Abstract
OBJECTIVE: MRI is established for measurement of body fat mass (FM) and abdominal visceral adipose tissue (VAT). Anthropometric measurements and bioelectrical impedance analysis (BIA) have been proposed as surrogates to estimation by MRI. Aim of this work is to assess the predictive value of these methods for FM and VAT measured by MRI. METHODS: Patients were selected from cohort study PPS-Diab (prediction, prevention and subclassification of Type 2 diabetes). Total FM and VAT were quantified by MRI and BIA together with clinical variables like age, waist and hip circumference and height. Least-angle regressions were utilized to select anthropometric and BIA parameters for their use in multivariable linear regression models to predict total FM and VAT. Bland-Altman plots, Pearson correlation coefficients, Wilcoxon signed-rank tests and univariate linear regression models were applied. RESULTS: 116 females with 35 ± 3 years and a body mass index of 25.1 ± 5.3 kg/m(2) were included into the analysis. A multivariable model revealed weight (β = 0.516, p < 0.001), height (β = -0.223, p < 0.001) and hip circumference (β = 0.156, p = 0.003) as significantly associated with total FM measured by MRI. A additional multivariable model also showed a significant predictive value of FM(BIA) (β = 0.583, p < 0.001) for FM. In addition, waist circumference (β = 0.054, p < 0.001), weight (β = 0.016, p = 0.031) in one model and FM(BIA) (β = 0.026, p = 0.018) in another model were significantly associated with VAT quantified by MRI. However, deviations reached more than 5 kg for total FM and more than 1 kg for VAT. CONCLUSION: Anthropometric measurements and BIA show significant association with total FM and VAT. ADVANCES IN KNOWLEDGE: As these measurements show significant deviations from the absolute measured values determined by MRI, MRI should be considered the gold-standard for quantification.