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Bioelectrical impedance analysis and hormonal assessment in adolescents with pubertal gynecomastia

  • Tarık Kırkgöz ORCID logo EMAIL logo and Serkan Bilge Koca ORCID logo
Published/Copyright: November 10, 2025

Abstract

Objectives

Gynecomastia is common during adolescence, yet its relationship with body composition remains unclear. This study investigates differences in body composition, fat distribution, and hormonal profiles between adolescents with gynecomastia and healthy controls.

Methods

This case–control study included 70 adolescents diagnosed with gynecomastia and 67 healthy controls matched for age and Tanner stage. Anthropometric measurements, bioelectrical impedance analysis (BIA), and serum hormonal profiles were assessed. Body composition parameters, including fat mass (FM), fat-free mass (FFM), muscle mass (MM), bone mass (BM), total body water (TBW), muscle-to-fat mass ratio (MFR), and basal metabolic rate (BMR), were measured using the Tanita MC-780 MA device.

Results

Adolescents with gynecomastia exhibited significantly higher trunk fat mass (trunk fat mass: 20.60 ± 9.48 % vs. 17.64 ± 6.61 %, p=0.0462) and hormonal alterations, including reduced follicle-stimulating hormone (FSH) and free thyroxine (fT4) levels (FSH: 2.7 ± 1.4 vs. 3.5 ± 2.0 IU/L, p=0.0164; fT4 12.4 ± 1.9 vs. 13.1 ± 2.5 p=0.0193).

Conclusions

These findings highlight the interplay between adiposity and endocrine changes in gynecomastia, warranting further exploration of underlying causative factors.


Corresponding author: Tarık Kırkgöz, Kayseri City Hospital, Kayseri, Türkiye, E-mail:

  1. Research ethics: The local Institutional Review Board approved the study.

  2. Informed consent: Informed consent was obtained from all individuals included in this study.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

References

1. Nordt, CA, DiVasta, AD. Gynecomastia in adolescents. Curr Opin Pediatr 2008;20:375–82. https://doi.org/10.1097/mop.0b013e328306a07c.Search in Google Scholar

2. Lazala, C, Saenger, P. Pubertal gynecomastia. J Pediatr Endocrinol Metab 2002;15:553–60. https://doi.org/10.1515/jpem.2002.15.5.553.Search in Google Scholar PubMed

3. Gallagher, D, Andres, A, Fields, DA, Evans, WJ, Kuczmarski, R, Lowe, WLJr, et al.. Body composition measurements from birth through 5 years: challenges, gaps, and existing & emerging technologies-A national institutes of health workshop. Obes Rev 2020;21:e13033. https://doi.org/10.1111/obr.13033.Search in Google Scholar PubMed PubMed Central

4. Thajer, A, Truschner, K, Jorda, A, Skacel, G, Horsak, B, Greber-Platzer, S, et al.. A strength and neuromuscular exercise programme did not improve body composition, nutrition and psychological status in children with obesity. Acta Paediatr 2021;110:288–9. https://doi.org/10.1111/apa.15498.Search in Google Scholar PubMed PubMed Central

5. Więch, P, Sałacińska, I, Bazaliński, D, Dąbrowski, M. Body composition and phase angle as an indicator of nutritional status in children with juvenile idiopathic arthritis. Pediatr Rheumatol Online J 2018;16:82. https://doi.org/10.1186/s12969-018-0297-y.Search in Google Scholar PubMed PubMed Central

6. Mafra, D, Guebre-Egziabher, F, Fouque, D. Body mass index, muscle and fat in chronic kidney disease: questions about survival. Nephrol Dial Transpl 2008;23:2461–6. https://doi.org/10.1093/ndt/gfn053.Search in Google Scholar PubMed

7. Brener, A, Peleg, I, Rosenfeld, T, Kern, S, Uretzky, A, Elkon-Tamir, E, et al.. Beyond body mass index – body composition assessment by bioimpedance in routine endocrine practice. Endocr Pract. 2021 and https://doi.org/10.1016/j.eprac.2020.10.013., 27: 419-25.Search in Google Scholar PubMed

8. Ward, LC. Bioelectrical impedance analysis for body composition assessment: reflections on accuracy, clinical utility, and standardisation. Eur J Clin Nutr 2019;73:194–9. https://doi.org/10.1038/s41430-018-0335-3.Search in Google Scholar PubMed

9. Koca, SB, Kırkgöz, T, Kara, L. The diagnostic utility of bioelectrical impedance analysis in distinguishing precocious puberty from premature thelarche. J Pediatr Endocrinol Metab 2025;38:599–606. https://doi.org/10.1515/jpem-2025-0028.Search in Google Scholar PubMed

10. Brantlov, S, Ward, LC, Jødal, L, Rittig, S, Lange, A. Critical factors and their impact on bioelectrical impedance analysis in children: a review. J Med Eng Technol 2017;41:22–35. https://doi.org/10.1080/03091902.2016.1209590.Search in Google Scholar PubMed

