Anthropometric Determinants and Predictive Modeling of Upper Body Strength in Athletes
DOI:
https://doi.org/10.34256/ijk2619Keywords:
Upper Body Strength, Bench Press, Arm Girth, PerformanceAbstract
Introduction: The purpose of our study was to predict upper-body strength on the basis of anthropometric variables. Methods: A total of 50 male athletes were chosen as subjects for the study. The age criteria for the subjects were between 18 and 25 years. The anthropometric variables were chosen as independent variable i.e. Standing Height and Weight were obtained using an electronic scale (Seca Instruments Ltd. Hamburg, Germany) with a precision of up to .001m, Arm Span, Iliac Crest Height, Arm Length was measured with the Segmometer (Cescorf Flexible Segmometer), Sitting Height was measured with the Holtain Sitting Height Table, Girth Measurement (Biceps, Waist, Thigh, Calf, Hip) were determined using a Steel tape, Skin fold for Biceps, Triceps, Subscapular, Supraspinale, Thigh, Calf were obtained with a skinfold caliper and recorded in millimetres (Harpenden Skinfold). Body Composition was facilitated by Bioelectrical Impedance Analysis (BIA). Bone Breadth of Humerus, Femur, and Shoulder was measured by Small (CESCORF Slide Caliper) and large Sliding Caliper (Cescorf Large Sliding Caliper) and the dependent variable, i.e. Upper arm strength, was measured with bench press 1 RM Test. Pearson product-multiple correlation was used to find out the relationship between anthropometric variables and bench press strength. A regression equation was used to predict upper arm strength based on anthropometric characteristics. Results: A strong correlation (r = 0.791) indicates that body measurements collectively have a significant impact on upper body strength. R Square (.619) as a predictor was included, which means that 61.9% of the variance in the bench press was associated with changes in the anthropometric variable. Conclusion: Regression equation finding the combination of constant flexed arm girth could provide a reasonably good estimation of bench press performance.
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Copyright (c) 2026 Sanjay Kumar Prajapati, Mukesh Kumar Verma, Harshit Verma, Sanjeev Shivanagouda Patil, Susheel Gupta, Vivek Venugopal Pai
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Articles published in the International Journal of Kinanthropometry are licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, provided appropriate credit is given to the original authors and the source.
