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OBJECTIVES: The aim of this study was to evaluate body composition variability assessed by bioimpedance in relation to nutritional status assessed by anthropometry in children and adolescents living in countries characterized by contrasting nutritional conditions. METHODS: The sample was comprised of 8614 children (4245 males; 4369 females), aged 3 to 19 years, from Nepal (477 children), Uganda (488 children and adolescents), UK (297 children and adolescents) and US (7352 children and adolescents). Height-for-age (HAZ) and body mass index-for-age (BAZ) z-scores were calculated according to WHO growth references. Specific bioelectrical impedance vector analysis (BIVA) was used to evaluate body composition variability. In each population sample, the relationship of HAZ and BAZ with bioelectrical outcomes was analysed by confidence ellipses and cubic spline regression, controlling for sex and age. RESULTS: The participants from Uganda and Nepal were more affected by undernutrition, and those from the US and UK by obesity. In all groups, phase angle and specific vector length were weakly associated with HAZ, with null or opposite relationships in the different samples, whereas they were positively associated with BAZ. The stronger association was between vector length, indicative of the relative content of fat mass, and BAZ in the UK and US samples. Confidence ellipses showed that the relationships are more strongly related to phase angle in Nepalese and Ugandan samples. CONCLUSIONS: Bioelectrical values were more strongly associated with BAZ than HAZ values in all population samples. Variability was more related to markers of muscle mass in Ugandan and Nepalese samples and to indicators of fat mass in UK and US samples. Specific BIVA can give information on the variability of body composition in malnourished individuals.

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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.

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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.

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BACKGROUND & AIMS: Bioelectrical impedance analysis (BIA) for body composition estimation is increasingly used in clinical and field settings to guide nutrition and training programs. Due to variations among BIA devices and the proprietary prediction equations used, studies have recommended the use of raw measures of resistance (R) and reactance (Xc) within population-specific equations to predict body composition. OBJECTIVE: We compared raw measures from three BIA devices to assess inter-device variation and the impact of differences on body composition estimations. METHODS: Raw R, Xc, impedance (Z) parameters were measured on a calibrated phantom and athletes using tetrapolar supine (BIASUP4), octapolar supine (BIASUP8), and octapolar standing (BIASTA8) devices. Measures of R and Xc were compared across devices and graphed using BIA vector analysis (BIVA) and raw parameters were entered into recommended athlete-specific equations for predicting fat-free mass (FFM) and appendicular lean soft tissue (ALST). Whole-body FFM and regional ALST were compared across devices and to a criterion five-compartment (5C) model and dual energy X-ray absorptiometry for ALST. RESULTS: Data from 73 (23.2 ± 4.8 y) athletes were included in the analyses. Technical differences were observed between Z (range 12.2-50.1Ω) measures on the calibrated phantom. Differences in whole-body impedance were apparent due to posture (technological) and electrode placement (biological) factors. This resulted in raw measures for all three devices showing greater dehydration on BIVA compared to published norms for athletes using a separate BIA device. Compared to the 5C FFM, significant differences (p < 0.05) were observed on all three equations for BIASUP8 and BIASTA8, with constant error (CE) from -2.7 to -4.6 kg; no difference was observed for BIASUP4 or when device-specific algorithms were used. Published equations resulted in differences as large as 8.8 kg FFM among BIA devices. For ALST, even after a correction in the error of the published empirical equation, all three devices showed significant (p < 0.01) CE from -1.6 to -2.9 kg. CONCLUSIONS: Raw bioimpedance measurements differ among devices due to technical, technological, and biological factors, limiting interchangeability of data across BIA systems. Professionals should be aware of these factors when purchasing systems, comparing data to published reference ranges, or when applying published empirical body composition prediction equations.

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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.

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Managing renal fibrosis is challenging owing to the complex cell signaling redundancy in diseased kidneys. Renal fibrosis involves an immune response dominated by macrophages, which activates myofibroblasts in fibrotic niches. However, macrophages exhibit high heterogeneity, hindering their potential as therapeutic cell targets. Herein, we aimed to eliminate specific macrophage subsets that drive the profibrotic immune response in the kidney both temporally and spatially. We identified the major profibrotic macrophage subset (Fn1+Spp1+Arg1+) in the kidney and then constructed a 12-mer glycopeptide that was designated as bioactivated in vivo assembly PK (BIVA-PK) to deplete these cells. BIVA-PK specifically binds to and is internalized by profibrotic macrophages. By inducing macrophage cell death, BIVA-PK reshaped the renal microenvironment and suppressed profibrotic immune responses. The robust efficacy of BIVA-PK in ameliorating renal fibrosis and preserving kidney function highlights the value of targeting macrophage subsets as a potential therapy for patients with CKD.

