Abstract
Objectives. 1) Examine associations between visceral adipose tissue (VAT), subcutaneous abdominal adipose tissue (SAAT), and anthropometric and demographic variables; 2) generate and cross-validate prediction equations for estimating VAT and SAAT in overweight Latino children. Study design. Cross-sectional. Participants. 196 overweight 8–13-year-old Latino youth. Two-thirds (n = 131) were randomly assigned to a development group to generate prediction equations for VAT and SAAT; one-third (n = 65) was used as a cross-validation group. Methods and procedures. Anthropometric measurements (height, weight, skinfold thicknesses, and circumferences) were performed. VAT and SAAT were measured using magnetic resonance imaging (MRI). Results. The strongest univariate correlate for VAT was waist circumference (WC) (r = 0.65, p < 0.01) while the strongest correlate for SAAT was hip circumference (r = 0.88, p < 0.001). Regression analyses showed ∼50% of the variance in VAT was explained by WC (43.8%), Tanner stage (4.2%) and calf skinfold (1.7%). Variance in the SAAT model was explained by WC (77.8%), triceps skinfold (4.2%) and gender (2.3%). Residual analyses showed no bias in either equation. Though mean differences between measured and predicted VAT and SAAT were small, there was a large degree of variability at the individual level especially for VAT. Conclusions. Both VAT and SAAT prediction equations performed well at the group level, but the relatively high degree of variability suggests limited clinical utility of the VAT equation. MRI is currently required to derive an accurate measure of VAT at the individual level.
The authors would like to thank Ms. Quintilia Avila for study coordination as well as all of the children and families who participated in this research. This study was supported by the National Institutes of Health (R01 DK 59211 and R01 HD/HL 33064) and by the General Clinical Research Center, National Center for Health Resources (M01 RR 00043). GDCB was supported by a Postdoctoral Fellowship from the Canadian Institutes of Health Research and the American Diabetes Association Mentor-Based Postdoctoral Fellowship Grant (awarded to MIG).