Body Fat Mass is Better Indicator than Indirect Measurement Methods in Obese Children for Fatty Liver and Metabolic Syndrome

Masallah Baran, Kivanc Celikkalkan, Yeliz Cagan Appak, Miray Karakoyun, Mehmet Bozkurt, Cemil Kocyigit, Ali Kanik, Bumin Nuri Dundar


Introduction: To compare the bioelectric impedance analysis (BIA) with indirect measurement methods in the evaluation of obese children. To determine the diagnostic value of BIA in the fatty liver and metabolic syndrome (MS) in obese children.  Population and methods: One hundred thirty-four obese children whom ≥10 years of age were prospectively assessment. All patients were evaluated by foot to foot BIA and indirect measurement methods. Blood biochemical parameters such as glucose, lipids and insulin levels were studied and oral glucose tolerance test was performed. Fatty liver was assessed by ultrasonography. Compared BIA records and indirect measurements findings according to fatty liver and MS. Results: The study included females/males: 77/57, mean age of 13.3 ± 2.2 years. Fatty liver was detected in 94 patients, MS was diagnosed in 58 cases. There were no gender difference in terms of fatty liver and MS. Fatty liver was seen more frequently in patients with metabolic syndrome than in those without metabolic syndrome (p < 0.001). Fat Mass (FM) of ≥ 97th percentile was observed in 63% of the 94 patients with fatty liver versus 37.5% of 40 patients without fatty liver. A FM of ≥97th percentile was observed in 72% (n=42) of the 58 patients with metabolic syndrome, 42% (n=33) of 76 patients without MS. Body mass index, upper mid-arm circumference, waist circumference (WC), and hip circumference values were significantly increased in patients with fatty liver. There was a better correlation was determined between FM and FM Index with fatty liver compared to indirect measurement methods. BIA records were found moderately correlated with indirect measurements. Conclusion: Our results revealed that FM and FMI have a better correlated in obese children with fatty liver and metabolic syndrome than indirect measurement methods. The measurement of body FM by BIA can be used together with the indirect measurement methods to detect the fatty liver. FMI may be an alternative diagnostic criterion instead of WC for diagnosis of MS in children.


Body Composition; Obesity; Children; Fatty Liver.


McGill, H.C., McMahan, C.A., Gidding, S.S. (2008). Preventing heart disease in the 21st century: implications of the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study. Circulation, 117(9), 1216-1227. doi: 10.1161/CIRCULATIONAHA.107.717033.

Dehghan, M., Merchant, A.T. (2008). Is bioelectrical impedance accurate for use in large epidemiological studies? Nutr J, 7, 26. doi: 10.1186/1475-2891-7-26.

Deckelbaum, R. J., & Williams, C. L. (2001). Childhood Obesity: The Health Issue. Obesity Research, 9(S11), 239S–243S. doi:10.1038/oby.2001.125.

Fosbøl, M.Ø., Zerahn, B. (2015). Contemporary methods of body composition measurement. Clin Physiol Funct Imaging, 35 (2), 81-97. doi: 10.1111/cpf.12152

Lazzer, S., Bedogni, G., Agosti, F., De Col, A., Mornati, D., Sartorio, A. (2008). Comparison of dual-energy X-ray absorptiometry, air displacement plethysmography and bioelectrical impedance analysis for the assessment of body composition in severely obese Caucasian children and adolescents. Br J Nutr,100(4), 918-924. doi: 10.1017/S0007114508922558.

Alberti, G., Zimmet, P., Shaw, J., Bloomgarden, Z., Kaufman, F., Silink, M.; Consensus Workshop Group. (2004). Type 2 diabetes in the young: the evolving epidemic: the international diabetes federation consensus workshop. Diabetes Care 2004; 27(7): 1798-1811. doi: 10.2337/diacare.27.7.1798.

