ArticleNutrients2024
Application of Bioelectrical Impedance Analysis in Weight Management of Children with Spina Bifida.
Article in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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
3 citing papers in PubMed.
- Applications of bioimpedance measurement in clinical and allied fields: a comprehensive review.Biomedical engineering online · 2026Review
- Article
- The Prospective Applications of Bioelectrical Impedance Analysis in Postpartum Women.Journal of clinical medicine · 2025Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
backgroundChildren with spina bifida (SB) face an elevated risk of obesity, which necessitates precise methods for assessing body composition to ensure effective weight management. Conventional measures like BMI are inadequate for this population because of variations in growth patterns and skeletal structure. Bioelectrical impedance analysis (BIA) is a method that offers a clearer picture of body composition, yet its use in children with SB remains underexplored.
methodsConducted on 57 children with SB and 28 healthy controls, with a median age of 11 years, this study evaluated anthropometrics, including BMI and BIA-derived metrics. The Hoffer's scale to assess physical activity was applied in SB children.
resultsResults showed that while 32% of SB patients were classified as overweight or obese based on BMI, 62% exhibited high body fat percentage via BIA. Fat-free mass, muscle and fat mass, and fat-to-muscle ratio (FMR) differed significantly compared to the reference group. Non-ambulators showed a higher median body fat mass percentage (25.9% vs. 17.8%,
conclusionsIn SB children, BIA-measured fat mass is a better obesity indicator than BMI. Non-ambulatory, SB patients with obesity had the highest FMR values, indicating a higher risk for metabolic syndrome.
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