Conventional Bioelectrical Impedance Analysis Research Articles

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.

Towards personalized hydration assessment in patients, based on measurement of total body electrical resistance: Back to basics

Assessment of tissue hydration by conventional bioelectrical impedance analysis (BIA) has produced conflicting results because of flaws in the algorithms that are used to translate measurements of total body electrical resistance (TBER) into liters of body water. This type of error can be eliminated by a return to the TBER measurement itself, without attempting to convert Ohms into liters of body water. Aims of this study were to quantify tissue hydration based on TBER, to establish TBER normal values (TBERnorm), to improve the prediction of TBERnorm values in individual patients, and to evaluate this approach in patients on hemodialysis (HD). TBERnorm values were obtained in 213 healthy controls and corrected for body height (H-TBERnorm).Inter-individual H-TBERnorm variability was reduced by correction for arm muscle cross-sectional area (AMA). Performance of this approach was evaluated in 94 patients on HD. H-TBERnorm was inversely related to AMA. Correction for AMA reduced the H-TBERnorm standard deviation by 31% in men and 23% in women. When applied to patients on HD, H-TBER changes within subjects were inversely related to ultrafiltration volumes, with a mean R2 of 0.95±0.04 in men and 0.93±0.07 in women. Clinically significant H-TBER increments occurred after volume reductions of 0.39±0.25L in men and 0.37±0.18L in women. TBER measurements, corrected for height and AMA, have the potential to become an objective and sensitive method to assess hydration in patients. Its clinical value remains to be shown in intervention studies.

Comparison Between Two Methods of Bioelectrical Impedance Analyses for Measuring Abdominal Visceral Fat Tissue

Background: The assessment of visceral adiposity is essential for the management of obesity. Bioelectrical impedance analysis (BIA) has been established as a practical method for the assessment of visceral adiposity. Methods: We compared two BIA methods (seca, mBCA 515; Omron, HDS-2000) of assessing visceral adiposity. Results: Visceral adipose tissue volume measured using seca mBCA 515 was highly correlated with visceral fat area measured using HDS-2000; however, they were differently correlated with waist circumference and body mass index, respectively. Conclusions: The seca mBCA 515 can distinguish fat mass from lean mass more accurately compared with conventional BIA methods. J Endocrinol Metab. 2018;8(4):76-78 doi: https://doi.org/10.14740/jem518w

Quantification of visceral adiposity: evaluation of the body electrical loss analysis

Body electrical loss analysis (BELA) is a measurement of the electrical losses caused by the human abdomen when placed into an alternating magnetic field. This study aimed at finding a prediction formula for visceral fat area (VFA) from BELA. Thirty-eight test subjects covering the body mass index of 19.6–39.4 kg m−2 and the waist circumference of 78–128 cm underwent BELA, single-frequency electrical abdominal impedance measurement (SAI), conventional bioelectrical impedance analysis and cross-sectional magnetic resonance imaging (MRI). The BELA was compared with the amount of visceral and subcutaneous fat calculated from MR images. The strongest correlation between BELA and VFA (r = 0.61, SEE = 59.30) was found at the height of umbilicus +5 cm, and it tended to decrease when the measurement height was lowered. The correlation to subcutaneus fat area (SFA) at the height of umbilicus +5 cm was r = 0.43 (lower is better), and it tended to increase when the measurement height was lowered. The correlation of BELA to VFA in the evaluation cohort is not strong enough to tolerate obtaining the prediction formula for VFA by regression among BELA and MRI. Also the large SEE value suggests a poor agreement with MRI. Thus the results suggest that in its current form BELA cannot be applied as a diagnostic device to measure visceral fat. Although SAI can help in identifying the abdominal SF layer thickness, it did not help when applied to BELA analysis.

