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Abstract The assessment of athletic performance using non‐invasive methods has been a significant focus in research aimed at measuring physiological parameters. This study explores the application of bioelectrical impedance vector analysis (BIVA) among track and field athletes, with a focus on sex differences, electrode configuration, and the correlation between BIVA parameters and jump performances. This cross‐sectional study involved 61 Italian track and field athletes: 31 females and 30 males (age: 21.4 ± 3.8; 21.1 ± 2.6 years; stature: 166.1 ± 6.1; 180.1 ± 5.0 cm; body mass: 57.4 ± 9.7; 72.5 ± 10.5 kg, respectively). Anthropometric measurements, bioelectrical impedance analysis, and athletic jump performance were conducted. The RXc graph, two‐sample Hotelling's T2 test for BIVA, and one‐way ANOVA for specialty comparisons were employed. Pearson and Spearman's tests evaluated the correlations between BIVA parameters and jump performance. Differences in bioimpedance values were observed between athlete groups. Lateral asymmetries were more pronounced in females. Correlations between BIVA and jump performance also varied by sex and electrode configuration, ranging from r = −0.072, p = 0.699–r = 0.555, p = 0.001 in females, and from r = 0.204, p = 0.281–r = 0.691, p = 0.001 in males. This study highlights the utility of BIVA in providing rapid and non‐invasive assessments of body composition and its relationship with jump performance, considering variations in athlete sex and electrode configuration.

Objectives: The study aimed to investigate the relationship between raw bioelectrical data and physical performance in track and field athletes. Specifically, the objectives were to determine: 1) whether a regional bioelectrical impedance approach provides additional insights compared to whole-body analysis, 2) the reliability of the Levi Muscle Index (LMI) in this context, and 3) whether there are differences in these relationships between male and female athletes. Design: This study utilized a cross-sectional design involving thirty-one female athletes (mean age 21.4 ± 3.8 years) and thirty male athletes (mean age 21.1 ± 2.6 years) from track and field. On a single day, participants underwent whole-body and regional bioelectrical impedance assessments focusing on the lower limbs, alongside strength and speed performance tests. Results: The study found no significant differences in the relationship between whole-body versus regional bioelectrical impedance and performance tests. Resistance (R) demonstrated an inverse correlation, while phase angle (PhA) and Levi Muscle Index (LMI) showed direct correlations with most performance variables in track and field athletes. Significant differences were observed between male and female athletes across all parameters, with male athletes exhibiting superior performance, higher PhA and LMI values, and stronger correlation coefficients compared to females. Conclusions: In summary, this study highlights the intricate relationship between body composition and physical performance in athletes. It underscores the importance of considering sex differences and the reliability of raw bioelectrical data, whether obtained through regional or whole-body approaches, in assessing athletic performance.

Assessment of cellular states of body is essential to ascertain physical fitness of a human. This paper investigates the cellular states of university students by analyzing body composition features such as body cell mass (BCM), total body water (TBW), skeletal muscle mass (SMM), basal metabolic rate (BMR) and bio-impedance measurements including bioelectrical impedance (BI), phase angle (PA) of human body. Utilizing bioelectrical impedance spectroscopy (BIS), data were collected and categorized into healthy cellular states (HCS) and stiffened cellular states (SCS) based on body cell mass (BCM) and total body water (TBW). Bioelectrical impedance vector analysis (BIVA) and Nyquist plot were employed for further differentiation. Support-vector machines (SVM), decision trees (DT), and random forest (RF) machine-learning models were applied for classification, with RF exhibiting the highest accuracy. Results reveal that students in HCS exhibit elevated BCM (35.22–55.68 kg), TBW (39.25–56.61 l), SMM (26.83–34.93 kg), BMR (25.67—28.67 kg), and PA (7.21–9.29 degree), but lower BI (443.39–569.45 Ω) compared to SCS students. Therefore, RF classifier was selected for its superior performance in detecting cellular states.

