Bioelectrical Impedance Vector Research Articles

Bioelectrical Impedance Vector Analysis, Nutritional Ultrasound®, and Handgrip Strength as Innovative Methods for Monitoring Critical Anorexia Nervosa Physical Recovery: A Pilot Study.

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.

Fat-free mass predictive equation using multifrequency bioelectrical impedance data in adolescent soccer athletes: development and cross-validation

Objectives: This study aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using multifrequency bioelectrical impedance data (MF-BIA) in adolescent soccer athletes. Methods: Male adolescent soccer athletes (n=149; 13 to 19 years old) were randomly sorted using Excel and independently selected for development group (n=100) or cross-validation group (n=49). The FFM reference values were determined using dual-energy X-ray absorptiometry (DXA). Single-frequency BIA was used to plot tolerance ellipses. Multifrequency-BIA raw data were used as independent variables in regression models. Student's independent t-test was used to compare development and cross-validation groups. Stepwise multiple regression was used to develop the FFM predictive equation. Bland-Altman plots, Lin's concordance correlation coefficient (CCC), according to McBride criteria, precision, accuracy, and standard error of estimation (SEE) were calculated to evaluate the concordance and reliability of estimates. Bioelectrical impedance vector analysis (BIVA) was plotted to evaluate hydration status. Results: No differences (P>0.05) were observed between development and validation groups in chronological age, anthropometric data, bioelectrical impedance data, and FFM values obtained using DXA. BIVA tolerance showed that all participants presented adequate hydration status when compared with the reference population. The new FFM predictive equation developed and validated: FFM (kg)= 7.064+ 0.592 * Age (years)+ 0.554* Weight(kg) + 0.365 * Height²/Resistance (cm²/Ω), presented R²= 0.95; SEE= 1.76 kg; CCC= 0.95, accuracy= 0.98, and strength of concordance= 0.99. Conclusions: The present study developed and cross-validated an FFM predictive equation based on multifrequency bioelectrical data providing substantial FFM accuracy for male adolescent soccer athletes.

Machine-learning models for detection of cellular states of human body using bio-impedance spectroscopy

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.

Proposal and validation of an equation to identify sarcopenia using bioelectrical impedance analysis-derived parameters

ObjectiveThis study aimed to develop a simpler approach for diagnosing sarcopenia by using only bioelectrical impedance vector analysis parameters. MethodsThe study design was a cross-sectional study. The research was conducted based on the Itabashi Longitudinal Study on Aging, a community-based cohort study, with data collected from the 2022 and 2023 surveys in Itabashi Ward, Tokyo, Japan. The development cohort consisted of 1146 participants from the 2022 survey, and the validation cohort included 656 participants from the 2023 survey. Both cohorts were comprised of community-dwelling older adults with similar inclusion criteria. Sarcopenia was defined according to the Asian Working Group for Sarcopenia 2019 criteria. The logistic model utilized height divided by impedance at 50 kHz and phase angle to establish a new regression equation to identify sarcopenia. Regression equations were generated for the development cohort and validated for the validation cohort. Discriminatory ability was assessed using the area under the receiver operating characteristic curve (AUC) for men and women. ResultsThe prevalence of sarcopenia was 20.7% and 14.8% in the development and validation cohort, respectively. The AUC (95% confidence interval) of the logistic model in discriminating sarcopenia was 0.92 (0.88, 0.95) for men and 0.82 (0.78, 0.86) for women in the development cohort and 0.85 (0.78, 0.91) for men and 0.90 (0.86, 0.95) for women in the validation cohort. ConclusionThe study demonstrated that a simple formula using bioelectrical parameters at 50 kHz proved useful in identifying sarcopenia in the older adult population.

Somatotype and bioelectrical impedance vector analysis of Italian CrossFit® practitioners

ObjectivesCrossFit® 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. MethodsAnthropometrical 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. ResultsThe 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. ConclusionsCrossFit® 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.

Association Between Pro-inflammatory Cytokine Levels (IL-1β, IL-6, and TNF-α) in Human Colostrum and Maternal Body Composition Components.

