Comparison of Several Prediction Equations Using Skinfold Thickness for Estimating Percentage Body Fat vs. Body Fat Percentage Determined by BIA in 6–8-Year-Old South African Children: The BC–IT Study

Abstract

Body composition measurement is useful for assessing percentage body fat (%BF) and medical diagnosis, monitoring disease progression and response to treatment, and is essential in assessing nutritional status, especially in children. However, finding accurate and precise techniques remains a challenge. The study compares %BF determined by bioelectrical impedance analysis (BIA) and calculated from available prediction equations based on skinfolds in young South African children. A cross-sectional study performed on 202 children (83 boys and 119 girls) aged 6–8 years. Height and weight, triceps and subscapular skinfolds were determined according to standard procedures. %BF was determined with BIA and three relevant available equations. SPSS analyzed the data using paired samples tests, linear regression, and Bland–Altman plots. Significant paired mean differences were found for BIA and Slaughter (t201 = 33.896, p < 0.001), Wickramasinghe (t201 = 4.217, p < 0.001), and Dezenberg (t201 = 19.910, p < 0.001). For all of the equations, the standards for evaluating prediction errors (SEE) were above 5. The Bland–Altman plots show relatively large positive and negative deviations from the mean difference lines and trends of systematic under- and over-estimation of %BF across the %BF spectrum. All three equations demonstrated a smaller %BF than the %BF measured by BIA, but the difference was smallest with the Wickramasinghe equation. In comparison, a poor SEE was found in the three %BF predicted equations and %BF derived from BIA. As such, an age-specific %BF equation incorporating criterion methods of deuterium dilution techniques or ‘gold-standard’ methods is needed to refute these findings. However, in the absence of developed %BF equations or ‘gold-standard’ methods, the available prediction equations are still desirable.

Validity and agreement between dual-energy X-ray absorptiometry, anthropometry and bioelectrical impedance in the estimation of fat mass in young adults

“…Regarding the reported differences in fat mass results between DXA and BIA, previous studies have also pointed out that BIA may be a method whose concordance and validity is limited with respect to DXA ( 58–60 ). This could be since previous studies, as in the present one, a BIA device was used that do not report the raw electrical conductivity data ( 61 ), but rather the device’s own software gives the fat mass estimation as a result ( 61 , 62 ). Previous studies have suggested that the validity of BIA may be increased when the device gives the raw data and then this data is used by the researcher to estimate fat mass using the most appropriate formula for the population being analysed ( 21 ).…”

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“…Regarding the reported differences in fat mass results between DXA and BIA, previous studies have also pointed out that BIA may be a method whose concordance and validity is limited with respect to DXA (58)(59)(60). This could be since previous studies, as in the present one, a BIA device was used that do not report the raw electrical conductivity data (61), but rather the device's own software gives the fat mass estimation as a result (61,62). Previous studies have suggested that the validity of BIA may be increased when the device gives the raw data and then this data is used by the researcher to estimate fat mass using the most appropriate formula for the population being analysed (21).…”

Image_3.JPEG

“…Regarding the reported differences in fat mass results between DXA and BIA, previous studies have also pointed out that BIA may be a method whose concordance and validity is limited with respect to DXA (58)(59)(60). This could be since previous studies, as in the present one, a BIA device was used that do not report the raw electrical conductivity data (61), but rather the device's own software gives the fat mass estimation as a result (61,62). Previous studies have suggested that the validity of BIA may be increased when the device gives the raw data and then this data is used by the researcher to estimate fat mass using the most appropriate formula for the population being analysed (21).…”