Comparison Between Two Methods of Bioelectrical Impedance Analyses for Measuring Abdominal Visceral Fat Tissue

Background: The assessment of visceral adiposity is essential for the management of obesity. Bioelectrical impedance analysis (BIA) has been established as a practical method for the assessment of visceral adiposity. Methods: We compared two BIA methods (seca, mBCA 515; Omron, HDS-2000) of assessing visceral adiposity. Results: Visceral adipose tissue volume measured using seca mBCA 515 was highly correlated with visceral fat area measured using HDS-2000; however, they were differently correlated with waist circumference and body mass index, respectively. Conclusions: The seca mBCA 515 can distinguish fat mass from lean mass more accurately compared with conventional BIA methods. J Endocrinol Metab. 2018;8(4):76-78 doi: https://doi.org/10.14740/jem518w

Evaluation of body composition with bioimpedence. A comparison between athletic and non-athletic children

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

Fatness of female field hockey players: Comparison of estimates with different methods

The aim of the study was to compare relative body fat (% fat) in female field hockey players using several methods with dual-energy X-ray absorptiometry (DXA) as the reference. Participants were 31 Polish hockey players 16–30 years of age, 17 national and 14 youth level. Percent body fat was estimated by DXA (reference method), conventional and segmental bioelectrical impedance analysis (BIA), and predicted from skinfolds (SKF). National and youth team members did not differ in estimated body fat. Correlations between BIA and skinfold estimates of % fat and DXA % fat though significant, were moderate. Both % fat SKF and % fat SBIA differed significantly from % fat DXA, while estimated % fat BIA and % fat DXA did not differ. Limits of agreement were narrow for conventional BIA (−1.20 to 1.71% fat), followed by segmental BIA (3.72–6.09% fat) and broadest for SKF (5.97–9.28% fat). Differences between DXA % fat and estimated % fat with SKF and SBIA increased from the leanest to fattest athletes, whereas conventional BIA overestimated % fat relative to DXA in the small sample of individuals with low relative fatness and underestimated % fat in individuals with elevated relative fatness. Estimated % fat from conventional BIA most closely approximated DXA % fat in this sample of female field hockey players suggesting that the method may be suitable for field surveys to monitor body composition during the season.

Validity of Bioelectrical Impedance Analysis to Estimate Body Composition Changes After Bariatric Surgery in Premenopausal Morbidly Women

In obese patients, subtle variations of the hydration of soft tissues can propagate errors in bioelectrical impedance analysis (BIA) measures of body composition. Bioelectrical impedance vector analysis (BIVA) is a useful method to evaluate tissue hydration. Laparoscopic adjustable gastric banding (LAGB) is a purely restrictive bariatric surgical procedure resulting in lower fat-free mass (FFM) loss than other malabsorptive or mixed intervention. The aim of this study was to evaluate the 6- and 12-month changes in body composition in a homogeneous group of premenopausal morbidly obese women treated by LAGB by comparing the results of conventional BIA and BIVA with dual-energy X-ray absorptiometry (DXA) method. Forty-five consecutive morbidly obese patients (mean age, 35.3 +/- 9.1 years; body mass index, 34.5-48.7 kg/m(2)) were prospectively evaluated at the Endocrinology Unit of the Department of Molecular and Clinical Endocrinology and Oncology. The LAGB device (Lap-Band System; Inamed Health, Santa Barbara, CA, USA) was inserted laparoscopically. Soft tissue hydration was evaluated by BIVA; fat mass (FM) and FFM were evaluated by BIA (BIA 101 RJL, Akern Bioresearch, Firenze, Italy) and by DXA (Hologic QDR 4500A S/N 45622; Hologic Inc., Bedford, MA, USA). Pre- and postoperative BIVA vectors indicated a normal hydration in all patients. Postoperatively, the excess of body weight loss was mainly due to a decrease in FM. The regression analysis of BIA and DXA methods at baseline and at the 6- and 12-month follow-up for FM r (2) values were 0.98, 0.94, and 0.99, respectively (p < 0.001); FM% r (2) values were 0.91, 0.89, and 0.98, respectively (p < 0.001); and FFM r (2) values were 0.87, 0.82, 0.99, respectively (p < 0.001). BIA and DXA measurements of body composition exhibit a high relative agreement in the study group of normo-hydrated obese subjects. BIA tends to overestimate FFM, but this effect is reduced along with the weight loss during the follow-up. Under the stable hydration, the BIA method may be useful as an alternative to DXA in a selected clinical setting when repeated comparisons of body composition are required.

