An Index for the Differential Diagnosis of Morbid Obese Children with and without Metabolic Syndrome
Authors: Mustafa M. Donma, Orkide Donma
Abstract:
Metabolic syndrome (MetS) is a severe health problem caused by morbid obesity, the severest form of obesity. The components of MetS are rather stable in adults. However, the diagnosis of MetS in morbid obese (MO) children still constitutes a matter of discussion. The aim of this study was to develop a formula, which facilitated the diagnosis of MetS in MO children and was capable of discriminating MO children with and without MetS findings. The study population comprised MO children. Age and sex-dependent body mass index (BMI) percentiles of the children were above 99. Increased blood pressure, elevated fasting blood glucose (FBG), elevated triglycerides (TRG) and/or decreased high density lipoprotein cholesterol (HDL-C) in addition to central obesity were listed as MetS components for each child. Two groups were constituted. In the first group, there were 42 MO children without MetS components. Second group was composed of 44 MO children with at least two MetS components. Anthropometric measurements including weight, height, waist and hip circumferences were performed during physical examination. BMI and homeostatic model assessment of insulin resistance (HOMA-IR) values were calculated. Informed consent forms were obtained from the parents of the children. Institutional Non-Interventional Clinical Studies Ethics Committee approved the study design. Routine biochemical analyses including FBG, insulin (INS), TRG, HDL-C were performed. The performance and the clinical utility of Diagnostic Obesity Notation Model Assessment Metabolic Syndrome Index (DONMA MetS index) [(INS/FBG)/(HDL-C/TRG)*100] was tested. Appropriate statistical tests were applied to the study data. p value smaller than 0.05 was defined as significant. MetS index values were 41.6 ± 5.1 in MO group and 104.4 ± 12.8 in MetS group. Corresponding values for HDL-C values were 54.5 ± 13.2 mg/dl and 44.2 ± 11.5 mg/dl. There was a statistically significant difference between the groups (p < 0.001). Upon evaluation of the correlations between MetS index and HDL-C values, a much stronger negative correlation was found in MetS group (r = -0.515; p = 0.001) in comparison with the correlation detected in MO group (r = -0.371; p = 0.016). From these findings, it was concluded that the statistical significance degree of the difference between MO and MetS groups was highly acceptable for this recently introduced MetS index. This was due to the involvement of all of the biochemically defined MetS components into the index. This is particularly important because each of these four parameters used in the formula is a cardiac risk factor. Aside from discriminating MO children with and without MetS findings, MetS index introduced in this study is important from the cardiovascular risk point of view in MetS group of children.
Keywords: Fasting blood glucose, high density lipoprotein cholesterol, insulin, metabolic syndrome, morbid obesity, triglycerides.
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[1] S. L. Samson, and A. J. Garber, “Metabolic syndrome,” Endocrinol. Metab. Clin. North. Am., vol. 43, no. 1, pp. 1-23, Mar. 2014.
[2] D. H. Sherling, P. Perumareddi, and C. H. Hennekens, “Metabolic syndrome,” J. Cardiovasc. Pharmacol. Ther., vol. 22, no. 4, pp. 365-367, Jul. 2017.
[3] M. G. Saklayen, “The global epidemic of the metabolic syndrome,” Curr. Hypertens. Rep., vol. 26, no. 20(2), pp. 12, Feb. 2018.
[4] I. Lemieux, and J. P. Després, “Metabolic syndrome: past, present and future,” Nutrients., vol. 14, no. 12(11), pp. 3501, Nov. 2020.
[5] I. Soldatovic, R. Vukovic, D. Culafic, M. Gajic, and V. Dimitrijevic-Sreckovic, “siMS score: “Simple Method for Quantifying Metabolic Syndrome,” PLoS One., vol. 8, no. 11(1) pp. e0146143, Jan. 2016.
[6] C. Li, and E. S. Ford, “Is there a single underlying factor for the metabolic syndrome in adolescents? a confirmatory factor analysis,” Diabetes Care., 2007 vol. 30, no. 6, pp. 1556-1561, Jun. 2007.
