Correlación entre parámetros antropométricos y riesgo cadiometabólico en militares (Correlation between anthropometric parameters and cardiometabolic risk in military)

Autores/as

  • Marly Melo Zanetti Instituto de Pesquisa da Capacitação Física do Exército (IPCFEx), Rio de Janeiro, Brazil https://orcid.org/0000-0002-9740-1577
  • Leandro de Lima e Silva Programa de Pós-Graduação em Ciências do Exercício e do Esporte, Universidade do Estado do Rio de Janeiro (PPGCEE/UERJ), Rio de Janeiro, Brazil https://orcid.org/0000-0002-6644-8452
  • Marcio Antonio de Barros Sena Instituto de Pesquisa da Capacitação Física do Exército (IPCFEx), Rio de Janeiro, Brazil https://orcid.org/0000-0003-4671-5100
  • Eduardo Borba Neves Universidade Tecnológica Federal do Paraná (UTFPR) https://orcid.org/0000-0003-4507-6562
  • Paula Fernandez Ferreira Instituto de Pesquisa da Capacitação Física do Exército (IPCFEx), Rio de Janeiro, Brazil https://orcid.org/0000-0003-3742-1549
  • Felipe Keese Instituto de Pesquisa da Capacitação Física do Exército (IPCFEx), Rio de Janeiro, Brazil https://orcid.org/0000-0002-1991-8271
  • Rodolfo Alkmim Moreira Nunes Programa de Pós-Graduação em Ciências do Exercício e do Esporte, Universidade do Estado do Rio de Janeiro (PPGCEE/UERJ), Rio de Janeiro, Brazil https://orcid.org/0000-0001-9707-2649
  • Marcos de Sá Rego Fortes Instituto de Pesquisa da Capacitação Física do Exército (IPCFEx), Rio de Janeiro, Brazil http://orcid.org/0000-0003-2038-5545

DOI:

https://doi.org/10.47197/retos.v44i0.91559

Palabras clave:

Grasa, Enfermedad Cardiometabólica, Bioquímica, (Fat, cardiometabolic disease, biochemistry)

Resumen

Introducción. El objetivo fue verificar la relación entre parámetros antropométricos y biomarcadores asociados a enfermedades cardiometabólicas en personal militar. Métodos: Se trata de un estudio analítico de corte transversal, que involucró a 26 hombres soldados del Ejército Brasileño (EB), con una edad media de 32,7 ± 2,12 años, físicamente activos y de diversas organizaciones militares de la EB. Se evaluaron biomarcadores clínicos serológicos: glucosa (GLIC), insulina (INSUL), triglicéridos (TRIG), colesterol total (CT) y lipoproteínas de alta densidad (HDL-c) y variables antropométricas obtenidas con densitómetro de absorción de rayos X de energía dual (DXA) y circunferencias corporales. La prueba de Shapiro-Wilk y la prueba de correlación de Pearson se aplicaron utilizando el software Statistics® versión 12.0. Resultados: Correlaciones negativas significativas entre GLIC y masa magra (LM) (r = -0.46; p = 0.031) y masa libre de grasa (FFM) (r = -0.46; p = 0.032) y positiva con el porcentaje de grasa (% F) (r = 0,43; p = 0,043). La insulina (INSUL) mostró correlaciones positivas con la masa grasa (MG) (r = 0,52; p = 0,012); tejido adiposo visceral (IVA) (r = 0,48; p = 0,024), circunferencia de cintura (CC) (r = 0,53; p = 0,01) e índice de masa corporal (IMC) (r = 0, 54; p = 0,009). El índice del modelo para evaluar la homeostasis de la insulina (HOMA-IR) mostró correlaciones positivas con% F (r = 0.44; p = 0.04), MG (r = 0.55; p = 0.007), TAV (r = 0.52; p = 0.014), CC (r = 0,54; p = 0,01) y con el IMC (r = 0,52; p = 0,014). Conclusión: Hubo una asociación positiva entre las variables que representan la resistencia a la insulina y las relacionadas con la grasa corporal. Además de correlaciones negativas entre GLIC y variables relacionadas con la masa muscular.