Background: Obesity is characterized as a low-grade chronic inflammatory state, marked by elevated inflammatory biomarkers. Breast milk (BM) is rich in nutritional elements, vitamins, minerals, immunological factors, and bioactive components. These bioactive components, capable of influencing biological processes, may vary in concentration based on maternal body composition. Research Aim/Question(s): This study aimed to explore the association between pro-inflammatory cytokine levels (interleukin-1 beta [IL-1β], interleukin-6 [IL-6], and tumor necrosis factor-alpha [TNF-α]) in human colostrum and maternal body composition, as analyzed through bioelectrical impedance vector analysis (BIVA). Method: In this cross-sectional study, 117 healthy postpartum participants were included, with each group (normal weight, overweight, and obese) comprising 39 individuals, as classified by BIVA. Colostrum samples were collected within the first 24 hours postpartum. Results: IL-1β levels did not significantly differ across the groups, with concentrations of 69.5 ± 103 pg/mL in normal-weight, 79.7 ± 97.9 pg/mL in overweight, and 68.7 ± 108 pg/mL in obese women. IL-6 levels were significantly higher in the overweight group (55 ± 72.4 pg/mL) than in the normal-weight (48.1 ± 74.1 pg/mL) and obese groups (28.9 ± 36.2 pg/mL) (p = 0.02). Similarly, TNF-α levels were higher in the overweight group, with concentrations of 58.7 ± 74.9 pg/mL, than in the normal-weight group, with concentrations of 38.6 ± 95.4 pg/mL, and 52.6 ± 115 pg/mL in obese women (p = 0.02). Conclusion: This study shows that IL-6 and TNF-α concentrations were statistically higher in the colostrum of overweight women, suggesting that maternal body composition may influence the inflammatory profile of BM.

Association between BMI z-score and body composition indexes with blood pressure and grip strength in school-age children: a cross-sectional study

Childhood obesity is linked to diverse health outcomes, including elevated blood pressure (EBP). Emerging evidence showed that excess fat mass (FM) may have a deleterious impact on blood pressure even in normal-weight children. The primary objective of this study was to assess the association between body weight status by BMI z-score and body composition parameters by conventional bioelectrical impedance analysis (BIA) and bioelectrical impedance vector analysis (BIVA). Also, we aimed to explore the performance of BMI z-score, %FM, and FM index (FMI) in discriminating EBP in a sample of school-age Mexican children. Children were classified as having normal weight, overweight or obesity according to WHO criteria for BMI z-score. FMI was considered high when above 75th percentile, and fat free mass index (FFMI) was considered low when below 25th percentile of the reference population. Body composition was also classified according to the BIVA method and EBP was determined when systolic and/or diastolic blood pressure ≥ 90th percentile. BMI z-score groups were compared by Student´s t-test or the Mann–Whitney U test, or by the chi-square test or Fisher exact test. Receiving operating characteristic (ROC) analysis was performed. 61 children were included (52.5% boys, median age 9.8 (25th, 75th percentiles: 8.5, 11.0)) years. High FMI was observed in 32.3% of children with normal weight. Low FFMI was present in 93.5% of children with normal weight and 53.3% of those with overweight/obesity. According to BIVA, 58.1% and 43.3% of children with normal weight and overweight/obesity were classified as having cachexia. All the three adiposity indicators showed significant areas under the ROC curve (AURC) greater than 0.775 for EBP, with the largest one displayed for FM% (0.794). Hight FMI and low FFMI are common in children with normal weight. Identifying deficiency of FFM might be limited by using solely BMI indicators. Cachexia by BIVA was present in a high proportion of children with either normal weight or overweight/obesity. Both BMI z-score and FM (% and FMI) performed well at discriminating EBP, with a numerically greater AURC observed for FM%. Body composition in pediatric population is relevant for identifying body composition abnormalities at early age.

One-Year Changes in Bioelectrical Impedance Data in Adolescent Athletes.

Raw bioelectrical impedance (BI) data and vector analysis (BIVA) have been used to evaluate fat-free mass (FFM) cross-sectionally in adolescent athletes; however, there have been no longitudinal studies about it. This study aimed to assess the magnitude of changes in raw BI data (resistance [R], reactance [Xc], and phase angle [PhA]), BIVA, and FFM in adolescent athletes (n = 137, 40% female). BI data were collected using a single-frequency device at baseline and after one year of sports practice. Baseline chronological age categorized the participants (11, 12, or 13 years [y]). In females, Xc/H increased (13 to 14 y, p = 0.04) while R/H decreased in all age groups (p = 0.001). PhA (11 to 12 y, p = 0.048) and FFM (11 to 12 y and 12 to 13 y groups p = 0.001) increased and showed the lowest magnitude of changes in the 13 to 14 y group (p = 0.05). In males, Xc/H decreased (11 to 12 and 12 to 13 y groups, p = 0.001) with a higher magnitude of changes in the 13 to 14 y group (p = 0.004); R/H decreased (p = 0.001); FFM increased in all groups (p = 0.001); however, no magnitude of changes was observed. PhA increased in the 13 to 14 y group (p = 0.004). BIVA showed no differences among ellipse distances in females. In males, a high distance was observed in the 11 to 12 y group. "Time interval" influenced PhA and Xc/H in the female group and R/H and Xc/H in the male group. "Initial age" and "time interval" influenced the increase in PhA in the male group. Raw BI data and BIVA patterns can detect the magnitude of the changes in a sex-dependent manner.