Modeling upper and lower limb muscle volume by bioelectrical impedance analysis

Most studies employing bioelectrical impedance analysis (BIA) for estimating appendicular skeletal muscle mass using descriptive BIA models rely on statistical rather than biophysical principles. The aim of the present study was to evaluate the feasibility of estimating arm and leg muscle volume (MV) based on multiple bioimpedance measurements and using a recently proposed mathematical model and to compare this technique to conventional segmental BIA at high and low frequencies. MV of the arm and leg, respectively, was determined in 15 young, healthy, active men [age 22 +/- 2 (SD) yr, total body fat 15.6 +/- 5.1%] by magnetic resonance imaging (MRI) and BIA using a conventional and new bioimpedance model. MRI-determined MV for leg and arm was 6,268 +/- 1,099 and 1,173 +/- 172 cm(3), respectively. Estimated MV by the new BIA model [leg: 6,294 +/- 1,155 cm(3) (50 kHz), 6,278 +/- 1,103 cm(3) (500 kHz); arm: 1,216 +/- 172 cm(3) (50 kHz), 1,155 +/- 157 cm(3) (500 kHz)] was not statistically different from MRI-determined MV (leg: P= 0.958; arm: P= 0.188). The new BIA model was superior to conventional BIA and performed best at 500 kHz for estimating leg MV as indicated by the lower relative total error [new: 3.6% (500 kHz), 5.2% (50 kHz); conventional: 7.6% (500 kHz) and 8.3% (50 kHz)]. In contrast, the new BIA model, both at 50 and 500 kHz, did not improve the accuracy for estimating arm MV [new: 10.8% (500 kHz), 10.6% (50 kHz); conventional: 11.8% (500 kHz), 11.4% (50 kHz)]. It was concluded that modeling of multiple BIA measurements has advantages for the determination of lower limb muscle volume in healthy, active adult men.

Role of dietary intervention on metabolic abnormalities and nutritional status after renal transplantation

In these last years, several traditional risk factors for cardiovascular disease, like obesity, dyslipidaemia, hypertension and post-transplant diabetes mellitus have been also identified as important non-immunological risk factors leading to the development of chronic allograft nephropathy, the first cause of graft loss in transplanted patients. The aim of the present study was to determine the effects of a 12-month dietary regimen on the nutritional status and metabolic outcome of renal transplant recipients in the first post-transplant year. Forty-six cadaver-donor renal transplant recipients (mean age 40.8 +/- 10.1-years), enrolled during the first post-transplant year (4.8 +/- 3.3 months) and followed prospectively for a 12 month period. Biochemical and nutritional markers, anthropometric measurements, body composition (by conventional bioelectrical impedance analysis) and dietary records (using a detailed food-frequency questionnaire) at baseline and after 12 months. Compliance to the diet was related to sex (male better than female) and was associated with weight loss primarily due to a decrease in fat mass, with decrease in total cholesterol and glucose plasma levels and with a concomitant rise in serum albumin. After renal transplantation, health benefits of proper metabolic balance that include reduced body fat, weight loss, lower cholesterol and triglycerides levels and an improvement, fasting glucose levels can be obtained when dietary intervention occurred.

