Adiposity Measurements by BMI, Skinfolds and Dual Energy X-Ray Absorptiometry in relation to Risk Markers for Cardiovascular Disease and Diabetes in Adult Males
Background. Choice of adiposity measure may be important in the evaluation of relationships between adiposity and risk markers for cardiovascular disease and diabetes. Aim. We explored the strengths of risk marker associations with BMI, a simple measure of adiposity, and with measures provided by skinfold thicknesses and dual energy X-ray absorptiometry (DXA). Subjects and Methods. We evaluated in three subgroups of white males ( –349), participating in a health screening program, the strengths of relationship between measures of total and regional adiposity and risk markers relating to blood pressure, lipids and lipoproteins, insulin sensitivity, and subclinical inflammation. Results. Independent of age, smoking, alcohol intake, and exercise, the strongest correlations with adiposity measures were seen with serum triglyceride concentrations and indices of insulin sensitivity, with strengths of association showing little difference between BMI and skinfold and DXA measures of total and percent body fat ( –0.46, ). Significant but weaker associations with adiposity were seen for serum HDL cholesterol and only relatively inconsistent associations with adiposity for total and LDL cholesterol and indices of subclinical inflammation. Conclusions. BMI can account for variation in risk markers in white males as well as more sophisticated measures derived from skinfold thickness measurements or DXA scanning. 1. Introduction The relationships between obesity and cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) are currently understood in terms of systemic changes that excess adipose tissue can induce in the physiologic and metabolic risk markers for these diseases. Adipose tissue products are involved in the pathogenesis of essential hypertension [1]; moreover, as an endocrine organ, through its release of various adipokines, adipose tissue can influence the transport and metabolism of lipids and lipoproteins [2, 3], glucose metabolism, and insulin sensitivity [4, 5] and can promote subclinical inflammation [6]. Variation in regional adipose tissue distribution may significantly affect risk markers for T2DM and CVD and risk of these diseases, with stronger associations for central obesity than for generalised obesity [7–12]. Elucidation of relationships between adiposity and physiologic and metabolic variables is important for our understanding of the role of increasing adiposity in health and disease, and evaluation of relationships between adiposity and risk markers is an important aspect of CVD and T2DM risk evaluation. Choice of adiposity
References
[1]
U. Schorr, K. Blaschke, S. Turan, A. Distler, and A. M. Sharma, “Relationship between angiotensinogen, leptin and blood pressure levels in young normotensive men,” Journal of Hypertension, vol. 16, no. 10, pp. 1475–1480, 1998.
[2]
V. Mohamed-Ali, J. H. Pinkney, and S. W. Coppack, “Adipose tissue as an endocrine and paracrine organ,” International Journal of Obesity, vol. 22, no. 12, pp. 1145–1158, 1998.
[3]
S. W. Coppack, T. J. Yost, R. M. Fisher, R. H. Eckel, and J. M. Miles, “Periprandial systemic and regional lipase activity in normal humans,” The American Journal of Physiology—Endocrinology and Metabolism, vol. 270, no. 4, pp. E718–E722, 1996.
[4]
G. S. Hotamisligil, N. S. Shargill, and B. M. Spiegelman, “Adipose expression of tumor necrosis factor-α: direct role in obesity-linked insulin resistance,” Science, vol. 259, no. 5091, pp. 87–91, 1993.
[5]
J. M. L. Stouthard, R. P. J. O. Elferink, and H. P. Sauerwein, “Interleukin-6 enhances glucose transport in 3T3-L1 adipocytes,” Biochemical and Biophysical Research Communications, vol. 220, no. 2, pp. 241–245, 1996.
[6]
C. R. Caruso, C. R. Balistreri, and G. Candore, “The role of adipose tissue and adipokines in obesity-related inflammatory diseases,” Mediators of Inflammation, vol. 2010, Article ID 802078, 19 pages, 2010.
[7]
E. B. Rimm, M. J. Stampfer, E. Giovannucci et al., “Body size and fat distribution as predictors of coronary heart disease among middle-aged and older US men,” The American Journal of Epidemiology, vol. 141, no. 12, pp. 1117–1127, 1995.
[8]
K. M. Rexrode, J. E. Buring, and J. E. Manson, “Abdominal and total adiposity and risk of coronary heart disease in men,” International Journal of Obesity, vol. 25, no. 7, pp. 1047–1056, 2001.