Bioelectrical impedance vector analysis as an indicator of malnutrition in children under five years with and without pneumonia in Mchinji District, Malawi: An exploratory mixed-methods analysis

Background Bioelectrical impedance vector analysis (BIVA) is a non-invasive approach to assessing body composition and cellular health, which may improve the assessment of nutritional status in sick children. We explored the reliability, clinical utility, and acceptability of BIVA, as an indicator of nutritional status for children under five years with and without pneumonia, in Malawi. Methods We conducted a parallel convergent mixed-methods exploratory study in Mchinji District Hospital, Malawi, in 2017. We recruited a convenience sample of children aged 0–59 months with clinical pneumonia, and without an acute illness. Children had duplicate anthropometric and BIVA measurements taken. BIVA measurements of phase angle were taken of the whole body, and trunk and arm segments. Reliability was assessed by comparing the variability in the two measures, and clinical utility by estimating the association between anthropometry and phase angle using linear regression. Focus group discussions with healthcare workers who had not previously used BIVA instrumentation were conducted to explore acceptability. Results A total of 52 children (24 with pneumonia and 28 healthy) were analysed. The reliability of sequential phase angle measurements was lower than anthropometric measurements, but trunk and arm segments performed better. The largest associations with phase angle were a negative relationship with weight-for-age z-score (WAZ) in children with pneumonia in the trunk segment, and a positive association with WAZ in the full body measurement in healthy children. Healthcare workers in focus group discussions expressed trust in BIVA technology and that it would enable more accurate diagnosis of malnutrition; however, they raised concerns about the sustainability and necessary resources to implement BIVA. Conclusions While healthcare workers were positive towards BIVA as a novel technology, implementation challenges should be expected. The differential direction of association between anthropometry and phase angle for children with pneumonia warrants further investigation.

Phase Angle and Bioelectrical Impedance Vector Analysis (BIVA) in Amyotrophic Lateral Sclerosis (ALS) Patients

Phase angle (PhA) and bioelectrical impedance vector analysis (BIVA) have emerged as valuable tools for assessing nutritional status and prognosis in various patient populations, but there is a lack of studies in rare neurodegenerative diseases. The purpose of this cross-sectional study was to investigate these bioelectrical parameters in patients with amyotrophic lateral sclerosis (ALS), compared with healthy peers. The tetrapolar impedance method was applied and bioimpedance analysis (BIA) was performed. Bioelectrical parameters were obtained (Resistance—R; Reactance—Xc) or calculated (PhA; BIVA). For BIVA, bivariate vectors and confidence ellipses were graphically represented. In addition, R and Xc were used to determine body composition (BC) (Fat Mass—FM; Fat-Free Mass—FFM; and Total Body Water—TBW). In this study, 40 participants were divided into two groups: case group (n = 20, ALS patients) and control group (n = 20, healthy subjects. Our main results showed that ALS patients presented low levels of BMI, FFM, R, and Xc adjusted by height (R/H, Xc/H), hydration, and cellularity, compared to the healthy subjects. Our findings highlight BC and bioelectrical parameters, including PhA and BIVA, as valuable indicators of nutrition status, which should be implemented in the nutrition care process of ALS patients during the disease course.

