[1. Angulo P, Hui JM, Marchesini G, Bugianesi E, George J, Farrell GC, et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology. 2007; 45:846-54.10.1002/hep.21496]Open DOISearch in Google Scholar
[2. Church TS, Kuk JL, Ross R, Priest EL, Biltoft E, Blair SN. Association of cardiorespiratory fitness, body mass index, and waist circumference to nonalcoholic fatty liver disease. Gastroenterology. 2006; 130: 2023-30.10.1053/j.gastro.2006.03.019]Open DOISearch in Google Scholar
[3. Park SH, Kim BI, Kim SH, Kim HJ, Park DI, Cho YK, et al. Body fat distribution and insulin resistance: beyond obesity in nonalcoholic fatty liver disease among overweight men. J Am Coll Nutr. 2007; 26:321-6.10.1080/07315724.2007.10719618]Open DOISearch in Google Scholar
[4. Duvnjak M, Lerotic I, Barsic N, Tomasic V, Virovic Jukic L, Velagic V. Pathogenesis and management issues for non-alcoholic fatty liver disease. World J Gastroenterol. 2007; 13:4539-50.10.3748/wjg.v13.i34.4539]Open DOISearch in Google Scholar
[5. Bouloumie A, Curat CA, Sengenes C, Lolmede K, Miranville A, Busse R. Role of macrophage tissue infiltration in metabolic diseases. Curr Opin Clin Nutr Metab Care. 2005; 8:347-54.10.1097/01.mco.0000172571.41149.52]Open DOISearch in Google Scholar
[6. Wan YP, Xu RY, Fang H, Lu LP, Zhang XM, Cai W. [The prevalence of non-alcoholic fatty liver disease and its related risk factors in 1180 school children in Shanghai]. Zhonghua Gan Zang Bing Za Zhi. 2007; 15: 644-8.]Search in Google Scholar
[7. Kim HJ, Kim HJ, Lee KE, Kim DJ, Kim SK, Ahn CW, et al. Metabolic significance of nonalcoholic fatty liver disease in nonobese, nondiabetic adults. Arch Intern Med. 2004; 164:2169-75.10.1001/archinte.164.19.2169]Open DOISearch in Google Scholar
[8. Hsieh SD, Yoshinaga H, Muto T. Waist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women. Int J Obes Relat Metab Disord. 2003; 27:610-6.10.1038/sj.ijo.0802259]Open DOISearch in Google Scholar
[9. Chumlea WM, Guo SS. Assessment and prevalence of obesity: application of new methods to a major problem. Endocrine. 2000; 13:135-42.10.1385/ENDO:13:2:135]Open DOISearch in Google Scholar
[10. Chumlea WC, Guo SS, Kuczmarski RJ, Flegal KM, Johnson CL, Heymsfield SB, et al. Body composition estimates from NHANES III bioelectrical impedance data. Int J Obes Relat Metab Disord. 2002; 26:159 6-609.10.1038/sj.ijo.080216712461676]Open DOISearch in Google Scholar
[11. Plan and operation of the Third National Health and Nutrition Examination Survey, 1988-94. Series 1: programs and collection procedures. Vital Health Stat 1. 1994;32:1-407.]Search in Google Scholar
[12. Chumlea WC, Guo SS, Zeller CM, Reo NV, Baumgartner RN, Garry PJ, et al. Total body water reference values and prediction equations for adults. Kidney Int. 2001; 59:2250-8.10.1046/j.1523-1755.2001.00741.x11380828]Open DOISearch in Google Scholar
[13. Sun SS, Chumlea WC, Heymsfield SB, Lukaski HC, Schoeller D, Friedl K, et al. Development of bioelectrical impedance analysis prediction equations for body composition with the use of a multicomponent model for use in epidemiologic surveys. Am J Clin Nutr. 2003; 77:331-40.10.1093/ajcn/77.2.331]Search in Google Scholar
[14. Sui X, LaMonte MJ, Laditka JN, Hardin JW, Chase N, Hooker SP, et al. Cardiorespiratory fitness and adiposity as mortality predictors in older adults. JAMA. 2007; 298:2507-16.10.1001/jama.298.21.2507]Search in Google Scholar
[15. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985; 28:412-9.10.1007/BF00280883]Open DOISearch in Google Scholar
[16. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004; 27:1487-95.10.2337/diacare.27.6.1487]Open DOISearch in Google Scholar
[17. Ruhl CE, Everhart JE. Leptin concentrations in the United States: relations with demographic and anthropometric measures. Am J Clin Nutr. 2001; 74: 295-301.10.1093/ajcn/74.3.295]Search in Google Scholar