[7] V. Martínez-Vizcaíno, M. S. Martínez, F. S. Aguilar, S. S. Martínez, R. F. Gutiérrez, M. S. López, P. M. Martínez, and F. Rodríguez-Artalejo, “Validity of a single-factor model underlying the metabolic syndrome in children: a confirmatory factor analysis,” Diabetes Care., vol. 33, no. 6, pp. 1370-1372, Jun. 2010.
[8] M. Donma, and O. Donma, “Associations between surrogate insulin resistance indices and the risk of metabolic syndrome in children,” “Int. J. Med. Health Sci.,” vol. 14, no. 2, pp. 61-64, 2020.
[9] M. Zhao, C.A. Caserta, C. C. M. Medeiros, A. López-Bermejo, A. Kollias, Q. Zhang, L. Pacifico, T. Reinehr, M. Litwin, J. Bassols, E. L. Romeo, T. D. A. Ramos, G. S. Stergiou, L. Yang, S. Xargay-Torrent, A. Amante, T. M. Estrela, E. Grammatikos, Y. Zhang, A. Prats- Puig, D. Franklin de Carvalho, L. Yang, G. Carreras-Badosa, M. de Oliveira Simões, Y. Hou, E. Lizarraga-Mollinedo, W. Shui, T. Guo, M. Wang, Y. Zhang, P. Bovet, and B. Xi, “International childhood vascular structure evaluation consortium. metabolic syndrome, clustering of cardiovascular risk factors and high carotid intima- media thickness in children and adolescents,” J. Hypertens., 2vol. 38, no. 4, pp. 618-624, Apr. 2020.
[10] R. Weiss, A. A. Bremer, and R. H. Lustig, “What is metabolic syndrome, and why are children getting it?,” Ann. N. Y. Acad. Sci., vol. 1281, no. 1, pp. 123-140, Apr. 2013.
[11] A. Serbis, V. Giapros, A. Galli-Tsinopoulou, and E. Siomou. “Metabolic syndrome in children and adolescents: is there a universally accepted definition? does it matter?,” Metab. Syndr. Relat. Disord., vol. 18, no. 10, pp. 462-470, Dec. 2020.
[12] L. X. Wang, M. J. Gurka, and M. D. Deboer, “Metabolic syndrome severity and lifestyle factors among adolescents,” Minerva Pediatr., vol. 70, no. 5, pp. 467-475, Oct. 2018.
[13] M. Mansour, Y. E. Nassef, M. A. Shady, A. A. Aziz, and H. A. Malt, “metabolic syndrome and cardiovascular risk factors in obese adolescent,” Open Access Maced J. Med. Sci., vol. 15, no. 4(1), pp.118-121, Mar. 2016.
[14] M. Rumińska, A. Majcher, B. Pyrzak, A. Czerwonogrodzka-Senczyna, M. Brzewski, and U. Demkow, “cardiovascular risk factors in obese children and adolescents,” Adv. Exp. Med. Biol., vol. 878, pp.39-47, 2016.
[15] J. Steinberger, S. R. Daniels, R. H. Eckel, L. Hayman, R. H. Lustig, B. McCrindle, and M. L. Mietus-Snyder, “Progress and challenges in metabolic syndrome in children and adolescents: a scientific statement from the American Heart Association Atherosclerosis, Hypertension, and Obesity in the Young Committee of the Council on Cardiovascular Disease in the Young; Council on Cardiovascular Nursing; and Council on Nutrition, Physical Activity, and Metabolism,” Circulation vol. 119, pp. 628–647, 2009.
[16] B. J. Shen, R. B. Goldberg RB, M. M. Llabre, and N. Schneiderman, “Is the factor structure of the metabolic syndrome comparable between men and women and across three ethnic groups: the Miami Community Health Study,” Ann. Epidemiol. vol. 16, pp. 131–137, 2006.
[17] S. Novak, L. M. Stapleton, J. R. Litaker, and K. A. Lawson, “A confirmatory factor analysis evaluation of the coronary heart disease risk factors of metabolic syndrome with emphasis on the insulin resistance facto,”. Diabetes Obes. Metab., vol. 5, pp. 388–396, 2003.