Body mass index and bioelectrical vector distribution in 8-year-old children

Objective To describe bioelectrical impedance vector distribution in relation to BMI (body mass index; body weight/stature 2) in a population of healthy children in order to detect possible changes in body composition status. Design Observational study involving 464 healthy 8-year-old children. The subjects were divided into three groups based on their BMI: 218 normal weight (NW) children with BMI < 18.4 for male and BMI < 18.3 for female; 135 overweight (OW) children with BMI 18.4 to <21.6 for male and with BMI 18.3 to <21.6 for female; 111 obese (OB) children with BMI ≥ 21.6. Skinfold thickness was measured at the triceps using a Holtain caliper. Bioelectrical impedance analysis (BIA) measurements were performed. Total body water (TBW), fat-mass (FM), fat-free mass (FFM), body cell mass (BCM) and extra-cellular water (ECW) were estimated using conventional BIA regression equations. The resistance–reactance graph (RXc graph) method was used for vector BIA using as reference population the set of 353 children with BMI 14.0–21.5 kg/m 2. Results Mean vector displacement followed a definite pattern, with progressive vector shortening in groups with increasing BMI class, and along a fixed phase angle. This pattern indicates an increase in TBW due to an increase in soft tissue mass with an average, normal hydration. In NW children, vectors out of the right and upper half of the 75% tolerance ellipse indicating leanness, and vectors falling out of the right and lower half of the tolerance ellipse indicating undernutrition, show a significantly reduced value of BCM but no significant differences in FM or triceps skinfold thickness (TST), respectively, compared to vectors falling within the 75% tolerance ellipse. Conclusions Although BMI is a reliable measure to grade overweight, it cannot differentiate whether weight change is due to variation of FM, FFM or water. In our study a different impedance vector pattern has been associated with normal weight to obesity, and we have established the trajectory followed by the impedance vector of standardized age, healthy children grouped by BMI. This BIVA may be useful for clinical purposes due to ability to detect changes in hydration or body composition in children.

A simplified approach to analysing bio-electrical impedance data in epidemiological surveys

Bio-electrical impedance analysis (BIA) is widely used to estimate body composition. It is simple, quick and cheap, but less accurate than other methods. It has potential epidemiological value, but has conventionally required validation before application. To develop a simple method of expressing weight, height and impedance data that avoids the need for population-specific validation equations in order to facilitate epidemiological application. Body composition was measured using the four-component model in young adults (43 males, 90 females). Impedance (R) was measured hand-foot and foot-foot. Lean mass and fat mass were adjusted for height to give lean mass index (LMI) and fat mass index (FMI). Based on theoretical principles, we generated the index 1/R, which provides an index of body water adjusted for height. Sex-specific regression models were used to investigate the relationships between (a) 1/R and LMI, and (b) body mass index (BMI) adjusted for 1/R and FMI. The success of this approach was evaluated in relation to the conventional BIA approach, using correlation analysis. 1/R was a highly significant predictor of LMI. BMI adjusted for 1/R was a significant predictor of FMI. Our approach performed as well as the conventional approach for LMI, but not for FMI. Direct use of BIA data, rather than their combination with population-specific equations for the prediction of total body water, proved successful at ranking individuals of both sexes in terms of LMI and FMI. The index 1/R may prove particularly valuable in epidemiological studies where ranking of LMI is required.

Bioelectrical impedance analysis and age-related differences of body composition in the elderly

Background and aim Significant changes in body composition that have important health related effects may occur in the elderly. In this study, we evaluated the bioelectrical characteristics in a large group of apparently healthy Caucasian men in the age range 50–80 years, as a function of age and body mass index. Methods We studied 315 men with ages ranging from 50 to 80 years. They were divided into three groups according to body mass index (kg/m 2): 18.5–24.9 normoweight (NW); 25.0–29.9 overweight (OW); ≥30 obese (OB), and they were classified in nine age subgroups: 50–59 (young-old, YO); 60–69 (old, O); 70–80 (oldest, OS). Fat-free mass, fat mass and body cell mass were investigated using conventional bioelectrical impedance analysis. Body composition was also assessed by bioelectrical impedance vector analysis and the RXc graph method. Results Body cell mass decreased significantly with age particularly in subgroups of the OW and OB groups ( p < 0.05). Mean vector displacement followed a definite pattern, with downward migration of the ellipses in the OW and OB groups, after 70 years of age. Conclusions Ageing was associated with a pattern of vector bioelectrical impedance analysis indicating decreased soft tissue mass (fat-free mass and body cell mass), particularly in OW and OB-OS healthy men. We suggest 70 years of age as a cut-off for significant quantitative and qualitative (tissue electrical properties) body composition modifications. This bioelectrical impedance vector analysis pattern associated with ageing and across the different body mass index categories, may be useful for clinical purposes and can be used in geriatric routine to accurately assess the body composition modifications occurring in the elderly.