Mok, E., Béghin, L., Gachon, P., Daubrosse, C., Fontan, J.E., Cuisset, J.M., Gottrand, F., Hankard, R. (2006). Estimating body composition in children with Duchenne muscular dystrophy: comparison of bioelectrical impedance analysis and skinfold-thickness measurement. Am J Clin Nutr, 83(1), 65-69. doi: 10.1093/ajcn/83.1.65.

Bundak, R., Furman, A., Gunoz, H., Darendeliler, F., Bas, F., Neyzi, O. (2006). Body mass index references for Turkish children. Acta Paediatr, 95(2),194-198. doi: 10.1080/08035250500334738

Elmaoğulları, S., Tepe, D., Uçaktürk, S.A., Karaca Kara, F., Demirel, F. (2015). Prevalence of Dyslipidemia and Associated Factors in Obese Children and Adolescents. J Clin Res Pediatr Endocrinol, 7(3), 228-234. doi: 10.4274/jcrpe.1867.

Schutz, Y., Kyle, U.U., Pichard, C. (2002). Fat-free mass index and fat mass index percentiles in Caucasians aged 18-98 y. Int J Obes Relat Metab Disord, 26(7):953–960. doi: 10.1038/sj.ijo.0802037.

Kurtoglu, S., Mazicioglu, M.M., Ozturk, A., Hatipoglu, N., Cicek, B., Ustunbas, H.B. (2010). Body fat reference curves for healthy Turkish children and adolescents. Eur J Pediatr,169,1329-1335. doi: 10.1007/s00431-010-1225-4.

Zimmet, P., Alberti, K.G., Kaufman, F., Tajima, N., Silink, M., Arslanian, S., Wong, G., Bennett, P., Shaw, J., Caprio, S.; IDF Consensus Group. (2007). The metabolic syndrome in children and adolescents - an IDF consensus report. Pediatr Diabetes, 8(5): 299-306. doi: 10.1111/j.1399-5448.2007.00271.x.

American Diabetes Association. Classification and diagnosis of diabetes. (2016). Standards of Medical Care in Diabetes. Diabetes Care, 39(1), 13-22. doi: 10.2337/dc16-er09.

Kurtoğlu, S., Hatipoğlu, N., Mazicioğlu, M., Kendirici, M., Keskin, M., Kondolot, M. (2010). Insulin resistance in obese children and adolescents: HOMA-IR cut-off levels in the prepubertal and pubertal periods. J Clin Res Pediatr Endocrinol, 2(3),100-106. doi: 10.4274/jcrpe.v2i3.100.

Kawasaki, T., Hashimoto, N., Kikuchi, T., Takahashi, H., Uchiyama, M. (1997). The relationship between fatty liver and hyperinsulinemia in obese Japanese children. J Pediatr Gastroenterol Nutr, 24(3), 317-321. doi: 10.1097/00005176-199703000-00015.

Erol, M., Bostan Gayret, O., Tekin Nacaroglu, H., Yigit, O., Zengi, O., Salih Akkurt, M., Tasdemir, M. (2016). Association of Osteoprotegerin with Obesity, Insulin Resistance and Non-Alcoholic Fatty Liver Disease in Children. Iran Red Crescent Med J, 18 (11), e41873. doi: 10.5812/ircmj.41873.

Marzuillo,. P., Grandone, A., Perrone, L., Miraglia Del Giudice, E. (2015). Controversy in the diagnosis of pediatric non-alcoholic fatty liver disease. World J Gastroenterol, 21(21) 6444-6450. doi: 10.3748/wjg.v21.i21.6444.

Joseph, A.E., Saverymuttu, S.H., Al-Sam, S., Cook. M.G., Maxwell, J.D. (1991). Comparison of liver histology with ultrasonography in assessing diffuse parenchymal liver disease. Clin Radiol, 43(1),26-31. doi: 10.1016/s0009-9260(05)80350-2.