[18] S. Shah, S. Novak, and L. M. Stapleton, “Evaluation and comparison of models of metabolic syndrome using confirmatory factor analysis,” Eur. J. Epidemiol., vol. 21, pp. 343–349, 2006.
[19] WHO World Health Organization (WHO). The WHO Child Growth Standards. 2016 June. Access: http://www.who.int/childgrowth/en/
[20] P. Zimmet, K. G. AlbertiG, F. Kaufman, N. Tajima, M. Silink, S. Arslanian, G. Wong, P. Bennet, J. Shaw, S. Caprio, and IDF consensus group, “The metabolic syndrome in children and adolescents-an IDF consensus report,” Pediatr. Diabetes, vol. 8, no. 5, pp. 299-306, 2007.s
[21] S. H. Khan, A. N. Khan, N. Chaudhry, R. Anwar, N. Fazal, and M. Tariq, “Comparison of various steady state surrogate insulin resistance indices in diagnosing metabolic syndrome,” Diabetol. Metab. Syndr., vol. 14, no. 11, pp. 44, Jun. 2019.
[22] M. K. Bhatnagar, S. Arora, V. Singh, and J. Bhattacharjee, “Assessment of insulin resistance using surrogate markers in patients of metabolic syndrome,” Diabetes Metab. Syndr., vol. 5, no. 1, pp. 29-32, Jan-Mar. 2011.
[23] M. K. Garg, N. Tandon, R. K. Marwaha, and Y. Singh, “Evaluation of surrogate markers for insulin resistance for defining metabolic syndrome in urban Indian adolescents,” Indian Pediatr., vol. 51, no. 4, pp. 279-284, Apr. 2014.
[24] N. Rashid, A. Nigam, S. Kauser, P. Prakash, S. K. Jain, and S. Wajid, “Assessment of insulin resistance and metabolic syndrome in young reproductive aged women with polycystic ovarian syndrome: analogy of surrogate indices,” Arch. Physiol. Biochem., vol. 128, no. 3, pp. 740-747, Jun. 2022.
[25] M. T. Martínez-Larrad, C. Lorenzo, C. González-Villalpando, R. Gabriel, S. M. Haffner, and M. Serrano-Ríos, “Associations between surrogate measures of insulin resistance and waist circumference, cardiovascular risk and the metabolic syndrome across Hispanic and non-Hispanic white populations,” Diabet. Med., vol. 29, no. 11, pp. 1390-1394, Nov. 2012.
[26] B. Singh, and A. Saxena, “Surrogate markers of insulin resistance: a review,” World J. Diabetes., vol. 15, no. 1(2), pp. 36-47, May. 2010.
[27] M. R. Salazar, H. A. Carbajal, W. G. Espeche, M. Aizpurúa, C. A. Dulbecco, and G. M. Reaven, “Comparison of two surrogate estimates of insulin resistance to predict cardiovascular disease in apparently healthy individuals,” Nutr. Metab. Cardiovasc. Dis., vol. 27, no. 4, pp. 366-373, Apr. 2017.
[28] A. K. Nur Zati Iwani, M. Y. Jalaludin, A. Yahya, F. Mansor, F. Md Zain, J. Y. H. Hong, R. M. Wan Mohd Zin, and A. H. Mokhtar, “TG: HDL-C Ratio as Insulin Resistance Marker for Metabolic Syndrome in Children with Obesity,” Front. Endocrinol. (Lausanne)., vol. 10, no. 13, pp. 852290, Mar. 2022.
[29] C. Frithioff-Bøjsøe, C. Trier, C. Esmann Fonvig, A. Nissen, J. T. Kloppenborg, P. M. Mollerup, P. J. Bjerrum, O. Pedersen, T. Hansen, and J. C. Holm, “Estimates of insulin sensitivity and β-cell function in children and adolescents with and without components of the metabolic syndrome,” Pediatr. Endocrinol. Diabetes Metab., vol. 23, no. 3, pp. 122-129, 2017.