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Hydration status after cardiac surgery can be difficult to assess, often requiring invasive measurements. Bioelectrical impedance vector analysis (BIVA) is based on patterns of resistance (R) and reactance (Xc), corrected by height, and has been used in various clinical scenarios to determine body composition and monitor its changes over time. The purpose of the present study was to apply this method in cardiac surgery patients to assess the variation in hydration status and to compare its changes according to the use of extracorporeal circulation. Single-center, observational, prospective study including patients older than 18 years undergoing elective or urgent cardiac surgery. Intensive cardiac care unit of a tertiary center in a metropolitan area. The study comprised 76 patients with a median age of 60 years and mostly undergoing coronary artery bypass grafting (CABG) (n = 47 [61.8%]) with extracorporeal circulation (n = 54 [73%]). Bioimpedance was measured with a standard tetrapolar single-frequency bioimpedance meter using a standardized procedure and plotted in an R–Xc graph. The study demonstrated an increase in total body water immediately after surgery that was sustained until producing hyperhydration 24 hours later. Off-pump CABG was associated with a normal hydration status after surgery, whereas on-pump CABG produced a significant increase in total body water. Fluid status assessment with BIVA in cardiac surgery showed an increase in total body water up to 24 hours after surgery. Off-pump surgery prevented overhydration, which partially could explain the reduction in some of the postoperative complications. BIVA could serve as a useful method for monitoring fluid status in the setting of goal-directed therapy to assist in maintaining euvolemia in cardiac surgical patients. [ABSTRACT FROM AUTHOR]

Background. This study aimed to examine the association between regional Phase Angle (PhA) and physical performance in athletes where the use of specific body segments is required. Methods. Sixteen elite-level rowers (13 male aged 17.6 ± 2.1 yr; 3 female aged 21.0 ± 4.4 yr) participated in this investigation. Raw bioimpedance parameters were obtained with a phase-sensitive 50 kHz bioelectrical impedance analysis (BIA) device and fat-free mass, percentage of fat mass (FM%), and arms and legs lean soft tissue (ALST and LLST, respectively) were estimated using specific BIA-equation developed for athletes. The time (2000t) and the mean power (MP) expressed during the 2000 m test performed on a rowing ergometer were measured. Results. The major findings of the study were that upper hemisome PhA (UPhA) were more strongly related with 2000t (R2 = 0.35, p = 0.015) and MP (R2 = 0.40, p = 0.009) than whole-body PhA. Additionally, not only UPhA maintained a significant relationship with 2000t (p = 0.001) and MP (p = 0.001), even after adjustment for the co-variables sex, ALST, and FM%, but the explained variance increased to R2 = 0.72 and R2 = 0.78, respectively. Conclusions. These results suggest that the regional PhA might be used as a tool for evaluating performance related parameters in sports where specific body segments are involved, preferring it to the whole-body measured value. [ABSTRACT FROM AUTHOR]

Bioelectrical impedance vector analysis (BIVA) is a technique used for the assessment of body composition based on the electrical properties of biological tissues and for evaluating variations related to hydration and nutrition status changes. The present study aimed to investigate the possibility of predicting performance status and injuries using segmental BIVA analysis. Data were collected from 14 professional male athletes aged between 20 and 39 years of Caucasian and Afro-American ethnicity belonging to the US Victoria Libertas Pallacanestro Pesaro team in the Italian Serie A basketball championship. From an analysis of training injuries, the data highlight a possible positive link between the number of training injuries and upper hemisoma reactance (XCEmsSup) (t = 2.881, p = 0.007), an inverse relationship between training injury duration and higher right lower limb reactance (XCLegDx) (t = −4.213, p < 0.001), and an inverse relationship between injury duration and higher body mass index (t = −4.213, p < 0.001), highlighting how higher cellularity seems less prone to severe training injuries. Analyzing match-day injuries, right upper-limb higher reactance (XCArmdx) negatively correlates with match-day number of injuries (t = −4.469, p < 0.001), right upper limb resistance (RZArmDx) negatively correlates with lower match-day injury duration (t = −4.202, p < 0.001), and trunk resistance (RZTrunk) positive correlates with lower match-day injury duration (t = 2.803, p = 0.008), in contrast with the training data analysis. Analyzing the relationship between the BIVA parameters and performance indicators, right upper limb resistance (RzArmDx) has a positive link with plus–minus (t = 2.889, p = 0.007); however, RzArmDx negatively correlates with assist number (t = −3.362, p = 0.002), and BMI is directly proportional to assist number (t = 2.254, p = 0.032). These first data suggest a good correlation between the cellularity of different body districts and the risk of injuries in training but still leave several doubts surrounding the concrete predictive potential regarding performance and injuries during competitions while considering the numerous factors involved. Further studies on BIVA and similar applications could provide tools for managing athlete health and physical integrity preservation and potentially help us better understand the factors involved in improving performance.

The aim of this study was to analyse the association between specific bioelectric impedance vector analysis (BIVA) and dual-energy X-ray absorptiometry (DXA) to assess segmental body composition using DXA as the reference technique. The sample comprised 50 young active students who practised or played different sports (25 men, age: 24.37 ± 4.79 y; 25 women, age: 24.32 ± 4.43 y) from the National Institute of Physical Education of Catalonia (INEFC). Anthropometric data (height, weight, arm, waist, and calf circumferences) and bioelectrical measurements (R, ohm; Xc, ohm) were recorded. Body composition was analysed with specific BIVA. DXA was used as the reference method to assess body composition of the whole-body, the trunk, and the limbs. The percentage of fat mass (%FM DXA) and fat-free mass index (FFMI DXA = FFM/length2) were calculated. The agreement between specific BIVA and DXA was evaluated by a depth–depth analysis, two-way ANOVA, and Pearson's correlations. The depth–depth analysis showed a good agreement between DXA and BIVA (F = 14.89, p < 0.001) in both sexes and all body segments. Specific vector length (Zsp; i.e. indicative of %FM) was correlated with %FM DXA in the whole body and all body segments, and the phase angle was correlated with FFMI DXA , with he trunk in women as the only exception. Specific BIVA demonstrated to balance the effect of body size on bioelectrical measurements in both whole and segmental approaches. Segmental specific BIVA and DXA provided a consistent evaluation of body composition in both sexes, of the whole body and each body segment. The indices %FM and FFMI obtained with DXA were correlated to vector length and phase angle in each segment, respectively. Specific BIVA represents a promising technique for monitoring segmental body composition changes in sport science and clinical applications. • Segmental specific BIVA and DXA provided a consistent evaluation of body composition in both sexes. • In each segment, %FM and FFMI, obtained with DXA, were correlated with Zsp and PA, respectively. • Specific BIVA demonstrated to balance the effect of body size on bioelectrical measurements. [ABSTRACT FROM AUTHOR]

