Bio-electrical impedance vector analysis: testing Piccoli’s model against objective body composition data in children and adolescents

• Published in: European journal of clinical nutrition Vol. 73; no. 6; pp. 887 - 895
• Main Authors: Wells, Jonathan C. K., Williams, Jane E., Quek, Rina Y., Fewtrell, Mary S.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.06.2019; Nature Publishing Group
• Subjects: 631/443; 692/53; 692/700/2814; Adipose tissue; Adolescence; Adolescent; Adolescent Nutritional Physiological Phenomena; Adolescents; Age; Anthropometry; Bioelectricity; Body Composition; Body fat; Body Water; Child; Child Nutritional Physiological Phenomena; Child, Preschool; Children; Clinical Nutrition; Electric Impedance; Electrical impedance; Epidemiology; Fat-free body mass; Female; Humans; Hydration; Impedance; Internal Medicine; Male; Medicine; Medicine & Public Health; Metabolic Diseases; Model testing; Models, Theoretical; Nutritional Status; Public Health; Reactance; Reference Values; Regression analysis; Teenagers; Vector analysis; Young Adult
• ISSN: 0954-3007; 1476-5640; 1476-5640
• DOI: 10.1038/s41430-018-0292-x

Background/Objectives Bio-electrical impedance (BI) analysis is a simple body composition method ideal for children. However, its utility in sick or malnourished children is complicated by variability in hydration. BI vector analysis (BIVA) potentially resolves this, using a theoretical model that differentiates hydration from cell mass. We tested this model against reference methods in healthy children varying widely in age and nutritional status. Subjects/Methods We compiled body composition data from 291 children and adolescents (50% male) aged 4–20 years of European ancestry. Measurements included anthropometry, BIVA outcomes (height-adjusted resistance (R/H) and reactance (Xc/H); phase angle (PA)), and fat-free mass (FFM), fat mass (FM) and FFM-hydration (H FFM ) by the criterion 4-component model. All outcomes were converted to age- and sex-standardised standard deviation scores (SDS). Graphic analysis and regression analysis were used to evaluate the BIVA model. Results R/H and Xc/H declined with age in curvilinear manner, whereas PA increased linearly with age. R/H-SDS and Xc-SDS were negatively correlated with FFM-SDS, H FFM -SDS. and FM-SDS. PA was positively correlated with FFM-SDS but unrelated to H FFM -SDS and FM-SDS. Conclusions While previous studies of adults with major fluid perturbations support the BIVA model, it is less successful in predicting variability in FFM in healthy children and adolescents. BIVA outcomes varied as predicted by the model with H FFM , but not as predicted with FFM. Variability in adiposity also explains some of the variability in BIVA traits. Further work is needed to develop a theoretical BIVA model for application in paediatric patients without major fluid disturbances.