Poster Topical Area: Obesity
Location: Hall D
Poster Board Number: 708
Objective: To compare percent body fat (%BF) estimated by bioelectrical impedance analysis (BIA) and by the 4 predictive equations from body mass index (BMI) in men in the rural western highlands of Guatemala, a region characterized by high rates of stunting.
Methods: A convenience sample of 48 men from the rural area of Sololá, Guatemala participated in the study. Weight (to the nearest 0.1kg) and height (to the nearest 0.5cm) were measured with SECA model 874 and 213, respectively. BIA was conducted using the Medical Body Composition Analyzer SECA® 525. The values of %BF from 4 BMI equations (Womersley & Durnin 1977, Jackson & Pollock 1978, Deurenberg et al. 1991, Gallagher et al. 2000) and BIA were compared by paired t-test. Effect sizes of the differences were determined by Cohen’s d statistic. The constant error (CE) was determined as the mean difference between the equations and the BIA model. The methods of Bland and Altman (BA) were used to identify the 95% limits of agreement (LOA) between each predictive equation and the BIA model. Linear regression was used to determine the Pearson correlation coefficient. SAS® v9.4 was used for statistical analysis.
Results: The participants had an average age of 36 ± 20 years (18-89) and a mean BMI of 25.2 ± 3.4 kg/m2 (19.9-35.2). All equations produced significantly different %BF values compared to the BIA model (p<0.001). The CEs ranged from -3.3 (Deurenberg) to -5.5 (Gallagher). The LOA ranged from ±8.4 (Gallagher) to ±9.3 (Womersley). The Pearson coefficients were 0.82 (Gallagher) and 0.78 (Womersley, Jackson, Deurenberg). The BA trend was universally negative, and significant for the Womersley, Jackson, and Gallagher equations (p<0.01).
Conclusion: The BF% generated by BIA gives significantly higher values compared to the values calculated using the 4 predictive BMI-based equations among rural men in Guatemala. The wide LOA and significant BA trends prevents the possibility of any simple correction factor. This precludes the usage of these equations in a population with a high prevalence of short stature, although studies in different populations are needed to corroborate this result. While BIA is independent of BMI, further independent body-composition methods would reinforce the strength of our conclusions.
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