Anthropometric and morphological correlations of fat accumulation in active mesomorphic phenotypes: A cross-sectional observational study
Article Sidebar
Main Article Content
Abstract
Background: Although military personnel typically present lower BMI than civilians, significant body fat accumulation may still occur despite high levels of physical activity. The availability of tools for genome mapping has opened new perspectives on the study of body composition and polymorphisms. It has been shown that phenotypes studied for their differences, such as mesomorphy and endomorphy, share commonalities. This study investigated the relationship between body fat accumulation and the phenotypes defined by Heath-Carter somatotyping in active military personnel, aiming to understand the mechanisms driving the increasing prevalence of overweight and obesity in this workforce.
Methods: 130 military personnel who volunteered for this cross-sectional observational study were assessed for anthropometric measurements. The correlation between anthropometric variables and physical performance was analyzed using Principal Component Analysis. Statistical tests were performed using RStudio.
Results: The most common somatotype encountered was the endomorphic mesomorph (53.8%). Two distinct groups with different physical characteristics were identified. In the endomesomorphic group, body mass, body mass index, and % body fat values were 19%, 15%, and 83% higher than in the ectomesomorphic group. The ectomesomorphic group achieved 12% better V̇O2peak results and 7% better results in the 100m swimming tests. Principal Component 1 accounted for 69% of the variance in the data, with body mass index, endomorphy, mesomorphy, and % body fat showing strong positive correlations within this component.
Conclusion: The main finding was that mesomorphy, endomorphy, and body fat percentage were strongly correlated, despite these classic phenotypes being opposites. Observing individuals with extreme somatotype components, i.e., above 5.5 units for mesomorphy, may be an indicator of fat accumulation, even in groups undergoing constant training and high physical activity demands in their occupational activities.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Andreenko, E., & Mladenova, S. (2015). Changes in somatotype characteristics in middle-aged Bulgarian men. Nutrición Hospitalaria, 32(6), 2910–2915. https://doi.org/10.3305/nh.2015.32.6.9810
Araujo, A. O., Cancela, J. M., Rocha-Rodrigues, S., & Rodrigues, L. P. (2019). Association between somatotype profile and health-related physical fitness in a a special police unit. Journal of Occupational and Environmental Medicine, 61(2), e51–e55. https://doi.org/10.1097/JOM.0000000000001515
Bolonchuk, W. W., Siders, W. A., Lykken, G. I., & Lukaski, H. C. (2000). Association of dominant somatotype of men with body structure, function during exercise, and nutritional assessment. American Journal of Human Biology, 12(2), 167–180. https://doi.org/10.1002/(SICI)1520-6300(200003/04)12:2<167::AID-AJHB2>3.0.CO;2-3
Carter, J. E. L., & Heath, B. H. (1990). Somatotyping: Development and applications (Vol. 5). Cambridge University Press.
Fraga, A. B., de Lima Silva, F., Hongyu, K., Da Silva Santos, D., Murphy, T. W., & Lopes, F. B. (2016). Multivariate analysis to evaluate genetic groups and production traits of crossbred Holstein × Zebu cows. Tropical Animal Health and Production, 48(3), 533–538. https://doi.org/10.1007/s11250-015-0985-2
Gomes, D. V., Porto Alegre, A. C. A., Sant’Anna, M. L., & Salerno, V. P. (2022). Correlação da idade com estado nutricional e medidas antropométricas em Fuzileiros Navais da Marinha do Brasil: Um estudo transversal. Revista de Educação Física / Journal of Physical Education, 91(1), 5–15. https://doi.org/10.37310/ref.v91i1.2802
Guedes, D. P., & Guedes, J. E. R. P. (2006). Manual prático para avaliação em educação física (1ª ed.). Manole.
Hruby, A., & Hu, F. B. (2015). The epidemiology of obesity: A big picture. Pharmacoeconomics, 33(7), 673–689. https://doi.org/10.1007/s40273-014-0243-x
Ibanez-Zamacona, M. E., Poveda, A., & Rebato, E. (2019). Contribution of obesity-associated genetic variants to anthropometric somatotype components. Anthropologischer Anzeiger, 76(2), 101–111. https://doi.org/10.1127/anthranz/2019/0945
Jackson, A. S., & Pollock, M. L. (1985). Practical assessment of body composition. The Physician and Sportsmedicine, 13(5), 76–90. https://doi.org/10.1080/00913847.1985.11708790
Jelenkovic, A., Poveda, A., & Rebato, E. (2010). A statistical investigation into the sharing of common genetic factors between blood pressure and obesity phenotypes in nuclear families from Greater Bilbao (Spain). Journal of Hypertension, 28(4), 723–731. https://doi.org/10.1097/HJH.0b013e328336ecf3
Kaminsky, L. A., Arena, R., Myers, J., Peterman, J. E., Bonikowske, A. R., Harber, M. P., Medina Inojosa, J. R., Lavie, C. J., & Squires, R. W. (2022). Updated reference standards for cardiorespiratory fitness measured with cardiopulmonary exercise testing: Data from the Fitness Registry and the Importance of Exercise National Database (FRIEND). Mayo Clinic Proceedings, 97(2), 285–293. https://doi.org/10.1016/j.mayocp.2021.08.020
