##plugins.themes.bootstrap3.article.main##

Background: Visceral to subcutaneous adiposity ratio (VSR) may be more crucial than visceral and subcutaneous adipose tissue per se. It reflects relative distribution of abdominal adiposity which is a better indicator of cardio-meta­bolic risk.

Aim: to examine if the VSR has diagnostic value in identifying metabolic syndrome (MS) compared with VAT and SAT among sample of obese Egyptians.

Subjects and Methods: The over here study included 456 obese Egyptian adults (106 male and 350 female), ageing across 25- 55 years. All participants subjected to blood pressure and anthropometric assessment, abdominal ultrasound, and laboratory tests.

Results: Males had quite high level of triglycerides and low HDL than females, who had significantly higher frequency of wide WC than men. There was insignificant sex difference in the frequency of MS. VAT and SAT were significantly higher in presence of wide WC and hypertension among both sexes. Also, VSR was significantly higher in presence of wide WC and hypertension among women only. While presence of MS led to significantly higher value of SAT among men, and VAT among women. Area under the curves (AUCs) for VAT, SAT and VSR; to predict MS; were 0.59, 0.63 and 0.46 among men and 0.63, 0.56 and 0.55 among women.

Conclusion: Visceral and subcutaneous adipose tissue; not visceral/subcutaneous ratio; were significantly affected by the presence of MS in both sexes. SAT was significantly superior among men, while VAT was superior among women. VSR cannot be used as a predictor of MS.

