
The objective of this study was to analyze the correlations between anthropometric data and maximal grip strength (MGS) in order to establish a simple model to predict "normal" MGS. Randomized bilateral measurement of MGS was performed on a homogeneous population of 100 subjects. MGS was measured according to a standardized protocol with three dynamometers (Jamar, Myogrip and Martin Vigorimeter) for both dominant and non-dominant sides. Several anthropometric data were also measured: height; weight; hand, wrist and forearm circumference; hand and palm length. Among these data, hand circumference had the strongest correlation with MGS for all three dynamometers and for both hands (0.789 and 0.782 for Jamar; 0.829 and 0.824 for Myogrip; 0.663 and 0.730 for Vigorimeter). In addition, the only anthropometric variable systematically selected by a stepwise multiple linear regression analysis was also hand circumference. Based on this parameter alone, a predictive regression model presented good results (r(2) = 0.624 for Jamar; r(2) = 0.683 for Myogrip and r(2) = 0.473 for Vigorimeter; all adjusted r(2)). Moreover a single equation was predictive of MGS for both men and women and for both non-dominant and dominant hands. "Normal" MGS can be predicted using hand circumference alone.
[SDV.IB] Life Sciences [q-bio]/Bioengineering, Adult, Male, hand grip, Anthropometry, Hand Strength, Muscle Strength Dynamometer, Hand, Functional Laterality, Sex Factors, Reference Values, Body Size, Humans, Regression Analysis, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Female
[SDV.IB] Life Sciences [q-bio]/Bioengineering, Adult, Male, hand grip, Anthropometry, Hand Strength, Muscle Strength Dynamometer, Hand, Functional Laterality, Sex Factors, Reference Values, Body Size, Humans, Regression Analysis, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Female
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