Objectives: CrossFit® is a high-intensity sport characterized by various workouts that require strength, speed, endurance, or agility, impacting participants' body composition. This observational study aimed to determine the morphological (anthropometrical and bioelectrical) profile of CrossFit® athletes and to compare them with other athletic populations. Methods: Anthropometrical measurements and bioelectrical vector analysis (classic and specific approaches) were performed on 145 CrossFit® practitioners (107 men aged 30.7 ± 8.4 years and 38 women aged 28.1 ± 6.7 years). Each participant's relative somatotype was calculated and compared between sexes and with a Spanish CrossFit® athletes' group. Resistance-reactance graphs and Hotelling's T2 test were applied to characterize the sample, compare them with an athletes' reference population, and identify differences between somatotype groups. Results: The most represented somatotype in both groups was the balanced mesomorph (male 3.5–5.2 - 1.7 and female 4.4–4.5 - 1.8). Compared with Spanish CrossFit® athletes, significant differences were denoted for men but not women (SAD = 2.3). The bioelectrical graphs indicated that the distribution of CrossFit® athletes is quite heterogeneous and within average values for the athlete's reference. The mesomorphic and endomorphic components were associated with a higher phase angle. Conclusions: CrossFit® practitioners predominantly present a mesomorphic component and show a body type like other power athletes, although with less pronounced characteristics. The somatotype may influence the vector's position in the RXc graphs. This study provided the bioelectrical tolerance ellipses for CrossFit® practitioners in classic and specific approaches for the first time.

Abstract Background Bioelectrical impedance analysis (BIA) is a rapid and user-friendly technique for assessing body composition in sports. Currently, no sport-specific predictive equations are available, and the utilization of generalized formulas can introduce systematic bias. The objectives of this study were as follows: (i) to develop and validate new predictive models for estimating fat-free mass (FFM) components in male elite soccer players; (ii) to evaluate the accuracy of existing predictive equations. Methods A total of 102 male elite soccer players (mean age 24.7 ± 5.7 years), participating in the Italian first league, underwent assessments during the first half of the in-season period and were randomly divided into development and validation groups. Bioelectrical resistance (R) and reactance (Xc), representing the bioimpedance components, were measured using a foot-to-hand BIA device at a single frequency of 50 kHz. Dual-energy X-ray absorptiometry was employed to acquire reference data for FFM, lean soft tissue (LST), and appendicular lean soft tissue (ALST). The validation of the newly developed predictive equations was conducted through regression analysis, Bland–Altman tests, and the area under the curves (AUC) of regression receiver operating characteristic (RROC) curves. Results Developed models were: FFM = − 7.729 + (body mass × 0.686) + (stature2/R × 0.227) + (Xc × 0.086) + (age × 0.058), R2 = 0.97, Standard error of estimation (SEE) = 1.0 kg; LST = − 8.929 + (body mass × 0.635) + (stature2/R × 0.244) + (Xc × 0.093) + (age × 0.048), R2 = 0.96, SEE = 0.9 kg; ALST = − 24.068 + (body mass × 0.347) + (stature2/R × 0.308) + (Xc × 0.152), R2 = 0.88, SEE = 1.4 kg. Train-test validation, performed on the validation group, revealed that generalized formulas for athletes underestimated all the predicted FFM components (p 0.05), with R2 values ranging from 0.83 to 0.91, and no trend (p > 0.05). The AUC scores of the RROC curves indicated an accuracy of 0.92, 0.92, and 0.74 for FFM, LST, and ALST, respectively. Conclusions The utilization of generalized predictive equations leads to an underestimation of FFM and ALST in elite soccer players. The newly developed soccer-specific formulas enable valid estimations of body composition while preserving the portability of a field-based method.

In humans, the transient receptor potential vanilloid 1 (TRPV1) gene is activated by exogenous (e.g., high temperatures, irritating compounds such as capsaicin) and endogenous (e.g., endocannabinoids, inflammatory factors, fatty acid metabolites, low pH) stimuli. It has been shown to be involved in several processes including nociception, thermosensation, and energy homeostasis. In this study, we investigated the association between TRPV1 gene variants, sensory perception (to capsaicin and PROP), and body composition (BMI and bioimpedance variables) in human populations. By comparing sequences deposited in worldwide databases, we identified two haplotype blocks (herein referred to as H1 and H2) that show strong stabilizing selection signals (MAF approaching 0.50, Tajima’s D > +4.5) only in individuals with sub-Saharan African ancestry. We therefore studied the genetic variants of these two regions in 46 volunteers of sub-Saharan descent and 45 Italian volunteers (both sexes). Linear regression analyses showed significant associations between TRPV1 diplotypes and body composition, but not with capsaicin perception. Specifically, in African women carrying the H1-b and H2-b haplotypes, a higher percentage of fat mass and lower extracellular fluid retention was observed, whereas no significant association was found in men. Our results suggest the possible action of sex-driven balancing selection at the non-coding sequences of the TRPV1 gene, with adaptive effects on water balance and lipid deposition.

