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Background: Most body composition techniques assume constant properties of Fat Free Mass (FFM) (hydration and density) regardless of nutritional status, which may lead to biased values. Aim: To evaluate the interactive associations of age and Body Mass Index (BMI) with hydration and density of FFM. Methods: Data from subjects aged between 4 and 22 years old from several studies conducted in London, UK were assessed. Hydration (H FFM) and density (D FFM) of FFM obtained from 4 component model in 936 and 905 individuals, respectively, were assessed. BMI was converted in z-scores, and categorised into five groups using z-score cutoffs (thin, normal weight, overweight, obese and severely obese). Linear regression models for H FFM and D FFM were developed using age, sex and BMI group as predictors. Results: Nearly 30% of the variability in H FFM was explained by models including age and BMI groups, showing increasing H FFM values in heavier BMI groups. On the other hand, ∼40% of variability of the D FFM was explained by age, sex and BMI groups, with D FFM values decreasing in association with higher BMI groups. Conclusion: Nutritional status should be considered when assessing body composition using two-component methods, and reference data for H FFM and D FFM is needed to higher BMI groups to avoid bias. Further research is needed to explain intraindividual variability of FFM properties.

Background & aims: The aim was to generate a predictive equation to assess body composition (BC) in children with obesity using bioimpedance (BIA), and avoid bias produced by different density levels of fat free mass (FFM) in this population. Methods: This was a cross-sectional validation study using baseline data from a randomized intervention trial to treat childhood obesity. Participants were 8 to 14y (n ¼ 315), underwent assessments on anthropometry and BC through Air Displacement Plethysmography (ADP), Dual X-Ray Absorptiometry and BIA. They were divided into a training (n ¼ 249) and a testing subset (n ¼ 66). In addition, the testing subset underwent a total body water assessment using deuterium dilution, and thus obtained results for the 4-compartment model (4C). A new equation to estimate FFM was created from the BIA outputs by comparison to a validated model of ADP adjusted by FFM density in the training subset. The equation was validated against 4C in the testing subset. As reference, the outputs from the BIA device were also compared to 4C. Results: The predictive equation reduced the bias from the BIA outputs from 14.1% (95%CI: 12.7, 15.4) to 4.6% (95%CI: 3.8, 5.4) for FFM and from 18.4% (95%CI: 16.9, 19.9) to 6.4% (95% CI: 5.3, 7.4) for FM. Bland eAltman plots revealed that the new equation significantly improved the agreement with 4C; furthermore, the observed trend to increase the degree of bias with increasing FM and FFM also disappeared. Conclusion:The new predictive equation increases the precision of BC assessment using BIA in children with obesity.