The estimation of visceral adipose tissue with a body composition monitor predicts the metabolic syndrome.

BACKGROUND: Central obesity has a higher risk of the metabolic syndrome (MetS) and cardiovascular diseases. It is estimated by measuring waist circumference (WC) and waist-to-hip ratio (WHR), which are operator-dependent. The present study aimed to validate a body composition monitor (BCM) as a tool for estimating visceral adipose tissue (VAT), as well as to assess its capacity to predict the MetS and its correlation with anthropometric parameters.

METHODS: We measured WC, WHR and body mass index (BMI) in 60 recruited subjects. BCM estimated VAT (1-30 points). Body composition and resting energy expenditure (REE) were compared with bioelectrical impedance analysis (BIA) and indirect calorimetry, respectively. VAT was estimated by BCM (range 1-30 points), We evaluated the capability of VAT, WC, BMI and WHR to predict the MetS by ATP-III criteria.

RESULTS: The mean (SD) age of subjects was 36.8 (12.9) years, 80% were female, and 47% had the MetS. Body composition and REE estimated by BCM had a significant correlation with BIA (r = 0.85-0.91, P< 0.001) and REE (r = 0.86, P < 0.001), respectively, even after adjusting by sex. VAT estimation by BCM was positively correlated with WC (r = 0.75, P< 0.001) and WHR (r = 0.61, P < 0.001). The area under the receiver operator characteristic curves to predict the MetS was 0.93 for VAT, 0.81 for WC, 0.76 for WHR and 0.74 for BMI. VAT ≥10 points had a sensitivity of 100% and a specificity of 82% for predicting the MetS.

CONCLUSIONS: VAT estimation by BCM efficiently predicts the MetS and correlates with anthropometric parameters of central obesity. Its routine use could facilitate cardiovascular risk estimation and follow-up in overweight and obese patients in ambulatory practice.