Objective

The objective of the study was to establish a model that would reduce the bioimpedance measurement error as compared with the densitometric result, in terms of total and segmental fatty tissue content in children

Material and methods

The study consisted of 56 children, aged 6-18. All subjects underwent a densitometry examination (DXA) to assess total fatty tissue mass (%, g), and percentage of fatty tissue on limbs and trunk. The bioelectric impedance (BIA) analyses were performed using a Tanita scale, considering identical measurement parameters.

Results

The average percent deviation between values obtained with densitometry and bioimpedance was 14.23 ± 33.44% (median, 5.30; IQR, 1.35-10.9). The median of the mean absolute percentage error (MAPE) was 18.55 (median, 28.13; IQR, 18.47-38.88%). The coefficient of determination (R2) of the simple linear regression of bioimpedance, as compared with densitometry, was 0.83 (p < 0.0001). The multi-factorial model significantly improved the estimation accuracy (p < 0.0001) – the mean estimation error was 6.11 ± 29.30 (median, –0.04; IQR, –7.97 through 10.96), while the MAPE median was 18.54 ± 23.38 (median, 9.89; IQR, 4.21-23.37). The final prediction model was based on percentage of parameters of overall fatty tissue content, percentage of fatty tissue on the right and left lower limb, and on the left upper limb.

Conclusions

The use of a multi-factorial regression model reduces the differences between results obtained using densitometry and those achieved with bioelectric impedance, in terms of overall and segmental fatty tissue content evaluation in children, improving the measurement accuracy.