[9]
H. J. Schneider, N. Friedrich, J. Klotsche et al., “The predictive value of different measures of obesity for incident cardiovascular events and mortality,” Journal of Clinical Endocrinology and Metabolism, vol. 95, no. 4, pp. 1777–1785, 2010.
[10]
P. Bj?rntorp, “‘Portal’ adipose tissue as a generator of risk factors for cardiovascular disease and diabetes,” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 10, pp. 493–496, 1990.
[11]
J. Jaspan and K. Polonsky, “Glucose ingestion in dogs alters the hepatic extraction of insulin. In vivo evidence for a relationship between biologic action and extraction of insulin,” Journal of Clinical Investigation, vol. 69, no. 3, pp. 516–525, 1982.
[12]
R. Malmstr?m, C. J. Packard, M. Caslake et al., “Defective regulation of triglyceride metabolism by insulin in the liver in NIDDM,” Diabetologia, vol. 40, no. 4, pp. 454–462, 1997.
[13]
J. V. G. A. Durnin and J. Womersley, “Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years,” The British Journal of Nutrition, vol. 32, no. 1, pp. 79–97, 1974.
[14]
O. L. Svendsen, J. Haarbo, C. Hassager, and C. Christiansen, “Accuracy of measurements of body composition by dual-energy X-ray absorptiometry in vivo,” The American Journal of Clinical Nutrition, vol. 57, no. 5, pp. 605–608, 1993.
[15]
R. B. Mazess, H. S. Barden, J. P. Bisek, and J. Hanson, “Dual-energy X-ray absorptiometry for total-body and regional bone-mineral and soft-tissue composition,” The American Journal of Clinical Nutrition, vol. 51, no. 6, pp. 1106–1112, 1990.
[16]
I. F. Godsland, O. F. Agbaje, and R. Hovorka, “Evaluation of nonlinear regression approaches to estimation of insulin sensitivity by the minimal model with reference to Bayesian hierarchical analysis,” The American Journal of Physiology—Endocrinology and Metabolism, vol. 291, no. 1, pp. E167–E174, 2006.
[17]
I. F. Godsland, F. Leyva, C. Walton, M. Worthington, and J. C. Stevenson, “Associations of smoking, alcohol and physical activity with risk factors for coronary heart disease and diabetes in the first follow-up cohort of the heart disease and diabetes risk indicators in a screened cohort study (HDDRISC-1),” Journal of Internal Medicine, vol. 244, no. 1, pp. 33–41, 1998.
[18]
C. J. Ley, B. Lees, and J. C. Stevenson, “Sex- and menopause-associated changes in body-fat distribution,” The American Journal of Clinical Nutrition, vol. 55, no. 5, pp. 950–954, 1992.
[19]
W. T. Friedewald, R. I. Levy, and D. S. Fredrickson, “Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge,” Clinical Chemistry, vol. 18, no. 6, pp. 499–502, 1972.
[20]
D. R. Matthews, J. P. Hosker, A. S. Rudenski, B. A. Naylor, D. F. Treacher, and R. C. Turner, “Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man,” Diabetologia, vol. 28, no. 7, pp. 412–419, 1985.
[21]
M. Matsuda and R. A. DeFronzo, “Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp,” Diabetes Care, vol. 22, no. 9, pp. 1462–1470, 1999.
[22]
T. V. Perneger, “What's wrong with Bonferroni adjustments,” The British Medical Journal, vol. 316, no. 7139, pp. 1236–1238, 1998.
[23]
J. Steinberger, D. R. Jacobs Jr., S. Raatz, A. Moran, C. P. Hong, and A. R. Sinaiko, “Comparison of body fatness measurements by BMI and skinfolds vs dual energy X-ray absorptiometry and their relation to cardiovascular risk factors in adolescents,” International Journal of Obesity, vol. 29, no. 11, pp. 1346–1352, 2005.
[24]
H. Ito, K. Nakasuga, A. Ohshima et al., “Detection of cardiovascular risk factors by indices of obesity obtained from anthropometry and dual-energy X-ray absorptiometry in Japanese individuals,” International Journal of Obesity, vol. 27, no. 2, pp. 232–237, 2003.
[25]
J. Sierra-Johnson, B. D. Johnson, K. R. Bailey, and S. T. Turner, “Relationships between insulin sensitivity and measures of body fat in asymptomatic men and women,” Obesity Research, vol. 12, no. 12, pp. 2070–2077, 2004.
[26]
K. Lee, Y. M. Song, and J. Sung, “Which obesity indicators are better predictors of metabolic risk? Healthy twin study,” Obesity, vol. 16, no. 4, pp. 834–840, 2008.