Abstract. Introduction: The objective was to verify the relationship between anthropometric parameters and biomarkers associated with cardiometabolic diseases in military personnel. Methods: This is an analytical cross-sectional study, which involved 26 male Brazilian Army (EB) soldiers, with a mean age of 32.7 ± 2.12, physically active and from various EB military organizations. Serological clinical biomarkers were evaluated: glucose (GLUC), insulin (INSUL), triglyceride (TRIG), total cholesterol (TC) and high-density lipoprotein (HDL-c) and anthropometric variables obtained with a dual energy X-ray absorption densitometer (DXA) and body circumferences. The Shapiro-Wilk test and the Pearson correlation test were applied using the software Statistics® version 12.0. Results: Significant negative correlations between GLUC and lean mass (LM) (r = -0.46; p = 0.031) and fat-free mass (FFM) (r = -0.46; p = 0.032) and positive with the percentage of fat (%F) (r = 0.43; p = 0.043). Insulin (INSUL) showed positive correlations with fat mass (FM) (r = 0.52; p = 0.012); visceral adipose tissue (VAT) (r = 0.48; p = 0.024), waist circumference (WC) (r = 0.53; p = 0.01) and body mass index (BMI) (r = 0, 54; p = 0.009). The index of the model for assessing insulin homeostasis (HOMA-IR) showed positive correlations with %F (r = 0.44; p = 0.04), FM (r = 0.55; p = 0.007), VAT ( r = 0.52; p = 0.014), WC (r = 0.54; p = 0.01) and with the BMI (r = 0.52; p = 0.014). Conclusion: There was a positive association between variables representing insulin resistance and those related to body fat. In addition to negative correlations between GLUC and variables related to muscle mass.

Citas

Amorim, P., & Faria, F. J. M. (2012). Dispêndio energético das atividades humanas e sua repercussão para a saúde. 8(Supl. 2), 295-302.

Carrasco, N. F., Galgani, F. J. E., & Reyes, J. M. J. R. M. C. L. C. (2013). Síndrome de resistencia a la insulina. Estudio y manejo. 24(5), 827-837.

Castro, A. V. B., Kolka, C. M., Kim, S. P., & Bergman, R. N. (2014). Obesity, insulin resistance and comorbidities–Mechanisms of association. Arquivos Brasileiros de Endocrinologia & Metabologia, 58, 600-609.

Enriquez-Del Castillo, L. A., Hernández, N. C., Luján, R. C., & Olivares, L. A. F. (2021). Capacidades físicas y su relación con la actividad física y composición corporal en adultos (Physical capacities and their relationship with physical activity and body composition in adults). Retos, 41, 674-683.

Goldie, C., Taylor, A. J., Nguyen, P., McCoy, C., Zhao, X.-Q., & Preiss, D. J. H. (2016). Niacin therapy and the risk of new-onset diabetes: a meta-analysis of randomised controlled trials. 102(3), 198-203.

Hayashi, T., Boyko, E. J., McNeely, M. J., Leonetti, D. L., Kahn, S. E., & Fujimoto, W. Y. (2008). Visceral adiposity, not abdominal subcutaneous fat area, is associated with an increase in future insulin resistance in Japanese Americans. Diabetes, 57(5), 1269-1275.

Henry, J. (2012). Diagnóstico Clínico e Tratamento-Por Métodos laboratoriais: Nelson Gomes de Oliveira Ed: Manole ltda. 18Ed. Pag.

Holt, H., Wild, S., Wareham, N., Ekelund, U., Umpleby, M., Shojaee-Moradie, F., Byrne, C. (2007). Differential effects of fatness, fitness and physical activity energy expenditure on whole-body, liver and fat insulin sensitivity. Diabetologia, 50(8), 1698-1706.

Imboden, M. T., Swartz, A. M., Finch, H. W., Harber, M. P., & Kaminsky, L. A. J. P. O. (2017). Reference standards for lean mass measures using GE dual energy x-ray absorptiometry in Caucasian adults. 12(4), e0176161.

Jung, U. J., & Choi, M.-S. J. I. j. o. m. s. (2014). Obesity and its metabolic complications: the role of adipokines and the relationship between obesity, inflammation, insulin resistance, dyslipidemia and nonalcoholic fatty liver disease. 15(4), 6184-6223.

Kumari, R., Kumar, S., & Kant, R. (2019). An update on metabolic syndrome: Metabolic risk markers and adipokines in the development of metabolic syndrome. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 13(4), 2409-2417.

