USE OF BIOELECTRICAL IMPEDANCE ANALYSIS TO ASSESS BODY COMPOSITION OF SEALS

Abstract: Bioelectrical impedance analysis (BIA) measures resistance and reactance of a current as it passes through an organism. The validity of using BIA as a tool to measure body water content, and hence body composition and condition, was tested on harp and ringed seals. The resistance and reactance readings from BIA were compared to estimates of total body water (TBW) determined via tritiated water dilution. The relationship between resistance and TBW (% of body mass) was linear after logarithmic transformation and the two variables were highly correlated. We describe the electrode configuration and placements which provide reliable results in these seals. Our findings indicate that BIA has considerable potential as an inexpensive, rapid, and reliable technique for estimating body composition of phocid seals.     

Validity of bioelectric impedance for body composition assessment in children

Whole-body bioelectrical impedance analysis (BIA) was evaluated for its reliability and accuracy in estimating body composition in children. The hypothesis that the index, body height2 divided by resistance (RI), can accurately predict fat-free body mass (FFB) and percent fat (%FAT) in children was tested on 94 caucasian children 10-14 yr old. Criterion variables were FFB and %FAT estimated using multicomponent equations developed for children. BIA measurements (resistance and reactance) were found to be reliable. Prediction accuracy (standard error of the estimate, SEE) for FFB from RI alone was 2.6 kg and for %FAT from RI and body weight was 4.2%. For RI, anthropometric variables and reactance, the SEE improved to 1.9 kg FFB. For RI and anthropometric variables, the SEE was 3.3% FAT. For anthropometric variables alone, the SEE's were 2.1 kg FFB and 3.2% FAT. Adult FFB and %FAT prediction equations cross-validated with this sample resulted in SEE's similar to those for adult samples. We conclude that RI together with anthropometry is a reliable and an acceptably accurate method of estimating FFB mass and %FAT in children.     

Noninvasive estimation of body composition in small mammals: a comparison of conductive and morphometric techniques

Body fat stores may serve as an index of condition in mammals. Thus, techniques that measure fat content accurately are important for assessing the ecological correlates of condition in mammal populations. We compared the ability of two conductive techniques, bioelectrical impedance analysis (BIA) and total body electrical conductivity (TOBEC), to predict body composition with that of morphometric methods in three small mammal species: red squirrels (n=13), snowshoe hares (n=30), and yellow-bellied marmots (n=4). Animals were livetrapped in northern Idaho; BIA (all subjects) and TOBEC (squirrels only) measurements were taken following chemical immobilization in the field, and morphometric measurements were taken postmortem. Information provided by BIA and TOBEC failed to improve upon the predictive power of morphometric equations for total body water (TBW) and lean body mass (LBM) in squirrels and hares, which do not store substantial amounts of fat (<5% body mass comprised of fat). Although the same pattern held with respect to LBM in marmots, which accumulate substantial amounts of body fat (>10% body mass), a BIA-based model proved best at estimating TBW, suggesting that the usefulness of conductive techniques may be a function of fat deposition. However, regardless of the technique used to predict body composition, estimates of body fat furnished by our equations failed to approximate actual fat levels accurately in all three test species, probably because these techniques only provide indirect estimates of fat content. These results highlight the limitations inherent in contemporary methods of animal fat estimation and underscore the need for the development of direct and accurate measures of body fat in mammals.     

Effect of Influenza-Induced Fever on Human Bioimpedance Values

Background and Aims

Bioelectrical impedance analysis (BIA) is a widely used technique to assess body composition and nutritional status. While bioelectrical values are affected by diverse variables, there has been little research on validation of BIA in acute illness, especially to understand prognostic significance. Here we report the use of BIA in acute febrile states induced by influenza.

Methods

Bioimpedance studies were conducted during an H1N1 influenza A outbreak in Venezuelan Amerindian villages from the Amazonas. Measurements were performed on 52 subjects between 1 and 40 years of age, and 7 children were re-examined after starting Oseltamivir treatment. Bioelectrical Impedance Vector Analysis (BIVA) and permutation tests were applied.

