Henry Lukaski

The authors address a current topic of practical clinical importance in a framework including theory and application of the bioimpedance (BIA) method. The narrative would benefit from more rigor in describing the physical and technical principles and...

Body composition assessment has traditionally focused on estimating body mass components and the estimation processes required to obtain them in vivo. Within this context, the five-level model and the methodological taxonomy proposed by Wang and colleagues provided a rigorous conceptual framework that has strongly shaped the field. However, contemporary research and practice reveal persistent ambiguity in the use of terms such as direct, indirect, and doubly indirect. This ambiguity has become increasingly evident as methods such as anthropometry and bioelectrical impedance analysis are widely used not only to estimate body mass components, but also to obtain whole-body variables that are directly measured and interpreted as clinically, physiologically, or performance-relevant descriptors. Confusion often arises when directly measured outputs (e.g., skinfolds, girths, phase angle) are not clearly distinguished from model-derived estimates of body composition (e.g., fat mass, fat-free mass). Accordingly, we propose a clarification framework for in vivo body composition assessment that distinguishes: (1) directly measured whole-body variables, (2) model-derived estimates of body composition, and (3) hybrid assessment pathways combining measured and inferred outputs. In this framework, classification depends on the specific variable of interest and the estimation process linking measurement to output, rather than on assigning a fixed label to the instrument itself. The term direct refers only to an output that is measured rather than model-derived, and does not imply direct assessment of body components, greater validity, or superior methodological accuracy. The proposed framework provides a practical conceptual tool for distinguishing measured from estimated body composition outputs, thereby improving methodological transparency, interpretation, and reporting consistency across research and clinical practice.

Despite bioelectrical impedance analysis (BIA)-derived phase angle (PhA) being recognized as a global marker of health, reflecting both cellular integrity and fluid distribution, its biological determinants still need to be described in youth. This narrative review provides a comprehensive framework examining to what extent dielectric properties shaping PhA are influenced by qualitative and quantitative determinants at multiple levels of body composition in healthy and clinical pediatric populations. At the atomic-molecular level, water content, glycogen, lipids, and ionic concentrations are expected to influence PhA by affecting electrical conductivity and/or capacitance. While the increase in the absolute values of intracellular (ICW) and extracellular water (ECW) enhances electric conductivity, an increase in the relative portion of ECW is expected to reflect hydration imbalances with an impact on electrical pathways. At the cellular level, body cell mass is a key determinant of PhA, mainly due to the presence of skeletal muscle cells favoring conductive and capacitive properties. At the tissue level, skeletal muscle architecture and orientation strongly influence conductivity, while increases in skeletal muscle mass positively impact PhA by enhancing electric conductivity and capacitance. Beyond the theoretical insights presented in this review, careful interpretation of dielectric data remains crucial due to the lack of methodological standardization. Future research should prioritize validated reference methods, investigate longitudinal changes, integrate localized BIA, and explore additional BIA models to refine the interpretation of PhA.

The use of bioelectrical impedance analysis (BIA) is now well established in healthcare as an essential support tool for patient management in various clinical settings. Its use in sports is rapidly expanding due to the valuable insights it offers, helping to better structure athletes’ diets and training programs, thereby optimizing their performance. In the context of sport, however, there is a consensus regarding the importance of proper interpretation of BIA-derived data, which cannot be limited to mere estimation of body composition. In this sense, therefore, the evaluation and interpretation of raw bioelectrical parameters, including resistance, reactance, and phase angle (PhA) is of relevant importance. The assessment of PhA is particularly significant in the context of sports, as it is closely linked to key factors such as muscle mass, strength, and overall muscle quality. However, the existing relationship between PhA and systemic, and loco-regional inflammation, which, in a broader sense, is the rationale behind its use for assessing and monitoring localised muscle damage. Thus, the importance of PhA monitoring during training becomes evident, as it plays a crucial role in assessing and potentially identifying functional impairments, such as overtraining syndrome, as well as muscle injury and related changes in fluid distribution, at an early stage. The aim of this review is to provide the scientific basis necessary to consider the use of whole-body PhA as an indicator of overtraining.