Patterns of bioelectrical impedance vector distribution by body mass index and age: implications for body-composition analysis

Bioelectrical impedance analysis (BIA) gives resistance (R) and reactance (Xc). R and Xc normalized for body height (H) can be plotted as a bivariate vector (H(2)/Xc versus H(2)/R). Vector BIA is useful for studying the determinants of BIA results. We investigated the effect of age on BIA results and its relevance to body-composition analysis in a large database of impedance vector distributions stratified by age, sex, and body mass index (BMI). Mean bivariate vector distribution patterns (95% confidence ellipses) were examined in a German population of 15605 children and adolescents and 213294 adults. Children and adolescents were divided into 3 age groups with up to 5 BMI categories. In adults, 5 BMI categories were stratified into 7 age groups. Mean impedance vectors were shorter in children than in adults. The vector distribution pattern was influenced by sex, BMI, and age, with shorter vectors in females than in males and longer vectors with increasing BMI. Consistent with a decrease in body cell mass with increasing age, there was a downward slope in the mean vector with age as a result of a decrease in the H(2)/Xc vector component. By contrast, there was no age-dependent increase in the H(2)/R vector component. In women of the same BMI at different ages, H(2)/R and percentage fat mass tended to decrease with age. The lack of an age-dependent increase in the H(2)/R vector component renders conventional BIA unsuitable for an examination of the age-related increase in body fat mass. By contrast, the increase in the H(2)/Xc vector component with advancing age suggests the potential of BIA to depict the age-related decrease in body cell mass.

Laparoscopic gastric banding and body composition in morbid obesity

Gastric banding induced considerable and rapid weight loss in morbid obesity. Nevertheless data on changes in body composition following gastric banding are scanty. In this study, we evaluated the 2-year changes in body composition in a small group of morbidly obese women treated by laparoscopic adjustable gastric banding (LAGB) associated with a well balanced low-calorie diet. We studied 20 premenopausal morbid obese women with BMI ranging from 35 to 57 (kg/m2) before, and 6, 12 and 24 months after laparoscopic adjustable gastric banding (LAGB). A well balanced 5.4 MJ/day hypocaloric diet was prescribed after surgery. Total body water (TBW), fat-free mass (FFM) and fat mass (FM) were investigated using conventional bioelectrical impedance analysis (BIA). Tissue hydration was also assessed by impedance vector analysis and the RXc graph method. The subjects showed a total weight loss of 28% of baseline body weight. In the first 6 months after surgery, patients lost 18.5+/-5.9 kg of body weight (17.6+/-6.2 kg of FM and 0.7+/-1.4 kg of FFM). From 6 to 12 months, a further 12.5+/-7.5 kg of body weight was lost (10.5+/-8.2 kg of FM and 2.2+/-3.8 kg of FFM). During the last 12 months, weight loss was 3.0+/-2.3 kg (1.9+/-3.7 kg of FM and 1.1+/-2.9 kg of FFM). The weight loss observed after LAGB was mainly due to a decrease in FM, whereas TBW, FFM and BCM were only slightly and non-significantly reduced. No changes in body hydration status were observed after surgery. LAGB associated with a well balanced low-calorie diet achieved a satisfactory 2-year weight loss, while sparing FFM and not causing body fluid alterations.

A New Simple Method for the Measurement of Visceral Fat Accumulation by Bioelectrical Impedance

