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International Chair on Cardiometabolic Risk
My Healthy Waist

Waist Circumference

Evaluating CMR - Clinical Tools

Key Points

  • Within every BMI category, waist circumference is an important predictor of health risk.
  • Waist circumference should be measured at the top of the iliac crest.
  • Waist circumference is a crude but convenient anthropometric measure of abdominal adiposity and of its changes.

Waist Circumference and Health Risk

Jean Vague was the first to recognize the harmful health consequences of excess abdominal fat more than 50 years ago [1]. Since this initial observation, a great deal of research has strengthened abdominal obesity’s independent association with diabetes, hypertension, cardiovascular disease, some cancers, and mortality risk [2-5]. It is now acknowledged that waist circumference increases health risk beyond that explained by body mass index (BMI) alone [6-12]. In this regard, a consensus statement published by the International Atherosclerosis Society and the International Chair on Cardiometabolic Risk Working Group on Visceral Obesity has underlined the importance of measuring waist circumference in addition to the BMI as a vital sign in clinical practice [13].

Health-related Waist Circumference Cut-offs

Abdominal obesity can be assessed using waist circumference, and common measurement protocols include the visible narrowing of the waist, last rib, top of the iliac crest, or the midpoint between the last rib and the iliac crest. The World Health Organization recommends measuring waist circumference at the midpoint between the lower border of the rib cage and the top of the iliac crest [14]. The National Institutes of Health (NIH) in the United States has proposed measuring waist circumference using the iliac crest as the landmark [15]. Accordingly, the International Chair on Cardiometabolic Risk also recommends measuring waist circumference at the top of the iliac crest [16]. Indeed, following an extensive review of the literature, it was found that the waist circumference measurement protocol did not substantially affect the association between waist circumference with all-cause and cardiovascular disease mortality, cardiovascular disease and diabetes [16].

Sex-specific waist circumference thresholds (men: 102 cm, women: 88 cm) suggesting increased health risk within each BMI category have been published by the NIH [15]. Results of an analysis from Janssen and colleagues [6] have demonstrated that that individuals with an increased waist circumference (based on the NIH cut-offs) were characterized by several complications such as hypertension, dyslipidemia or diabetes compared to those with normal waist circumference values, regardless of BMI categories. However, unlike BMI categories, these waist circumference cut-offs were not based on their association with morbidity or mortality, but were instead based on waist circumference values corresponding to a BMI of 30 kg/m2 in Caucasian men and women [17]. Of note also, these cut-offs remained similar across BMI categories. In order to take into account this limitation, Ardern et al. [18] have proposed from large samples optimal waist circumference thresholds within BMI categories that predicted increased risk of coronary events. They found that the best waist circumference cut-offs increased as a function of increasing BMI.

However, these waist circumference thresholds seem appropriate for non-Hispanic blacks and Mexican Americans [19], but are likely too high for most Asian populations [20] and are unknown for many other ethnic groups. The appropriate cut-offs for determining health risk in Asian and other ethnic populations are still being studied, but reported values for Asians range from 85 to 90 cm for men and 80 to 90 cm for women [13,20]. For instance, the International Diabetes Federation position statement on the metabolic syndrome and its clinical diagnosis has proposed lower waist girth values (94 cm for European men), while recognizing the need to propose cut-offs specific to various ethnic populations [20]. A summary of ethnicity-specific waist circumference values for adults is also presented in the joint consensus statement of the International Atherosclerosis Society and the International Chair on Cardiometabolic Risk [13].

Thus, within a given BMI category, individuals with a waist circumference greater than the proposed thresholds generally have a worse metabolic profile than individuals with a waist circumference below these thresholds [6,13,18].  It is therefore important to measure waist circumference in addition to BMI when assessing health risk as the combination allows to identify high-risk obesity phenotypes.

Measuring Waist Circumference—Healthcare Professionals

Waist circumference should be measured with the tape directly on the individual’s skin (Figure 1). The individual should be asked to loosen and/or remove any restrictive garments or clothing that would interfere with the measure. The individual should be relaxed with their arms crossed on their chest and their feet shoulder-width apart. To ensure proper landmarking, mark the measurement site (i.e., iliac crest) on the right side of the individual’s body with a horizontal line after determining the correct location. The International Chair on Cardiometabolic Risk recommends that you palpate the iliac crest firmly with your hands and place the landmark at the uppermost border of the iliac crest. The bottom edge of the tape measure should be placed directly level with the landmark. Ensure the tape is horizontal to the floor, is snug without indenting the individual’s skin, and is not twisted or caught on clothing. Measure the waist at the end of a normal expiration to the nearest 0.1 cm.

