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

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...

Full description

Saved in:
Bibliographic Details
Published in:Archives of orthopaedic and trauma surgery 2012-12, Vol.132 (12), p.1807-1811
Main Authors: Klum, Matthias, Wolf, Maya B., Hahn, Peter, Leclère, Franck M., Bruckner, Thomas, Unglaub, Frank
Format: Article
Language:English
Subjects:
Adult
Arm - physiology
Body Height
Body Mass Index
Body measurements
Body Weight
Disability Evaluation
Female
Hand - physiology
Hand Strength - physiology
Handsurgery
Humans
Male
Medicine
Medicine & Public Health
Orthopedics
Predictive Value of Tests
Product design
Range of Motion, Articular
Shoulder - physiology
Surveys and Questionnaires
Wrist Joint - physiology
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0936-8051
1434-3916
DOI:10.1007/s00402-012-1602-8