We and others (1–9) have shown that the accumulation of visceral fat is associated with multiple risk factor syndrome more closely than with the BMI itself or the amount of subcutaneous fat. In these studies, computed tomography (CT) scan at the umbilical level (10) was used for the assessment of visceral fat area (VFA). However, the method is not cost-effective and/or radiation exposure is problematic; thus, it is often unsuitable for screening large groups of individuals. There is a need for a simple and noninvasive method to assess visceral fat accumulation. The bioelectrical impedance analysis (BIA) method, which is based on the electric resistance difference between the fat and components of other organs (11–14), should meet this need. Conventional BIA approaches have estimated total fat content but not regional fat distribution (11–13). Recently, attempts to assess the amount of abdominal subcutaneous fat by the local BIA method were reported (14). Here, we developed a new technique to specifically evaluate VFA by using the abdominal BIA method. The study subjects were 59 healthy volunteers and 32 inpatients with suspected cardiovascular disease at Osaka University Hospital. Waist circumference (Wc) at the umbilical level was measured in the late exhalation phase while standing. All subjects underwent the abdominal BIA method to estimate VFA. The voltage occurring at the flank to the flow of current between the umbilicus and the back correlates significantly …

Body composition measurements: interpretation finally made easy for clinical use.

This review presents the latest clinical applications of bioelectrical impedance analysis. It discusses the evaluation of nutritional status by using fat-free mass and body fat, percentiles of fat-free mass and body fat, height-normalized fat-free mass and body fat mass indices and a resistance/reactance vector graph. Fat-free mass and body fat can be used to evaluate nutritional status by comparing individuals or groups of individuals with themselves or with reference values. Percentile distributions are also useful in determining whether individuals or groups fall within the population range. Percentile ranks can also be used to define nutritional depletion and obesity. The use of the fat-free mass and body fat mass indices has the advantage of compensating for differences in body height. The use of low, normal, high and very high fat-free mass and body fat mass indices ranges that correspond to underweight, normal, overweight and obese body mass index categories further aid in the nutritional assessment process. With vector bioelectrical impedance analysis, an individual impedance vector is compared with the 50, 75, and 95% tolerance ellipses calculated in the reference, healthy population, allowing evaluation in any clinical condition. More accurate estimates of conventional bioelectrical impedance analysis equations might be obtained in individuals with a normal impedance vector. The assessment of fat-free mass and body fat provides valuable information about changes in body composition with weight gain or loss and physical activity, and during ageing. The use of percentiles and height-normalized fat-free mass and body fat permit the classification of patients as under or overnourished.

Impedance vector distribution by body mass index and conventional bioelectrical impedance analysis in obese women

Background and Aim: To compare the body fluid status assessments provided by conventional bioelectrical impedance analysis (BIA) and vector BIA in moderate and severe obesity. Methods and Results: We studied 516 normotensive Caucasian women (mean age: 48±9.2 years), who were agematched and divided into four groups on the basis of their body mass index (BMI): 99 normal weight women with a BMI of 19–25 Kg/m 2; 228 preboese overweight women with a BMI of 25–30 Kg/m 2; 132 women with class I–II obesity (BMI: 30–35 Kg/m 2), and 57 women with class III obesity (BMI: 40–64 Kg/m 2). Single-frequency (50 kHz) tetrapolar (hand-foot) bioelectrical impedance measurements were made, and total body water (TBW) and extracellular water (ECW) were estimated using conventional BIA regression equations. The RXc graph method was used for vector BIA, with the set of 327 women with a BMI of 19–30 Kg/m 2 being adopted as the reference population. Mean vector displacement followed a definite pattern, with progressive vector shortening as the BMI increased, and along a fixed phase angle. This pattern indicates more TBW due to a greater soft tissue mass with average normal hydration. Short and downsloping vectors indicating fluid overload were more frequent in the group with class III obesity than in the group with class I obesity (19 vs 5%). The absolute values of TBW and ECW were significantly higher in the obese and overweight subjects than in those with normal weight subjects. TBW as a percentage of body weight was significantly lower in the obese subjects. Conclusions: BMI influenced the impedance vector distribution pattern, which proved to be consistent up to a BMI of 64 Kg/m 2. Obese women with an altered body composition can be identified and monitored using vector BIA.

