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Comparison of anthropometric, area- and volume-based assessment of abdominal subcutaneous and visceral adipose tissue volumes using multi-detector computed tomography

Abstract

Purpose:

Cross-sectional imaging may enable accurate localization and quantification of subcutaneous and visceral adipose tissue. The reproducibility of multi-detector computed tomography (MDCT)-based volumetric quantification of abdominal adipose tissue and the ability to depict age- and gender-related characteristics of adipose tissue deposition have not been reported.

Methods:

We evaluated a random subset of 100 Caucasian subjects (age range: 37–83 years; 49% women) of the Framingham Heart Study offspring cohort who underwent MDCT scanning. Two readers measured subcutaneous and visceral adipose tissue volumes (SAV and VAV; cm3) and areas (SAA and VAA; cm2) as well as abdominal sagital diameter (SD) and waist circumference (WC).

Results:

Inter-reader reproducibility was excellent (relative difference: −0.34±0.52% for SAV and 0.59±0.93% for VAV, intra-class correlation (ICC)=0.99 each). The mean SAA/VAA ratio was significantly different from the mean SAV/VAV ratio (2.0±1.2 vs 1.7±0.9; P<0.001). The ratio of SAV/VAV was only weakly inversely associated with SD (ICC=−0.32, P=0.01) and not significantly associated with WC (ICC=−0.14, P=0.14) or body mass index (ICC=−0.17, P=0.09). The mean SAV/VAV ratio was significantly different between participants <60 vs >60 years (1.9±1.0 vs 1.5±0.7; P<0.001) and between men and women (1.2±0.5 vs 2.2±0.9; P<0.001).

Conclusion:

This study demonstrates that MDCT-based volumetric quantification of abdominal adipose tissue is highly reproducible. In addition, our results suggest that volumetric measurements can depict age- and gender-related differences of visceral and subcutaneous abdominal adipose tissue deposition. Further research is warranted to assess whether volumetric measurements may substantially improve the predictive value of obesity measures for insulin resistance, type 2 diabetes mellitus and other diseases.

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References

  1. WHO. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser 1995; 854: 1–452.

  2. Rosenbaum M, Leibel RL, Hirsch J . Obesity. N Engl J Med 1997; 337: 396–407.

    Article  CAS  Google Scholar 

  3. Lapidus L, Bengtsson C, Larsson B, Pennert K, Rybo E, Sjostrom L . Distribution of adipose tissue and risk of cardiovascular disease and death: a 12 year follow up of participants in the population study of women in Gothenburg, Sweden. Br Med J (Clin Res Ed) 1984; 289: 1257–1261.

    Article  CAS  Google Scholar 

  4. Peiris AN, Sothmann MS, Hoffmann RG, Hennes MI, Wilson CR, Gustafson AB et al. Adiposity, fat distribution, and cardiovascular risk. Ann Intern Med 1989; 110: 867–872.

    Article  CAS  Google Scholar 

  5. Kopelman PG . Obesity as a medical problem. Nature 2000; 404: 635.

    Article  CAS  Google Scholar 

  6. Hubert HB, Feinleib M, McNamara PM, Castelli WP . Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham Heart Study. Circulation 1983; 67: 968–977.

    Article  CAS  Google Scholar 

  7. Larsson B, Svardsudd K, Welin L, Wilhelmsen L, Bjorntorp P, Tibblin G . Abdominal adipose tissue distribution, obesity, and risk of cardiovascular disease and death: 13 year follow up of participants in the study of men born in 1913. Br Med J (Clin Res Ed) 1984; 288: 1401–1404.

    Article  CAS  Google Scholar 

  8. Jonsson S, Hedblad B, Engstrom G, Nilsson P, Berglund G, Janzon L . Influence of obesity on cardiovascular risk. Twenty-three-year follow-up of 22 025 men from an urban Swedish population. Int J Obes Relat Metab Disord 2002; 26: 1046–1053.

    Article  CAS  Google Scholar 

  9. Anjana M, Sandeep S, Deepa R, Vimaleswaran KS, Farooq S, Mohan V . Visceral and central abdominal fat and anthropometry in relation to diabetes in Asian Indians. Diabetes Care 2004; 27: 2948–2953.

    Article  Google Scholar 

  10. Matsuzawa Y . Adipocytokines and metabolic syndrome. Semin Vasc Med 2005; 5: 34–39.

    Article  Google Scholar 

  11. Hotamisligil GS, Shargill NS, Spiegelman BM . Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science 1993; 259: 87–91.

    Article  CAS  Google Scholar 

  12. Matsuzawa Y . Adiponectin: identification, physiology and clinical relevance in metabolic and vascular disease. Atheroscler Suppl 2005; 6: 7–14.

