Evaluation of anthropometric indices as predictors of metabolic syndrome: 3-year cohort in Ecuadorian military personnel
Keywords:
metabolic syndrome, military personnel, anthropometric indices.Abstract
Introduction: The metabolic syndrome is a condition that predisposes to the development of cardiovascular and metabolic diseases, where the presence of altered blood pressure, insulin resistance, hyperglycemia, dyslipidemia and abdominal obesity is evaluated in order to know the risk of developing this disease.Objective: To evaluate the anthropometric indices that predict the presence of developing metabolic syndrome in Ecuadorian military personnel.
Methods: The research work is quantitative, observational and longitudinal with a correlational scope, it was made analyzing the annual medical records of preventive medicine, in the military personnel of the Army Soldiers Training School "Vencedores del Cenepa", during a 3-year cohort from 2019 to 2021.
Results: The study shows an overweight military population, with a prevalence of metabolic syndrome: according to Asociación Latinoamericana de Diabetes criteria of 1 %, 1.66 % and 0.76 %, in the years 2019, 2020 and 2021 respectively; in contrast, according to Adult Treatment Panel III criteria, with a prevalence of 6.67 %, 6.31 % and 5.70 % in the years 2019, 2020 and 2021 respectively.
Conclusions: The anthropometric indices, such as the waist-height index, abdominal perimeter and body mass index significantly predict the development of metabolic syndrome in the military personnel of the "Vencedores del Cenepa" Army Soldier Training School.
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References
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10. Muñoz A, Muñoz G. Cuantificación del riesgo de enfermedad cardiovascular, según el score Framingham, en el personal militar durante el año 2015. Rev Ecuat Med Cienc Biol. 2018; 39(1): 31-7. DOI: 10.26807/remcb.v39i1.560
11. Oguoma V, Coffe N, Alsharrah S, Abu M, Al-Refaei F, Alkandari A. Anthropometric cut-points for discriminating diabetes and metabolic syndrome among Arabs and Asians: The Kuwait Diabetes Epidemiology Program. Br J Nutr. 2021; 127(1): 92-102. DOI: 10.1017/S0007114521000751
12. Joshi H, Shak K, Patel P, Prajapati J, Parmar M, Doshi D. Novel indexes for diagnosing metabolic syndrome in apparently healthy Gujarati Asian Indians: A cross-sectional study. Qjm. 2016; 109(11):717-22. DOI: 10.1093/qjmed/hcw056
13. Hosein R, Hamid R, Hamid R, Tavakoli M, Hossein R. Mohammad M. Metabolic syndrome prevalence among armed forces personnel: a systematic review and meta-analysis. Mil Med. 2019; 184(9-10): 417-25. DOI: 10.1093/milmed/usz144
14. Guan X, Sun G, Zheng L, Hu W, Li W, Sun Y. Associations between metabolic risk factors and body mass index, waist circumferences, waist-to-height ratio and waist-to-hip ratio in a Chinese rural populations. J Diabetes Investig. 2016; 7(4):601-6. DOI: 10.1111/jdi.12442
15. Peer N, Steyn K, Levitt N. Differential obesity indices identify the metabolic syndrome in black men and women in Cape Town: the CRIBSA study. J Public Heal (United Kingdom). 2016; 38(1):175-82. [acceso:16/04/2022]. DOI: 10.1093/pubmed/fdu115
2. Hussain M, Oldenburg B, Wang Y, Zoungas S, Tonkin A. Assessment of Cardiovascular Disease Risk in South Asian Populations. Int J Vasc Med. 2013. [acceso: 16/04/2022]. 2013: 786801. DOI: 10.1155/2013/786801
