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  • Original Article
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Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity

Abstract

Context:

Body mass index (BMI) is widely used as a measure of overweight and obesity, but underestimates the prevalence of both conditions, defined as an excess of body fat.

Objective:

We assessed the degree of misclassification on the diagnosis of obesity using BMI as compared with direct body fat percentage (BF%) determination and compared the cardiovascular and metabolic risk of non-obese and obese BMI-classified subjects with similar BF%.

Design:

We performed a cross-sectional study.

Subjects:

A total of 6123 (924 lean, 1637 overweight and 3562 obese classified according to BMI) Caucasian subjects (69% females), aged 18–80 years.

Methods:

BMI, BF% determined by air displacement plethysmography and well-established blood markers of insulin sensitivity, lipid profile and cardiovascular risk were measured.

Results:

We found that 29% of subjects classified as lean and 80% of individuals classified as overweight according to BMI had a BF% within the obesity range. Importantly, the levels of cardiometabolic risk factors, such as C-reactive protein, were higher in lean and overweight BMI-classified subjects with BF% within the obesity range (men 4.3±9.2, women 4.9±19.5 mg l−1) as well as in obese BMI-classified individuals (men 4.2±5.5, women 5.1±13.2 mg l−1) compared with lean volunteers with normal body fat amounts (men 0.9±0.5, women 2.1±2.6 mg l−1; P<0.001 for both genders).

Conclusion:

Given the elevated concentrations of cardiometabolic risk factors reported herein in non-obese individuals according to BMI but obese based on body fat, the inclusion of body composition measurements together with morbidity evaluation in the routine medical practice both for the diagnosis and the decision-making for instauration of the most appropriate treatment of obesity is desirable.

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References

  1. Haslam D, James WPT . Obesity. Lancet 2005; 366: 1197–1209.

    Article  Google Scholar 

  2. Frühbeck G, Diez-Caballero A, Gómez-Ambrosi J, Cienfuegos JA, Salvador J . Preventing obesity. Doctors underestimate obesity. BMJ 2003; 326: 102–103.

    Article  Google Scholar 

  3. Frühbeck G . Screening and interventions for obesity in adults. Ann Intern Med 2004; 141: 245–246.

    Article  Google Scholar 

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

    Google Scholar 

  5. World Health Organization. Obesity. Preventing and managing the global epidemic. Report of a WHO consultation on obesity. WHO/NUT/NCD/981. WHO: Geneva, 1998.

  6. US Preventive Services Task Force. Screening for obesity in adults: recommendations and rationale. Ann Intern Med 2003; 139: 930–932.

    Article  Google Scholar 

  7. International Obesity Task Force. 2009. Available: http://www.iotf.org.

  8. Flegal KM, Shepherd JA, Looker AC, Graubard BI, Borrud LG, Ogden CL et al. Comparisons of percentage body fat, body mass index, waist circumference, and waist-stature ratio in adults. Am J Clin Nutr 2009; 89: 500–508.

    Article  CAS  Google Scholar 

  9. Jackson AS, Stanforth PR, Gagnon J, Rankinen T, Leon AS, Rao DC et al. The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study. Int J Obes Relat Metab Disord 2002; 26: 789–796.

    Article  CAS  Google Scholar 

  10. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004; 363: 157–163.

    Article  Google Scholar 

  11. Goh VH, Tain CF, Tong TY, Mok HP, Wong MT . Are BMI and other anthropometric measures appropriate as indices for obesity? A study in an Asian population. J Lipid Res 2004; 45: 1892–1898.

    Article  CAS  Google Scholar 

  12. Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y . Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr 2000; 72: 694–701.

    Article  CAS  Google Scholar 

  13. Frankenfield DC, Rowe WA, Cooney RN, Smith JS, Becker D . Limits of body mass index to detect obesity and predict body composition. Nutrition 2001; 17: 26–30.

    Article  CAS  Google Scholar 

  14. Kyle UG, Schutz Y, Dupertuis YM, Pichard C . Body composition interpretation. Contributions of the fat-free mass index and the body fat mass index. Nutrition 2003; 19: 597–604.

    Article  Google Scholar 

  15. 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 2008; 32: 959–966.

    Article  CAS  Google Scholar 

  16. Rothman KJ . BMI-related errors in the measurement of obesity. Int J Obes 2008; 32 (Suppl 3): S56–S59.

    Article  Google Scholar 

  17. Prentice AM, Jebb SA . Beyond body mass index. Obes Rev 2001; 2: 141–147.

    Article  CAS  Google Scholar 

  18. Sharma AM, Kushner RF . A proposed clinical staging system for obesity. Int J Obes 2009; 33: 289–295.

    Article  CAS  Google Scholar 

  19. Pou KM, Massaro JM, Hoffmann U, Lieb K, Vasan RS, O′Donnell CJ et al. Patterns of abdominal fat distribution: the Framingham Heart Study. Diabetes Care 2009; 32: 481–485.

    Article  Google Scholar 

  20. 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: 737–746.