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PURPOSE OF THE REVIEW: The use of bioelectrical impedance analysis (BIA) for monitoring body composition during the ketogenic diet has experienced a rapid surge. This scoping review aimed to assess the validity of procedures applying BIA in the ketogenic diet and to suggest best practices for optimizing its utilization. RECENT FINDINGS: We conducted a systematic scoping review of peer-reviewed literature involving BIA for assessing body composition in individuals adhering to a ketogenic diet. Searches of international databases yielded 1609 unique records, 72 of which met the inclusion criteria and were reviewed. Thirty-five studies used foot-to-hand technology, 34 used standing position technology, while 3 did not declare the technology used. Raw bioelectrical parameters were reported in 21 studies. A total of 196 body mass components were estimated, but predictive equations were reported in only four cases. Most research on BIA during ketogenic diets did not report the equations used for predicting body composition, making it impossible to assess the validity of BIA outputs. Furthermore, the exceedingly low percentage of studies reporting and analyzing raw data makes it challenging to replicate methodologies in future studies, highlighting that BIA is not being utilized to its full potential. There is a need for more precise technology and device characteristics descriptions, full report of raw bioelectrical data, and predictive equations utilized. Moreover, evaluating raw data through vectorial analysis is strongly recommended. Eventually, we suggest best practices to enhance BIA outcomes during ketogenic diets.

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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.

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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.

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(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.

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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.

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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 < 0.01), while the new predictive models showed no mean bias (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.

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Technical clothing has recently been brought into the spotlight as one of the most promising tools to improve sports performance and to enhance sports recovery. Among technical clothing items, garments engineered to emit far infrared (FIR) spectrum frequencies have come to the fore as a treatment for pain, muscle fatigue, and tissue healing due to their potential antioxidative and anti-inflammatory properties, with applications not only during recovery phases but also in the active phases of exercise. These garments, composed of fibers mixed with noble metals and/or bioceramics that respond to body infrared frequencies by returning an FIR emission backwards, are thought to improve muscle oxygenation and therefore recovery. In this double-blind, randomized, placebo-controlled, crossover study, ten male trail running athletes wore a whole-body-covering suit marketed as Accapì-FIR (Bruno Chiaruttini S.r.l., Rezzato, BS, Italy), while a total body suit with the same polyester fiber without metal components was used as control for the intervention. Parameters such as weight, height, bioimpedance parameters (BIVA), lactate from capillary sampling, salivary cortisol, and average temperatures of different body areas were obtained before and after a twelve-minute incremental work run protocol on a treadmill whilst wearing the two kinds of garment. Using the intervention suit, compared to control, statistically significant reductions in BIVA parameters such as body resistance (-6.7%) and reactance (-5.4%) were observed before and after exercise while a greater, but not significant, weight reduction was observed with the intervention suit. Decrease in resistance could be the result of a different distribution of fluids and ions due to FIR influence on capillary and superficial circulation, leading ultimately to more efficient management of body heat and promoting recovery and supercompensation. Further studies on larger samples will be necessary to confirm and clarify these results.

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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.