[18. Muntner P, He J, Chen J, Fonseca V, Whelton PK. Prevalence of non-traditional cardiovascular disease risk factors among persons with impaired fasting glucose, impaired glucose tolerance, diabetes, and the metabolic syndrome: analysis of the Third National Health and Nutrition Examination Survey (NHANES III). Ann Epidemiol. 2004; 14:686-95.10.1016/j.annepidem.2004.01.002]Search in Google Scholar
[19. Prati D, Taioli E, Zanella A, Della Torre E, Butelli S, Del Vecchio E, et al. Updated definitions of healthy ranges for serum alanine aminotransferase levels. Ann Intern Med. 2002; 137:1-10.10.7326/0003-4819-137-1-200207020-00006]Open DOISearch in Google Scholar
[20. Rohrmann S, Crespo CJ, Weber JR, Smit E, Giovannucci E, Platz EA. Association of cigarette smoking, alcohol consumption and physical activity with lower urinary tract symptoms in older American men: findings from the third National Health And Nutrition Examination Survey. BJU International. 2005; 96:77-82.10.1111/j.1464-410X.2005.05571.x]Open DOISearch in Google Scholar
[21. Chitturi S, Farrell GC, Hashimoto E, Saibara T, Lau GK, Sollano JD. Non-alcoholic fatty liver disease in the Asia-Pacific region: definitions and overview of proposed guidelines. J Gastroenterol Hepatol. 2007; 22:778-87.10.1111/j.1440-1746.2007.05001.x]Open DOISearch in Google Scholar
[22. Alberti KG, Zimmet P, Shaw J. The metabolic syndrome-a new worldwide definition. Lancet. 2005; 366(9491):1059-62.10.1016/S0140-6736(05)67402-8]Search in Google Scholar
[23. Romero-Corral A, Somers VK, Sierra-Johnson J, Thomas RJ, Collazo-Clavell ML, Korinek J, et al. Accuracy of body mass index in diagnosing obesity in the adult general population. Int J Obes (Lond). 2008; 32:959-66.10.1038/ijo.2008.11287750618283284]Open DOISearch in Google Scholar
[24. Demerath EW, Schubert CM, Maynard LM, Sun SS, Chumlea WC, Pickoff A, et al. Do changes in body mass index percentile reflect changes in body composition in children? Data from the Fels Longitudinal Study. Pediatrics. 2006; 117:e487-95.10.1542/peds.2005-057216510627]Search in Google Scholar
[25. Dervaux N, Wubuli M, Megnien JL, Chironi G, Simon A. Comparative associations of adiposity measures with cardiometabolic risk burden in asymptomatic subjects. Atherosclerosis. 2008; 201:413-7.10.1016/j.atherosclerosis.2007.11.03218191136]Search in Google Scholar
[26. Han TS, Lean ME, Seidell JC. Waist circumference remains useful predictor of coronary heart disease. BMJ. 1996; 312:1227-8.10.1136/bmj.312.7040.1227e23509728634585]Search in Google Scholar
[27. Kvist H, Sjostrom L, Tylen U. Adipose tissue volume determinations in women by computed tomography: technical considerations. Int J Obes. 1986; 10:53-67.]Search in Google Scholar
[28. Smith SR, Lovejoy JC, Greenway F, Ryan D, deJonge L, de la Bretonne J, et al. Contributions of total body fat, abdominal subcutaneous adipose tissue compartments, and visceral adipose tissue to the metabolic complications of obesity. Metabolism. 2001; 50:425-35.10.1053/meta.2001.2169311288037]Open DOISearch in Google Scholar
[29. Han TS, Carter R, Currall JE, Lean ME. The influence of fat free mass on prediction of densitometric body composition by bioelectrical impedance analysis and by anthropometry. Eur J Clin Nutr. 1996; 50:542-8.]Search in Google Scholar
[30. Ryo M, Maeda K, Onda T, Katashima M, Okumiya A, Nishida M, et al. A new simple method for the measurement of visceral fat accumulation by bioelectrical impedance. Diabetes Care. 2005; 28: 451-3.10.2337/diacare.28.2.45115677816]Open DOISearch in Google Scholar