    Article  CAS  Google Scholar 

  13. Shimomura I, Funahashi T, Takahashi M, Maeda K, Kotani K, Nakamura T et al. Enhanced expression of PAI-1 in visceral fat: possible contributor to vascular disease in obesity. Nat Med 1996; 2: 800–803.

    Article  CAS  Google Scholar 

  14. Steppan CM, Bailey ST, Bhat S, Brown EJ, Banerjee RR, Wright CM et al. The hormone resistin links obesity to diabetes. Nature 2001; 409: 307–312.

    Article  CAS  Google Scholar 

  15. Hug C, Lodish HF . Medicine. Visfatin: a new adipokine. Science 2005; 307: 366–367.

    Article  CAS  Google Scholar 

  16. Wannamethee SG, Shaper AG, Morris RW, Whincup PH . Measures of adiposity in the identification of metabolic abnormalities in elderly men. Am J Clin Nutr 2005; 81: 1313–1321.

    Article  CAS  Google Scholar 

  17. Seidell JC, Cigolini M, Charzewska J, Ellsinger BM, Deslypere JP, Cruz A . Fat distribution in European men: a comparison of anthropometric measurements in relation to cardiovascular risk factors. Int J Obes Relat Metab Disord 1992; 16: 17–22.

    CAS  PubMed  Google Scholar 

  18. Ledoux M, Lambert J, Reeder BA, Despres JP . Correlation between cardiovascular disease risk factors and simple anthropometric measures. Canadian Heart Health Surveys Research Group. Can Med Assoc J 1997; 157 (Suppl 1): S46–S53.

    Google Scholar 

  19. Dobbelsteyn CJ, Joffres MR, MacLean DR, Flowerdew G . A comparative evaluation of waist circumference, waist-to-hip ratio and body mass index as indicators of cardiovascular risk factors. The Canadian Heart Health Surveys. Int J Obes Relat Metab Disord 2001; 25: 652–661.

    Article  CAS  Google Scholar 

  20. Rexrode KM, Buring JE, Manson JE . Abdominal and total adiposity and risk of coronary heart disease in men. Int J Obes Relat Metab Disord 2001; 25: 1047–1056.

    Article  CAS  Google Scholar 

  21. Molarius A, Seidell JC . Selection of anthropometric indicators for classification of abdominal fatness – a critical review. Int J Obes Relat Metab Disord 1998; 22: 719–727.

    Article  CAS  Google Scholar 

  22. Sjostrom L, Kvist H, Cederblad A, Tylen U . Determination of total adipose tissue and body fat in women by computed tomography, 40K, and tritium. Am J Physiol 1986; 250: E736–E745.

    CAS  Google Scholar 

  23. Borkan GA, Gerzof SG, Robbins AH, Hults DE, Silbert CK, Silbert JE . Assessment of abdominal fat content by computed tomography. Am J Clin Nutr 1982; 36: 172–177.

    Article  CAS  Google Scholar 

  24. Yoshizumi T, Nakamura T, Yamane M, Islam AH, Menju M, Yamasaki K et al. Abdominal fat: standardized technique for measurement at CT. Radiology 1999; 211: 283–286.

    Article  CAS  Google Scholar 

  25. Kvist H, Chowdhury B, Sjostrom L, Tylen U, Cederblad A . Adipose tissue volume determination in males by computed tomography and 40K. Int J Obes 1988; 12: 249–266.

    CAS  PubMed  Google Scholar 

  26. Shrout P, Fleiss J . Intraclass correlations: uses in assessing rater reliability. Psychol Bull 1979; 86: 420–428.

    Article  CAS  Google Scholar 

  27. Cnop M, Landchild MJ, Vidal J, Havel PJ, Knowles NG, Carr DR et al. The concurrent accumulation of intra-abdominal and subcutaneous fat explains the association between insulin resistance and plasma leptin concentrations: distinct metabolic effects of two fat compartments. Diabetes 2002; 51: 1005–1015.

    Article  CAS  Google Scholar 

  28. Goodpaster BH, Krishnaswami S, Harris TB, Katsiaras A, Kritchevsky SB, Simonsick EM et al. Obesity, regional body fat distribution, and the metabolic syndrome in older men and women. Arch Intern Med 2005; 165: 777–783.

    Article  Google Scholar 

  29. von Eyben FE, Mouritsen E, Holm J, Montvilas P, Dimcevski G, Suciu G et al. Intra-abdominal obesity and metabolic risk factors: a study of young adults. Int J Obes Relat Metab Disord 2003; 27: 941–949.

    Article  CAS  Google Scholar 

  30. Kobayashi J, Tadokoro N, Watanabe M, Shinomiya M . A novel method of measuring intra-abdominal fat volume using helical computed tomography. Int J Obes Relat Metab Disord 2002; 26: 398–402.