Soccer is a multifactorial sport, in which players are expected to possess well developed physical, psychological, technical, and tactical skills. Thus, the anthropometric and fitness measures play a determinant role and could vary according to the competitive level. Therefore, the present study aimed to verify differences in body composition and physical performance between two soccer team. 162 young soccer players (from the Under 12 to Under 15 age categories; age: 13.01 ± 1.15 years) of different competitive levels (elite—n = 98 and non-elite—n = 64) were recruited. Anthropometric characteristics (height, weight, lengths, widths, circumferences, and skinfold thicknesses (SK)), bioelectrical impedance, physical performance test as countermovement jump (CMJ), 15 m straight-line sprints, Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo), and 20 + 20 m repeated-sprint ability (RSA)) were carried out. In addition, Body mass index (BMI), body composition parameters (percentage of fat mass (%F), Fat mass (FM, kg), and Fat-free mass (FFM, kg)) and the areas of the upper arm, calf and thigh were calculated, and the Bioelectric Impedance Vector Analysis (BIVA) procedures were applied. In addition, a linear discriminant analysis was assessed to determine which factors better discriminate between an elite and non-elite football team. Many differences were observed in body composition between and within each football team’s category, especially in triceps SK (p < 0.05), %F (p < 0.05), and all performance tests (p < 0.01). The canonical correlation was 0.717 (F(7,128) = 19.37, p < 0.0001), and the coefficients that better discriminated between two teams were 15 m sprint (−2.39), RSA (1−26), suprailiac SK (−0.5) and CMJ (−0.45). Elite soccer team players present a better body composition and greater physical efficiency. In addition, BIVA outcome could be a relevant selection criterion to scout among younger soccer players.

Change in hydration is common in children with severe acute malnutrition (SAM) including during treatment, but is difficult to assess. We investigated the utility of bio-electrical impedance vector analysis (BIVA), a quick non-invasive method, for indexing hydration during treatment. We studied 350 children 0·5–14 years of age with SAM (mid-upper arm circumference <11·0 cm or weight-for-height <70% of median, and/or nutritional oedema) admitted to a hospital nutrition unit, but excluded medically unstable patients. Weight, height (H), resistance (R), reactance (Xc) and phase angle (PA) were measured and oedema assessed. Similar data were collected from 120 healthy infants and preschool/school children for comparison. Means of height-adjusted vectors (R/H, Xc/H) from SAM children were interpreted using tolerance and confidence ellipses of corresponding parameters from the healthy children. SAM children with oedema were less wasted than those without (p < 0·001), but had BIVA parameters that differed more from those of healthy children (P < 0·05) than those non-oedematous. Initially, both oedematous and non-oedematous SAM children had mean vectors outside the reference 95% tolerance ellipse. During treatment, mean vectors migrated differently in the two SAM groups, indicating fluid loss in oedematous patients, and tissue accretion in non-oedematous patients. At admission, R/H was lower (oedematous) or higher (non-oedematous) among children who died than those who exited the hospital alive. BIVA can be used in children with SAM to distinguish tissue-vs. hydration-related weight changes during treatment, and also identify children at high risk of death enabling early clinical interventions. [ABSTRACT FROM AUTHOR]

Aims: The present study aimed to assess the ability of bioelectrical impedance vector analysis (BIVA) in discriminating fitness levels in futsal players, exploring the association of body composition and bioelectrical parameters with aerobic power. Methods: Forty-eight professional futsal players (age 23.8 ± 5.3 years) were involved in a cross-sectional study during their pre-season phase. Fat mass (FM) and muscle mass were determined by dual-energy X-ray absorptiometry. VO2max was obtained by indirect calorimetry through a graded exercise test performed on a treadmill. Bioelectrical resistance (R), reactance (Xc), and phase angle (PhA) were directly measured using a foot-to-hand bioimpedance technology at a 50 kHz frequency. Bioelectric R and Xc were standardized for the participants’ height and used to plot the bioimpedance vector in the R-Xc graph according to the BIVA approach. Results: The participants divided into groups of VO2max limited by tertiles showed significant differences in mean vector position in the R-Xc graph (p < 0.001), where a higher VO2max resulted in a longer vector and upper positioning. FM, muscle mass, and PhA differed (p < 0.01) among the athletes grouped by tertiles of VO2max, where athletes with a greater aerobic power showed a lower percentage of FM and a higher percentage of muscle mass and PhA. FM and PhA were associated with VO2max (FM: r = −0.658, p < 0.001; PhA: r = 0.493, p < 0.001). These relationships remained significant after adjusting for age and body mass (FM: ß = −0.335, p = 0.046; PhA: ß = 0.351, p = 0.003). Conclusions: Bioelectrical impedance vectors positioned on the lower pole of the R-Xc graph identified futsal players with a lower VO2max, while longer vectors corresponded to a greater aerobic power. Additionally, PhA, that describes the vector direction, was positively associated with VO2max, while a higher FM negatively affected VO2max in the futsal players. BIVA and PhA evaluation may represent a valid support for screening the aerobic fitness level in professional futsal players, when more sophisticated assessment methods are not available.