Bioimpedance Vector Analysis-Derived Body Composition Influences Strength and Power in Alpine Skiers

ABSTRACT Purpose: Alpine ski racing is a complex sport where no single factor can exclusively account for performance. We assessed body composition, using bioelectrical impedance vector analysis (BIVA), and our purpose was to study its influence on the strength and power profile of young alpine skiers. Methods: Anthropometric measurements and advanced BIVA parameters were recorded on eighteen alpine ski racers (6 females/12 males; 17.0 ± 1.3 years; 172.2 ± 9.3 cm; 68.5 ± 9.8 kg). Dynamic force and power were assessed using countermovement jumps (CMJ), while maximal isometric strength was evaluated for hip flexion-extension and abduction-adduction movements. Stepwise regression models examined the relationship between BIVA-derived parameters and strength/power variables. Results: Body cellular mass (BCM) positively related to jump height (p = .021, R 2 = 74%), jump momentum (p < .001, R 2 = 89%), reactive strength index modified (p = .026, R 2 = 75%) and peak concentric power (p < .001, R 2 = 82%), while intracellular water (ICW) related to peak eccentric (p < .001, R 2 = 76%) and concentric force (p < .001, R 2 = 77%) as well as to concentric rate of force development together with the phase angle (PhA) (p = .008, R2 = 79% and R2 = 0.015). Regarding isometric assessment, ICW was a significant predictor for all four movement directions, and PhA contributed to hip adduction strength. Conclusions: Body composition, particularly BCM and ICW, significantly predict force- and power-related factors in young alpine skiers.

Prognostic value of overhydration and bioelectrical impedance vector on short- and long-term outcomes in hospitalized patients with cancer

Water, an essential component of body composition, appears to be a significant predictor of adverse outcomes in clinical populations, despite being frequently underexplored. Bioelectrical impedance analysis (BIA) and vector analysis (BIVA) are easy and cost-effective bedside tools for estimating body composition, particularly water content. Therefore, our study aimed to assess the impact of hydration and fluid status using both BIA and BIVA on outcomes in hospitalized patients with cancer. A prospective cohort study involving hospitalized individuals with cancer was conducted. Total body water (TBW) was estimated using BIA. Extracellular-water/TBW (ECW/TBW) and ECW/intracellular-water (ECW/ICW) ratios were calculated. BIVA ellipses vectors were constructed to enhance our analysis of hydration status. Participants were followed during their hospital stay and up to six months after discharge to assess outcomes, including in-hospital mortality, 6-month non-elective rehospitalization, and 6-month mortality. TBW, ECW/TBW, ECW/ICW ratios, and BIVA plots were not associated with non-elective rehospitalization during the follow-up period. However, TBW and an elevated ECW/ICW ratio were independent predictors of in-hospital mortality [hazard ratio (HR): 1.07 (1.01; 1.13) p=0.020; HR: 4.23 (1.69; 10.58) p=0.002]. Elevated ratios ECW/TBW and ECW/ICW were independent predictors of 6-month mortality [HR: 1.87 (1.10; 3.21) p=0.022; HR: 2.49 (1.37; 4.51) p=0.003]. BIVA vectors for in-hospital and 6-month mortality shifted significantly to the right, leading to cachexia and overhydration quadrants (p<0.05). Abnormalities related to overhydration were important predictors of short- and long-term mortality in hospitalized patients with cancer.

Specific bioelectrical vectors pattern in individuals with sarcopenic obesity

BackgroundSarcopenic obesity is a common condition in the elderly associated with excessive adiposity and low muscle mass and strength. AimsThis study aims to establish a method for detecting bioelectrical characteristics in individuals with sarcopenic obesity through specific Bioelectrical Impedance Vector Analysis (specificBIVA), while considering the characteristics of individuals with healthy, sarcopenic, and obese conditions. MethodsThe sample was composed by 975 Italian adults over 50 years of age (men: 74.3±8.8 y; women:76.3±8.8 y) living in Sardinia (Italy). A dataset of 1590 US adults aged 21- to 49 years retrieved from the 2003-2004 National Health and Nutrition Examination Survey was also considered in a final step of the study. Anthropometric (stature, weight, waist, arm, and calf circumferences) and whole-body bioelectrical variables were taken. In the Italian sample, bioelectrical impedance was applied to estimate the relative content of fat mass and skeletal muscle mass. Groups with healthy body composition (NS-NO), or consistent with sarcopenia (S), sarcopenic obesity (SO), and obesity (O) were defined based on the cut-offs suggested by European expert guidelines (EWGSOP2 and ESPEN-EASO). SpecificBIVA was applied to compare groups and to identify the area for sarcopenic obesity within young-adults tolerance ellipses. The position of the specific vector of US individuals with SO, selected on the basis of DXA measurements, was also considered. ResultsIn both sexes of the Italian sample, the bioelectrical characteristics of the four groups were different (p<0.001). The differences were mainly related to vector length, indicative of higher fat mass, which was longer in the O and SO groups, and phase angle, a proxy of intracellular/extracellular water and muscle mass, lower in the sarcopenic groups. Bioelectrical vectors of the SO group fell in the right quadrant, outside of the 95% tolerance ellipses of young adults. The mean vector of the US sample with SO fell in the same area. Within the SO area, women had similar bioelectrical values, while men showed phase angle variability, which was related to the severity of the condition. ConclusionsSpecificBIVA detects body composition peculiarities of individuals with sarcopenic obesity, thus allowing their diagnosis when associated with low handgrip strength values.

