Bioelectrical Impedance Vector Analysis (BIVA) in Slovak population: application in a clinical sample

Technology of Two-dimensional Bioimpedance Analysis of the Human Body Composition

The BIA primary result sheets as a rule contain one-dimensional graphical scales with a selected area of normal values. In 1994, Piccoli et al. proposed BIVA, an alternative form of BIA data presentation, where two bioimpedance parameters are considered simultaneously as tolerance ellipses: resistance and reactance normalized to height. The purpose of this study is to develop an approach to data analysis in body composition bioimpedance research in two-dimensional representations. The data of 1.124.668 patients aged 5 to 85 years who underwent a bioimpedance study in Russian Health Centers from 2009 to 2015 were used. Statistical programming in the R Studio environment was carried out to estimate two-dimensional distribution densities of pairs of body composition parameters for each year of life. The non-Gaussian distribution is found in most parameters of bioimpedance analysis of body composition for most ages (Lilliefors test, p-value << 0.0001). The slices of the actual two-dimensional distribution pairs of body composition parameters had an irregular shape. The authors of the article propose using the actually observed distribution for populations where numerous bioimpedance studies have already been carried out. Such technology can be called two-dimensional bioimpedance analysis of human body composition (2DBIA). The 2DBIA approach is clearer for practitioners and their patients due to the use of body composition parameters in addition to electrical impedance parameters.

Body composition of Slovak midlife women with cardiovascular complications

The aim of this study was to analyse differences in body composition of women with and without cardiovascular complications. Bioelectrical parameters were measured with bioimpedance monofrequency analyser (BIA 101) and tissue electric properties were analysed by bioelectric impedance vector analysis (BIVA). The clinical sample (with CVD) consisted of 254 women ranging in age between 39 and 65 years. The sample of women without CVD consisted of 318 women in the same age range and was created from database of our previous studies. Statistical analysis adjusted for age showed significant differences in body composition characteristics of the studied samples. The results of vector analysis showed significantly different tissue electric properties of women in studied groups, what was confirmed by the Hotelling T2- test (p=0.0000). More women with CVD attained risky mean values of obesity indices of BMI and WHR than their “healthy” counterparts. Among women with CVD 80.2% had higher value of the BMI index than optimal one (>24.9 kg/m2) and 74.4% of women had higher value of the WHR index than optimal (>0.80). From the BIA parameters strong correlation coefficient was found between BMI and FM in both groups (r=0.962 for women with CVD; r=0.968 for relatively healthy women). Our data confirmed that cardiovascular disease complications are strongly linked in body composition changes. The cross-sectional nature of our study makes it difficult to draw conclusions regarding causal pathways, though variables of obesity are in line with unhealthy conditions.

Bioimpedance Vector Analysis in Diagnosing Severe and Non-Severe Dengue Patients

Real-time monitoring and precise diagnosis of the severity of Dengue infection is needed for better decisions in disease management. The aim of this study is to use the Bioimpedance Vector Analysis (BIVA) method to differentiate between healthy subjects and severe and non-severe Dengue-infected patients. Bioimpedance was measured using a 50 KHz single-frequency bioimpedance analyzer. Data from 299 healthy subjects (124 males and 175 females) and 205 serologically confirmed Dengue patients (123 males and 82 females) were analyzed in this study. The obtained results show that the BIVA method was able to assess and classify the body fluid and cell mass condition between the healthy subjects and the Dengue-infected patients. The bioimpedance mean vectors (95% confidence ellipse) for healthy subjects, severe and non-severe Dengue-infected patients were illustrated. The vector is significantly shortened from healthy subjects to Dengue patients; for both genders the p-value is less than 0.0001. The mean vector of severe Dengue patients is significantly shortened compare to non-severe patients with a p-value of 0.0037 and 0.0023 for males and females, respectively. This study confirms that the BIVA method is a valid method in differentiating the healthy, severe and non-severe Dengue-infected subjects. All tests performed had a significance level with a p-value less than 0.05.