[31. Nagai M, Komiya H, Mori Y, Ohta T, Kasahara Y, Ikeda Y. Development of a new method for estimating visceral fat area with multi-frequency bioelectrical impedance. Tohoku J Exp Med. 2008; 214:105-12.10.1620/tjem.214.10518285667]Search in Google Scholar
[32. Kim JA, Park HS. Association of abdominal fat distribution and cardiometabolic risk factors among obese Korean adolescents. Diabetes Metab. 2008; 34:126-30.10.1016/j.diabet.2007.10.01218289908]Open DOISearch in Google Scholar
[33. Rexrode KM, Carey VJ, Hennekens CH, Walters EE, Colditz GA, Stampfer MJ, et al. Abdominal adiposity and coronary heart disease in women. JAMA. 1998; 280:1843-8.10.1001/jama.280.21.18439846779]Search in Google Scholar
[34. Kuk JL, Katzmarzyk PT, Nichaman MZ, Church TS, Blair SN, Ross R. Visceral fat is an independent predictor of all-cause mortality in men. Obesity (Silver Spring). 2006; 14:336-41.10.1038/oby.2006.4316571861]Open DOISearch in Google Scholar
[35. Romero-Corral A, Lopez-Jimenez F, Sierra-Johnson J, Somers VK. Differentiating between body fat and lean mass-how should we measure obesity? Nat Clin Pract Endocrinol Metab. 2008; 4:322-3.]Search in Google Scholar
[36. Romero-Corral A, Somers VK, Sierra-Johnson J, Korenfeld Y, Boarin S, Korinek J, et al. Normal weight obesity: a risk factor for cardiometabolic dysregulation and cardiovascular mortality. Eur Heart J. 2010; 31: 737-46.10.1093/eurheartj/ehp487283867919933515]Open DOISearch in Google Scholar
[37. Rosito GA, Massaro JM, Hoffmann U, Ruberg FL, Mahabadi AA, Vasan RS, et al. Pericardial fat, visceral abdominal fat, cardiovascular disease risk factors, and vascular calcification in a community-based sample: the Framingham Heart Study. Circulation. 2008; 117:605-13.10.1161/CIRCULATIONAHA.107.74306218212276]Open DOISearch in Google Scholar
[38. Chaston TB, Dixon JB. Factors associated with percent change in visceral versus subcutaneous abdominal fat during weight loss: findings from a systematic review. Int J Obes (Lond). 2008; 32:619-28.10.1038/sj.ijo.080376118180786]Open DOISearch in Google Scholar
[39. Ross R, Rissanen J, Hudson R. Sensitivity associated with the identification of visceral adipose tissue levels using waist circumference in men and women: effects of weight loss. Int J Obes Relat Metab Disord. 1996; 20:533-8.]Search in Google Scholar
[40. Lovejoy JC, Smith SR, Rood JC. Comparison of regional fat distribution and health risk factors in middle-aged white and African American women: The Healthy Transitions Study. Obes Res. 2001; 9: 10-6.10.1038/oby.2001.211346662]Open DOISearch in Google Scholar
[41. Carroll JF, Chiapa AL, Rodriquez M, Phelps DR, Cardarelli KM, Vishwanatha JK, et al. Visceral fat, waist circumference, and BMI: impact of race/ethnicity. Obesity (Silver Spring). 2008; 16:600-7.10.1038/oby.2007.9218239557]Open DOISearch in Google Scholar
[42. Yokoyama H. [Gamma glutamyl transpeptidase (gammaGTP) in the era of metabolic syndrome]. Nihon Arukoru Yakubutsu Igakkai Zasshi. 2007; 42:110-24.]Search in Google Scholar
[43. Lee MY, Koh SB, Koh JH, Nam SM, Shin JY, Shin YG, et al. Relationship between γ-glutamyltransferase and metabolic syndrome in a Korean population. Diabet Med. 2008; 25:469-75.10.1111/j.1464-5491.2008.02415.x18346161]Open DOISearch in Google Scholar
[44. Monami M, Bardini G, Lamanna C, Pala L, Cresci B, Francesconi P, et al. Liver enzymes and risk of diabetes and cardiovascular disease: results of the Firenze Bagno a Ripoli (FIBAR) study. Metabolism. 2008; 57: 387-92.10.1016/j.metabol.2007.10.01518249212]Open DOISearch in Google Scholar
[45. Kim DJ, Noh JH, Cho NH, Lee BW, Choi YH, Jung JH, et al. Serum γ-glutamyltransferase within its normal concentration range is related to the presence of diabetes and cardiovascular risk factors. Diabet Med. 2005; 22:1134-40. 10.1111/j.1464-5491.2005.01581.x16108838]Open DOISearch in Google Scholar