This study aimed to analyze anthropometric and whole-body/muscle-localized bioelectrical impedance vector analysis (BIVA) adaptations and their relation to creatine kinase (CK) as a biomarker of muscle damage in a group of seven male players in the maximum category of professional rink hockey. There were three checkpoint assessments in relation to a high-intensity training session: pre-session (PRE), post-session (POST), and 24 h-post-session (POST24H). The resistance, reactance, and impedance module were adjusted by height (R/h, Xc/h, and Z/h, respectively). The Wilcoxon signed-rank test was used to compare the data at baseline and follow-up, while Spearman correlation was used to explore the relationship between CK and the rest of the parameters. The results registered a decrease in body mass at POST (p = 0.03) and a reestablishment at POST24H (p = 0.02). Whole-body BIVA registered a significant increase in R/h between PRE–to–POST (p = 0.02) and returned to baseline values at POST24H (p = 0.02), which was expected since this parameter is related to hydration processes. Muscle-localized BIVA in the rectus femoris muscle showed an increase in both Xc/h and phase angle in POST (p = 0.04 and p = 0.03, respectively) and a decrease in Xc/h at POST24H (p = 0.02). CK correlated with R/h in the rectus femoris at all the checkpoints (PRE–to–POST: r = 0.75, p = 0.05; PRE–to–POST24H: r = 0.81, p = 0.03; POST–to–POST24H: r = 0.82, p = 0.02). Our results indicate that BIVA is a sensitive methodology to assess general and muscle-localized hydration induced by a high-intensity training session in rink hockey players. A correlation between BIVA and CK was also reported.

The whole-body bioelectrical phase-angle (PhA) is emerging as a new tool in stratifying prognosis in patients with both acute (AHF) and chronic heart failure (CHF). To evaluate the determinants of PhA in HF patients. We analyzed data from 900 patients with AHF or CHF (mean age: 76±10 years, 54% AHF). Clinical, serum biochemical, echocardiographic and bioelectrical measurements were collected from all of patients. PhA was quantified in degrees. Congestion was assessed by a multiparametric approach, including the presence of peripheral edema, brain natriuretic peptides (BNP) plasma levels, blood urea nitrogen to creatinine ratio (BUN/Cr), and relative plasma volume status (PVS) calculated by Kaplan-Hakim's formula. Geriatric Nutritional Risk Index (GNRI) was adopted as indicator for nutritional status. At univariate analysis, PhA was significantly lower in females, in patients with peripheral edema, and AHF. PhA significantly correlates age, BNP, PVS, BUN/Cr, and GNRI. At multivariate analysis, congestion biomarkers emerged as the major determinant of PhA as they explained the 34% of data variability, while age, GNRI, and gender only explained 6%, 0.5%, and 0.5%, respectively (adjusted R 2 = 0.41). In particular, PVS (regression of coefficient B =−0.17) explained the 20% of PhA variability, while peripheral congestion (B =−0.27) and BNP (B =−0.15) contributed to 10% and 2%, respectively. The main determinant of bioelectrical PhA in patients with HF is congestion and PVS in particular, while nutritional status has marginal impact. [ABSTRACT FROM AUTHOR]

Purpose: This study investigates the relationship between whole-body bioimpedance vector displacement, using bioelectrical impedance vector analysis (BIVA), and renal function through serum biomarkers [creatinine, urea, sodium, C-reactive protein (CRP), and creatine kinase] and urine biomarkers after a marathon.Methods: Bioimpedance measurements were taken among 19 non-elite runners at 24 h pre-race, immediately post-race, and at 48 h post-race. The bioimpedance measurements were analyzed by BIVA using the Hotelling’s T2 test. The runners were divided according to a cutoff of serum creatinine level immediately post-race in G1 (

The present study compared changes in body composition during the COVID-19-associated lockdown with the same period of the following season in elite soccer players. Fifteen elite male soccer players (30.5 ± 3.6 years.) underwent a bioelectrical impedance analysis (BIA) before (end of February) and after (end of May) the lockdown, which occurred during the 2019/2020 season, and at the same period during the following competitive season in 2020/2021, when restrictions were lifted. Fat and muscle mass were estimated using predictive equations, while phase angle (PhA) and bioelectrical impedance vector analysis (BIVA) patterns were directly measured. After lockdown, fat mass remained unchanged (p > 0.05), while muscle mass (95%CI = −1.12/−0.64; ES = −2.04) and PhA (95%CI = 0.51/−0.24, ES = −1.56) decreased. A rightward displacement of the BIVA vector was also found (p < 0.001, ES = 1.50). After the same period during the regular season, FM% and muscle mass did not change (p > 0.05), while the PhA increased (95%CI = 0.01/0.22; ES = 0.63). A leftward vector displacement (p < 0.001, ES = 1.05) was also observed. The changes in muscle mass correlated with changes in PhA (“lockdown” season 2019/2020: ß = −1.128, p = 0.011; “regular” season 2020/21: ß = 1.963, p = 0.011). In conclusion, coaches and strength conditioners should monitor muscle mass in soccer players during detraining periods as this parameter appears to be mainly affected by changes in training plans.

Background: Little is known on the clinical relevance of the nutritional status and body composition of patients hospitalized with SARS-CoV-2 infection. The aim of our study was to assess the prevalence of malnutrition in patients with COVID-19 pneumonia using bioelectrical impedance vector analysis (BIVA), and to evaluate the relationship of their nutritional status with the severity and outcome of disease. Methods: Among 150 consecutive patients who were hospitalized with COVID-19 pneumonia, 37 (24.3%) were classified as malnourished by BIVA, and were followed-up for 60 days from admission. Outcome measures were differences in the need for invasive mechanical ventilation, in-hospital mortality, and the duration of hospital stay in survivors. Results: During 60 days of follow-up, 10 (27%) malnourished patients and 13 (12%) non-malnourished patients required invasive mechanical ventilation (p = 0.023), and 13 (35%) malnourished patients and 9 (8%) non-malnourished patients died (p < 0.001). The average duration of the hospital stay in survivors was longer in patients with malnutrition (18.2 ± 15.7 vs. 13.2 ± 14.8 days, p < 0.001). In survival analyses, mechanical ventilation free (log-rank 7.887, p = 0.050) and overall (log-rank 17.886, p < 0.001) survival were significantly longer in non-malnourished than malnourished patients. The Cox proportional ratio showed that malnutrition was associated with an increased risk of mechanical ventilation (HR 4.375, p = 0.004) and death (HR 4.478, p = 0.004) after adjusting for major confounders such as age, sex, and BMI. Conclusions: Malnutrition diagnosed with BIVA was associated with worse outcomes in hospitalized patients with COVID-19 pneumonia.

