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.
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.
Authors: C K Spies; T Bruckner; L P Müller; F Unglaub; P Eysel; S Löw; M J Filbert Journal: Arch Orthop Trauma Surg Date: 2021-05-01 Impact factor: 3.067