[27]
E. Hemmingsson, J. Uddén, and M. Neovius, “No apparent progress in bioelectrical impedance accuracy: validation against metabolic risk and DXA,” Obesity, vol. 17, no. 1, pp. 183–187, 2009.
[28]
Q. Sun, R. M. van Dam, D. Spiegelman, S. B. Heymsfield, W. C. Willett, and F. B. Hu, “Comparison of dual-energy X-ray absorptiometric and anthropometric measures of adiposity in relation to adiposity-related biologic factors,” The American Journal of Epidemiology, vol. 172, no. 12, pp. 1442–1454, 2010.
[29]
D. Spiegelman, R. G. Israel, C. Bouchard, and W. C. Willett, “Absolute fat mass, percent body fat, and body-fat distribution: which is the real determinant of blood pressure and serum glucose?” The American Journal of Clinical Nutrition, vol. 55, no. 6, pp. 1033–1044, 1992.
[30]
D. S. Freedman, P. T. Katzmarzyk, W. H. Dietz, S. R. Srinivasan, and G. S. Berenson, “The relation of BMI and skinfold thicknesses to risk factors among young and middle-aged adults: the Bogalusa heart study,” Annals of Human Biology, vol. 37, no. 6, pp. 726–737, 2010.
[31]
R. Scherzer, W. Shen, P. Bacchetti et al., “Simple anthropometric measures correlate with metabolic risk indicators as strongly as magnetic resonance imaging-measured adipose tissue depots in both HIV-infected and control subjects,” The American Journal of Clinical Nutrition, vol. 87, no. 6, pp. 1809–1817, 2008.
[32]
C. S. Fox, J. M. Massaro, U. Hoffmann et al., “Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham heart study,” Circulation, vol. 116, no. 1, pp. 39–48, 2007.
[33]
M. Piché, A. Lapointe, S. J. Weisnagel et al., “Regional body fat distribution and metabolic profile in postmenopausal women,” Metabolism, vol. 57, no. 8, pp. 1101–1107, 2008.
[34]
J. D. Smith, A. L. Borel, J. A. Nazare et al., “Visceral adipose tissue indicates the severity of cardiometabolic risk in patients with and without type 2 diabetes: results from the INSPIRE ME IAA study,” Journal of Clinical Endocrinology and Metabolism, vol. 97, no. 5, pp. 1517–1525, 2012.
[35]
E. L. Thomas, G. Frost, S. D. Taylor-Robinson, and J. D. Bell, “Excess body fat in obese and normal-weight subjects,” Nutrition Research Reviews, vol. 25, no. 1, pp. 150–161, 2012.
[36]
N. Abate, A. Garg, R. M. Peshock, J. Stray-Gundersen, and S. M. Grundy, “Relationships of generalized and regional adiposity to insulin sensitivity in men,” Journal of Clinical Investigation, vol. 96, no. 1, pp. 88–98, 1995.
[37]
B. H. Goodpaster, F. L. Thaete, J. Simoneau, and D. E. Kelley, “Subcutaneous abdominal fat and thigh muscle composition predict insulin sensitivity independently of visceral fat,” Diabetes, vol. 46, no. 10, pp. 1579–1585, 1997.
[38]
Y. Miyazaki, L. Glass, C. Triplitt, E. Wajcberg, L. J. Mandarino, and R. A. DeFronzo, “Abdominal fat distribution and peripheral and hepatic insulin resistance in type 2 diabetes mellitus,” The American Journal of Physiology—Endocrinology and Metabolism, vol. 283, no. 6, pp. E1135–E1143, 2002.
[39]
D. E. Laaksonen, S. Kainulainen, A. Rissanen, and L. Niskanen, “Relationships between changes in abdominal fat distribution and insulin sensitivity during a very low calorie diet in abdominally obese men and women,” Nutrition, Metabolism and Cardiovascular Diseases, vol. 13, no. 6, pp. 349–356, 2003.
[40]
S. M. Kang, J. W. Yoon, H. Y. Ahn et al., “Android fat depot is more closely associated with metabolic syndrome than abdominal visceral fat in elderly people,” PLoS ONE, vol. 6, no. 11, Article ID e27694, 2011.
[41]
E. Bonora, “Relationship between regional fat distribution and insulin resistance,” International Journal of Obesity, vol. 24, supplement 2, pp. S32–S35, 2000.