The literature suggests that waist circumference measures are highly repeatable and that measures between trained technicians are very comparable [21,22]. Proper training helps to position the measurement tape properly and apply constant tension, which ensures an accurate assessment of waist circumference. The use of spring-loaded measurement tapes (Figure 2) can improve accuracy by ensuring that constant tension is applied to the tape while waist circumference is being measured.

Figure 1:
Technician-measured waist circumference using a Myotape (A) or a Gulick tape (B)
Figure 2:
Spring-loaded waist circumference measurement tapes

Measuring Waist Circumference—Self-measurement

It is recommended that you measure waist circumference in front of a mirror in your undergarments or without any clothing that would interfere with the measurement (Figure 3). Measure your waist circumference with the measuring tape directly on your skin. Stand in a relaxed position with your feet shoulder-width apart. The use of a Myotape is recommended to ensure proper landmarking and measurement. Use your hands to find the uppermost border of your hip bones on both sides of your body. Align the bottom edge of your measuring tape with the top of your hipbones. Use the mirror to ensure that you have placed the measuring tape correctly (i.e., horizontally, and not twisted or caught on clothing). The measure should be snug without indenting your skin. Relax and measure your waist at the end of a normal expiration to the nearest 0.1 cm.

 

Errors associated with self-reported waist circumference
Men and women tend to underestimate their waist size when it is measured using a traditional measuring tape, with the underestimation increasing with waist size [23]. Consequently, only 35.5% of abdominally obese men (>102 cm) and 44.9% of abdominally obese women (>88 cm) correctly classified themselves into the highest health risk category. However, when the same individuals used a tape measure with a spring mechanism, the measurement error dropped to 0.5 cm and 0.4 cm in men and women respectively, and only 2% of the sample misclassified their waist circumference category. This suggests that spring-loaded tape measures may be a useful clinical tool for minimizing the underestimation of waist circumference and may provide an accurate method for self-assessment of health risk.

Figure 3:
Self-measured circumference using a Myotape

Association Between Waist Circumference and Visceral Fat

Increases in abdominal fat are largely responsible for increases in waist circumference. Abdominal fat can be divided into two major components: subcutaneous fat and visceral fat. Subcutaneous fat lies just below the skin and is outside the abdominal muscle wall, whereas visceral fat is located inside the abdominal muscular wall and lies in between the organs or viscera. Waist circumference is a good correlate of both total abdominal fat and its sub-compartments. However, the importance of waist circumference in predicting health risk is more commonly thought to be due to the relationship between waist circumference and visceral fat. Indeed, waist circumference is a stronger predictor of visceral fat than BMI [13,24-29]. Moreover, the INSPIRE ME IAA imaging study revealed that an increase in waist circumference within BMI categories was associated with a greater visceral adipose tissue accumulation [30]. Because visceral fat is a strong independent predictor of morbidity [31-34] and mortality [35], considerable attention has been given to the ability of waist circumference as a clinical tool to predict visceral fat within any given BMI category.

Previous studies have reported that the percentage of error for estimates of visceral fat using waist circumference is roughly 25 to 35% [25-28]. Factors such as age, sex, race, and fitness partly explain the variation in the amount of visceral fat for a given waist circumference [36-38]. These differences in the amount of visceral fat for a given waist circumference may explain why different waist cut-offs are needed for men and women and for different racial groups. For example, Filipino women with a waist circumference of 80 cm would be expected to have 22% more visceral fat than Caucasian women and 35% more visceral fat than African American women with the same waist circumference [38].

Age is another factor that greatly influences the amount of visceral fat for a given waist circumference. An older man (>50 years of age) with a waist circumference of 102 cm would be expected to have 70% more visceral fat than a 25-year-old man with the same waist circumference, and 140% more visceral fat than a 25-year-old woman [36] (Figure 4). However, how these differences translate into specific waist circumference cut-offs for various populations is unclear.