References

  1. Yan Y, Liu J, Zhao X, Cheng H, Huang G, Mi J. Abdominal visceral and subcutaneous adipose tissues in association with cardio- metabolic risk in children and adolescents: the China Child and Adolescent Cardiovascular Health (CCACH) study. BMJ Open Diabetes Research and Care.2017; (1): e000824.
     Google Scholar
  2. Sakuno T. Tomita ML,Tomita CM, Back Giuliano I. de Carlos, Ibagy A, Perin N.Medeiros, et al.Sonographic evaluation of visceral and subcutaneous fat in obese children.Radiol.2014; 47(3).
     Google Scholar
  3. Jung C, Rhee EJ, Kwon H, Chang Y, Ryu S, Lee WY.Visceral-to-Subcutaneous Abdominal Fat Ratio Is Associated with Nonalcoholic Fatty Liver Disease and Liver Fibrosis. Endocrinol Metab.2020; 35:165-176.
     Google Scholar
  4. Kwon S, Han A. The Correlation between the Ratio of Visceral Fat Area to Subcutaneous Fat Area on Computed Tomography and Lipid Accumulation Product as Indexes of Cardiovascular Risk. Journal of Obesity & Metabolic Syndrome. 2019;28:186-193.
     Google Scholar
  5. Meuller W, Maughan RJ. The need for a novel approach to measure bodycomposition: Is ultrasound an answer? Br J Sports Med.2013;47: 1001–1002.
     Google Scholar
  6. Meuller W, Lohman TG, Stewart AD, Maughan RJ, Meyer NL, Sardinha LB, et al . Subcutaneous fat patterning in athletes: Selection of appropriate sites and standardization of a novel ultrasound measurement technique: Ad Hoc Working Group on Body Composition,Health and Performance, under the auspices of the IOC Medical Commission. Br J Sports Med. 2016; 50:45–54.
     Google Scholar
  7. Eifler RV. The role of ultrasound in the measurement of subcutaneous and visceral fat and its correlation with hepatic steatosis. Radio Bras.2013; 46(5):273-278.
     Google Scholar
  8. Hiernaux J, Tanner JM.Growth and physical studies. In J.S. Weiner, S.A. Lourie (Eds.), Human Biology: A guide to field methods. London: IBP; Oxford, UK: Blackwell Scientific Publications, 1969.
     Google Scholar
  9. WHO. Global database on Body Mass Index: BMI Classification. Geneva: World Health Organization, 2006.
     Google Scholar
  10. Ribeiro-Filho F, Faria AN, Azjen S, Zanella MT, Ferreira SR. Methods of estimation of visceral fat: advantages of ultrasonography.Obes Res.2003;11(12):1488-1494.
     Google Scholar
  11. Allain CC, Poon LS, Chen CSG, Richmond W, Fu PC. Enzymatic determination of total serum cholesterol. Clin Chem.1974;20:470-475.
     Google Scholar
  12. Fossati P, Principe L.Serum triglycerides determination colorimetrically with an enzyme that produces hydrogen peroxide.Clin Chem.1982;28:2077-2088.
     Google Scholar
  13. Burstein M, Scholnick HR, Morfin R. Rapid method for the isolation of lipoproteins from human serum by precipitation with polyanions. J Lipid Res.1970; 11:583-595.
     Google Scholar
  14. Friedewald WI, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma without use of preparative ultracentrifuge.Clin Chem.1972;18:499–502.
     Google Scholar
  15. International Diabetes Federation. The IDF consensus worldwide definition of the metabolic syndrome. Brussels, Belgium, 2017.
     Google Scholar
  16. Chiriţă-emandi A, Camelia papa M, Abrudan L, Amelia dobrescu M,Puiu M, Velea IP, et al. A novel method for measuring subcutaneous adipose tissue using ultrasound in children – interobserver consistency. Rom J MorpholEmbryol.2017; 58(1):115–123.
     Google Scholar
  17. Jung JH,Kyung JM, Eun KK, Kwon A,WookChae H,Yoon C, et al. Ultrasound measurement of pediatric visceral fat thickness: correlations with metabolic and liver profiles. Ann Pediatr. Endocrinol Metab. 2016; 21(2): 75–80.
     Google Scholar
  18. De Lucia RE, Norris SA, Sleigh A, Brage S, Dunger D, Stolk RP, Ong K.Validation of Ultrasound Estimates of Visceral Fat in Black South African Adolescents.Obesity. 2011;19 (9):1892–1897.
     Google Scholar
  19. Al-Sarraj T, Saadi H, Volek JS, Fernandez ML. Metabolic syndrome prevalence,dietary intake, and cardiovascular risk profile among overweight and obese adults 18-50 years old from the United Arab Emirates. Metab Syndr RelatDisord. 2010;8:39–46.
     Google Scholar
  20. Al Dhaheri AS, Mohamad MN, Jarrar AH,Ohuma OE, Leila IC,Al Meqbaali TF, et al. A cross-sectional study of the prevalence of metabolic syndrome among young female Emirati adults. PLoS One. 2016; 11: e0159378.
     Google Scholar
  21. Baek J, Jung SJ, Shim J, Jeon YW, Seo E, Kim HC.Comparison of Computed Tomography-based Abdominal Adiposity Indexes as Predictors of Non-alcoholic Fatty Liver Disease among Middle-aged Korean Men and Women. J Prev Med Public Health.2020; 53(4): 256–265.
     Google Scholar
  22. Oh YH,Moon JH, Ju KH, Kong MH.Visceral-to-subcutaneous fat ratio as a predictor of the multiple metabolic risk factors for subjects with normal waist circumference in Korea. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 2017; 10: 505-511.
     Google Scholar
  23. Kanhai DA, Kappelle LJ, van der Graaf Y, Uiterwaal CS, Visseren FL, SMART Study Group. The risk of general and abdominal adiposity in the occurrence of new vascular events and mortal¬ity in patients with various manifestations of vascular disease. Int J Obes (Lond). 2012; 36:695-702.
     Google Scholar
  24. Jørgensen ME, Borch-Johnsen K, Stolk R, Bjerregaard P. Fat distribution and glucose intolerance among Greenland Inuit,” DiabetesCare.2013;36:2988-2994.
     Google Scholar
  25. Philipsen A, Jørgensen ME, Vistisen D, Sandbaek A, Almdal TP, Christiansen JS, et al. Associations between ultrasound measures of abdominal fat distribution and indices of glucose metabolism in a population at high risk of type 2 diabetes: the ADDITION-PRO study. PLoS One.2015;10:e0123062.
     Google Scholar
  26. He H, Ni Y, Chen J, Zhigang Z,Jian Z, Daoyan L,et al. Sex difference in cardiometabolic risk profile and adiponectin expression in subjects with visceral fat obesity. Transl Res. 2011; 155:71–77.
     Google Scholar
  27. Kim S, Cho B, Lee H, KyojooC, Hwang S, Donghee K,et al. Distribution of abdominal visceral and subcutaneous adipose tissue and metabolic syndrome in a Korean population. Diabetes Care.2011;34:504–506.
     Google Scholar
  28. Hudda MT, Fewtrell MS,Haroun D,Lum S,William JE,Wells JCK, et al. Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data.BMJ. 2019; 366: l4293.
     Google Scholar