[42]
S. K. Gan, A. D. Kriketos, A. M. Poynten et al., “Insulin action, regional fat, and myocyte lipid: altered relationships with increased adiposity,” Obesity Research, vol. 11, no. 11, pp. 1295–1305, 2003.
[43]
B. Larsson, K. Sv?rdsudd, L. Welin, L. Wilhelmsen, P. Bj?rntorp, and G. Tibblin, “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,” The British Medical Journal, vol. 288, pp. 1401–1404, 1984.
[44]
G. Hu, J. Tuomilehto, K. Silventoinen, N. Barengo, and P. Jousilahti, “Joint effects of physical activity, body mass index, waist circumference and waist-to-hip ratio with the risk of cardiovascular disease among middle-aged Finnish men and women,” European Heart Journal, vol. 25, no. 24, pp. 2212–2219, 2004.
[45]
E. L. Thomas, J. R. Parkinson, G. S. Frost et al., “The missing risk: MRI and MRS phenotyping of abdominal adiposity and ectopic fat,” Obesity, vol. 20, no. 1, pp. 76–87, 2012.
[46]
A. J. Cameron, D. J. Magliano, J. E. Shaw et al., “The influence of hip circumference on the relationship between abdominal obesity and mortality,” International Journal of Epidemiology, vol. 41, no. 2, Article ID dyr198, pp. 484–494, 2012.
[47]
R. B. Terry, M. L. Stefanick, W. L. Haskell, and P. D. Wood, “Contributions of regional adipose tissue depots to plasma lipoprotein concentrations in overweight men and women: possible protective effects of thigh fat,” Metabolism, vol. 40, no. 7, pp. 733–740, 1991.
[48]
J. C. Seidell, L. Pérusse, J.-. Després, and C. Bouchard, “Waist and hip circumferences have independent and opposite effects on cardiovascular disease risk factors: the Quebec family study,” The American Journal of Clinical Nutrition, vol. 74, no. 3, pp. 315–321, 2001.
[49]
M. B. Snijder, J. M. Dekker, M. Visser et al., “Trunk fat and leg fat have independent and opposite associations with fasting and postload glucose levels: the hoorn study,” Diabetes Care, vol. 27, no. 2, pp. 372–377, 2004.
[50]
H. Wu, Q. Qi, Z. Yu et al., “Independent and opposite associations of trunk and leg fat depots with adipokines, inflammatory markers, and metabolic syndrome in middle-aged and older Chinese men and women,” Journal of Clinical Endocrinology and Metabolism, vol. 95, no. 9, pp. 4389–4398, 2010.
[51]
K. N. Manolopoulos, F. Karpe, and K. N. Frayn, “Gluteofemoral body fat as a determinant of metabolic health,” International Journal of Obesity, vol. 34, no. 6, pp. 949–959, 2010.
[52]
H. S. Park, J. Y. Park, and R. Yu, “Relationship of obesity and visceral adiposity with serum concentrations of CRP, TNF-α and IL-6,” Diabetes Research and Clinical Practice, vol. 69, no. 1, pp. 29–35, 2005.
[53]
S. A. Lear, M. M. Chen, C. L. Birmingham, and J. J. Frohlich, “The relationship between simple anthropometric indices and C-reactive protein: ethnic and gender differences,” Metabolism, vol. 52, no. 12, pp. 1542–1546, 2003.
[54]
C. A. Wilson, G. Bekele, M. Nicolson, E. Ravussin, and R. E. Pratley, “Relationship of the white blood cell count to body fat: role of leptin,” The British Journal of Haematology, vol. 99, no. 2, pp. 447–451, 1997.
[55]
J. B. Dixon and P. E. O'Brien, “Obesity and the white blood cell count: changes with sustained weight loss,” Obesity Surgery, vol. 16, no. 3, pp. 251–257, 2006.
[56]
I. F. Godsland, R. Bruce, J. A. R. Jeffs, F. Leyva, C. Walton, and J. C. Stevenson, “Inflammation markers and erythrocyte sedimentation rate but not metabolic syndrome factor score predict coronary heart disease in high socioeconomic class males: the HDDRISC study,” International Journal of Cardiology, vol. 97, no. 3, pp. 543–550, 2004.
[57]
I. F. Godsland, B. V. North, and D. G. Johnston, “Simple indices of inflammation as predictors of death from cancer or cardiovascular disease in a prospective cohort after two decades of follow-up,” Quarterly Journal of Medicine, vol. 104, no. 5, pp. 387–394, 2011.