    Article  CAS  Google Scholar 

  31. Piche ME, Weisnagel SJ, Corneau L, Nadeau A, Bergeron J, Lemieux S . Contribution of abdominal visceral obesity and insulin resistance to the cardiovascular risk profile of postmenopausal women. Diabetes 2005; 54: 770–777.

    Article  CAS  Google Scholar 

  32. Onat A, Avci GS, Barlan MM, Uyarel H, Uzunlar B, Sansoy V . Measures of abdominal obesity assessed for visceral adiposity and relation to coronary risk. Int J Obes Relat Metab Disord 2004; 28: 1018–1025.

    Article  CAS  Google Scholar 

  33. Albu JB, Kovera AJ, Allen L, Wainwright M, Berk E, Raja-Khan N et al. Independent association of insulin resistance with larger amounts of intermuscular adipose tissue and a greater acute insulin response to glucose in African American than in white nondiabetic women. Am J Clin Nutr 2005; 82: 1210–1217.

    Article  CAS  Google Scholar 

  34. Gallagher D, Kuznia P, Heshka S, Albu J, Heymsfield SB, Goodpaster B et al. Adipose tissue in muscle: a novel depot similar in size to visceral adipose tissue. Am J Clin Nutr 2005; 81: 903–910.

    Article  CAS  Google Scholar 

  35. Baumgartner RN, Heymsfield SB, Roche AF . Human body composition and the epidemiology of chronic disease. Obes Res 1995; 3: 73–95.

    Article  CAS  Google Scholar 

  36. Seidell JC, Visscher TL . Body weight and weight change and their health implications for the elderly. Eur J Clin Nutr 2000; 54 (Suppl 3): S33–S39.

    Article  Google Scholar 

  37. Thomas EL, Bell JD . Influence of undersampling on magnetic resonance imaging measurements of intra-abdominal adipose tissue. Int J Obes Relat Metab Disord 2003; 27: 211–218.

    Article  CAS  Google Scholar 

  38. Greenfield JR, Samaras K, Chisholm DJ, Campbell LV . Regional intra-subject variability in abdominal adiposity limits usefulness of computed tomography. Obes Res 2002; 10: 260–265.

    Article  Google Scholar 

  39. Lemieux S, Prud'homme D, Bouchard C, Tremblay A, Despres JP . Sex differences in the relation of visceral adipose tissue accumulation to total body fatness. Am J Clin Nutr 1993; 58: 463–467.

    Article  CAS  Google Scholar 

  40. Ross R, Leger L, Morris D, de Guise J, Guardo R . Quantification of adipose tissue by MRI: relationship with anthropometric variables. J Appl Physiol 1992; 72: 787–795.

    Article  CAS  Google Scholar 

  41. Machann J, Thamer C, Schnoedt B, Haap M, Haring HU, Claussen CD et al. Standardized assessment of whole body adipose tissue topography by MRI. J Magn Reson Imaging 2005; 21: 455–462.

    Article  Google Scholar 

  42. Chowdhury B, Sjostrom L, Alpsten M, Kostanty J, Kvist H, Lofgren R . A multicompartment body composition technique based on computerized tomography. Int J Obes Relat Metab Disord 1994; 18: 219–234.

    CAS  PubMed  Google Scholar 

  43. Positano V, Gastaldelli A, Sironi AM, Santarelli MF, Lombardi M, Landini L . An accurate and robust method for unsupervised assessment of abdominal fat by MRI. J Magn Reson Imaging 2004; 20: 684–689.

    Article  Google Scholar 

  44. Wilhelm Poll L, Wittsack HJ, Koch JA, Willers R, Cohnen M, Kapitza C et al. A rapid and reliable semiautomated method for measurement of total abdominal fat volumes using magnetic resonance imaging. Magn Reson Imaging 2003; 21: 631–636.

    Article  Google Scholar 

  45. Sobol W, Rossner S, Hinson B, Hiltbrandt E, Karstaedt N, Santago P et al. Evaluation of a new magnetic resonance imaging method for quantitating adipose tissue areas. Int J Obes Relat Metab Disord 1991; 15: 589–599.

    CAS  Google Scholar 

  46. Seidell JC, Bakker CJ, van der Kooy K . Imaging techniques for measuring adipose-tissue distribution – a comparison between computed tomography and 1.5-T magnetic resonance. Am J Clin Nutr 1990; 51: 953–957.

    Article  CAS  Google Scholar 

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Acknowledgements

The Framingham Heart Study is supported by the National Heart, Lung and Blood Institute (N01-HC-25195).

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Correspondence to U Hoffmann.

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Maurovich-Horvat, P., Massaro, J., Fox, C. et al. Comparison of anthropometric, area- and volume-based assessment of abdominal subcutaneous and visceral adipose tissue volumes using multi-detector computed tomography. Int J Obes 31, 500–506 (2007). https://doi.org/10.1038/sj.ijo.0803454

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