Figure 4:
Visceral fat in elderly versus young men with the same waist circumference

Association Between Changes in Waist Circumference and Visceral Fat

Waist circumference is also commonly used to assess changes in abdominal obesity, and is a stronger predictor of changes in visceral fat than waist-to-hip ratio [39-41]. Changes in waist circumference are associated with changes in visceral fat in response to diet and/or exercise-induced weight loss (Figure 5) [39-45]. Although the exact amount of visceral fat loss for a given reduction in waist circumference varies considerably [36,41,46,47], reductions in waist circumference are likely to be accompanied by some loss of visceral fat. Exercise can often reduce visceral fat and waist circumference, even if it does not reduce body weight significantly [47-53]. Accordingly, waist circumference should be measured as part of interventions aimed at reducing visceral fat and related health risk.

Waist circumference is a strong predictor of health risk beyond that explained by BMI alone. Waist circumference is also a crude but useful anthropometric predictor of visceral fat and changes to it. Because abdominal obesity has such a harmful impact on one’s health, it is important to routinely measure waist circumference in the clinical assessment of cardiometabolic risk. Indeed, at any given BMI category, an elevated waistline is predictive of a greater accumulation of visceral fat and therefore of an increased cardiometabolic risk.

Figure 5:
Relationship between reductions in waist circumference and visceral fat

References

  1. Vague J. Sexual differentiation, a factor affecting the forms of obesity. Presse Méd 1947; 30: 339-40.

    PubMed ID: 18918084

  2. Folsom AR, Kushi LH, Anderson KE, et al. Associations of general and abdominal obesity with multiple health outcomes in older women: the Iowa Women’s Health Study. Arch Intern Med 2000; 160: 2117-28.

    PubMed ID: 10904454

  3. Rexrode KM, Carey VJ, Hennekens CH, et al. Abdominal adiposity and coronary heart disease in women. JAMA 1998; 280: 1843-8.

    PubMed ID: 9846779

  4. Woo J, Ho SC, Yu AL, et al. Is waist circumference a useful measure in predicting health outcomes in the elderly? Int J Obes Relat Metab Disord 2002; 26: 1349-55.

    PubMed ID: 12355330

  5. Bigaard J, Frederiksen K, Tjonneland A, et al. Waist and hip circumferences and all-cause mortality: usefulness of the waist-to-hip ratio? Int J Obes Relat Metab Disord 2004; 28: 741-7.

    PubMed ID: 15052280

  6. Janssen I, Katzmarzyk PT and Ross R. Body mass index, waist circumference, and health risk: evidence in support of current National Institutes of Health guidelines. Arch Intern Med 2002; 162: 2074-9.

    PubMed ID: 12374515

  7. Karter AJ, D’Agostino RB, Jr., Mayer-Davis EJ, et al. Abdominal obesity predicts declining insulin sensitivity in non-obese normoglycaemics: the Insulin Resistance Atherosclerosis Study (IRAS). Diabetes Obes Metab 2005; 7: 230-8.

    PubMed ID: 15811139

  8. Janssen I, Katzmarzyk PT and Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004; 79: 379-84.

    PubMed ID: 14985210

  9. Ardern CI, Katzmarzyk PT, Janssen I, et al. Discrimination of health risk by combined body mass index and waist circumference. Obes Res 2003; 11: 135-42.

    PubMed ID: 12529496

  10. Pischon T, Boeing H, Hoffmann K, et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med 2008; 359: 2105-20.

    PubMed ID: 19005195

  11. Cerhan JR, Moore SC, Jacobs EJ, et al. A pooled analysis of waist circumference and mortality in 650,000 adults. Mayo Clin Proc 2014; 89: 335-45.

    PubMed ID: 24582192

  12. Zhang C, Rexrode KM, van Dam RM, et al. Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women. Circulation 2008; 117: 1658-67.

    PubMed ID: 18362231

  13. Ross R, Neeland IJ, Yamashita S, et al. Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. Nat Rev Endocrinol 2020; 16: 177-89.

    PubMed ID: 32020062

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

    PubMed ID: 8594834

  15. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults–The evidence report. National Institutes of Health. Obes Res 1998; 6 Suppl 2: 51S-209S.

    PubMed ID: 9813653

  16. Ross R, Berentzen T, Bradshaw AJ, et al. Does the relationship between waist circumference, morbidity and mortality depend on measurement protocol for waist circumference? Obes Rev 2008; 9: 312-25.

