BIA Vectorial Analysis: new population references published after 30 years

New references for bioelectrical impedance vector (BIVA) and phase angle (PhA) referred to the general population are now available, thanks to a study conducted by Dr. F. Campa, a researcher in Prof. A. Paoli’s group at the University of Padua. The study involved a sample of more than 4,000 adults, ranging in age from 18 to 65 years, and bioelectrical data were collected exclusively using Akern analyzers.

Bioelectrical impedance vector analysis (BIVA) allows, through the resistance-reactance graph (R-Xc) or Biavector, to assess changes in body fluids and conduct a qualitative analysis of body composition from the classical bioelectrical impedance analysis (BIA). In BIVA, the vector resulting from the ratio of resistance (R) to reactance (Xc) standardized for the individual’s height can be compared against bivariate percentiles, i.e., tolerance ellipses of 50%, 75%, and 95%, representative of the reference population.

BIVA allows to identify the bioelectric phase angle (PhA), which defines the direction of the vector within the R-Xc graph. This biomarker, a result of the relationship between R and Xc, is also a qualitative index of body composition in relation to cell quantity and cell membrane integrity. Phase angle is associated with appendicular muscle strength and may also reflect inflammatory/edematous status of the individual. It is known for its prognostic value related to survival and rehospitalization in pathological subjects.

The first tolerance ellipses present in BIVA had been validated by Prof. Piccoli of the University of Padua in 1995, including groups of subjects of different ages. The multicenter, cross-sectional study conducted by Dr. Campa, 30 years after Prof. Piccoli’s study, aims to provide new tolerance ellipses specific to the adult population, presenting percentile curves and reference values for the bioelectric phase angle.

Dr. F. Campa, author of the study, comments, “…These new references are more representative for a general population that has changed significantly in recent decades. In addition, statistical methods and technology have evolved and refined in parallel with these changes…. “, and goes ahead, “…. changes are reflected in the different pattern of the vector distribution within the R-Xc graph and the average phase angle generally higher compared to the previous distribution of BIVA introduced by Prof. Piccoli in 1995.”

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