Association of simple anthropometric measures of obesity with visceral fat and the metabolic syndrome in male Caucasian and Indo-Asian subjects.

AIMS

The aims of this study were first, to investigate the relationship between simple anthropometric measures of obesity with visceral fat as assessed by a single slice magnetic resonance imaging (MRI)-scan in patients attending a hospital clinic. Second, to determine which anthropometric measure best relates to the adverse metabolic profile of the metabolic syndrome.

METHODS

Forty-one male subjects [body mass index (BMI): 30.2 + 5.8 kg/m(2), age: 50.3 + 13.6 years] were studied by MRI-scan to measure visceral fat at L4/L5 level and to investigate its relationship with simple anthropometric measures. Second, we studied 83 male subjects to determine which anthropometric measure best predicts the metabolic complications (using the ATPIII criteria) of obesity in the setting of a hospital clinic.

RESULTS

Waist circumference was the best anthropometric measurement that correlated with MRI-visceral fat mass assessed at L4/L5 in 41 subjects who had an MRI scan (P = 0.0001, r(2) = 0.36, beta = 0.56) amongst variables which also included age, BMI, sagittal diameter, diabetes and ethnicity. Stepwise multiple regression analysis showed sagittal diameter (P = 0.001, r(2) = 0.4, beta = 0.406), age (P = 0.003, beta = 0.271) and waist circumference (P = 0.012, beta = 0.297) were the best predictors of the adverse metabolic profile of the metabolic syndrome in all 83 male subjects amongst BMI, waist-hip ratio (WHR), ethnicity and diabetes-related factors.

CONCLUSIONS

Waist circumference is a simple anthropometric parameter that best correlates with single slice MRI-scan, but sagittal diameter (measured using abdominal calipers) better predicts the adverse metabolic profile of the metabolic syndrome. Although there is considerable variation in abdominal fat topography between ethnic groups, and also within populations, sagittal diameter assessment is a technique that is simple and best predicts the metabolic syndrome.