    PubMed ID: 17956544

  17. Lean ME, Han TS and Morrison CE. Waist circumference as a measure for indicating need for weight management. BMJ 1995; 311: 158-61.

    PubMed ID: 7613427

  18. Ardern CI, Janssen I, Ross R, et al. Development of health-related waist circumference thresholds within BMI categories. Obes Res 2004; 12: 1094-103.

    PubMed ID: 15292473

  19. Zhu S, Heymsfield SB, Toyoshima H, et al. Race-ethnicity-specific waist circumference cutoffs for identifying cardiovascular disease risk factors. Am J Clin Nutr 2005; 81: 409-15.

    PubMed ID: 15699228

  20. Alberti KG, Zimmet P and Shaw J. The metabolic syndrome–a new worldwide definition. Lancet 2005; 366: 1059-62.

    PubMed ID: 16182882

  21. Klipstein-Grobusch K, Georg T and Boeing H. Interviewer variability in anthropometric measurements and estimates of body composition. Int J Epidemiol 1997; 26 Suppl 1: S174-80.

    PubMed ID: 9126545

  22. Ferrario M, Carpenter MA and Chambless LE. Reliability of body fat distribution measurements. The ARIC Study baseline cohort results. Atherosclerosis Risk in Communities Study. Int J Obes Relat Metab Disord 1995; 19: 449-57.

    PubMed ID: 8520633

  23. Han TS and Lean ME. Self-reported waist circumference compared with the ‘Waist Watcher’ tape-measure to identify individuals at increased health risk through intra-abdominal fat accumulation. Br J Nutr 1998; 80: 81-8.

    PubMed ID: 9797647

  24. Janssen I, Heymsfield SB, Allison DB, et al. Body mass index and waist circumference independently contribute to the prediction of nonabdominal, abdominal subcutaneous, and visceral fat. Am J Clin Nutr 2002; 75: 683-8.

    PubMed ID: 11916754

  25. Després JP, Prud’homme D, Pouliot MC, et al. Estimation of deep abdominal adipose-tissue accumulation from simple anthropometric measurements in men. Am J Clin Nutr 1991; 54: 471-7.

    PubMed ID: 1877502

  26. Han TS, McNeill G, Seidell JC, et al. Predicting intra-abdominal fatness from anthropometric measures: the influence of stature. Int J Obes Relat Metab Disord 1997; 21: 587-93.

    PubMed ID: 9226490

  27. Ross R, Shaw KD, Rissanen J, et al. Sex differences in lean and adipose tissue distribution by magnetic resonance imaging: anthropometric relationships. Am J Clin Nutr 1994; 59: 1277-85.

    PubMed ID: 8198051

  28. Ross R, Leger L, Morris D, et al. Quantification of adipose tissue by MRI: relationship with anthropometric variables. J Appl Physiol (1985) 1992; 72: 787-95.

    PubMed ID: 1559959

  29. Seidell JC, Björntorp P, Sjöström L, et al. Regional distribution of muscle and fat mass in men–new insight into the risk of abdominal obesity using computed tomography. Int J Obes 1989; 13: 289-303.

    PubMed ID: 2767882

  30. Nazare JA, Smith J, Borel AL, et al. Usefulness of measuring both body mass index and waist circumference for the estimation of visceral adiposity and related cardiometabolic risk profile (from the INSPIRE ME IAA study). Am J Cardiol 2015; 115: 307-15.

    PubMed ID: 25499404

  31. Carr DB, Utzschneider KM, Hull RL, et al. Intra-abdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome. Diabetes 2004; 53: 2087-94.

    PubMed ID: 15277390

  32. Kuk JL, Nichaman MZ, Church TS, et al. Liver fat is not a marker of metabolic risk in lean premenopausal women. Metabolism 2004; 53: 1066-71.

    PubMed ID: 15281020

  33. Goodpaster BH, Krishnaswami S, Harris TB, et al. Obesity, regional body fat distribution, and the metabolic syndrome in older men and women. Arch Intern Med 2005; 165: 777-83.

    PubMed ID: 15824297

  34. Boyko EJ, Fujimoto WY, Leonetti DL, et al. Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans. Diabetes Care 2000; 23: 465-71.

    PubMed ID: 10857936

  35. Kuk JL, Katzmarzyk PT, Nichaman MZ, et al. Visceral fat is an independent predictor of all-cause mortality in men. Obes Res 2006; 14: 336-41.