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BACKGROUND & AIMS: The bioelectrical impedance vector analysis (BIVA) represents a qualitative analysis of body composition. The vector, defined by resistance (R) and reactance (Xc) standardized by stature, can be evaluated compared to the 50%,75%, and 95% tolerance ellipses representative of the reference populations. The tolerance ellipses for healthy adults have been provided in 1995 and were developed by mixing underage, adult, and elderly subjects, possibly misrepresenting the actual adult population. The current multicentric, cross-sectional study aimed to provide new tolerance ellipses specific for the general adult population and as a secondary aim to present centile curves for the bioelectrical phase angle. METHODS: R, Xc, and phase angle were measured in 2137 and 2230 males and females using phase-sensitive foot-to-hand analyzers at 50 kHz. A minimum of 35 subjects were included for each sex and age category from 18 to 65 years. RESULTS: The new mean vectors showed a leftward shift on the R-Xc graph with respect to the former reference values (males: F = 75.3; p < 0.001; females: F = 36.6, p < 0.001). The results provided new 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th percentile curves for phase angle, identifying time point phases of decrement (males: -0.03° per year at 33.0-51.0 years and -0.05° per year after 51 years; females: -0.03° per year from 37.2 to 57.9 years). CONCLUSIONS: Compared to the original references, the new data are characterized by a different distribution within the R-Xc graph with a higher phase angle. Thirty years after the BIVA invention, the current study presents new tolerance ellipses and phase angle reference values for the adult population.

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Kettlebell sport (KBs) is increasingly popular, but very few studies have been focused on this discipline. This research aims to investigate the effects of KBs on body composition, strength symmetry, and segmental body composition symmetry in a sample of Italian elite athletes. Data were collected from a sample of 16 athletes of both sexes (11 men and 5 women; 34.5 ± 9.0 years of age). Anthropometric (height, weight, arm, thigh, calf, and waist circumferences), hand grip strength, and total and segmental bioelectrical variables were taken. Body composition was analysed by using specific bioelectrical impedance vector analysis (BIVA). Paired t-tests and confidence ellipses were applied to analyse bilateral differences. Elite athletes of both sexes showed high values of phase angle, indicative of high body cell mass and quality and proxy of muscle mass. Hand grip strength and body composition were symmetrical, with the only exception of a higher %FM in the right leg (Zsp: t = 3.556; p = 0.003). In conclusion, this study suggests that KBs contributes to muscle mass improvement, body composition, and strength symmetry, especially in the upper body.

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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.

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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 <12 g/dL (women) or <13 g/dL (men). The brain natriuretic peptide (BNP) and hydration index (HI) were measured. The endpoint of the study was all-cause mortality. Anaemia occurred in 59% of patients with AHF and in 35% with CHF (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.

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BACKGROUND: There is a need to detect and prevent fluid overload and malnutrition in heart failure. Bioelectrical impedance analysis and bioelectrical impedance vector analysis are medical instruments that can advance heart failure management by generating values of body composition and body water, assisting clinicians to detect fluid and nutritional status. However, there is a lack of evidence to summarise how they have been used among heart failure patients. METHOD: A systematic search was conducted. RESULT: Two hundred and four papers were screened. Forty-eight papers were reviewed, and 46 papers were included in this review. The literature shows that bioelectrical impedance analysis and bioelectrical impedance vector analysis were mostly used to assess fluid and nutritional status, together with diagnostic and prognostic values. Contraindication of using BIA and implications for practice are also demonstrated. CONCLUSION: The findings suggest that bioelectrical impedance vector analysis is superior to bioelectrical impedance analysis when assessing hydration/nutritional status in heart failure. Assessing a patient using bioelectrical impedance analysis /bioelectrical impedance vector analysis, together with natriuretic peptide -heart failure biomarkers, increases the diagnostic accuracy of heart failure. Further studies are required to examine the cost effectiveness of using these instruments in clinical practice.

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Phase angle (PhA) is a recently proposed marker of nutritional status in many clinical conditions. Its use in patients with obesity presents different critical concerns due to the higher variability of the two measured parameters (resistance, R, and reactance, Xc) that contribute to the determination of PhA. Controversial is the relation between PhA and BMI that might vary with graded levels of obesity due to the variation in fat and free fat mass. Obesity is frequently associated with metabolic, hepatic, cardiovascular and kidney diseases that introduce variations in PhA values, in relation to multimorbidity and severity degree of these diseases. It is reported that the improvement of clinical condition is associated with a positive change in PhA. Also, the treatment of obesity with weight loss might confirm this effect, but with different responses in relation to the type and duration of the intervention applied. In fact, the effect appears not only related to the percentage of weight loss but also the possible loss of free fat mass and the nutritional, metabolic and structural modifications that might follow each therapeutic approach to decrease body weight. We can conclude that the PhA could be used as marker of health status in patients with obesity supporting an appropriate weight loss intervention to monitor efficacy and fat free mass preservation.

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