Phase angle and vector analysis in the evaluation of body composition in sarcopenic obesity: A systematic review

Sarcopenic obesity (SO) is a condition characterized by low muscle mass and strength and high adiposity. Bioelectrical impedance analysis (BIA) derived phase angle (PhA) and bioelectrical impedance vector analysis (BIVA) are simple and inexpensive tools for the evaluation of body composition, with an emerging consensus in health research and application.

The aim of this systematic review was to analyze research on sarcopenic obesity using PhA or BIVA.

A bibliographic search was performed on 13 January 2025, using three databases: PubMed, Scopus and Web of Science. The search terms were: ("phase angle" OR BIVA) and (sarcopenic OR sarcopenia OR obesity). Studies addressing only obesity or sarcopenia were excluded. The quality of the studies was evaluated using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies, from the National Institute of Health. No meta-analysis was conducted.

Nine studies were selected, mostly published in 2022 (89%) or later and focused on clinical applications (55.6%). The reviewed studies showed substantial methodological variability. Diagnostic criteria included the ESPEN-EASO algorithm as well as protocols based on different definitions of sarcopenia and obesity. Indices and cut-offs used to define body composition varied accordingly. Variability was also observed in population samples and in bioimpedance devices. All selected studies used PhA and two of them used BIVA. Although quantitative results are variable, with PhA values ranging from 3.9° to 7.1°, and mostly below 5.6°. The qualitative pattern of bioelectrical characteristics associated with body composition in SO is broadly consistent across studies: PhA is tendentially lower than in healthy subjects and patients with obesity and similar to those with sarcopenia; the specific vector is longer.

Research is still quite heterogeneous in terms of methods and diagnostic procedures, which limits the comparability of the results. However, the observed tendencies confirm the suitability of PhA for recognizing the reduced muscle mass associated with sarcopenia, while specific BIVA also appears capable of detecting excess fat mass related to obesity. Further research is needed to standardize procedures for characterizing sarcopenic obesity and monitoring its progression.