Mora, R. M. S., Oliver, A. J. S., Carmona, W. S., & Jurado, J. A. G. (2021). Efecto de un programa de ejercicio físico sobre la condición física y la grasa visceral en personas con obesidad (Effect of a physical exercise program on physical fitness and visceral fat in people with obesity). Retos, 39, 723-730.

Nelson, D. L., & Cox, M. M. (2018). Princípios de Bioquímica de Lehninger-7: Artmed Editora.

Oliveira, A. G., Araujo, T. G., Carvalho, B. M., Guadagnini, D., Rocha, G. Z., Bagarolli, R. A., . . . Saad, M. J. J. O. (2013). Acute exercise induces a phenotypic switch in adipose tissue macrophage polarization in diet‐induced obese rats. 21(12), 2545-2556.

Oliveros, E., Somers, V. K., Sochor, O., Goel, K., & Lopez-Jimenez, F. (2014). The concept of normal weight obesity. Progress in cardiovascular diseases, 56(4), 426-433.

Organization, W. H. (1995). Physical status: The use of and interpretation of anthropometry, Report of a WHO Expert Committee: World Health Organization.

Ortega, F. B., Silventoinen, K., Tynelius, P., & Rasmussen, F. (2012). Muscular strength in male adolescents and premature death: cohort study of one million participants. Bmj, 345, e7279.

Resolução, B. (2012). 466/2012. Diretrizes e normas regulamentadoras de pesquisas envolvendo seres humanos.

Rosa, S. E. d., Martinez, E. C., Marson, R. A., Fortes, M. d. S. R., & Fernandes, J. (2018). Military Physical training, muscular strength, and body composition of Brazilian Military Personnel. Revista Brasileira de Medicina do Esporte, 24, 153-156.

Sasai, H., Brychta, R. J., Wood, R. P., Rothney, M. P., Zhao, X., Skarulis, M. C., & Chen, K. Y. (2015). Does visceral fat estimated by dual-energy X-ray absorptiometry independently predict cardiometabolic risks in adults? J Diabetes Sci Technol, 9(4), 917-924.

Schleinitz, D., Böttcher, Y., Blüher, M., & Kovacs, P. J. D. (2014). The genetics of fat distribution. 57(7), 1276-1286.

Simão, A. F., Précoma, D. B., Andrade, J. P. d., Correa Filho, H., Saraiva, J., Oliveira, G., . . . Avezum Junior, A. J. A. b. d. c. (2013). I Diretriz brasileira de prevenção cardiovascular. 101(6), 1-63.

Tam, C. S., Xie, W., Johnson, W. D., Cefalu, W. T., Redman, L. M., & Ravussin, E. J. D. c. (2012). Defining insulin resistance from hyperinsulinemic-euglycemic clamps. 35(7), 1605-1610.

Thomas, J. R., Nelson, J. K., & Silverman, S. J. (2012). Métodos de pesquisa em atividade física: Artmed Editora.

Walton, C., Lees, B., Crook, D., Worthington, M., Godsland, I. F., & Stevenson, J. C. (1995). Body fat distribution, rather than overall adiposity, influences serum lipids and lipoproteins in healthy men independently of age. Am J Med, 99(5), 459-464.

Zanetti, F., Firmino Neto, Neufeld. (2021). Association between visceral fat and biomarkers in military members of the Brazilian Army. SODEBRAS, 16(182):38-43.

Zanetti, F., Neufeld. (2020). Análise comparativa da composição corporal e marcadores séricos em militares não obesos e obesos do Exército Brasileiro. Coleção Pesquisa em Educação Física, 20(1): 31-38.

Descargas

Publicado

2022-02-13

Cómo citar

Zanetti, M. M., Lima e Silva, L. de, Sena, M. A. de B., Neves, E. B., Ferreira, P. F., Keese, F., Nunes, R. A. M., & Fortes, M. de S. R. (2022). Correlación entre parámetros antropométricos y riesgo cadiometabólico en militares (Correlation between anthropometric parameters and cardiometabolic risk in military). Retos, 44, 1099–1103. https://doi.org/10.47197/retos.v44i0.91559

Número

Sección

Artículos de carácter científico: trabajos de investigaciones básicas y/o aplicadas

Artículos más leídos del mismo autor/a