Self-Reported Physical Activity Improves Prediction of Body Fatness in Young Adults

Abstract

To examine self-reported physical activity levels from the International Physical Activity Questionnaire (IPAQ) as an independent predictor of dual-energy x-ray absorptiometry (DXA)-measured percent body fat (%BF) from body mass index (BMI), gender, and race. Two hundred and seventy-eight students, aged 18-24 yr, volunteered to participate. There were 133 males (85 white and 48 black) and 145 females (77 white and 68 black). Total activity levels were quantified in MET hours per week (MET h wk(-1)) using the IPAQ short form. Height and weight were measured, and BMI values were calculated (kg m(-2)). %BF was assessed using DXA. Linear regression analysis was used to develop and compare a body fat prediction equation with (full) and without (reduced) the variable MET-h.wk. Both models included BMI, gender, and race as predictor variables. The prediction sum of squares (PRESS) statistic was used to cross-validate both models, and the individual predictive accuracy was compared using modified Bland-Altman plots. Mean +/- SD values were as follows: BMI = 24.4 +/- 4.1 kg m(-2), %BF = 24.5 +/- 9.3%, and MET h wk(-1) = 37.4 +/- 21.9. Gender, BMI, and race explained 81% of the variance in %BF, with a root mean square error (RMSE) of 4.07. The full model with MET-h.wk improved the prediction of %BF by 2% (R2 = 0.83, RMSE = 3.87). When cross-validated, the corresponding PRESS statistics for the reduced and full model were 4.10 and 3.90, respectively. Bland-Altman limits of agreement were greater for the reduced model compared with the full model (-8.09, 8.10 vs -7.67, 7.68). These results suggest that %BF can be predicted with greater precision and accuracy in a young adult population when MET-h.wk are included in addition to BMI, gender, and race.