Performance of Abdominal Bioelectrical Impedance Analysis and Comparison with Other Known Parameters in Predicting the Metabolic Syndrome

Abstract

Although obesity is a powerful risk factor for metabolic syndrome (MetS) it is not present in all obese individuals. Increased visceral adipose tissue is the hallmark of this syndrome. In this cross sectional survey we aimed to use abdominal bioelectrical impedance analysis to measure the visceral adipose tissue (VAT) and trunk fat percentages (TF%) in the study population, correlate these findings with traditional anthropometric measures and biochemical parameters of metabolic syndrome and estimate a cut-off value of visceral fat for development of MetS. A total of 285 subjects were enrolled. VAT and TF% were measured by the AB-140 device via abdominal bioelectrical impedance analysis. Fat% was measured by a body composition analyzer (TBF-300). VAT was significantly positively correlated with body mass index, waist circumference, TF%, HOMA IR, fat percentage, fasting plasma glucose and triglycerides. Strongest correlations were between VAT and TF%, VAT and device measured waist circumference and between VAT and manual waist circumference (r=0.95, r=0.93, r=0.92 respectively). Correlations of VAT and TF% with metabolic parameters were significant but weak. The mean VAT and TF% in MetS (+) groups were significantly higher than patients in MetS (−) groups in both sexes. The areas under the ROC curves were 0.730 (95% CI: 0.661–0.791) for female VAT and 0.702 (95% CI: 0.654–0.749) for male VAT in predicting MetS which were similar to the areas under ROC curves calculated for device and manually measured waist circumference, HOMA IR and TF% in predicting MetS (p>0.05 for all comparisons). The accuracy of VAT and TF% for predicting MetS was not sufficient. From our results we can deduce that the performance of abdominal BIA in predicting MetS is weak but could be used in the follow-up of patients with obesity and/or MetS. This has to be confirmed in future studies.

Key words

metabolic syndrome - obesity - abdominal bioelectrical impedance analysis - insulin resistance