    PubMed ID: 16571861

  36. Kuk JL, Lee S, Heymsfield SB, et al. Waist circumference and abdominal adipose tissue distribution: influence of age and sex. Am J Clin Nutr 2005; 81: 1330-4.

    PubMed ID: 15941883

  37. Janssen I, Katzmarzyk PT, Ross R, et al. Fitness alters the associations of BMI and waist circumference with total and abdominal fat. Obes Res 2004; 12: 525-37.

    PubMed ID: 15044671

  38. Araneta MR and Barrett-Connor E. Ethnic differences in visceral adipose tissue and type 2 diabetes: Filipino, African-American, and white women. Obes Res 2005; 13: 1458-65.

    PubMed ID: 16129729

  39. van der Kooy K, Leenen R, Seidell JC, et al. Waist-hip ratio is a poor predictor of changes in visceral fat. Am J Clin Nutr 1993; 57: 327-33.

    PubMed ID: 8438766

  40. Kamel EG, McNeill G and Van Wijk MC. Change in intra-abdominal adipose tissue volume during weight loss in obese men and women: correlation between magnetic resonance imaging and anthropometric measurements. Int J Obes Relat Metab Disord 2000; 24: 607-13.

    PubMed ID: 10849583

  41. Ross R, Rissanen J and 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.

    PubMed ID: 8782729

  42. Ross R. Effects of diet- and exercise-induced weight loss on visceral adipose tissue in men and women. Sports Med 1997; 24: 55-64.

    PubMed ID: 9257410

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    PubMed ID: 28162956

  44. Verheggen RJ, Maessen MF, Green DJ, et al. A systematic review and meta-analysis on the effects of exercise training versus hypocaloric diet: distinct effects on body weight and visceral adipose tissue. Obes Rev 2016; 17: 664-90.

    PubMed ID: 27213481

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    PubMed ID: 23409182

  46. Janiszewski PM and Ross R. Physical activity in the treatment of obesity: beyond body weight reduction. Appl Physiol Nutr Metab 2007; 32: 512-22.

    PubMed ID: 17510691

  47. Ross R, Janssen I, Dawson J, et al. Exercise-induced reduction in obesity and insulin resistance in women: a randomized controlled trial. Obes Res 2004; 12: 789-98.

    PubMed ID: 15166299

  48. Ross R, Dagnone D, Jones PJ, et al. Reduction in obesity and related comorbid conditions after diet-induced weight loss or exercise-induced weight loss in men. A randomized, controlled trial. Ann Intern Med 2000; 133: 92-103.

    PubMed ID: 10896648

  49. Lee S, Kuk JL, Davidson LE, et al. Exercise without weight loss is an effective strategy for obesity reduction in obese individuals with and without Type 2 diabetes. J Appl Physiol (1985) 2005; 99: 1220-5.

    PubMed ID: 15860689

  50. Gan SK, Kriketos AD, Ellis BA, et al. Changes in aerobic capacity and visceral fat but not myocyte lipid levels predict increased insulin action after exercise in overweight and obese men. Diabetes Care 2003; 26: 1706-13.

    PubMed ID: 12766098

  51. Giannopoulou I, Ploutz-Snyder LL, Carhart R, et al. Exercise is required for visceral fat loss in postmenopausal women with type 2 diabetes. J Clin Endocrinol Metab 2005; 90: 1511-8.

    PubMed ID: 15598677

  52. Binder EF, Birge SJ and Kohrt WM. Effects of endurance exercise and hormone replacement therapy on serum lipids in older women. J Am Geriatr Soc 1996; 44: 231-6.

    PubMed ID: 8600189

  53. Ross R and Bradshaw AJ. The future of obesity reduction: beyond weight loss. Nat Rev Endocrinol 2009; 5: 319-25.

    PubMed ID: 19421242
Reference 1 CLOSECLOSE

Vague J. Sexual differentiation, a factor affecting the forms of obesity. Presse Méd 1947; 30: 339-40.

PubMed ID: 18918084
Reference 2 CLOSECLOSE

Folsom AR, Kushi LH, Anderson KE, et al. Associations of general and abdominal obesity with multiple health outcomes in older women: the Iowa Women’s Health Study. Arch Intern Med 2000; 160: 2117-28.