Purpose: This study investigates the relationship between whole-body bioimpedance vector displacement, using bioelectrical impedance vector analysis (BIVA), and renal function through serum biomarkers [creatinine, urea, sodium, C-reactive protein (CRP), and creatine kinase] and urine biomarkers after a marathon. Methods: Bioimpedance measurements were taken among 19 non-elite runners at 24 h pre-race, immediately post-race, and at 48 h post-race. The bioimpedance measurements were analyzed by BIVA using the Hotelling's T2 test. The runners were divided according to a cutoff of serum creatinine level immediately post-race in G1 (<1.2 mg/dl of serum creatinine level) and G2 (≥1.2 mg/dl of serum creatinine level). The increase of the serum creatinine levels in 83% of G2 runners was related to acute kidney injury (AKI) stage 1. Results: Neither G1 nor G2 showed a creatinine clearance rate (CCr) lower than 60 ml/min. G2 showed a significant increase in CRP values at 48 h post-race vs baseline compared to G1 (P < 0.05), with over 5 mg/L (6.8–15.2) in 92% of the runners, and in CK values with over 215 U/L (282–1,882) at 48 h post-race in 100% of the runners. By BIVA, the 95% confidence ellipses of G2 showed shorter bioimpedance vectors than G1, with a noticeable minor Xc/H (P < 0.01), indicating an expansion on extracellular water and inflammation. The runners with 48 h post-race Xc/H values ≤30.5 Ω, with a decrease from −3 to −12% with respect to the Xc/H value at 24 h pre-race, indicated AKI stage 1 with 85.7% sensitivity and 91.7% specificity, with a direct correlation between AKI stage 1 with greater CRP values at 48 h post-race and bioimpedance vector displacement, but not with CK values at 48 h post-race. Conclusion: Through this data collection, it was evidenced that a transient reduction in renal function is more related to inflammatory factors than muscle damage. The BIVA method along with serum biomarkers could be used to follow up the kidney function in runners. [ABSTRACT FROM AUTHOR]

To analyze the association of classic and specific bioelectrical impedance vector analysis (BIVA) and phase angle with reference techniques for the assessment of body composition in athletes. 202 athletes of both sexes (men: 21.5 ± 5.0; women: 20.7 ± 5.1) engaged in different sports were evaluated during the in-season period. Bioelectrical resistance (R, ohm) and reactance (Xc, ohm) were obtained with a phase-sensitive 50 kHz bioelectrical impedance analysis device. The classic and specific BIVA procedures, which respectively correct bioelectrical values for body height (R/H and Xc/H, ohm/m) and body geometry (Rsp and Xcsp, ohm cm), were applied. Dual energy X-ray absorptiometry was used as the reference method to assess fat-mass (FM), fat-free mass (FFM) and %FM. Deuterium dilution and bromide dilution where used as the criterion method for total body water (TBW) and extracellular water (ECW), respectively. Intracellular water (ICW) was calculated as TBW minus ECW. Specific bioelectrical values (Rsp, Xcsp, Zsp) were positively correlated with FM and %FM (%FM; Zsp men: r = 0.569, p < 0.001; Zsp women: r = 0.773, p < 0.001). Classic values (R/H, Xc/H, Z/H) were negatively correlated with FM and FFM, but were correlated with %FM only in men (Z/H men: r = −0.214, p = 0.013; Z/H women: r = 0.218, p = 0.097). As to body fluid, classic BIVA showed strong associations (Z/H men: r = −0.880, p < 0.001; Z/H women: r = −0.829, p < 0.001) with TBW, whereas Zsp was not correlated. Phase angle was negatively correlated with ECW/ICW ratio in both sexes (men: r = −0.493, p < 0.001; women: r = −0.408, p < 0.001) and positively with ICW (men: r = 0.327, p < 0.001; women: r = 0.243, p = 0.080). Specific BIVA turns out to be more accurate for the analysis of %FM in athletes, while it does not correctly evaluate TBW, for which classic BIVA appears to be a suitable approach. Phase angles, and hence both BIVA approaches, can detect ECW/ICW changes. • Classic and specific BIVA, and PA were tested against DXA and dilution techniques. • Classic BIVA correctly detected changes of TBW, but not those of %FM. • Specific BIVA detected changes of %FM, but not those of TBW. • PA (equal in classic and specific BIVA) was sensitive to ECW/ICW ratio and ICW. [ABSTRACT FROM AUTHOR]

Background and Aims: A progressive decrease in muscle mass until full-blown sarcopenia may occur in patients on peritoneal dialysis (PD) and worsen their life quality and expectancy. Here we investigate the prevalence of obesity and obesity-associated muscle wasting in PD patients.Patients and Methods: The study design was observational, cross sectional. Body composition was assessed with BIA and BIVA in 88 PD patients (53.4 ± 13.1 years; 67% male). Patients with obesity and/or with reduced muscle mass were identified using FMI and SM/BW cutoff values, respectively. Inflammatory status was assessed by measuring CRP and fibrinogen blood levels.Results: A total of 44.3% of the patients showed a reduced muscle mass (37.5% moderate and 6.8% severe). The prevalence of obesity was 6.1%, 81.8%, and 100% in patients with normal, moderately, and severely reduced muscle mass, respectively (p < 0.05). Of the total, 15.2% of the patients with normal muscle mass, 18.4% of those with moderately reduced muscle mass, and 66.7% of those with severely reduced muscle mass had diabetes. The prevalence of severe muscle mass loss was higher in those with diabetes than in those without diabetes (22.2% vs. 2.8%, p < 0.05). Patients with obesity-associated muscle wasting showed higher fibrinogen (613.9 ± 155.1 vs. 512.9 ± 159.5 mg/dL, p < 0.05) and CPR (1.4 ± 1.3 vs. 0.6 ± 0.8 mg/dL, p < 0.05) blood concentrations than those with normal body composition.Conclusion: Obesity and diabetes were strongly associated with muscle mass loss in our PD patients. It remains to be established whether prevention of obesity with nutritional interventions can halt the occurrence of muscle mass loss in patients on PD. [ABSTRACT FROM AUTHOR]