Eating disorders (EDs) manifest as persistent disruptions in eating habits or related behaviors, significantly impacting physical health and psychosocial well-being. Nutritional assessment in ED patients is crucial for monitoring treatment efficacy. While dual-energy X-ray absorptiometry (DEXA) remains standard, interest in alternative methods such as bioelectrical impedance vector analysis (BIVA) and Nutritional Ultrasound® (NU) has risen due to their affordability and portability. Additionally, hand dynamometry offers a user-friendly approach to assessing grip strength (HGS), indicative of nutritional status. A prospective study was carried out to evaluate the utility of BIVA, NU®, and HGS in 43 female AN patients. Measurements were taken at baseline and hospital discharge. A total of 41 patients completed the study. After the intervention, numerous BIVA-related parameters such as fat (3.5 ± 2 kg vs. 5.3 ± 2.7 kg, p < 0.001) and free fat mass (33.9 ± 3.8 kg vs. 37.5 ± 4.1 kg, p < 0.001) were partially restored. Similarly, Nutritional Ultrasound® showed promising results in assessing body composition changes such as total abdominal fat tissue (0.5 ± 0.3 cm vs. 0.9 ± 0.3 cm, p < 0.05). In the same way, rectus femoris cross-sectional area values correlated with clinical outcomes such as free fat mass (0.883, p < 0.05) and appendicular muscle mass (0.965, p < 0.001). HGS reached the normality percentile after the intervention (21.6 ± 9.1 kg vs. 25.9 ± 12.3 kg, p < 0.05), demonstrating a significant association between grip strength and body composition parameters such as free fat mass (0.658, p < 0.001) and appendicular muscle mass (0.482, p < 0.001). Incorporating BIVA-, NU®-, and HGS-enhanced nutritional assessment into the treatment of AN patients offers cost-effective, portable, and non-invasive alternatives to DEXA. These techniques offer valuable insights into changes in body composition and nutritional status, which, in turn, facilitate treatment monitoring and contribute to improved patient outcomes.

Background This study aims to investigate body fluids and muscle changes evoked by different trail races using anthropometric, bioelectrical, and creatine kinase (CK) measurements. Methods A total of 92 subjects (55 men, 37 women) participating in three different races of 14, 35, and 52 km were evaluated before (PRE) and after (POST) the races. Classic bioelectrical impedance vector analysis was applied at the whole-body level (WB-BIVA). Additionally, muscle-localized bioelectrical assessments (ML-BIVA) were performed in a subgroup of 11 men (in the quadriceps, hamstrings, and calves). PRE-POST differences and correlations between bioelectrical values and CK, running time and race distance were tested. Results Changes in whole-body vectors and phase angles disclosed an inclination towards dehydration among men in the 14, 35, and 52 km groups (p < 0.001), as well as among women in the 35 and 52 km groups (p < 0.001). PRE Z/H was negatively correlated with running time in the 35 km men group and 14 km women group (r = −0.377, p = 0.048; r = −0.751, p = 0.001; respectively). POST Z/H was negatively correlated with running time in the 14 km women group (r = −0.593, p = 0.02). CK was positively correlated with distance in men and women (p < 0.001) and negatively correlated with reactance and vector length in the 14 km men group (p < 0.05). ML-BIVA echoed the same tendency as the WB-BIVA in the 35 and 52 km runners, with the most notable changes occurring in the calves (p < 0.001). Conclusions WB-BIVA and CK measurements underscored a conspicuous trend towards post-race dehydration and muscle damage, displaying a weak association with performance. Notably, ML-BIVA detected substantial alterations primarily in the calves. The study underscores the utility of BIVA as a technique to assess athlete’s body composition changes.

(1) Background: Cardiovascular disease is one of the leading causes of mortality after liver transplantation. Body composition and cardiovascular performance assessment represent a potential approach for modulating lifestyle correction and proper follow-up in chronic disease patients. This study aimed to verify the additional role of an unsupervised physical activity program in a sample of male liver transplant recipients who follow the Mediterranean diet. (2) Methods: Thirty-three male liver transplant recipients were enrolled. Sixteen subjects followed a moderate-intensity home exercise program in addition to nutritional support, and seventeen received advice on the Mediterranean diet. After six months, bioelectrical vector impedance analysis (BIVA) and cardiopulmonary exercise testing (CPET) were performed. (3) Results: No differences in CPET (VO2 peak: exercise 21.4 ± 4.1 vs. diet 23.5 ± 6.5 mL/kg/min; p = 0.283) and BIVA (Z/H: exercise 288.3 ± 33.9 vs. diet 310.5 ± 34.2 Ω/m; p = 0.071) were found. Furthermore, the BIVA values of resistance correlate with the submaximal performance of the Ve/VCO2 slope (R = 0.509; p < 0.05) and phase angle with the maximal effort of the VO2 peak (R = 0.557; p < 0.05). (4) Conclusions: Unsupervised physical exercise alone for six months does not substantially modify liver transplant recipients’ cardiovascular performance and hydration status, despite their adherence to a Mediterranean diet. The body composition analysis is useful to stratify the risk profile, and it is potentially associated with better outcomes in transplanted subjects.

