用上述参数预测手部力量的模型。

方法

本研究以健康劳动人群(n=750)的正常数据为基础进行统计学分析。使用多元回归分析建立手部力量预测模型。

结果

性别、体重和身高、BMI 和伸展 ROM 与握力和捏力呈正相关,而年龄和 DASH 评分与握力和捏力呈负相关。职业体力劳动负荷对握力和捏力没有影响。所开发模型对握力的预测能力为 68.4%,对捏力的预测能力为 57.1%。

结论

所开发的模型可以使用易于获得的数据点预测手部力量。这些模型将在临床实践、生理研究、医学证据和康复决策中得到应用。

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