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25 November 2025

Anthropometric Obesity Phenotypes in Young Physically Active Men: The Role of Body Composition and Fat Distribution

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1
Department of Health Promotion, Faculty of Physical Education and Health in Biala, Podlaska, Jozef Pilsudski University of Physical Education in Warsaw, 00-968 Warsaw, Poland
2
Institute of Sport, Tourism and Nutrition, Faculty of Biological Sciences, University of Zielona Góra, 65-417 Zielona Góra, Poland
*
Author to whom correspondence should be addressed.
This article belongs to the Special Issue New Updates in Adipocytes and Adipose Tissue—3rd Edition

Abstract

Background: BMI does not distinguish fat from lean mass, reducing its usefulness in active young adults. This study assessed obesity phenotypes and their associations with lean mass and adipose tissue distribution. Methods: A total of 174 male university students (mean age 20.88 ± 0.86 years) underwent anthropometric measurements, including BMI, waist circumference (WC), and waist-to-hip ratio (WHR), and body composition assessment using bioelectrical impedance analysis (BIA). Participants were classified into four phenotypes (MHNW, MHO, MUO, and NWO) based on BMI, body fat percentage (%BF), WC, and WHR. One-way ANOVA with Newman–Keuls post hoc tests was used to assess group differences. A multiple linear regression model was applied to determine the independent predictors of %BF. Results: MHNW was the most prevalent phenotype (66.7%), followed by MHO (19.0%), MUO (8.0%), and NWO (6.9%). Significant differences were observed in body composition and fat distribution among phenotypes. BMI poorly reflected %BF. Multiple regression analysis identified WC and WHR as the strongest independent predictors of %BF, whereas BMI was not significant after adjustment. Higher lean body mass in MHNW and MHO was associated with more favorable fat distribution patterns. Conclusions: BMI alone is insufficient to assess metabolic risk in young, physically active adults. WC and WHR showed superior predictive value for body fatness and should complement BMI in metabolic risk evaluation. Including lean body mass and fat distribution measures improves the identification of individuals at risk of metabolic and cardiovascular disorders.

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