This study was performed to evaluate the prognostic value of relative changes from admission to discharge (Δ%) of integrated congestion assessment to predict adverse outcomes in patients with irreversible heart failure (HF) during a one-year follow-up. The study included 122 patients (60% males, median age of 69 years) with decompensated HF. Most of the patients (92%) had a history of arterial hypertension, 53.3% had coronary heart disease, and 40.2% had type 2 diabetes mellitus. All patients underwent assessments, including NT-proBNP, lung ultrasound (LUS) B-line score, liver stiffness by transient elastography, and resistance and reactance by bioimpedance vector analysis (BIVA). The assessments were performed at admission and discharge, and a relative change from admission (delta percentage, Δ%) was calculated. Long-term clinical outcomes were assessed by a structured interview conducted 1, 3, 6, and 12 months after discharge. The cut-offs for the occurrence of the endpoint events were Δ% NT-proBNP of ≥ -25, Δ% liver stiffness of ≥ -44, Δ% B-line score on lung ultrasound of ≥ -73, Δ% BIVA resistance of ≤ 18, and Δ% BIVA reactance of ≤ 40. It was revealed that 55% of endpoint events, including 22 (18%) deaths and 33 (27%) readmissions, occurred within a median of 74 days (interquartile range: 33-147). Patients with an endpoint event had significantly worse values of all studied parameters in contrast to patients without it. There was a significant direct association between Δ% NT-proBNP and Δ% B-lines (r=0.18; P=0.04), and a highly reliable inverse association was observed between Δ% liver stiffness and Δ% BIVA reactance (r=-0.4; P

Aim. To study the effects of azilsartan medoxomil/chlorthalidone (AZM/CTD) and losartan/hydrochlorothiazide (LOS/HCT) combinations for NTproBNP levels, 6-minute walk test results, hydration status along with their antihypertensive efficacy according to clinical and 24-hour blood pressure in patients with hypertension and heart failure with preserved ejection fraction (HFpEF).Material and methods. An open randomized study included 56 patients with uncontrolled or untreated hypertension and HFpEF. Patients randomized to receive the AZM/CTD 40/12.5 mg/day (group 1; n=28) or LOS/HCT 100/12.5 (group 2; n=28) within 4 weeks. Patients who did not achieve the target BP

Background: Hydration status has a direct role in sports performance. Bioelectrical Impedance Vector Analysis (BIVA) and Urine Specific Gravity (USG) are commonly used to assess hydration. The study aims to identify the sensitivity and relationship between BIVA and USG in a field sports setting. Methods: BIVA and USG measurements were conducted five times throughout one rugby season. 34 elite male rugby players (25.1 ± 4.4 years; 184.0 ± 7.8 cm; 99.9 ± 13.4 kg) were enrolled. Differences over time were tested using one-way repeated measures ANOVA, and Bonferroni’s post-hoc test was applied in pairwise comparisons. Resistance-reactance graphs and Hotelling’s T2 test were used to characterize the sample and to identify bioelectrical changes. A repeated measures correlation test was conducted for BIVA-USG associations. Results: Two clear trends were seen: (1) from July to September, there was a vector shortening and an increase of the phase angle (p < 0.001); and (2) from December to April, there was a vector lengthening and a decrease of the phase angle (p < 0.001). USG reported neither changes nor correlation with BIVA longitudinally (p > 0.05). Vector variations indicated a body fluid gain (especially in the intracellular compartment) and a body cell mass increase during the preseason, suggesting a physical condition and performance improvement. During the last months of the season, the kinetic was the opposite (fluid loss and decreased body cell mass). Conclusions: Results suggested that BIVA is sensitive to physiological changes and a better option than USG for assessing hydration changes during a rugby sports season.

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.

This study aimed to characterize and monitor the body fluid and muscle changes during the Giro d’Italia in nine elite cyclists via bioelectrical (whole-body and muscle-localized) anthropometric and hematological analysis. There were three checkpoint assessments: at the beginning, middle, and end of the race. The Wilcoxon signed-rank test was used to compare the data at baseline and follow up. The Spearman correlation was used to explore relationships between variables. Hotelling’s T2 test was used to determine bioelectrical differences in the complex vector. Bodyweight did not change during the competition, despite bioelectrical and hematological data indicating that at the first half of the race, there was a fluid gain, and in the second half a fluid loss occurred, reaching baseline values. These changes were especially prevalent in the extracellular water compartment. Significant correlations between whole-body bioelectrical vector changes and red blood cell parameter changes were reported. The muscle group most sensitive to changes were the calves. Quadriceps, hamstrings, and calves reported a PhA decrease trend during the first half of the race, and an increase during the second half. Bioelectrical impedance vector analysis appears to be sensitive enough to detect hydration and cellular integrity adaptions induced by competitions as demanding as the Giro d’Italia.

