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KMID : 0980720170360010026
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Keimyung Medical Journal
2017 Volume.36 No. 1 p.26 ~ p.35
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Development of Predictive Model for Assessment of Grip Strength among Koreans: Data from 2014-2015 Korea National Health and Nutrition Examination Survey
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Baek Ki-Ook
Yang Seon-Hee
Chung In-Sung
Lee Mi-Young
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Abstract
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Grip strength is used in the various field to assess the disorder of upper limb. Normative data on the grip strength of population is needed to assess decreased grip strength. In this study, we tried to make a estimating model considering age and anthropometry investigation data, by analyzing 2014-2015 Korean National Health and Nutrition Examination Survey data. The subjects of this study were 10,430 participants who measured grip strength of both hands, have no missing data on anthropometry data and survey. Analysis showed that the grip strength had a curve-shaped correlation which could best be explained by the cubic expression of age, and linear correlation between height, weight and waist circumference. After the stratification of the gender, a prediction formula with age, height, and body weight as independent variables for dominant hand and non-dominant hand grip strength was presented. In addition, the distribution of estimated value to measured value ratio among subjects was suggested, which can be used to assess the abnormal value of grip strength. The distribution of non-dominant hand grip strength to dominant hand grip strength was also suggested, which can be used to determine decreased unilateral grip strength. Several studies have suggested normative value for grip strength by gender and age of Koreans, but there are no consideration for adjusting height and weight. In this study, the model was developed to calculate the predicted grip force considering age, height, and weight. With the distribution data of measured value to predicted value ratio and non-dominant hand grip strength to dominant hand grip strength ratio, the model can be helpful to assess a reduction in grip strength.
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KEYWORD
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Grip, Hand strength, Statistical regression
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