Knapik, J. J., Farina, E. K., Steelman, R. A., Trone, D. W., & Lieberman, H. R. (2023). The medical burden of obesity and overweight in the US military: Association of BMI with clinically diagnosed medical conditions in United States military service members. The Journal of Nutrition, 153(10), 2951–2967. https://doi.org/10.1016/j.tjnut.2023.08.023
Lê, S., Josse, J., & Husson, F. (2008). FactoMineR: An R package for multivariate analysis. Journal of Statistical Software, 25(1), 1–18. https://doi.org/10.18637/jss.v025.i01
Lehnert, T., Sonntag, D., Konnopka, A., Riedel-Heller, S., & König, H. H. (2013). Economic costs of overweight and obesity. Best Practice & Research Clinical Endocrinology & Metabolism, 27(2), 105–115. https://doi.org/10.1016/j.beem.2013.01.002
Loos, R. J. F., & Yeo, G. S. H. (2014). The bigger picture of FTO: The first GWAS-identified obesity gene. Nature Reviews Endocrinology, 10(1), 51–61. https://doi.org/10.1038/nrendo.2013.227
Lu, Y., & Loos, R. J. F. (2013). Obesity genomics: Assessing the transferability of susceptibility loci across diverse populations. Genome Medicine, 5(6), 55. https://doi.org/10.1186/gm459
Madden, A. M., & Smith, S. (2016). Body composition and morphological assessment of nutritional status in adults: A review of anthropometric variables. Journal of Human Nutrition and Dietetics, 29(1), 7–25. https://doi.org/10.1111/jhn.12278
Moura, J., Aboul-Enein, B. H., Bernstein, J., & Kruk, J. (2017). Selected weight management interventions for military populations in the United States: A narrative report. Nutrition and Health, 23(2), 67–74. https://doi.org/10.1177/0260106017704797
Ponce-Gonzalez, J. G., Martinez-Avila, A., Velazquez-Diaz, D., Perez-Bey, A., Gomez-Gallego, F., Marin-Galindo, A., Corral-Perez, J., & Casals, C. (2023). Impact of the FTO gene variation on appetite and fat oxidation in young adults. Nutrients, 15(9). https://doi.org/10.3390/nu15092037
Potter, A. W., Nindl, L. J., Pazmino, A., Soto, D. L., Hancock, J. W., Looney, D. P., Tharion, J. W., McEttrick, D. M., & Friedl, K. E. (2022). US Marine Corps Body Composition and Military Appearance Program (BCMAP) Study (Report No. 43). U.S. Army Research Institute of Environmental Medicine. https://doi.org/10.13140/RG.2.2.30155.87845
Rebato, E., Jelenkovic, A., & Salces, I. (2007). Heritability of somatotype components in Biscay families. HOMO — Journal of Comparative Human Biology, 58(3), 199–210. https://doi.org/10.1016/j.jchb.2006.08.005
Reyes-Guzman, C. M., Bray, R. M., Forman-Hoffman, V. L., & Williams, J. (2015). Overweight and obesity trends among active duty military personnel: A 13-year perspective. American Journal of Preventive Medicine, 48(2), 145–153. https://doi.org/10.1016/j.amepre.2014.08.033
Rosique, J., Rebato, E., Apraiz, A. G., & Pacheco, J. L. (1994). Somatotype related to centripetal fat patterning of 8- to 19-year-old Basque boys and girls. American Journal of Human Biology, 6(2), 171–181. https://doi.org/10.1002/ajhb.1310060205
Saranga, S. P., Prista, A., Nhantumbo, L., Beunen, G., Rocha, J., Williams-Blangero, S., & Maia, J. A. (2008). Heritabilities of somatotype components in a population from rural Mozambique. American Journal of Human Biology, 20(6), 642–646. https://doi.org/10.1002/ajhb.20733
Savegnago, R. P., Caetano, S. L., Ramos, S. B., Nascimento, G. B., Schmidt, G. S., Ledur, M. C., & Munari, D. P. (2011). Estimates of genetic parameters and cluster and principal components analyses of breeding values related to egg production traits in a White Leghorn population. Poultry Science, 90(10), 2174–2188. https://doi.org/10.3382/ps.2011-01474
Silventoinen, K., Maia, J., Jelenkovic, A., Pereira, S., Gouveia, E., Antunes, A., Thomis, M., Lefevre, J., Kaprio, J., & Freitas, D. (2021). Genetics of somatotype and physical fitness in children and adolescents. American Journal of Human Biology, 33(3), e23470. https://doi.org/10.1002/ajhb.23470
Silventoinen, K., Maia, J., Li, W., Sund, R., Gouveia, E. R., Antunes, A., Marques, G., Thomis, M., Jelenkovic, A., Kaprio, J., & Freitas, D. (2023). Genetic regulation of body size and morphology in children: A twin study of 22 anthropometric traits. International Journal of Obesity, 47(3), 181–189. https://doi.org/10.1038/s41366-023-01253-0
Simenko, J. (2018). Somatotype profile of a special police unit. International Journal of Morphology, 36(4), 1225–1228. https://doi.org/10.4067/s0717-95022018000401225
Siri, W. E. (1961). Body composition from fluid spaces and density: Analysis of methods in techniques for measuring body composition. In Techniques for measuring body composition (pp. 223–244). National Academy of Science-National Research Council.
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & STROBE Initiative. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Annals of Internal Medicine, 147(8), 573–577. https://doi.org/10.7326/0003-4819-147-8-200710160-00010