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Performance of Body Adiposity Index and Relative Fat Mass in Predicting Bioelectric Impedance Analysis-Derived Body Fat Percentage: A Cross-Sectional Study among Patients with Type 2 Diabetes in the Ho Municipality, Ghana. | LitMetric

AI Article Synopsis

  • The study aimed to evaluate how accurately body adiposity index (BAI) and relative fat mass (RFM) can estimate body fat percentage (BFP) in patients with type 2 diabetes in Ho municipality, involving 236 patients.
  • Results indicated that while BAI had some bias in both genders, RFM showed high predictive accuracy for females, and both measures had limitations in overall agreement with BFP.
  • The optimal cut-off values and diagnostic metrics (sensitivity, specificity) for both BAI and RFM varied between genders, with females showing better accuracy in distinguishing BFP levels compared to males.

Article Abstract

Objective: The study sought to determine the diagnostic accuracy of body adiposity index (BAI) and relative fat mass (RFM) to predict BIA-derived BFP among patients with type 2 diabetes in the Ho municipality. . This hospital-based cross-sectional study involved 236 patients with type 2 diabetes. Demographic data, including age and gender were obtained. Height, waist circumference (WC), and hip circumference (HC) were measured using standard methods. BFP was estimated on a bioelectrical impedance analysis (BIA) scale. The validity of BAI and RFM as alternative estimates for BIA-derived BFP was evaluated based on mean absolute percentage error (MAPE), Passing-Bablok regression, Bland-Altman plots, receiver-operating characteristic curve (ROC), and kappa statistics analyses. A value less than 0.05 was considered statistically significant.

Results: BAI showed systematic bias in estimating BIA-derived BFP in both genders, but this was not evident between RFM and BFP among females ( = -0.62; = 0.534). While BAI showed "good" predictive accuracy in both genders, RFM exhibited "high" predictive accuracy for BFP (MAPE: 7.13%; 95% CI: 6.27-8.78) among females according to MAPE analysis. From the Bland-Altman plot analysis, the mean difference between RFM and BFP was acceptable among females [0.3 (95% LOA: -10.9 to 11.5)], but both BAI and RFM recorded large limits of agreement and low Lin's concordance correlation coefficient with BFP (Pc < 0.90) in the two gender populations. The optimal cut-off, sensitivity, specificity, and Youden index for RFM were >27.2, 75%, 93.75%, and 0.69, respectively, while those of BAI were >25.65, 80%, 84.37%, and 0.64, respectively, among males. Among females, the values for RFM were >27.26, 92.57%, 72.73%, and 0.65, whereas those of BAI were >29.4, 90.74%, 70.83%, and 0.62, respectively. The accuracy of discriminating between BFP levels was higher among females [BAI (AUC: 0.93) and RFM (AUC: 0.90)] compared to males [BAI (AUC: 0.86) and RFM (AUC: 0.88)].

Conclusion: RFM had a better predictive accuracy of BIA-derived BFP in females. However, both RFM and BAI failed as valid estimates for BFP. Furthermore, gender-specific performance in the discrimination of BFP levels for RFM and BAI was observed.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10125734PMC
http://dx.doi.org/10.1155/2023/1500905DOI Listing

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