Which Obesity Indicators Are Better Predictors of Metabolic Risk?: Healthy Twin Study

No consensus exists as to the most sensitive and specific obesity indicator associated with metabolic risk factors. We aimed to validate anthropometry as the predictor for obesity‐related metabolic risk factors through comparison with direct body composition measures in Korean adults. A total of 995 Korean women and 577 Korean men who participated in the Healthy Twin study were the subjects. Anthropometric measurements included BMI, waist circumference (WC), waist‐to‐hip ratio (WHR), and waist‐to‐height ratio (WHTR). Direct body composition measures included the percentage of body fat (%BF) measured using dual‐energy X‐ray absorptiometry scanners and bioelectrical impedance analyzer (BIA). The following criteria were used to define abnormal metabolic risk factors: blood pressure ≥ 130/85 mm Hg, fasting glucose (≥ 100 mg/dl), insulin (≥ 25 μU/ml), homeostasis model assessment (HOMA) (≥ 2.61), high‐density lipoprotein (HDL) (<40 mg/dl for men or <50 mg/dl for women), triacylglycerol (≥ 150 mg/dl), uric acid (>7 mg/dl for men or >6 mg/dl for women), high‐sensitivity C‐reactive protein (hs‐CRP) (≥ 2.11 mg/l). In multiple regression analyses (adjusted for age, education, smoking, alcohol, exercise and past/current medical history, and treated families as a random effect), WC, WHTR, and BMI were consistently associated with all metabolic risk factors regardless of the subject's gender. Some of the areas under the receiver‐operating characteristic curves regarding abnormal metabolic risk factors were significantly higher for the three indicators of central obesity than for %BF. Our study validates the usefulness of anthropometry over direct body fat measures to predict metabolic risks.

[1]  Sung-il Cho,et al.  Healthy Twin: a twin-family study of Korea--protocols and current status. , 2006, Twin research and human genetics : the official journal of the International Society for Twin Studies.

[2]  M. Ashwell,et al.  Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity , 2005, International journal of food sciences and nutrition.

[3]  T. Muto,et al.  Metabolic syndrome in Japanese men and women with special reference to the anthropometric criteria for the assessment of obesity: Proposal to use the waist-to-height ratio. , 2006, Preventive medicine.

[4]  W. Gulliver,et al.  Comparison of multifrequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for assessment of percentage body fat in a large, healthy population. , 2005, The American journal of clinical nutrition.

[5]  T. Lam,et al.  Waist to stature ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices. , 2003, Annals of epidemiology.

[6]  W. Ahrens,et al.  Multicenter case-control study of exposure to environmental tobacco smoke and lung cancer in Europe. , 1998, Journal of the National Cancer Institute.

[7]  S. Grundy,et al.  National Cholesterol Education Program Third Report of the National Cholesterol Education Program ( NCEP ) Expert Panel on Detection , Evaluation , and Treatment of High Blood Cholesterol in Adults ( Adult Treatment Panel III ) Final Report , 2022 .

[8]  J. Schrezenmeir,et al.  Value of body fat mass vs anthropometric obesity indices in the assessment of metabolic risk factors , 2006, International Journal of Obesity.

[9]  T Muto,et al.  Waist-to-height ratio, a simple and practical index for assessing central fat distribution and metabolic risk in Japanese men and women , 2003, International Journal of Obesity.

[10]  E. Janus,et al.  Association between simple anthropometric indices and cardiovascular risk factors , 2001, International Journal of Obesity.

[11]  T. Muto,et al.  The superiority of waist-to-height ratio as an anthropometric index to evaluate clustering of coronary risk factors among non-obese men and women. , 2005, Preventive medicine.

[12]  Winfried März,et al.  Accuracy of anthropometric indicators of obesity to predict cardiovascular risk. , 2007, The Journal of clinical endocrinology and metabolism.

[13]  H. Kahn Obesity and risk of myocardial infarction: the INTERHEART study , 2006, The Lancet.

[14]  Paul Zimmet,et al.  [A new international diabetes federation worldwide definition of the metabolic syndrome: the rationale and the results]. , 2005, Revista espanola de cardiologia.

[15]  Fernando Costa,et al.  Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute scientific statement. , 2006, Current opinion in cardiology.

[16]  P. Deurenberg,et al.  Body mass index and percent body fat: a meta analysis among different ethnic groups , 1998, International Journal of Obesity.

[17]  H. Mabuchi,et al.  The relationship of percent body fat by bioelectrical impedance analysis with blood pressure, and glucose and lipid parameters. , 2006, Journal of atherosclerosis and thrombosis.

[18]  R B Mazess,et al.  Dual-energy x-ray absorptiometry for total-body and regional bone-mineral and soft-tissue composition. , 1990, The American journal of clinical nutrition.

[19]  J. Aldrighi,et al.  Relationship of body fat distribution by waist circumference, dual-energy X-ray absorptiometry and ultrasonography to insulin resistance by homeostasis model assessment and lipid profile in obese and non-obese postmenopausal women , 2005, Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology.

[20]  P. Zimmet,et al.  Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus. Provisional report of a WHO Consultation , 1998, Diabetic medicine : a journal of the British Diabetic Association.

[21]  J. Després,et al.  The association of cardiovascular disease risk factors with abdominal obesity in Canada. Canadian Heart Health Surveys Research Group. , 1997, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

[22]  D. English,et al.  A Comparison of Adiposity Measures as Predictors of All‐cause Mortality: The Melbourne Collaborative Cohort Study , 2007, Obesity.

[23]  Elizabeth Breeze,et al.  Weight, shape, and mortality risk in older persons: elevated waist-hip ratio, not high body mass index, is associated with a greater risk of death. , 2006, The American journal of clinical nutrition.

[24]  P. Ridker,et al.  Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men. , 1997, The New England journal of medicine.

[25]  R. Andres,et al.  Differences in the relationship between lipid CHD risk factors and body composition in Caucasians and Japanese , 2005, International Journal of Obesity.

[26]  K. Suzuki,et al.  Associations of body mass index and percentage body fat by bioelectrical impedance analysis with cardiovascular risk factors in Japanese male office workers. , 2000, Industrial health.

[27]  M. Kawai,et al.  Body mass index (weight/height2) or percentage body fat by bioelectrical impedance analysis: which variable better reflects serum lipid profile? , 1999, International Journal of Obesity.

[28]  A. Barnett,et al.  Association of simple anthropometric measures of obesity with visceral fat and the metabolic syndrome in male Caucasian and Indo‐Asian subjects , 2004, Diabetic medicine : a journal of the British Diabetic Association.

[29]  Walter C Willett,et al.  Comparison of abdominal adiposity and overall obesity in predicting risk of type 2 diabetes among men. , 2005, The American journal of clinical nutrition.

[30]  J. Mckenney,et al.  National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) , 2002 .

[31]  G. Berglund,et al.  A prospective study of adiposity and all-cause mortality: the Malmö Diet and Cancer Study. , 2002, Obesity research.

[32]  M. Tenhunen-Eskelinen,et al.  Relationship of metabolic variables to abdominal adiposity measured by different anthropometric measurements and dual-energy X-ray absorptiometry in obese middle-aged women , 1997, International Journal of Obesity.

[33]  K. Jablonski,et al.  Effects of obesity and body fat distribution on lipids and lipoproteins in nondiabetic American Indians: The Strong Heart Study. , 2000, Obesity research.

[34]  R. Turner,et al.  Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man , 1985, Diabetologia.

[35]  Jack Wang Waist circumference: a simple, inexpensive, and reliable tool that should be included as part of physical examinations in the doctor's office. , 2003, The American journal of clinical nutrition.