Background:The measurement of adipose tissue (AT) depots in vivo requires expensive imaging methods not accessible to most clinicians and researchers. The study aim was to derive mathematical models to predict total AT (TAT) and subdepots from total body fat derived from a dual-energy X-ray absorptiometry (DXA) scan.Methods:Models were developed to predict magnetic resonance imaging-derived TAT and subdepots subcutaneous AT, visceral AT, and intermuscular AT from DXA total body fat (Fat DXA) using cross-sectional data (time 0 (T0)) and validated results using 1 (T1) and 2 (T2) y follow-up data. Subjects were 176 multiethnic healthy children ages 5-17 y at T0. Twenty-two were measured at T1 and T2. TAT was compared with Fat DXA.Results:At T0, TAT was greater than Fat DXA (12.5 ± 8.4 vs.12.0 ± 9.4 kg; P 0.0001), with a quadratic relationship between TAT and Fat DXA that varied by sex. Predicted mean TATs were not different from measured TATs: T1: (9.84 ± 4.45 kg vs. 9.50 ± 4.37 kg; P = 0.11); T2: (12.94 ± 6.75 kg vs. 12.89 ± 7.09 kg; P = 0.76). The quadratic relationship was not influenced by race or age.Conclusion:In general, the prediction equations for TAT and subdepots were consistent with the measured values using T1 and T2 data.