ArticleCureus2025
Correlation Between Age and Body Composition Values Using Bioelectrical Impedance Analysis in Young Children.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimBioelectrical impedance analysis (BIA) is an attractive method for measuring the fat-free mass (FFM) and fat mass (FM) in adults. Although BIA is not typically performed in young children, previously published prediction equations for BIA in young children have been used recently. The present study evaluated the relationship between age, sex, and body composition in BIAs of young children.
methodsThis study is a retrospective cross-sectional analysis. All patients weighing >8 kg and 12-100 months old were included in the study. The body composition values in the BIA (FFM, FM, and phase angle (PhA)) were calculated. A multiple linear regression analysis for the body composition values in the BIA was used with the variables of age (months) and sex, as well as a constant.
resultsA total of 147 patients (86 boys and 61 girls) with a median age of 47 months were enrolled. Using multiple regression analyses, the FFM equation included the age, sex, and a constant (FFM (kg) = 0.128 × age + 0.391 × sex [male = 1, female = 0] + 6.378 [R
conclusionsThe present study demonstrated that age and sex are significant predictors of body composition parameters in young children as measured by BIA. Specifically, FFM was strongly associated with both age and sex, while FM and PhA were moderately associated with age. The derived regression equations may serve as reference models for estimating body composition in pediatric populations using BIA.
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