Assessment of body composition by bioelectrical impedance analysis without the need for measurement of height

Conventional whole-body single frequency bioelectrical impedance analysis (BIA) of body composition typically uses height as a surrogate measure of conductor length. A new method of BIA analysis for the prediction of body cell mass (BCM) and extracellular water (ECW, as % body weight) not using height has been introduced–the Soft Tissue Analyser (STATM, Akern Sri, Florence, Italy)–making it ideal for use in subjects where measurement of height is difficult or impossible. The performance of the new analytical method in predicting BCM and ECW in 139 normal control subjects was assessed by comparison with reference data obtained from a four-component (4-C) model of body composition and with predictions obtained from conventional BIA analysis. Both predicted BCM and ECW were strongly (r=0.82, SEE=6.3 kg and 0.89, SEE=1.3 kg respectively) correlated with the corresponding 4-C model measurements although differing significantly from the lines of identity (P<0.0001). Fat-free mass, calculated from STA estimates of BCM and ECW, was better predicted (r=0.91, SEE=5.6 kg). The significant differences in STA-group mean values for BCM and ECW and wide limits of agreement compared with the reference data indicate that the method cannot be used with confidence for prediction of these body compartments despite the obvious advantage of not requiring an accurate measurement of height.

Comparison of Vector and Conventional Bioelectrical Impedance Analysis in the Optimal Dry Weight Prescription in Hemodialysis

Background: Dry weight prescription is commonly based on symptoms induced by inappropriate fluid removal by hemodialysis (HD). Aim of this study was to compare the assessment of volume status by conventional bioelectrical impedance analysis (BIA) and the resistance-reactance (RXc) graph method in HD patients achieving their target dry weight determined on clinical criteria. Methods: We studied 39 HD patients (23 males and 16 females, mean age 52 ± 17 years, dialytic age 41.2 ± 37 months). Dry weight, prescribed according to the standard clinical criteria, was constantly achieved in the last 3 months. Patients symptom-free over the last 3 months were defined as asymptomatic. Patients with either muscular cramps or hypotensive episodes were defined as symptomatic. Thirty-three healthy volunteers (11 males, 22 females, mean age 50 ± 11 years) constituted the control group. Standard, single frequency (50 kHz), tetrapolar, BIA measurements were obtained in controls, and in patients before, every 60 min, and 30 min after one HD session. Total body water (TBW), and extracellular water (ECW) were calculated using conventional BIA regression equations. In both groups, tissue hydration was also assessed by the RXc graph method. Results: On the basis of 95% tolerance interval (mean ± 2 SD) for the ECW (%) calculated in healthy subjects (ECW = 35–44%), HD patients were divided into 3 groups according to their post-HD ECW: 72% normohydrated with ECW 35–44%, 10% overhydrated with ECW >44%, and 18% underhydrated with ECW <35%. Patients were also classified into 3 categories according to the RXc graph method: 38% normohydrated with vectors within the reference 75% tolerance ellipse, 0% overhydrated with short vectors below the lower pole of the 75% tolerance ellipse, and 62% underhydrated with long vectors above the upper pole of the 75% tolerance ellipse. The progressive removal of body fluid during HD treatment was associated with a progressive increase in both impedance vector components, R and Xc. Eleven of thirty-nine patients (28%) were symptomatic during HD treatment in the last 3 months. The majority of these (73%) were classified as normohydrated according to ECW estimates, while 9 and 18% were classified as over- and underhydrated, respectively. This frequency distribution was significantly different from that obtained with the RXc graph method (χ² = 6.9, p = 0.03) where the majority (73%) were classified as underhydrated, while 0 and 27% were classified as over- and normohydrated, respectively. The frequency distribution of the 28 asymptomatic patients also significantly differed between conventional BIA and RXc graph hydration categories (χ² = 10.8, p = 0.005), since 11, 71 and 18% vs. 0, 43 and 57% of patients were classified as over-, normo-, and underhydrated, respectively. Conclusions: The classification of volume status based on conventional BIA was insensitive to either clinical situation (presence or absence of symptoms). In contrast, the classification based on the RXc graph was consistent with the clinical course in symptomatic patients (73% dehydrated, and 27% normohydrated), while it did not reflect the clinical course in asymptomatic patients, 57% of whom were classified as (already) underhydrated. A longitudinal study will establish the clinical usefulness of RXc graph indications in asymptomatic patients.