    Article  Google Scholar 

  21. Okorodudu DO, Jumean MF, Montori VM, Romero-Corral A, Somers VK, Erwin PJ et al. Diagnostic performance of body mass index to identify obesity as defined by body adiposity: a systematic review and meta-analysis. Int J Obes 2010; 34: 791–799.

    Article  CAS  Google Scholar 

  22. Poirier P, Giles TD, Bray GA, Hong Y, Stern JS, Pi-Sunyer FX et al. Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss: an update of the 1997 American Heart Association Scientific Statement on Obesity and Heart Disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation 2006; 113: 898–918.

    Article  Google Scholar 

  23. Van Gaal LF, Mertens IL, De Block CE . Mechanisms linking obesity with cardiovascular disease. Nature 2006; 444: 875–880.

    Article  CAS  Google Scholar 

  24. Kahn SE, Hull RL, Utzschneider KM . Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 2006; 444: 840–846.

    Article  CAS  Google Scholar 

  25. Sullivan PW, Ghushchyan V, Wyatt HR, Wu EQ, Hill JO . Impact of cardiometabolic risk factor clusters on health-related quality of life in the US. Obesity 2007; 15: 511–521.

    Article  Google Scholar 

  26. Pischon T, Boeing H, Hoffmann K, Bergmann M, Schulze MB, Overvad K et al. General and abdominal adiposity and risk of death in Europe. N Engl J Med 2008; 359: 2105–2120.

    Article  CAS  Google Scholar 

  27. Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P et al. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet 2005; 366: 1640–1649.

    Article  Google Scholar 

  28. Balkau B, Deanfield JE, Després JP, Bassand JP, Fox KAA, Smith JS et al. International Day for the Evaluation of Abdominal obesity (IDEA). A study of waist circumference, cardiovascular disease, and diabetes mellitus in 168 000 primary care patients in 63 countries. Circulation 2007; 116: 1942–1951.

    Article  Google Scholar 

  29. Segal KR, Dunaif A, Gutin B, Albu J, Nyman A, Pi-Sunyer FX . Body composition, not body weight, is related to cardiovascular disease risk factors and sex hormone levels in men. J Clin Invest 1987; 80: 1050–1055.

    Article  CAS  Google Scholar 

  30. Gómez-Ambrosi J, Salvador J, Páramo JA, Orbe J, de Irala J, Diez-Caballero A et al. Involvement of leptin in the association between percentage of body fat and cardiovascular risk factors. Clin Biochem 2002; 35: 315–320.

    Article  Google Scholar 

  31. Catalán V, Gómez-Ambrosi J, Ramírez B, Rotellar F, Pastor C, Silva C et al. Proinflammatory cytokines in obesity: impact of type 2 diabetes mellitus and gastric bypass. Obes Surg 2007; 17: 1464–1474.

    Article  Google Scholar 

  32. 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: 413–417.

    Article  CAS  Google Scholar 

  33. Heitmann BL, Erikson H, Ellsinger BM, Mikkelsen KL, Larsson B . Mortality associated with body fat, fat-free mass and body mass index among 60-year-old Swedish men-a 22-year follow-up. The study of men born in 1913. Int J Obes Relat Metab Disord 2000; 24: 33–37.

    Article  CAS  Google Scholar 

  34. Lahmann PH, Lissner L, Gullberg B, Berglund G . A prospective study of adiposity and all-cause mortality: the Malmö Diet and Cancer Study. Obes Res 2002; 10: 361–369.

    Article  Google Scholar 

  35. Bigaard J, Frederiksen K, Tjonneland A, Thomsen BL, Overvad K, Heitmann BL et al. Body fat and fat-free mass and all-cause mortality. Obes Res 2004; 12: 1042–1049.

    Article  Google Scholar 

  36. Flegal KM, Graubard BI . Estimates of excess deaths associated with body mass index and other anthropometric variables. Am J Clin Nutr 2009; 89: 1213–1219.

    Article  CAS  Google Scholar 

  37. Pietrobelli A, Heymsfield SB . Establishing body composition in obesity. J Endocrinol Invest 2002; 25: 884–892.

    Article  CAS  Google Scholar 

  38. Das SK . Body composition measurement in severe obesity. Curr Opin Clin Nutr Metab Care 2005; 8: 602–606.

    Article  Google Scholar 

  39. Fields DA, Goran MI, McCrory MA . Body-composition assessment via air-displacement plethysmography in adults and children: A review. Am J Clin Nutr 2002; 75: 453–467.

    Article  CAS  Google Scholar 

  40. Ginde SR, Geliebter A, Rubiano F, Silva AM, Wang J, Heshka S et al. Air displacement plethysmography: validation in overweight and obese subjects. Obes Res 2005; 13: 1232–1237.

    Article  Google Scholar 

  41. Gómez-Ambrosi J, Salvador J, Silva C, Pastor C, Rotellar F, Gil MJ et al. Increased cardiovascular risk markers in obesity are associated with body adiposity: Role of leptin. Thromb Haemost 2006; 95: 991–996.