PubMed ID: 10904454
Reference 3 CLOSECLOSE

Rexrode KM, Carey VJ, Hennekens CH, et al. Abdominal adiposity and coronary heart disease in women. JAMA 1998; 280: 1843-8.

PubMed ID: 9846779
Reference 4 CLOSECLOSE

Woo J, Ho SC, Yu AL, et al. Is waist circumference a useful measure in predicting health outcomes in the elderly? Int J Obes Relat Metab Disord 2002; 26: 1349-55.

PubMed ID: 12355330
Reference 5 CLOSECLOSE

Bigaard J, Frederiksen K, Tjonneland A, et al. Waist and hip circumferences and all-cause mortality: usefulness of the waist-to-hip ratio? Int J Obes Relat Metab Disord 2004; 28: 741-7.

PubMed ID: 15052280
Reference 6 CLOSECLOSE

Janssen I, Katzmarzyk PT and Ross R. Body mass index, waist circumference, and health risk: evidence in support of current National Institutes of Health guidelines. Arch Intern Med 2002; 162: 2074-9.

PubMed ID: 12374515
Reference 7 CLOSECLOSE

Karter AJ, D’Agostino RB, Jr., Mayer-Davis EJ, et al. Abdominal obesity predicts declining insulin sensitivity in non-obese normoglycaemics: the Insulin Resistance Atherosclerosis Study (IRAS). Diabetes Obes Metab 2005; 7: 230-8.

PubMed ID: 15811139
Reference 8 CLOSECLOSE

Janssen I, Katzmarzyk PT and Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004; 79: 379-84.

PubMed ID: 14985210
Reference 9 CLOSECLOSE

Ardern CI, Katzmarzyk PT, Janssen I, et al. Discrimination of health risk by combined body mass index and waist circumference. Obes Res 2003; 11: 135-42.

PubMed ID: 12529496
Reference 10 CLOSECLOSE

Pischon T, Boeing H, Hoffmann K, et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med 2008; 359: 2105-20.

PubMed ID: 19005195
Reference 11 CLOSECLOSE

Cerhan JR, Moore SC, Jacobs EJ, et al. A pooled analysis of waist circumference and mortality in 650,000 adults. Mayo Clin Proc 2014; 89: 335-45.

PubMed ID: 24582192
Reference 12 CLOSECLOSE

Zhang C, Rexrode KM, van Dam RM, et al. Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women. Circulation 2008; 117: 1658-67.

PubMed ID: 18362231
Reference 13 CLOSECLOSE

Ross R, Neeland IJ, Yamashita S, et al. Waist circumference as a vital sign in clinical practice: a Consensus Statement from the IAS and ICCR Working Group on Visceral Obesity. Nat Rev Endocrinol 2020; 16: 177-89.

PubMed ID: 32020062
Reference 14 CLOSECLOSE

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

PubMed ID: 8594834
Reference 15 CLOSECLOSE

Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults–The evidence report. National Institutes of Health. Obes Res 1998; 6 Suppl 2: 51S-209S.

PubMed ID: 9813653
Reference 16 CLOSECLOSE

Ross R, Berentzen T, Bradshaw AJ, et al. Does the relationship between waist circumference, morbidity and mortality depend on measurement protocol for waist circumference? Obes Rev 2008; 9: 312-25.

PubMed ID: 17956544
Reference 17 CLOSECLOSE

Lean ME, Han TS and Morrison CE. Waist circumference as a measure for indicating need for weight management. BMJ 1995; 311: 158-61.

PubMed ID: 7613427
Reference 18 CLOSECLOSE

Ardern CI, Janssen I, Ross R, et al. Development of health-related waist circumference thresholds within BMI categories. Obes Res 2004; 12: 1094-103.

PubMed ID: 15292473
Reference 19 CLOSECLOSE

Zhu S, Heymsfield SB, Toyoshima H, et al. Race-ethnicity-specific waist circumference cutoffs for identifying cardiovascular disease risk factors. Am J Clin Nutr 2005; 81: 409-15.

PubMed ID: 15699228
Reference 20 CLOSECLOSE

Alberti KG, Zimmet P and Shaw J. The metabolic syndrome–a new worldwide definition. Lancet 2005; 366: 1059-62.

PubMed ID: 16182882
Reference 21 CLOSECLOSE

Klipstein-Grobusch K, Georg T and Boeing H. Interviewer variability in anthropometric measurements and estimates of body composition. Int J Epidemiol 1997; 26 Suppl 1: S174-80.