• References

• 1 Third Report of the National Cholesterol Education Program (NCEP) . Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002; 106: 3143-3421
• 2 Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 1998; 15: 539-553
• 3 Kozan O, Oguz A, Abaci A et al. Prevalence of the metabolic syndrome among Turkish adults. Eur J Clin Nutr 2007; 61: 548-553
• 4 Goodpaster BH, Krishnaswami S, Resnick H et al. Association between regional adipose tissue distribution and both type 2 diabetes and impaired glucose tolerance in elderly men and women. Diabetes Care 2003; 26: 372-379
• 5 Kay SJ, Fiatarone Singh MA. The influence of physical activity on abdominal fat: a systematic review of the literature. Obes Rev 2006; 7: 183-200
• 6 Mundi MS, Karpyak MV, Koutsari C et al. Body fat distribution, adipocyte size, and metabolic characteristics of nondiabetic adults. Endocrine Care 2010; 95: 67-73
• 7 Misra A, Vikram NK. Clinical and pathophysiological consequences of abdominal adiposity and abdominal adipose tissue depots. Nutrition 2003; 19: 457-466
• 8 Pouliot MC, Després JP, Lemieux S et al. Waist circumference and abdominal sagittal diameter: Best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women. Am J Cardiol 1994; 73: 460-468
• 9 Anderson PJ, Critchley JA, Chan JC et al. Factor analysis of the metabolic syndrome: Obesity vs insulin resistance as the central abnormality. Int J Obes 2001; 25: 1782
• 10 Kuk JL, Katzmarzyk PT, Nichaman MZ et al. Visceral fat is an independent predictor of all-cause mortality in men. Obesity 2006; 14: 336-341
• 11 Fox CS, Massaro JM, Hoffmann U et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart Study. Circulation 2007; 116: 39-48
• 12 Goodpaster BH, Krishnaswami S, Harris TB et al. Obesity, regional body fat distribution, and the metabolic syndrome in older men and women. Arch Intern Med 2005; 165: 777-783
• 13 Boyko EJ, Fujimoto WY, Leonetti DL et al. Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans. Diabetes Care 2000; 23: 465-471
• 14 Wagenknecht LE, Langefeld CD, Scherzinger AL et al. Insulin sensitivity, insulin secretion, and abdominal fat: the Insulin Resistance Atherosclerosis Study (IRAS) Family Study. Diabetes 2003; 52: 2490-2496
• 15 Hamdy O, Porramatikul S, Al-Ozairi E. Metabolic obesity: The paradox between visceral and subcutaneous fat. Curr Diabetes Rev 2006; 2: 367-373
• 16 Chumlea WM, Guo SS. Assessment and prevalence of obesity: application of new methods to a major problem. Endocrine 2000; 13: 135-142
• 17 Lee SY, Gallagher D. Assessment methods in human body composition. Curr Opin Clin Nutr Metab Care 2008; 11: 566-572
• 18 Clasey JL, Bouchard C, Teates CD et al. The use of anthropometric and dual-energy X-ray absorptiometry (DXA) measures to estimate total abdominal and abdominal visceral fat in men and women. Obes Res 1999; 7: 256-264
• 19 Thomas EL, Saeed N, Hajnal JV et al. Magnetic resonance imaging of total body fat. J Appl Physiol 1998; 85: 1778-1785
• 20 Scharfetter H, Schlager T, Stollberger R et al. Assessing abdominal fatness with local bioimpedance analysis: basics and experimental findings. Int J Obes Relat Metab Disord 2001; 25: 502-511
• 21 Demura S, Sato S. Prediction of visceral fat area at the umbilicus level using fat mass of the trunk: the validity of bioelectrical impedance analysis. J Sports Sci 2007; 25: 823-833
• 22 Nagal M, Komiya H, Mori Y et al. Development of a new method for estimating visceral fat area with multi frequency bioelectrical impedance. Tohoku J Exp Med 2008; 214: 105-112
• 23 Thomas EL, Collins AL, McCarthy J et al. Estimation of abdominal fat compartments by bioelectrical impedance: the validity of the ViScan measurement system in comparison with MRI. Eur J Clin Nutr 2010; 64: 525-533
• 24 Zamrazilová H, Hlavatý P, Dusátková L et al. A new simple method for estimating trunk and visceral fat by bioelectrical impedance: comparison with magnetic resonance imaging and dual X-ray absorptiometry in Czech adolescents. Cas Lek Cesk 2010; 149: 417-422
• 25 Ozhan H, Alemdar R, Caglar O et al. Performance of Bioelectrical impedance analysis in the diagnosis of metabolic syndrome. J Investig Med 2012; 60: 587-591
• 26 Browning LM, Mugridge O, Chatfield MD et al. Validity of a new abdominal bioelectrical impedance device to measure abdominal and visceral fat: comparison with MRI. Obesity (Silver Spring) 2010; 18: 2385-2391
• 27 Browning LM, Mugridge O, Dixon AK et al. Measuring abdominal adipose tissue: comparison of simpler methods with MRI. Obes Facts 2011; 4: 9-15
• 28 Kuk JL, Lee SJ, Steven BH et al. Waist circumference and abdominal tissue distribution: influence of age and sex. Am J Clin Nutr 2005; 81: 1330-1334
• 29 Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004; 79: 379-384
• 30 Han TS, van Leer EM, Seidell JC et al. Waist circumference action levels in the identification of cardiovascular risk factors: prevalence study in a random sample. BMJ 1995; 311: 1401-1405
• 31 Janssen I, Katzmarzyk PT, Ross R. Body mass index, waist circumference, and health risk: evidence in support of current National Institutes of Health guidelines. Arch Intern Med 2002; 162: 2074-2079
• 32 Executive summary of the clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults. Arch Intern Med 1998; 158: 1855-1867