# Novel bioparameters derived from bioimpedance measurements for accurate prediction of weight status in infant–juvenile individuals: A regression analysis

**Authors:** Taira Batista Luna, Jose Luis García Bello, Alcibíades Lara Lafargue, Héctor Manuel Camué Ciria, Yohandys A. Zulueta

PMC · DOI: 10.2478/joeb-2025-0009 · Journal of Electrical Bioimpedance · 2025-05-26

## TL;DR

This study uses bioimpedance measurements to develop new bioparameters for predicting weight status in infants and juveniles in Cuba.

## Contribution

The study introduces specific resistance and reactance as novel bioparameters for accurate weight status prediction in infant-juvenile populations.

## Key findings

- Specific resistance and reactance bioparameters correlate with weight status and sex in the studied cohort.
- Predictive models using bioimpedance data accurately assess weight status and disease risks in infants and juveniles.
- The findings support the use of bioimpedance measurements in health and disease risk assessment for this population.

## Abstract

In this study, a linear support vector machine regression model was used to explore the correlation between weight status and two novel bioparameters, specific resistance and reactance, in an infant-juvenile cohort from eastern Cuba. The model was trained using various characteristics, including bioimpedance measurements, to predict phase angle, specific resistance, and reactance with high accuracy. The results showed that the variation of these characteristics with weight status and sex is consistent with previous literature. Additionally, two robust bioparameters derived from bioimpedance measurements and anthropometric-physiological parameters were identified for predicting weight status. The predictive models developed in this study are essential for accurately assessing weight status and disease risks in infants and juveniles in the eastern Cuban region. These findings highlight the potential applications of bioimpedance measurements and bioparameters in health and disease risk assessment, contributing to the growing body of literature on this topic.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12136677/full.md

## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12136677/full.md

## References

37 references — full list in the complete paper: https://tomesphere.com/paper/PMC12136677/full.md

---
Source: https://tomesphere.com/paper/PMC12136677