Chiloiro, M., Riezzo, G., Chiarappa, S., Correale, M., Guerra, V., Amati, L., Noviello, M.R., Jirillo, E. (2008). Relationship among fatty liver, adipose tissue distribution and metabolic profile in moderately obese children: an ultrasonographic study. Curr Pharm Des, 14 (2), 2693-2698. doi: 10.2174/138161208786264197.

Chan, D.F., Li, A.M., Chu, W.C., Chan, M.H., Wong, E.M., Liu, E.K., Chan, I.H., Yin, J., Lam, C.W., Fok, T.F., Nelson, E.A. (2004).Hepatic steatosis in obese Chinese children. Int J Obes Relat Metab Disord, 28(10), 1257-1263. doi: 10.1038/sj.ijo.0802734.

Pang, Q., Zhang, J.Y., Song, S.D., Qu, K., Xu, X.S., Liu, S.S., Liu, C. (2015). Central obesity and nonalcoholic fatty liver disease risk after adjusting for body mass index. World J Gastroenterol, 21(5), 1650-1662. doi: 10.3748/wjg.v21.i5.1650.

Vitturi, N., Soattin, M., De Stefano, F., Vianello, D., Zambon, A., Plebani, M., Busetto, L. (2015). Ultrasound, anthropometry and bioimpedance: a comparison in predicting fat deposition in non-alcoholic fatty liver disease. Eat Weight Disord, 20(2), 241-247. doi: 10.1007/s40519-014-0146-z.

Goluch-Koniuszy, Z.S., Kuchlewska, M. (2017). Body composition in 13-year-old adolescents with abdominal obesity,depending on the BMI value. Adv Clin Exp Med, 26(6):973-979. doi: 10.17219/acem/61613.

Botton, J., Heude, B., Kettaneh, A., Borys,. J.M., Lommez, A., Bresson, J.L., Ducimetiere, P., Charles, M.A.; FLVS Study Group. (2007). Cardiovascular risk factor levels and their relationships with overweight and fat distribution in children: The Fleurbaix Laventie Ville Sante´ II study. Metabolism, 56(5), 614–622. doi:10.1016/j.metabol.2006.12.006.

Nielsen, T.R.H., Fonvig, C.E., Dahl, M., Mollerup, P.M., Lausten-Thomsen, U., Pedersen, O., Hansen, T., Holm, J.C. (2018). Childhood obesity treatment; Effects on BMI SDS, body composition, and fasting plasma lipid concentrations. PLoS One, 13(2):e0190576. doi: 10.1371/journal.pone.0190576.

Verney, J., Metz, L., Chaplais, E., Cardenoux, C., Pereira, B., Thivel, D. (2016). Bioelectrical impedance is an accurate method to assess body composition in obese but not severely obese adolescents. Nutr Res, 36(7), 663-70. doi: 10.1016/j.nutres.2016.04.003.

Sweeting, H.N. (2008). Gendered dimensions of obesity in childhood and adolescence. Nutr J, 7,1-14. doi: 10.1186/1475-2891-7-1.

Wan, C.S., Ward, L.C., Halim, J., Gow, M.L., Ho, M., Briody, J.N., Leung, K., Cowell. C.T., Garnett, S.P. (2014). Bioelectrical impedance analysis to estimate body composition, and change in adiposity, in overweight and obese adolescents: comparison with dual-energy x-ray absorptiometry. BMC Pediatr, 14,249. doi: 10.1186/1471-2431-14-249.

Wu, C.S., Chen, Y.Y., Chuang, C.L., Chiang, L.M., Dwyer, G.B., Hsu, Y.L., Huang, A.C., Lai, C.L., Hsieh, K.C. (2015). Predicting body composition using foot-to-foot bioelectrical impedance analysis in healthy Asian individuals. Nutr J, 14:52. doi: 10.1186/s12937-015-0041-0.

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DOI: 10.28991/SciMedJ-2019-0104-2


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