3. Communication S. American Medical Association. Executive Summary of the Third Report (NCEP) Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). J Am Med Assoc. 2001; 285(19):2486-97. DOI: 10.1001/jama.285.19.2486
4. Baygi F, Herttua K, Jensen O, Djalalinia S, Ghorabi A, Asayesh H, et al. Global prevalence of cardiometabolic risk factors in the military population: a systematic review and meta-analysis. BMC Endocrine Disord. 2020;20(8):1-17. DOI: 10.1186/s12902-020-0489-6
5. Cheng L, Chang L, Lee E. Hyperuricemia is Associated with a higher prevalence of metabolic syndrome in military individuals. Mil Med. 2018 [acceso: 16/04/2022];183(11-12): e391-e395. Disponible en: https://academic.oup.com/milmed/article/183/11-12/e391/4994620
6. Payab M, Hassani R, Merati Y, Esteghamati A, Qorbani M, Hematabadi M. The prevalence of metabolic syndrome and different obesity phenotype in Iranian male military personnel. Am J Mens Health. 2017; 11(2): 404-13. DOI: 10.1177/1557988316683120
7. Filho R, D'Oliveira A. The prevalence of metabolic syndrome among soldiers of the military personnel. Am J Mens Health. 2014; 8(4): 310-5. DOI: 10.1177/1557988313510928
8. Perez J, Baldeon L, Franco O, Muka T, Drexhage H, Voortman T. Prevalence of overweight and metabolic syndrome, and associated sociodemographic factors among adult Ecuadorian populations: the ENSANUT-ECU study. J Endocrinol Invest. 2021; 44(1): 63-74. DOI: 10.1007/s40618-020-01267-9
9. Muñoz G, Muñoz A. Evaluation of anthropometric indices as metabolic syndrome predictors in Ecuadorian military personnel. Rev Ecuat Med Cienc Biol. 2020; 41(2): 141-7. DOI: 10.26807/REMCB.V41I2.872
10. Muñoz A, Muñoz G. Cuantificación del riesgo de enfermedad cardiovascular, según el score Framingham, en el personal militar durante el año 2015. Rev Ecuat Med Cienc Biol. 2018; 39(1): 31-7. DOI: 10.26807/remcb.v39i1.560
11. Oguoma V, Coffe N, Alsharrah S, Abu M, Al-Refaei F, Alkandari A. Anthropometric cut-points for discriminating diabetes and metabolic syndrome among Arabs and Asians: The Kuwait Diabetes Epidemiology Program. Br J Nutr. 2021; 127(1): 92-102. DOI: 10.1017/S0007114521000751
12. Joshi H, Shak K, Patel P, Prajapati J, Parmar M, Doshi D. Novel indexes for diagnosing metabolic syndrome in apparently healthy Gujarati Asian Indians: A cross-sectional study. Qjm. 2016; 109(11):717-22. DOI: 10.1093/qjmed/hcw056
13. Hosein R, Hamid R, Hamid R, Tavakoli M, Hossein R. Mohammad M. Metabolic syndrome prevalence among armed forces personnel: a systematic review and meta-analysis. Mil Med. 2019; 184(9-10): 417-25. DOI: 10.1093/milmed/usz144
14. Guan X, Sun G, Zheng L, Hu W, Li W, Sun Y. Associations between metabolic risk factors and body mass index, waist circumferences, waist-to-height ratio and waist-to-hip ratio in a Chinese rural populations. J Diabetes Investig. 2016; 7(4):601-6. DOI: 10.1111/jdi.12442
15. Peer N, Steyn K, Levitt N. Differential obesity indices identify the metabolic syndrome in black men and women in Cape Town: the CRIBSA study. J Public Heal (United Kingdom). 2016; 38(1):175-82. [acceso:16/04/2022]. DOI: 10.1093/pubmed/fdu115
Published
2022-05-20
How to Cite
1.
Muñoz Gualán GG, Muñoz Gualán AP. Evaluation of anthropometric indices as predictors of metabolic syndrome: 3-year cohort in Ecuadorian military personnel. Rev Cubana Med Milit [Internet]. 2022 May 20 [cited 2025 Apr. 19];51(2):e02201953. Available from: https://revmedmilitar.sld.cu/index.php/mil/article/view/1953
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