Predictive Validity of the Body Adiposity Index in Overweight and Obese Adults Using Dual-Energy X-ray Absorptiometry

Nutrients. 2016 Nov 30;8(12):737. doi: 10.3390/nu8120737.

Abstract

The body adiposity index (BAI) is a recent anthropometric measure proven to be valid in predicting body fat percentage (BF%) in some populations. However, the results have been inconsistent across populations. This study was designed to verify the validity of BAI in predicting BF% in a sample of overweight/obese adults, using dual-energy X-ray absorptiometry (DEXA) as the reference method. A cross-sectional study was conducted in 48 participants (54% women, mean age 41.0 ± 7.3 years old). DEXA was used as the "gold standard" to determine BF%. Pearson's correlation coefficient was used to evaluate the association between BAI and BF%, as assessed by DEXA. A paired sample t-test was used to test differences in mean BF% obtained with BAI and DEXA methods. To evaluate the concordance between BF% as measured by DEXA and as estimated by BAI, we used Lin's concordance correlation coefficient and Bland-Altman agreement analysis. The correlation between BF% obtained by DEXA and that estimated by BAI was r = 0.844, p < 0.001. Paired t-test showed a significant mean difference in BF% between methods (BAI = 33.3 ± 6.2 vs. DEXA 39.0 ± 6.1; p < 0.001). The bias of the BAI was -6.0 ± 3.0 BF% (95% CI = -12.0 to 1.0), indicating that the BAI method significantly underestimated the BF% compared to the reference method. Lin's concordance correlation coefficient was considered stronger (ρc = 0.923, 95% CI = 0.862 to 0.957). In obese adults, BAI presented low agreement with BF% measured by DEXA; therefore, BAI is not recommended for BF% prediction in this overweight/obese sample studied.

Keywords: adults; body composition; obesity; prediction; validity.

Publication types

  • Validation Study

MeSH terms

  • Absorptiometry, Photon*
  • Adiposity / physiology*
  • Adult
  • Female
  • Humans
  • Male
  • Middle Aged
  • Overweight / diagnosis*
  • Predictive Value of Tests
  • Reproducibility of Results