    Article  Google Scholar 

  42. Romero-Corral A, Somers VK, Sierra-Johnson J, Jensen MD, Thomas RJ, Squires RW et al. Diagnostic performance of body mass index to detect obesity in patients with coronary artery disease. Eur Heart J 2007; 28: 2087–2093.

    Article  Google Scholar 

  43. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and international association for the Study of Obesity. Circulation 2009; 120: 1640–1645.

    Article  CAS  Google Scholar 

  44. Siri WE . Body composition from fluid spaces and density: analysis of methods. In: Brozek J, Henschel A (eds). Techniques for Measuring Body Composition. National Academy of Sciences, National Research Council: Washington, DC, USA, 1961, pp 223–243.

    Google Scholar 

  45. Deurenberg P, Andreoli A, Borg P, Kukkonen-Harjula K, de Lorenzo A, van Marken Lichtenbelt WD et al. The validity of predicted body fat percentage from body mass index and from impedance in samples of five European populations. Eur J Clin Nutr 2001; 55: 973–979.

    Article  CAS  Google Scholar 

  46. De Lorenzo A, Deurenberg P, Pietrantuono M, Di Daniele N, Cervelli V, Andreoli A . How fat is obese? Acta Diabetol 2003; 40 (Suppl 1): S254–S257.

    Article  Google Scholar 

  47. Bosy-Westphal A, Geisler C, Onur S, Korth O, Selberg O, Schrezenmeir J et al. Value of body fat mass vs anthropometric obesity indices in the assessment of metabolic risk factors. Int J Obes 2006; 30: 475–483.

    Article  CAS  Google Scholar 

  48. Wellens RI, Roche AF, Khamis HJ, Jackson AS, Pollock ML, Siervogel RM . Relationships between the body mass index and body composition. Obes Res 1996; 4: 35–44.

    Article  CAS  Google Scholar 

  49. Gómez-Ambrosi J, Salvador J, Rotellar F, Silva C, Catalán V, Rodríguez A et al. Increased serum amyloid A concentrations in morbid obesity decrease after gastric bypass. Obes Surg 2006; 16: 262–269.

    Article  Google Scholar 

  50. Gómez-Ambrosi J, Catalán V, Ramírez B, Rodríguez A, Colina I, Silva C et al. Plasma osteopontin levels and expression in adipose tissue are increased in obesity. J Clin Endocrinol Metab 2007; 92: 3719–3727.

    Article  Google Scholar 

  51. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC . Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412–419.

    Article  CAS  Google Scholar 

  52. Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon III RO, Criqui M et al. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: a statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003; 107: 499–511.

    Article  Google Scholar 

  53. De Lorenzo A, Del Gobbo V, Premrov MG, Bigioni M, Galvano F, Di Renzo L . Normal-weight obese syndrome: early inflammation? Am J Clin Nutr 2007; 85: 40–45.

    Article  CAS  Google Scholar 

  54. Wildman RP, Muntner P, Reynolds K, McGinn AP, Rajpathak S, Wylie-Rosett J et al. The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering: prevalence and correlates of 2 phenotypes among the US population (NHANES 1999–2004). Arch Intern Med 2008; 168: 1617–1624.

    Article  Google Scholar 

  55. Thomas GN, Ho SY, Lam KS, Janus ED, Hedley AJ, Lam TH . Impact of obesity and body fat distribution on cardiovascular risk factors in Hong Kong Chinese. Obes Res 2004; 12: 1805–1813.

    Article  Google Scholar 

  56. Shen W, Punyanitya M, Chen J, Gallagher D, Albu J, Pi-Sunyer X et al. Waist circumference correlates with metabolic syndrome indicators better than percentage fat. Obesity 2006; 14: 727–736.

    Article  Google Scholar 

  57. Rattarasarn C, Leelawattana R, Soonthornpun S, Setasuban W, Thamprasit A, Lim A et al. Relationships of body fat distribution, insulin sensitivity and cardiovascular risk factors in lean, healthy non-diabetic Thai men and women. Diabetes Res Clin Pract 2003; 60: 87–94.

    Article  CAS  Google Scholar 

  58. Deurenberg P, Yap M, van Staveren WA . Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes Relat Metab Disord 1998; 22: 1164–1171.

    Article  CAS  Google Scholar 

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Acknowledgements

This study was supported by grants from the ISCIII (FIS PI061458, PS09/02330 and PI09/91029) and the Departments of Health (20/2005 and 31/2009) and Education of the Gobierno de Navarra. CIBER de Fisiopatología de la Obesidad y Nutrición (CIBERobn) is an initiative of the ISCIII, Spain.

Trial registration: ClinicalTrials.gov NCT01055626.

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Correspondence to G Frühbeck.

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Gómez-Ambrosi, J., Silva, C., Galofré, J. et al. Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. Int J Obes 36, 286–294 (2012). https://doi.org/10.1038/ijo.2011.100

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