Ramírez Vélez, RobinsonCorrea Bautista, Jorge EnriqueGonzález-Ruíz, KatherineVivas, AndrésGarcía Hermoso, AntonioTriana Reina, Héctor Reynaldo2024-10-012024-10-012016Ramírez-Vélez, R., Correa-Bautista, J. E., González-Ruíz, K., Vivas, A., García-Hermoso, A., Triana-Reina, H. R. (2016) Predictive validity of the body adiposity index in overweight and obese adults using dual-energy X-ray absorptiometry. Nutrients, 8(12), 1-11. https://doi.org/10.3390/nu81207372072-664310.3390/nu8120737https://academica-e.unavarra.es/handle/2454/51917The 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 (rc = 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.application/pdfeng© 2016 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.AdultsBody compositionObesityPredictionValidityinfo:eu-repo/semantics/article2024-10-01info:eu-repo/semantics/openAccess