11. Brantlov, S, Jødal, L, Lange, A, Rittig, S, Ward, LC. Standardisation of bioelectrical impedance analysis for the estimation of body composition in healthy paediatric populations: a systematic review. J Med Eng Technol 2017;41:460–79. https://doi.org/10.1080/03091902.2017.1333165.Search in Google Scholar PubMed

12. Frisch, RE, McArthur, JW. Menstrual cycles: fatness as a determinant of minimum weight for height necessary for their maintenance or onset. Science 1974;185:949–51. https://doi.org/10.1126/science.185.4155.949.Search in Google Scholar PubMed

13. Li, W, Liu, Q, Deng, X, Chen, Y, Yang, B, Huang, X, et al.. Association of prepubertal obesity with pubertal development in Chinese girls and boys: a longitudinal study. Am J Hum Biol 2018;30:e23195. https://doi.org/10.1002/ajhb.23195.Search in Google Scholar PubMed PubMed Central

14. Lian, Q, Mao, Y, Luo, S, Zhang, S, Tu, X, Zuo, X, et al.. Puberty timing associated with obesity and central obesity in Chinese Han girls. BMC Pediatr 2019;19:1. https://doi.org/10.1186/s12887-018-1376-4.Search in Google Scholar PubMed PubMed Central

15. Adami, F, Benedet, J, Takahashi, LAR, da Silva Lopes, A, da Silva Paiva, L, de Vasconcelos, FAG, et al.. Association between pubertal development stages and body adiposity in children and adolescents. Health Qual Life Outcome 2020;18:93. https://doi.org/10.1186/s12955-020-01342-y.Search in Google Scholar PubMed PubMed Central

16. Taylor, RW, Grant, AM, Williams, SM, Goulding, A. Sex differences in regional body fat distribution from pre- to postpuberty. Obesity 2010;18:1410–6. https://doi.org/10.1038/oby.2009.399.Search in Google Scholar PubMed

17. de Ridder, CM, Thijssen, JH, Bruning, PF, Van den Brande, JL, Zonderland, ML, Erich, WB, et al.. Body fat mass, body fat distribution, and pubertal development: a longitudinal study of physical and hormonal sexual maturation of girls. J Clin Endocrinol Metab 1992;75:442–6. https://doi.org/10.1210/jcem.75.2.1639945.Search in Google Scholar PubMed

18. Zheng, Y, Liang, J, Zeng, D, Tan, W, Yang, L, Lu, S, et al.. Association of body composition with pubertal timing in children and adolescents from guangzhou, China. Front Public Health 2022;10:943886. https://doi.org/10.3389/fpubh.2022.943886.Search in Google Scholar PubMed PubMed Central

19. Reinehr, T, Kulle, A, Barth, A, Ackermann, J, Lass, N, Holterhus, PM, et al.. Sex hormone profile in pubertal boys with gynecomastia and pseudogynecomastia. J Clin Endocrinol Metab 2020;105. https://doi.org/10.1210/clinem/dgaa044.Search in Google Scholar PubMed

20. Moore, DC, Schlaepfer, LV, Paunier, L, Sizonenko, PC. Hormonal changes during puberty: V. Transient pubertal gynecomastia: abnormal androgen-estrogen ratios. J Clin Endocrinol Metab 1984;58:492–9. https://doi.org/10.1210/jcem-58-3-492.Search in Google Scholar PubMed

21. Koca, SB, Kirkgoz, T, Kara, L. Body composition assessment measured via bioelectrical impedance analysis in euthyroid children with newly diagnosed hashimoto’s thyroiditis. J Pediatr Endocrinol Metab 2024;38:37–44. https://doi.org/10.1515/jpem-2024-0420.Search in Google Scholar PubMed

22. Ferreira, GOC, Ferrari, G, Langer, RD, Cossio-Bolaños, M, Gomez-Campos, R, Lázari, E, et al.. Phase angle and its determinants among adolescents: influence of body composition and physical fitness level. Sci Rep 2024;14:13697. https://doi.org/10.1038/s41598-024-62546-6.Search in Google Scholar PubMed PubMed Central

23. Spaziani, M, Carlomagno, F, Tenuta, M, Sesti, F, Angelini, F, Bonaventura, I, et al.. Extra-gonadal and non-canonical effects of FSH in males. Pharmaceuticals (Basel) 2023;16:813. https://doi.org/10.3390/ph16060813.Search in Google Scholar PubMed PubMed Central

24. Kleinberg, DL, Feldman, M, Ruan, W. IGF-I: an essential factor in terminal end bud formation and ductal morphogenesis. J Mammary Gland Biol Neoplasia 2000;5:7–17. https://doi.org/10.1023/a.1009507030633.Search in Google Scholar

Received: 2025-06-10
Accepted: 2025-10-22
Published Online: 2025-11-10
Published in Print: 2026-01-23

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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