Background: specific bioelectrical impedance vector analysis (BIVA) has been proposed as an alternative bioimpedance method for evaluating body composition. This investigation aimed to verify the ability of specific BIVA in identifying changes in fat mass after a 16-week lifestyle program in former athletes. Methods: The 94 participants included in the Champ4life project (clinicaltrials.gov: NCT03031951) were randomized into intervention (n = 49) and control (n = 45) groups, from which 82 athletes completed the intervention (age 43.9 ± 9.2 y; body mass index 31.1 ± 4.6 kg/m2). Fat mass was estimated by dual-energy X-ray absorptiometry. Bioelectric resistance, reactance, phase angle, and vector length were assessed by bioelectric impedance spectroscopy, and the BIVA procedure was applied. Results: A significant (p < 0.05) group x time interaction for fat mass, specific resistance, reactance, and vector length was found. Fat mass and vector length significantly (p < 0.05) decreased in the intervention group, while no change was measured in the control group. Considering the participants as a whole group, changes in vector length were associated with changes in fat mass percentage (r2 = 0.246; β = 0.33; p < 0.001) even after adjusting for age, sex, and group (R2 = 0.373; β = 0.23; p = 0.002). Conclusions: The specific BIVA approach is suitable to track fat mass changes during an intervention program aimed to reduce body fat in former athletes.

This investigation aimed to compare the effects of suspension training versus traditional resistance exercise using a combination of bands and bodyweight on body composition, bioimpedance vector patterns, and handgrip strength in older men. Thirty-six older men (age 67.4 ± 5.1 years, BMI 27.1 ± 3.3 kg/m2) were randomly allocated into suspension training (n = 12), traditional training (n = 13), or non-exercise (n = 11) groups over a 12-week study period. Body composition was assessed using conventional bioelectrical impedance analysis and classic and specific bioelectric impedance vector analysis, and handgrip strength was measured with a dynamometer. Results showed a significant (p < 0.05) group by time interaction for fat mass, fat-free mass, total body water, skeletal muscle index, classic and specific bioelectrical resistance, classic bioelectrical reactance, phase angle, and dominant handgrip strength. Classic and specific vector displacements from baseline to post 12 weeks for the three groups were observed. Handgrip strength increased in the suspension training group (p < 0.01, ES: 1.50), remained stable in the traditional training group, and decreased in the control group (p < 0.01, ES: −0.86). Although bodyweight and elastic band training helps to prevent a decline in muscle mass and handgrip strength, suspension training proved more effective in counteracting the effects of aging in older men under the specific conditions studied.

Body composition is acknowledged as a determinant of athletic health and performance. Its assessment is crucial in evaluating the efficiency of a diet or aspects related to the nutritional status of the athlete. Despite the methods traditionally used to assess body composition, bioelectric impedance analysis (BIA) and bioelectric impedance vector analysis (BIVA) have recently gained attention in sports, as well as in a research context. Only until recently have specific regression equations and reference tolerance ellipses for athletes become available, while specific recommendations for measurement procedures still remain scarce. Therefore, the present narrative review summarizes the current literature regarding body composition analysis, with a special focus on BIA and BIVA. The use of specific technologies and sampling frequencies is described, and recommendations for the assessment of body composition in athletes are provided. Additionally, the estimation of body composition parameters (i.e., quantitative analysis) and the interpretation of the raw bioelectrical data (i.e., qualitative analysis) are examined, highlighting the innovations now available in athletes. Lastly, it should be noted that, up until 2020, the use of BIA and BIVA in athletes failed to provide accurate results due to unspecific equations and references; however, new perspectives are now unfolding for researchers and practitioners. In light of this, BIA and especially BIVA can be utilized to monitor the nutritional status and the seasonal changes in body composition in athletes, as well as provide accurate within- and between-athlete comparisons.

The pathophysiology of peripheral congestion is poorly investigated in patients with acute heart failure (AHF). to evaluate the relative contribution of serum colloid osmotic pressure (COP), relative plasma volume status (PVS), biomarkers of renal function, electrolytes, haemoglobin, and brain natriuretic peptide (BNP) in peripheral fluid overload using bioimpedance vector analysis (BIVA). We retrospectively analysed data from 485 patients with AHF. Hydration status was evaluated by semiquantitative and quantitative approach using BIVA (R/Xc graph) and Hydration Index (HI), respectively. COP was calculated from albumin and total protein concentration, while relative PVS was calculated from validated equations. Congestion assessed by BIVA was observed in 304 (63%) patients and classified as mild (30%), moderate (42%), and severe (28%). On univariate analysis, HI was inversely correlated with COP (P < 0.01), glomerular filtration rate (P < 0.01), and haemoglobin (P < 0.01), while positive correlations were found for relative PVS (P < 0.05), BNP (P < 0.01), and blood urea nitrogen (BUN; P < 0.01). On stepwise multivariate analysis, COP explained 12% of the total variability, while BUN, PVS, haemoglobin, and BNP added a further 6%, 4%, 2%, and 1%, respectively, to the final explanatory model. COP was the major determinant of the presence and entity of peripheral congestion assessed by BIVA. BUN, PVS, haemoglobin, and BNP revealed reduced influence on congestion as compared with COP. Routine laboratory testing could be useful in peripheral fluid accumulation. Future studies should evaluate the relationship between COP and pharmacological target therapies for the fluid management of AHF patients. [ABSTRACT FROM AUTHOR]