PubMed ID: 9126545
Reference 22 CLOSECLOSE

Ferrario M, Carpenter MA and Chambless LE. Reliability of body fat distribution measurements. The ARIC Study baseline cohort results. Atherosclerosis Risk in Communities Study. Int J Obes Relat Metab Disord 1995; 19: 449-57.

PubMed ID: 8520633
Reference 23 CLOSECLOSE

Han TS and Lean ME. Self-reported waist circumference compared with the ‘Waist Watcher’ tape-measure to identify individuals at increased health risk through intra-abdominal fat accumulation. Br J Nutr 1998; 80: 81-8.

PubMed ID: 9797647
Reference 24 CLOSECLOSE

Janssen I, Heymsfield SB, Allison DB, et al. Body mass index and waist circumference independently contribute to the prediction of nonabdominal, abdominal subcutaneous, and visceral fat. Am J Clin Nutr 2002; 75: 683-8.

PubMed ID: 11916754
Reference 25 CLOSECLOSE

Després JP, Prud’homme D, Pouliot MC, et al. Estimation of deep abdominal adipose-tissue accumulation from simple anthropometric measurements in men. Am J Clin Nutr 1991; 54: 471-7.

PubMed ID: 1877502
Reference 26 CLOSECLOSE

Han TS, McNeill G, Seidell JC, et al. Predicting intra-abdominal fatness from anthropometric measures: the influence of stature. Int J Obes Relat Metab Disord 1997; 21: 587-93.

PubMed ID: 9226490
Reference 27 CLOSECLOSE

Ross R, Shaw KD, Rissanen J, et al. Sex differences in lean and adipose tissue distribution by magnetic resonance imaging: anthropometric relationships. Am J Clin Nutr 1994; 59: 1277-85.

PubMed ID: 8198051
Reference 28 CLOSECLOSE

Ross R, Leger L, Morris D, et al. Quantification of adipose tissue by MRI: relationship with anthropometric variables. J Appl Physiol (1985) 1992; 72: 787-95.

PubMed ID: 1559959
Reference 29 CLOSECLOSE

Seidell JC, Björntorp P, Sjöström L, et al. Regional distribution of muscle and fat mass in men–new insight into the risk of abdominal obesity using computed tomography. Int J Obes 1989; 13: 289-303.

PubMed ID: 2767882
Reference 30 CLOSECLOSE

Nazare JA, Smith J, Borel AL, et al. Usefulness of measuring both body mass index and waist circumference for the estimation of visceral adiposity and related cardiometabolic risk profile (from the INSPIRE ME IAA study). Am J Cardiol 2015; 115: 307-15.

PubMed ID: 25499404
Reference 31 CLOSECLOSE

Carr DB, Utzschneider KM, Hull RL, et al. Intra-abdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome. Diabetes 2004; 53: 2087-94.

PubMed ID: 15277390
Reference 32 CLOSECLOSE

Kuk JL, Nichaman MZ, Church TS, et al. Liver fat is not a marker of metabolic risk in lean premenopausal women. Metabolism 2004; 53: 1066-71.

PubMed ID: 15281020
Reference 33 CLOSECLOSE

Goodpaster BH, Krishnaswami S, Harris TB, et al. Obesity, regional body fat distribution, and the metabolic syndrome in older men and women. Arch Intern Med 2005; 165: 777-83.

PubMed ID: 15824297
Reference 34 CLOSECLOSE

Boyko EJ, Fujimoto WY, Leonetti DL, et al. Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans. Diabetes Care 2000; 23: 465-71.

PubMed ID: 10857936
Reference 35 CLOSECLOSE

Kuk JL, Katzmarzyk PT, Nichaman MZ, et al. Visceral fat is an independent predictor of all-cause mortality in men. Obes Res 2006; 14: 336-41.

PubMed ID: 16571861
Reference 36 CLOSECLOSE

Kuk JL, Lee S, Heymsfield SB, et al. Waist circumference and abdominal adipose tissue distribution: influence of age and sex. Am J Clin Nutr 2005; 81: 1330-4.

PubMed ID: 15941883
Reference 37 CLOSECLOSE

Janssen I, Katzmarzyk PT, Ross R, et al. Fitness alters the associations of BMI and waist circumference with total and abdominal fat. Obes Res 2004; 12: 525-37.

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