# Multi-Frequency Bioimpedance Analysis in Practice: A Review of Validated Prediction Equations for Key Body Composition Parameters

## TL;DR

This paper reviews validated equations for estimating body composition using bioimpedance analysis, highlighting gaps and the need for updated, diverse population models.

## Contribution

The paper compiles and analyzes 98 validated BIA prediction equations from 2000 to 2025, identifying demographic gaps and the potential of multi-frequency BIA.

## Key findings

- Most equations focus on fat-free mass and total body water, with fewer for extracellular and intracellular water.
- Multi-frequency BIA devices show potential for improved accuracy in body composition estimation.
- There is a geographic and demographic imbalance in the populations studied, calling for more inclusive models.

## Abstract

This review provides a comprehensive synthesis of validated prediction equations for body composition assessment using single- and multi-frequency bioelectrical impedance analysis (BIA), covering studies published between 2000 and April 2025. While traditional models for estimating compartments such as total body water (TBW) and fat-free mass (FFM) have long been established, they often fail to reflect current populations and technologies. The review includes 43 studies that developed 98 unique equations for TBW, FFM, extracellular water (ECW), intracellular water (ICW), body cell mass (BCM), and bone mineral content (BMC), derived using reference methods such as deuterium dilution, DXA, or multi-component models. Most equations targeted FFM and TBW, with a noticeable lack of models for ECW, ICW, and BMC. The review identifies a geographic and demographic imbalance in study populations and emphasizes the need for updated, population-specific models. It also highlights the growing use of multi-frequency BIA devices to improve estimation accuracy. The findings support the continued refinement of BIA-based prediction models for broader clinical applicability and underscore the importance of external validation across diverse populations and health conditions.