This study aimed to provide the first description of the wholebody bioimpedance vector of nine non-professional triathletes, and to assess body mass (BM) and vector variations evoked by an ultra-endurance triathlon event. Anthropometric and bioelectrical assessments were performed before (PRE), after (POST), and 48 hours following the race (POST48h). Bioimpedance vector analysis (BIVA) showed triathletes' vectors placed to the left of the major axis and mostly outside the 50% tolerance ellipse of the reference population. Vector migration in POST indicated dehydration, paralleled by a decrease in BM (p = 0.0001). Increased hydration status from POST to POST48h was suggested by a reversed vector migration and increased BM (p = 0.0001). Compared to PRE, POST48h values reflected fluid retention by changes in BIVA, while BM was still lower (p = 0.0001). Racing time was positively related to basal resistance -R/h- (r = 0.68; p = 0.04) and bioimpedance -Z/h- (r = 0.68; p = 0.045). Besides, basal R/h and Z/h were positively related to PRE-to-POST changes of R/h and Z/h (r = 0.80; p = 0.009). PRE-to-POST changes of R/h and Z/h were positively related to racing time (r = 0.80, p = 0.01) and internal workload (r = 0.80, p ≤ 0.02). Notwithstanding the lack of significant correlation between BM and bioelectrical parameters, the vector's behavior was explained from a multifactorial perspective (including BM variations) by using multiple regression analysis. On the other hand, BM changes were not related to racing time, internal workload or energy deficit (ranges: r = - 0.46 to 0.65; p = 0.06 to 0.98). In conclusion, these triathletes exhibit a specific bioelectrical distribution. Furthermore, vector migration was consistent with fluid loss induced by the event. Finally, vector analysis seems to provide additional information about hydration changes 48h after the event in comparison with BM alone. [ABSTRACT FROM AUTHOR]

Purpose: Bioimpedance data through bioimpedance vector analysis (BIVA) is used to evaluate cellular function and body fluid content. This study aimed to (i) identify whether BIVA patters differ according to the competitive period and (ii) provide specific references for assessing bioelectric properties at the start of the season in male elite soccer players. Methods: The study included 131 male soccer players (age: 25.1 ± 4.7 yr, height: 183.4 ± 6.1 cm, weight: 79.3 ± 6.6) registered in the first Italian soccer division (Serie A). Bioimpedance analysis was performed just before the start of the competitive season and BIVA was applied. In order to verify the need for period-specific references, bioelectrical values measured at the start of the season were compared to the reference values for the male elite soccer player population. Results: The results of the two-sample Hotelling T2 tests showed that in the bivariate interpretation of the raw bioimpedance parameters (resistance (R) and reactance (Xc)) the bioelectric properties significantly (T2 = 15.3, F = 7.6, p ≤ 0.001, Mahalanobis D = 0.45) differ between the two phases of the competition analyzed. In particular, the mean impedance vector is more displaced to the left into the R-Xc graph at the beginning of the season than in the first half of the championship. Conclusions: For an accurate evaluation of body composition and cellular health, the tolerance ellipses displayed by BIVA approach into the R-Xc graph must be period-specific. This study provides new specific tolerance ellipses (R/H: 246 ± 32.1, Xc/H: 34.3 ± 5.1, r: 0.7) for performing BIVA at the beginning of the competitive season in male elite soccer players.

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.

Protein Energy Wasting (PEW) in hemodialysis (HD) patients is a multifactorial condition due to specific pathology-related pathogenetic mechanisms, leading to loss of skeletal muscle mass in HD patients. Computed Tomography and Magnetic Resonance Imaging still represent the gold standard techniques for body composition assessment. However, their widespread application in clinical practice is difficult and body composition evaluation in HD patients is mainly based on conventional anthropometric nutritional indexes and bioelectrical impedance vector analysis (BIVA). Little data is currently available on ultrasound (US)-based measurements of muscle mass and fat tissue in this clinical setting. The purpose of our study is to ascertain: (1) if there are differences between quadriceps rectus femoris muscle (QRFM) thickness and abdominal/thigh subcutaneous fat tissue (SFT) measured by US between HD patients and healthy subjects; (2) if there is any correlation between QRFM and abdominal/thigh SFT thickness by US, and BIVA/conventional nutritional indexes in HD patients. We enrolled 65 consecutive HD patients and 33 healthy subjects. Demographic and laboratory were collected. The malnutrition inflammation score (MIS) was calculated. Using B-mode US system, the QRFM and SFT thicknesses were measured at the level of three landmarks in both thighs (superior anterior iliac spine, upper pole of the patella, the midpoint of the tract included between the previous points). SFT was also measured at the level of the periumbilical point. The mono frequency (50 KHz) BIVA was conducted using bioelectrical measurements (Rz, resistance; Xc, reactance; adjusted for height, Rz/H and Xc/H; PA, phase angle). 58.5% were men and the mean age was 69 (SD 13.7) years. QRFM and thigh SFT thicknesses were reduced in HD patients as compared to healthy subjects (p < 0.01). Similarly, also BIVA parameters, expression of lean body mass, were lower (p < 0.001), except for Rz and Rz/H in HD patients. The average QRFM thickness of both thighs at top, mid, lower landmarks were positively correlated with PA and body cell mass (BCM) by BIVA, while negatively correlated with Rz/H (p < 0.05). Abdominal SFT was positively correlated with PA, BCM and basal metabolic rate (BMR) (p < 0.05). Our study shows that ultrasound QRFM and thigh SFT thicknesses were reduced in HD patients and that muscle ultrasound measurements were significantly correlated with BIVA parameters.

