Obtaining Linear Regression Formulas Depending on Upper Arm Lenght for Estimating Stature
Abstract
Objective: In our study, it was aimed to obtain linear regression formulas for estimating stature from upper arm length values of young adult female and male individuals and to examine the effect of right-left side asymmetry on regression formulas.
Materials & Methods: The study was carried out on 70 healthy young adult volunteers (35 males, 35 females) aged 18-36 years. Upper arm length was obtained by measuring the distance from the acromion to the olecranon. Asymmetry and gender differences analyzed. For the estimation of stature, regression formulas were created by simple linear regression analysis separately according to the genders.
Results: The linear regression formulas required for the stature calculation were obtained. Among the linear regression formulas based on upper arm length, the Standard Error of the Estimate (SEE) value was the lowest in the female upper right arm. SEE values for women were 5.22882 for the right upper arm and 5.4979 for the left upper arm; in men it was 6.62943 for the right upper arm and 6.60019 for the left upper arm. A moderately positive correlation was found between arm length and stature in both genders.
Conclusion: In the formulas obtained for the estimation of arm length in men, the SEE value was found to be higher than in women. According to the regression analysis, arm length values in women give a better estimation of stature compared to men. In women, asymmetry was detected between the right and left upper arm lengths. The regression equation of the right side was found to be more reliable.
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Details
Primary Language
English
Subjects
Clinical Sciences, Internal Diseases
Journal Section
Research Article
Publication Date
August 31, 2022
Submission Date
May 17, 2022
Acceptance Date
June 14, 2022
Published in Issue
Year 2022 Volume: 5 Number: 2