The aim of this study was to evaluate the relationship between anaemia and biomarkers of central/peripheral congestion in heart failure (HF) and the impact on mortality. We retrospectively evaluated 434 acute/chronic HF (AHF/CHF) patients. Anaemia was defined as haemoglobin levels p < 0.001) and showed a significant correlation with the NYHA functional class and renal function. BNP and HI were significantly higher in patients with anaemia than in those without anaemia. Independent predictors of anaemia included BNP, estimated creatinine clearance (eCrCL), and HI. The all-cause mortality rate was 21%, which was significantly higher in patients with anaemia than in those without anaemia (30% vs. 14%, p < 0.001; hazard ratio: 2.6). At multivariate Cox regression analysis, BNP, eCrCL, and HI were independent predictors for mortality (Hazard ratios: 1.0002, 0.97, and 1.05, respectively), while anaemia was not. Anaemia correlates with HF status, functional class, renal function, BNP, and HI. Anaemia was not an independent predictor for mortality, acting as a disease severity marker in congestive patients rather than as a predictor of death.

This study aimed to compare phase angle (PhA) and bioelectrical impedance vector analysis (BIVA) values between adult patients with congenital adrenal hyperplasia caused by 21-hydroxylase deficiency (CAH21OHD) and a control group. A total of 22 patients (15 women, 22.9 ± 3.7 years) were compared with 17 controls (11 women, 27.0 ± 2.5 years). Body composition was determined by dual-energy X-ray absorptiometry. Bioelectrical impedance was used to calculate PhA, and BIVA was performed using specific software. Student’s t-test and analysis of covariance were used to compare groups. Hedges’ G and partial n2 were calculated for the effect estimates. Hotelling’s t2 test was used to compare the mean impedance vectors between the groups. The Mahalanobis test was used to determine the distance between confidence ellipses. Patients with CAH21OHD had a higher fat mass percentage than that of the control group (both sexes). There was no significant difference in PhA values between groups (CAH21OHD vs. control) in females (6.9° vs. 6.3°, p = 0.092) and males (8.2° vs. 8.1°, p = 0.849), after adjusting for covariates (age and height). BIVA analysis showed a significant difference in the mean impedance vectors between the female groups (T2 = 15.9, D = 1.58, p = 0.003) owing to the higher reactance/height (Δ = 8.5; p < 0.001) of the patients. The PhA did not significantly differ between the groups. Female patients had significantly higher reactance values. However, further studies are needed to determine the usefulness of bioimpedance parameters in evaluating the hydration status and cellular integrity of patients with CAH21OHD.

Circulating parathyroid hormone (PTH) concentrations increase in heart failure (HF) and are related to disease severity. The relationship between PTH and congestion is still a matter of debate. The objective of this analysis was to evaluate the role of PTH as a marker of congestion and prognosis in HF. We enrolled 228 patients with HF. Intact PTH concentrations and HYDRA score (constituted by: B-type natriuretic peptide, blood urea nitrogen–creatinine ratio, estimated plasma volume status, and hydration status) were evaluated. The study endpoint was all-cause mortality. PTH levels were higher in acute compared with chronic HF and in patients with clinical signs of congestion (i.e., peripheral oedema and orthopnea). PTH concentrations significantly correlated with NYHA class and HYDRA score. At multivariate analysis of HYDRA score, estimated glomerular filtration rate (eGFR), and corrected serum calcium were independently determinants of PTH variability. Fifty patients (22%) died after a median follow-up of 408 days (interquartile range: 283–573). Using univariate Cox regression analysis, PTH concentrations were associated with mortality (hazard ratio [HR]: 1.003, optimal cut-off: >249 pg/mL—area under-the-curve = 0.64). Using multivariate Cox regression analysis, PTH was no longer associated with death, whereas HYDRA score, left ventricular ejection fraction, and eGFR acted as independent predictors for mortality (HR: 1.96, 0.97, and 0.98, respectively). Our study demonstrated that intact PTH was related to clinical and subclinical markers of congestion. However, intact PTH did not act as an independent determinant of all-cause death in HF patients.

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.

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.

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.

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.

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.

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.

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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