Objectives Reference values of the bioelectrical impedance vector for the Spanish child and adolescent population are needed for assessing body composition and hydration status in this population. The aim of this study is to provide reference values of the bioelectrical impedance vector in Spanish children and adolescents aged 4-18 years from Castilla y León. Methods This was a cross-sectional descriptive study conducted in 4401 Spanish healthy children and adolescents aged 4-18 years (2265 boys and 2136 girls). Resistance and reactance were measured with a single-frequency impedance analyzer at 50 kHz (tetrapolar analysis). The values of resistance and reactance normalized by height were used to plot the bivariate 50th, 75th, and 95th percentiles of the population by age group. Mean impedance vectors were compared with Hotelling's T2 test for vector analysis (differences being considered significant if p < .05). Results Tolerance ellipses were drawn for the Spanish child and adolescent population studied. The mean impedance vector showed displacement across all age groups except for (1) girls aged 12-13 years, (2) girls aged 15-18 years, and (3) boys aged 16-18 years. There were sex-related differences in the mean impedance vector in all age ranges, even in prepubertal children. Among adolescents, the patterns of the vector displacement were consistent with the timing of normal growth and development in all groups and are attributable to the maturation process. Conclusions New tolerance ellipses have been constructed for Spanish children and adolescents by sex and age. These ellipses reflect the timing of normal childhood growth and development. [ABSTRACT FROM AUTHOR]

Purpose:Conventional Bioelectrical Impedance Analysis (BIA) or Bioelectrical Impedance Vector Analysis (BIVA) can provide direct evaluations of body composition. The purpose of this study was to evaluate lean and fat mass (FM), and hydration of children involved in daily competitive sports.Methods:190 non-athletic [8.2–10.5 years] and 29 competitive children [8.0–10.5 years] were enrolled. They were evaluated: at baseline (t0), 6 months (t1) and one year (t2). Anthropometric, BIA and BIVA, lean and FM, and hydration evaluations were performed.Results:Resistance (R/h) and reactance (Xc/h) were lower att0 in competitive individuals when compared to controls. Xc/h (+3.28) significantly increases in competitive when compared to non-competitive individuals (+0.66,pfor difference: 0.011), while phase angle (PA) was lower att0 (5.72 vs. 6.17,p < .001) and after 6 months (p = .001). Total body water adjusted for height (TBW/h) significantly increased only in non-athletes (+0.50 ± 0.13,p < .001) betweent0andt1. Att1, extracellular water (ECW) significantly decreased (p = .026) in the two groups: −0.45 ± 0.19% in non-competitive, −1.63 ± 0.49% in competitive subjects, while intracellular water (ICW) increased. At one-year follow-up (t2), there were no statistically significant differences in R/h, Xc/h and PA in competitive individuals when compared to baseline andt1. Furthermore, we observed att2that hours/week of training, age, male gender and body mass index can influence FFM/h and FM/h in both competitive and non-competitive subjects. In particular, a direct correlation was for hours/week and FFM/h, inverse for hours/week and FM/h.Conclusions:Body mass index does not allow evaluating differences in lean body mass and FM between athletes and non-athletes. BIA and BIVA can give more reliable details about body composition differences in competitive adolescents and non-competitive, outlining a progressive decline in ECW and increase in ICW without affecting TBW composition of athletes. [ABSTRACT FROM PUBLISHER]

We hypothesize that improvements in the gut microbiota are capable of ameliorating gut permeability and, consequently, reducing systemic inflammation and the risk of frailty. This study aims to evaluate some effects of synbiotic supplementation on inflammatory markers and the body composition of the elderly at risk of frailty. In a double-blind study that lasted three months, 17 elderly individuals fulfilling one frailty criteria (grip strength) were randomly distributed into two groups: SYN (n = 9), daily intake of synbiotic (6 g Frutooligossacarides, 108 to 109 CFU Lactobacillus paracasei, 108 to 109 CFU Lactobacillus rhamnosus, 108 to 109 CFU Lactobacillus acidophilus and 108 to 109 CFU Bifidobacterium lactis), or placebo (maltodextrin; PLA; n = 8). Subjects were analyzed for anthropometric measurements, bioelectric impedance with vectorial analysis (BIVA), IL-6 and TNF-α. A comparison between groups did not show any difference for the variables investigated. In turn, individual analysis of electrical impedance (BIVA) demonstrated that the majority of SYN individuals maintained or improved their tissue hydration, when compared to the PLA group after supplementation. In conclusion, three months of synbiotic supplementation did not promote any significant changes in inflammatory cytokines or body composition, but demonstrated a trend towards a preservation of hydration status in apparently healthy elderly individuals.

Elisabetta Marini,1 Roberto Buffa,1 Bruno Saragat,1 Alessandra Coin,2 Elena Debora Toffanello,2 Linda Berton,2 Enzo Manzato,2 Giuseppe Sergi21Department of Environmental and Life Sciences, University of Cagliari, Italy; 2Department of Medicine-DIMED, Geriatrics Section, University of Padua, ItalyPurpose: The aim of this paper is to investigate whether bioelectrical impedance vector analysis (BIVA) can be a suitable technique for the assessment of sarcopenia. We also investigate the potential use of specific BIVA as an indicator of sarcopenic obesity.Subjects and methods: The sample comprised 207 free-living elderly individuals of both sexes, aged 65 to 93 years. Anthropometric and bioelectrical measurements were taken according to standard criteria. The “classic” and “specific” BIVA procedures, which respectively correct bioelectrical values for body height and body geometry, were used. Dual energy X-ray absorptiometry (DXA) was used as the reference method for identifying sarcopenic and obese sarcopenic individuals. Bioelectrical and DXA values were compared using Student’s t-test and Hotelling’s T2 test, as well as Pearson’s correlation coefficient.Results: According to classic BIVA, sarcopenic individuals of both sexes showed higher values of resistance/height (R/H; p < 0.01) and impedance/height (Z/H; p < 0.01), and a lower phase angle (p < 0.01). Similarly, specific BIVA showed significant differences between sarcopenic and nonsarcopenic individuals (men: T2 = 15.7, p < 0.01; women: T2 = 10.7, p < 0.01), with the sarcopenic groups showing a lower specific reactance and phase angle. Phase angle was positively correlated with the skeletal muscle mass index (men: r = 0.52, p < 0.01; women: r = 0.31, p < 0.01). Specific BIVA also recognized bioelectrical differences between sarcopenic and sarcopenic obese men (T2 = 13.4, p < 0.01), mainly due to the higher values of specific R in sarcopenic obese individuals.Conclusion: BIVA detected muscle-mass variations in sarcopenic individuals, and specific BIVA was able to discriminate sarcopenic individuals from sarcopenic obese individuals. These procedures are promising tools for screening for presarcopenia, sarcopenia, and sarcopenic obesity in routine practice.Keywords: aging, body composition, BIVA, DXA

