Observational study of body weight, body fat with segmental fat distribution, visceral fat and body mass index in type 2 diabetic patients

Sunil Dube, Shanti Viswanathan, Manjree Dube


Background: There has been an increase in the prevalence of non-communicable diseases in the last decade. This prevalence has been steadily increasing and is expected to increase further in the coming decade. The change in our lifestyle plus a sedentary lifestyle has led to this .Various body composition monitoring methods help us evaluate obesity and its association with diabetes. In this study, we analysed the trend of body fat distribution in diabetics.

Methods: A multifrequency body composition monitor TANITA MC 980 was used to analyse visceral fat, body fat and segmental fat distribution. This was correlated with BMI.

Results: BMI showed a significant correlation between body fat (R2=0.558) and visceral fat (R2=0.166) where R>0.5 is significant. BMI showed a negative correlation with upper and lower body adiposity. Linear regression analysis also showed a positive relation between BMI and visceral fat and BMI and body fat. The overall accuracy of body fat and visceral fat to assess obesity was 0.829 and 0.731 respectively.

Conclusions: This study showed a positive correlation between BMI and visceral fat as well as body fat as measured by bioelectric impedance method. Visceral fat being a definite risk factor for development of Type 2 diabetes and its association with other comorbidities, there is a need not only to measure body fat but also visceral fat in type 2 diabetes.


Body mass index, Bioimpedance analysis, Body fat, Visceral fat

Full Text:



Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care. 2004;27(5):1047-53.

James PT. Obesity: The worldwide epidemic. Clin Dermatol. 2004;22:276-80.

Chumlea WC. Body Composition Assessment of Obesity Departments of Community Health and Pediatrics, Lifespan Health Research Center, Wright State University School of Medicine, Dayton, OH 45420, USA. 26:23-35.

Wells JCK, Fewtrell MS. Measuring body composition. Arch Dis Child. 2006;91(7):612-7.

Duren DL, Sherwood RJ, Czerwinski SA, Lee M, Choh AC, Siervogel RM, et al. Body Composition Methods: Comparisons and Interpretation. J Diabetes Sci Technol. 2008;2(6):1139-46.

Pelegrini A, Silva DSA, Silva GMLF, Grigollo L, Petroski EL. Anthropometric indicators of obesity in the prediction of high body fat in adolescents. Rev Paul Pediatr. 2015;33(1):56-62.

Roubenoff R. Applications of bioelectrical impedance analysis for body composition to epidemiologic studies. A J Clin Nutri. 1996;64(3):459S-62S.

Lukaski HC, Bolonechuk WW, Hall CB, Siders WA. Validation of the bioelectrical impedance method to assess human body composition. J Appl Physiol. 1987; 60:1327-32.

Rutherford WJ, Gary DA, Eric SD. Comparison of Bioelectrical Impedance and Skinfolds with Hydro-densitometry in the Assessment of Body Composition in Healthy Young Adults. ICHPER-SD J Res. 2011;6(2):56-60.

Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adult population. Clin Nutr. 2011;30(5):610-5.

Demura S, Sato S, Kitabayashi T. Percentage of total body fat as estimated by three automatic bioelectrical impedance analyzers. J Physiol Anthropol Appl Human Sci. 2004;23(3):93-9.

Bioelectrical Impedance Analysis in Body Composition Measurement National Institutes of Health Technology Assessment Conference Statement. 1994.

WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157-63.

Dudeja V, Misra A, Pandey RM, Devina G, Kumar G, Vikram NK. BMI does not accurately predict overweight in Asian Indians in northern India. Br J Nutr. 2001;86(1):105-12.

Blaak E. Gender differences in fat metabolism. Clin Nutr Metab Care. 2001;4(6):499-502.

Saelens BE, Seeley RJ, van Schaick K, Donnelly LF, O'Brien KJ. Visceral abdominal fat is correlated with whole-body fat and physical activity among 8-y-old children at risk of obesity. Am J Clin Nutr. 2007;85(1):46-53.

Sandeep S, Gokulakrishnan K, Velmurugan K, Deepa M, Mohan V. Visceral & subcutaneous abdominal fat in relation to insulin resistance & metabolic syndrome in non-diabetic south Indians. Indian J Med Res. 2010;131:629-35.

Klein S. Is Visceral Fat Responsible for the Metabolic Abnormalities Associated With Obesity? Diabetes Care. 2010;33(7):1693-4.

Jensen MD. Role of Body Fat Distribution and the Metabolic Complications of Obesity. J Clin Endocrinol Metab. 2008;93(11 Suppl 1):S57-63.

Haffner SM, Stern MP, Hazuda HP, Pugh J, Patterson JK. Do upper-body and centralized adiposity measure different aspects of regional body-fat distribution? Relationship to non-insulin-dependent diabetes mellitus, lipids, and lipoproteins. Diabetes. 1987;36(1):43-51.

Wattanapenpaiboon N, Lukito W, Strauss BJ, Hsu-Hage BH, Wahlqvist ML, Stroud DB. Agreement of skinfold measurement and bioelectrical impedance analysis (BIA) methods with dual energy X-ray absorptiometry (DEXA) in estimating total body fat in Anglo-Celtic Australians. Int J Obes. 1998;22:854-60.

Dehghan M, Merchant AT. Is bioelectrical impedance accurate for use in large epidemiological studies? Nutr J. 2008;7:26.