Evaluating CMR

Clinical Tools

Waist Circumference

Key Points


  • Waist circumference is an important predictor of health risk.
  • Waist circumference should be measured at the top of the iliac crest.
  • Waist circumference is the best anthropometric measure of intra-abdominal fat and changes to it.

Waist Circumference and Health Risk


Jean Vague was the first to recognize the harmful health consequences of excess abdominal fat over 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 (6-9)


Health-related Waist Circumference Cut-offs


Abdominal obesity is commonly 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. Current Canadian clinical practice guidelines and the National Institutes of Health (NIH) in the United States recommend measuring waist circumference using the iliac crest as the landmark (10, 11). Accordingly, the International Chair on Cardiometabolic Risk also recommends measuring waist circumference at the top of the iliac crest. The NIH has published sex-specific waist circumference thresholds (men: 102 cm, women: 88 cm) to denote increased health risk within each BMI category (11). 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. These waist circumference thresholds seem appropriate for non-Hispanic blacks and Mexican Americans (12), but are likely too high for most Asian populations (13) and are unknown for 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). For instance, the International Diabetes Federation position statement on the metabolic syndrome and its clinical diagnosis has lowered waist girth values to 94 cm for European men, while recognizing the need to propose cut-offs specific to various ethnic populations.

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). Moreover, high waist circumference predicts a later decline in insulin sensitivity over a 5 year follow-up (7). It has also been reported that once waist circumference is taken into account, BMI does not provide any added information in terms of predicting metabolic risk (8). For these reasons, it is important to measure waist circumference when assessing health risk. 


Measuring Waist Circumference—Health Care Professionals


Measure waist circumference with the measuring tape directly on the individual’s skin (Figure 1). Ask the individual 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 (14, 15). 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.


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 (16). 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.
 


Association Between Waist Circumference and Intra-abdominal 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 intra-abdominal fat. Subcutaneous fat lies just below the skin and is outside the abdominal muscle wall, whereas intra-abdominal (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 intra-abdominal fat. Indeed, waist circumference is a stronger predictor of intra-abdominal fat than BMI (17-23). Because intra-abdominal fat is a strong independent predictor of morbidity (24-27) and mortality (28), considerable attention has been given to the ability of waist circumference to predict intra-abdominal fat.

Previous studies have reported that the percentage of error for estimates of intra-abdominal fat using waist circumference is roughly 25 to 35% (18-21). Factors such as age, gender, race, and fitness partly explain the variation in the amount of intra-abdominal fat for a given waist circumference (29-31). These differences in the amount of intra-abdominal 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 intra-abdominal fat than Caucasian women and 35% more intra-abdominal fat than African American women with the same waist circumference (31).

Age is another factor that greatly influences the amount of intra-abdominal 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 intra-abdominal fat than a 25 year old man with the same waist circumference, and 140% more intra-abdominal fat than a 25 year old woman (29) (Figure 4). However, how these differences translate into specific waist circumference cut-offs for various populations is unclear.


Association Between Changes in Waist Circumference and Intra-abdominal Fat


Waist circumference is also commonly used to assess changes in abdominal obesity, and is a stronger predictor of changes in intra-abdominal fat than waist-to-hip ratio (23, 32, 33). Changes in waist circumference are associated with changes in intra-abdominal fat in response to diet and/or exercise-induced weight loss (Figure 5) (23, 32-34). Although the exact amount of intra-abdominal fat loss for a given reduction in waist circumference varies considerably (33), reductions in waist circumference are likely to reduce intra-abdominal fat. Exercise can often reduce intra-abdominal fat and waist circumference, even if it does not reduce body weight significantly (35-40). Accordingly, waist circumference should be measured as part of interventions aimed at reducing intra-abdominal fat and related health risk.

Waist circumference is a strong predictor of health risk beyond that explained by BMI alone. This may be partly due to the strong ties between waist circumference and intra-abdominal fat. Indeed, waist circumference is the strongest anthropometric predictor of intra-abdominal 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.


References


  1. Vague J. La differenciation sexuelle, facteur determinant des formes de l'obesite. La Presse Medicale 1947; 30: 339-40.
  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.
  3. Rexrode KM, Carey VJ, Hennekens CH, et al. Abdominal adiposity and coronary heart disease in women. JAMA 1998; 280: 1843-8.
  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.
  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.
  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.
  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.
  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.
  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.
  10. Lau DC, Douketis JD, Morrison KM, et al. 2006 Canadian clinical practice guidelines on the management and prevention of obesity in adults and children. CMAJ 2007; 176: S1-117.
  11. 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.
  12. 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.
  13. Alberti KG, Zimmet P and Shaw J. The metabolic syndrome--a new worldwide definition. Lancet 2005; 366: 1059-62.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. Ross R, Leger L, Morris D, et al. Quantification of adipose tissue by MRI: relationship with anthropometric variables. J Appl Physiol 1992; 72: 787-95.
  22. Seidell JC, Bjorntorp P, Sjostrom 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. Kuk JL, Katzmarzyk PT, Nichaman MZ, et al. Visceral Fat is an Independent Predictor of All-Cause Mortality in Men. Obes Res In Press.
  29. 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.
  30. 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.
  31. Araneta MRG and Barrett-Connor E. Ethnic Differences in Visceral Adipose Tissue and Type 2 Diabetes: Filipino, African-American, and White Women. Obesity Res 2005; 13: 1458-65.
  32. 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.
  33. 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.
  34. Ross R. Effects of diet- and exercise-induced weight loss on visceral adipose tissue in men and women. Sports Med 1997; 24: 55-64.
  35. 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.
  36. 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.
  37. 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 2005; 99: 1220-5.
  38. 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.
  39. 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.
  40. 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.

Reference
Previous Reference
Next Reference
1. Vague J. La differenciation sexuelle, facteur determinant des formes de l'obesite. La Presse Medicale 1947; 30: 339-40.
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.
3. Rexrode KM, Carey VJ, Hennekens CH, et al. Abdominal adiposity and coronary heart disease in women. JAMA 1998; 280: 1843-8.
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.
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.
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.
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.
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.
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.
10. Lau DC, Douketis JD, Morrison KM, et al. 2006 Canadian clinical practice guidelines on the management and prevention of obesity in adults and children. CMAJ 2007; 176: S1-117.
11. 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.
12. 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.
13. Alberti KG, Zimmet P and Shaw J. The metabolic syndrome--a new worldwide definition. Lancet 2005; 366: 1059-62.
14. 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.
15. 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.
16. 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.
17. 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.
18. 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.
19. 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.
20. 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.
21. Ross R, Leger L, Morris D, et al. Quantification of adipose tissue by MRI: relationship with anthropometric variables. J Appl Physiol 1992; 72: 787-95.
22. Seidell JC, Bjorntorp P, Sjostrom 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.
23. 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.
24. 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.
25. 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.
26. 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.
27. 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.
28. Kuk JL, Katzmarzyk PT, Nichaman MZ, et al. Visceral Fat is an Independent Predictor of All-Cause Mortality in Men. Obes Res In Press.
29. 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.
30. 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.
31. Araneta MRG and Barrett-Connor E. Ethnic Differences in Visceral Adipose Tissue and Type 2 Diabetes: Filipino, African-American, and White Women. Obesity Res 2005; 13: 1458-65.
32. 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.
33. 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.
34. Ross R. Effects of diet- and exercise-induced weight loss on visceral adipose tissue in men and women. Sports Med 1997; 24: 55-64.
35. 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.
36. 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.
37. 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 2005; 99: 1220-5.
38. 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.
39. 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.
40. 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.