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Objective To evaluate the role of bioelectrical impedance vector analysis (BIVA) and brain natriuretic peptide (BNP) in detecting peripheral congestion in heart failure (HF). Background BIVA/BNP are biomarkers for congestion in acute (ADHF) and chronic HF. Methods 487 ADHF and 413 chronic HF patients underwent BIVA and BNP tests. Results BIVA was more accurate than BNP in detecting peripheral congestion both in ADHF (AUC 0.88 vs 0.57 respectively; p < 0.001) and chronic HF patients (AUC 0.89 vs 0.68, respectively; p < 0.001). In ADHF patients, the optimal BNP cut-off for discriminating presence or absence of edema was >870 pg/mL (PPV = 48% and NPV = 58%) whereas in chronic HF it was >216 pg/mL (PPV = 18% and NPV = 95%). The BIVA detected edema when the vector fell into the lower pole of 75th percentile tolerance ellipse (PPV = 84% and NPV = 78%) in ADHF, the lower pole of 50% (PPV = 68% and NPV = 95%) in chronic HF. Conclusions In HF patients, BIVA is an easy, fast technique to assess peripheral congestion, and is even more accurate than BNP. [ABSTRACT FROM AUTHOR]

Background: Few dehydration assessment measures provide accurate information; most are based on reference change values and very few are diagnostically accurate from a single observation or measure. Bioelectrical impedance may lack the precision to detect common forms of dehydration in healthy individuals. Limitations in bioimpedance may be addressed by a unique resistance-reactance (RXc)-score graph method, which transforms vector components into z scores for use with any impedance analyzer in any population. Objective: We tested whether the RXc-score graph method provides accurate single or serial assessments of dehydration when compared with gold-standard measures of total body water by using stable isotope dilution (deuterium oxide) combined with body-weight changes. Design: We retrospectively analyzed data from a previous study in which 9 healthy young men participated in 3 trials: euhydration (EUH), extracellular dehydration (ED; via a diuretic), and intracellular dehydration (ID; via exercise in the heat). Results: Participants lost 4-5% of their body weight during the dehydration trials; volume loss was similar between trials (ID compared with ED group: 3.5 ± 0.8 compared with 3.0 ± 0.6 L; P > 0.05). Despite significant losses of body water, most RXc vector scores for ED and ID groups were classified as "normal" (within the 75% population tolerance ellipse). However, directional displacement of vectors was consistent with loss of volume in both ED and ID conditions compared with the EUH condition and tended to be longer in ED than in ID conditions (P = 0.054). Conclusions: We conclude that, whereas individual RXc-score graph values do not provide accurate detection of dehydration from single measurements, directional changes in vector values from serial measurements are consistent with fluid loss for both ED and ID conditions. The RXc-score graph method may therefore alert clinicians to changes in hydration state, which may bolster the interpretation of other recognized change measures of hydration. Am J Clin Nutr 2016;103:724-9. [ABSTRACT FROM AUTHOR]

Raw bioelectrical impedance analysis (BIA) data [resistance (R); reactance (Xc)] through bioelectrical impedance vector analysis (BIVA) and phase angle (PhA) have been used to evaluate cellular function and hydration status. The purpose of this investigation was to examine the effects of resistance training (RT) on classic and specific BIVA in elderly women. Twenty women (mean ± SD; age: 71.9 ± 6.9 years; BMI: 24.5 ± 3.0 kg m − 2 ) completed a 6-month RT program. Whole-body, single-frequency BIA, body geometry, and leg strength (5RM) measures were completed at baseline (t0), 3 months (t3), and 6 months (t6). The mean impedance vector displacements were compared using Hotelling's T 2 test to evaluate changes in R and Xc relative to height (R/ht; Xc/ht) or body volume (R sp ; Xc sp ) estimated from the arms, legs, and trunk. 5RM, PhA, and BIVA variables were compared using ANOVA. PhA improved at t6 (p < 0.01), while 5RM improved at t3 and t6 (p < 0.01). Using classic BIVA, 6 months (T 2 = 31.6; p < 0.01), but not 3 months of RT (T 2 = 4.5; p = 0.20), resulted in significant vector migration. Using specific BIVA, 6 months (T 2 = 24.4; p < 0.01), but not 3 months of RT (T 2 = 5.5; p = 0.10), also resulted in significant vector migration. 5RM was correlated to both PhA (r = 0.48–56) and Xc sp (r = 0.45–53) at all time points. Vector displacements were likely the result of improved cellular integrity (Xc sp ) and cellular health (PhA). [ABSTRACT FROM AUTHOR]

Background and purpose The prevalence of sarcopenia varies depending on environments and populations of older people. What is more, in separate studies different diagnostic criteria are used. The aim of this study was to investigate the prevalence of sarcopenia in an examined sample of older patients and to verify whether bioelectrical impedance analysis (BIVA) may be used as an auxiliary method in diagnosing of sarcopenia among hospitalized older patients. Materials and methods The European Working Group of Sarcopenia in Older People (EWGSOP) algorithm using two different muscle mass criteria was applied and among misclassified subjects we used BIVA parameters to verify the prevalence of sarcopenia. Results The prevalence of sarcopenia ranged between 60.7% and 79.8% according to the two suggested different muscle mass cutpoints. Seventeen subjects mismatched according to used muscle mass cutpoints were further analyzed individually on the basis of their mean BIVA parameters. The location of the confidence ellipse of misclassified women overlapped with the women group diagnosed as “nonsarcopenic”, while sarcopenic group was statistically different. Conclusions BIVA is a valuable tool that may be used as an auxiliary method to verify the prevalence of sarcopenia among older women. Mismatched women were characterized with BIVA parameters similar to that of nonsarcopenic women and clearly different from BIVA parameters of their sarcopenic peers. Due to the small number of nonsarcopenic men in our sample further studies are required to verify if this method may also be an additional assessment tool for men. [ABSTRACT FROM AUTHOR]