Unsupervised Exercise Intervention vs. Adherence to a Mediterranean Diet Alone: The Role of Bioelectrical Impedance Vector Analysis and Cardiovascular Performance in Liver-Transplanted Recipients.

(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.

Bioelectrical impedance vector analysis as an indicator of malnutrition in children under five years with and without pneumonia in Mchinji District, Malawi: An exploratory mixed-methods analysis

Background Bioelectrical impedance vector analysis (BIVA) is a non-invasive approach to assessing body composition and cellular health, which may improve the assessment of nutritional status in sick children. We explored the reliability, clinical utility, and acceptability of BIVA, as an indicator of nutritional status for children under five years with and without pneumonia, in Malawi. Methods We conducted a parallel convergent mixed-methods exploratory study in Mchinji District Hospital, Malawi, in 2017. We recruited a convenience sample of children aged 0–59 months with clinical pneumonia, and without an acute illness. Children had duplicate anthropometric and BIVA measurements taken. BIVA measurements of phase angle (PhA) were taken of the whole body, and trunk and arm segments. Reliability was assessed by comparing the variability in the two measures, and clinical utility by estimating the association between anthropometry and PhA using linear regression. Focus group discussions with healthcare workers who had not previously used BIVA instrumentation were conducted to explore acceptability. Results A total of 52 children (24 with pneumonia and 28 healthy) were analysed. The reliability of sequential PA measurements was lower than anthropometric measurements, but trunk and arm segments performed better. The largest associations with PhA were a negative relationship with weight-for-age z-score (WAZ) and PhA in children with pneumonia in the trunk segment, and a positive association with WAZ in the full body measurement in healthy children. Healthcare workers in focus group discussions expressed trust in BIVA technology and that it would enable more accurate diagnosis of malnutrition; however, they raised concerns about the sustainability and necessary resources to implement BIVA. Conclusions While healthcare workers were positive towards BIVA as a novel technology, implementation challenges should be expected. The differential direction of association between anthropometry and PhA for children with pneumonia warrants further investigation.

Body composition and sexual hormones for the glucose control of autoimmune diabetes in males: are they necessary to predict diabetes-related complications?

Glucose control in diabetes is essential for avoiding diabetes-related complications. To determine the impact of body composition and sexual hormones in glucose control and diabetes-related complications, in males with autoimmune diabetes. Thirty-nine patients with autoimmune diabetes and flash glucose monitoring were included. A morphofunctional nutritional evaluation with bioelectrical impedance vector analysis (BIVA), abdominal adipose tissue ultrasound, rectus femoris ultrasound and biochemical parameters, was performed. Strong, positive correlations were observed between body composition parameters, biochemical variables and sexual hormones (p<0.05). Adipose tissue measured by BIVA and ultrasound was more significantly associated with glucose control (including time in range >70%, glucose variability <36% determined by flash glucose monitoring; p<0.05) and the presence of microvascular/macrovascular complications (p<0.05) than lean mass. After adjusting by the duration of diabetes, BMI, abdominal circumference, fat mass and phase angle increased the risk for microvascular complications (OR 1.32(1.00 - 1.73), OR 1.06(1.00 - 1.12), OR 1.14(1.01 - 1.20), 0R 0.3(0.10 - 0.91) respectively; for macrovascular complications: BMI OR 1.38(1.04 - 1.84) and fat mass OR 1.26(1.00 - 1.58)]. Sexual hormone levels did not influence on glucose control or the development of diabetes-related complications. Anthrpometric parameters, especially adipose tissue, were associated with glucose control and variability determined by flash glucose monitoring. Furthermore, changes in fat and lean mass were associated with the presence of microvascular and macrovascular complications. Thus, a comprehensive nutritional evaluation might be useful for the evaluation of males with autoimmune diabetes, in order to identify patients with increased risk of complications.

Body fluids and muscle changes in trail runners of various distances.

This study aims to investigate body fluids and muscle changes evoked by different trail races using anthropometric, bioelectrical, and creatine kinase (CK) measurements. 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. 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). 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.

Evaluation of Hydration Status by Bioelectrical Impedance Vector Analysis in Patients with Ischemic Heart Disease Undergoing Exercise Stress Test.

Ischemic heart disease (IHD) represents a group of clinical syndromes characterized by myocardial ischemia, leading to an impairment in the myocardial blood supply and compromised perfusion. Several clinical variables assessed through a stress test, such as oxygen uptake (VO2) and heart rate oxygen pulse (HR/O2), have been attributed as cardiopulmonary prognostic factors in patients with IHD. However, other factors like hydration status (HS), potentially affecting the cardiopulmonary response, have been barely addressed. Unbalanced HS has a short-term effect on plasma volume and the sympathetic nervous system, which impacts blood volume, and lowers VO2 and HR/O2. Recently, bioelectrical impedance analysis (BIA), a method based on the opposition of body tissues (including fluid volume) to a low electrical current, has been widely used to assess HS by obtaining two components: resistance (R) and reactance (Xc) and using prediction formulas. However, several limitations as chronic illness or abnormal fluid status, may affect the results. In this sense, alternative BIA methods, such as bioelectrical impedance vector analysis (BIVA), have become relevant. R and Xc (adjusted by height) result in a vector plotted on the R/Xc graph, which allows interpreting the HS as normal or abnormal according to the distance of the mean vector. This study aims to describe how to determine HS by BIVA using a single-frequency device and compare the results with the cardiopulmonary response in patients with IHD.

Influence of body composition assessment with bioelectrical impedance vector analysis in cancer patients undergoing surgery.

Malnutrition is common in patients undergoing surgery for cancers and is a risk factor for postoperative outcomes. Body composition provides information for precise nutrition intervention in perioperative period for improving patients' postoperative outcomes. The aim was to determine changes in parameters of body composition and nutritional status of cancer patients during perioperative period. A total of 92 patients diagnosed with cancer were divided into gastrointestinal and non-gastrointestinal cancer group according to different cancer types. The patients body composition assessed by bioelectrical impedance vector analysis (BIVA) on the day before surgery, postoperative day 1 and 1 day before discharge. The changes between two groups were compared and the correlation between body composition and preoperative serum nutritional indexes was analyzed. The nutritional status of all patients become worse after surgery, and phase angle (PA) continued to decrease in the perioperative period. Fat-free mass (FFM), fat-free mass index (FFMI), skeletal muscle mass (SMM), extracellular water (ECW), total body water (TBW), hydration, and body cell mass (BCM) rise slightly and then fall in the postoperative period in patients with gastrointestinal cancer, and had a sustained increase in non-gastrointestinal patients, respectively (P<0.05). Postoperative body composition changes in patients with gastrointestinal cancer are related to preoperative albumin, pre-albumin, hemoglobin, and C-reactive protein (P<0.05), whereas postoperative body composition changes in patients with non-gastrointestinal cancer are related to age (P<0.05). Significant changes in body composition both in patients with gastrointestinal cancer and non-gastrointestinal cancer during perioperative period are observed. Changes in body composition for the cancer patients who undergoing surgery are related to age and preoperative serum nutrition index.

Hydration Status of Geriatric Patients Is Associated with Changes in Plasma Proteome, Especially in Proteins Involved in Coagulation.

Due to multifactorial reasons, such as decreased thirst and decreased total body water, elderly patients are vulnerable to dehydration. The study aims to investigate whether moderate dehydration or hyperhydration affects the blood proteome. Blood samples, medication, and bioelectrical impedance analysis (BIA) details were collected from 131 geriatric patients (77 women and 54 men aged 81.1 ± 7.2 years). Based on an evaluation by Bioelectrical Impedance Vector Analyses (BIVAs) of this cohort, for each hydration status (dehydrated, hyperhydrated, and control), five appropriate blood plasma samples for both males and females were analyzed by liquid chromatography-mass spectrometry (LC-MS). Overall, 262 proteins for female patients and 293 proteins for male patients could be quantified. A total of 38 proteins had significantly different abundance, showing that hydration status does indeed affect the plasma proteome. Protein enrichment analysis of the affected proteins revealed "Wound Healing" and "Keratinization" as the two main biological processes being dysregulated. Proteins involved in clot formation are especially affected by hydration status.