Results

For the entire sample, febrile individuals showed a tendency toward greater reactance (p=0.058) and phase angle (p=0.037) than afebrile individuals, while resistance and impedance were similar in the two groups. Individuals with repeated measurements showed significant differences in bioimpedance values associated with fever, including increased reactance (p<0.001) and phase angle (p=0.007), and decreased resistance (p=0.007) and impedance (p<0.001).

Conclusions

There are bioelectrical variations induced by influenza that can be related to dehydration, with lower extracellular to intracellular water ratio in febrile individuals, or a direct thermal effect. Caution is recommended when interpreting bioimpedance results in febrile states.     

ESTIMATION OF TOTAL BODY WATER IN HARBOR SEALS: HOW USEFUL IS BIOELECTRICAL IMPEDANCE ANALYSIS?

We evaluated bioelectrical impedance analysis (BIA) as a means of rapidly and inexpensively estimating total body water (TBW) of harbor seals ( Phoca vitulina ). Deuterium oxide dilution was used to estimate TBW in 17 adult females and 16 of their pups between birth and late lactation. Isotope dilution was also used to determine TBW in 12 adult males early and 10 of these males late in the breeding season. At the same time, resistance ( Rs ) and reactance ( Xc ) measurements were taken using a tetrapolar, impedance plethysmograph (Model 101 A, RJL Systems). Seals were sedated with diazepam prior to taking BIA measurements. Within-day duplicate Rs measurements on pups and adults, taken 2-240 min apart, differed by an average of 3.0%± 1.4% ( n = 42, CV = 102%). Movement of the seal during BIA measurements caused variability in both Rs and Xc values. BIA measurements were generally poor predictors of TBW. Rs was significantly correlated with TBW in pups only ( Rs = 0.93, P = 0.001, n = 11). Bioelectrical conductor volume (length2/ Rs ) was significantly correlated with TBW only in adult females ( Rs = 0.63, P = 0.02, n = 14). We conclude that BIA is not a reliable method of estimating TBW in wild harbor seals.     

Reliability and validity of body composition measures in female athletes.

The purpose of this investigation was to determine the reliability and validity of bioelectrical impedance (BIA) and near-infrared interactance (NIR) for estimating body composition in female athletes. Dual-energy X-ray absorptiometry was used as the criterion measure for fat-free mass (FFM). Studies were performed in 132 athletes [age = 20.4 +/- 1.5 (SD) yr]. Intraclass reliabilities (repeat and single trial) were 0.987-0.997 for BIA (resistance and reactance) and 0.957-0.980 for NIR (optical densities). Validity of BIA and NIR was assessed by double cross-validation. Because correlations were high (r = 0.969-0.983) and prediction errors low, a single equation was developed by using all 132 subjects for both BIA and NIR. Also, an equation was developed for all subjects by using height and weight only. Results from dual-energy X-ray absorptiometry analysis showed FFM = 49.5 +/- 6.0 kg, which corresponded to %body fat (%BF) of 20.4 +/- 3.1%. BIA predicted FFM at 49.4 +/- 5.9 kg (r = 0.981, SEE = 1.1), and NIR prediction was 49. 5 +/- 5.8 kg (r = 0.975, SEE = 1.2). Height and weight alone predicted FFM at 49.4 +/- 5.7 kg (r = 0.961, SEE = 1.6). When converted to %BF, prediction errors were approximately 1.8% for BIA and NIR and 2.9% for height and weight. Results showed BIA and NIR to be extremely reliable and valid techniques for estimating body composition in college-age female athletes.     

A new BIA equation estimating the body composition of young children

Bioelectric impedance analyses (BIA) provides a valid and reliable measure of body composition in field, clinical, and research settings if standard protocol procedures are followed, and population-specific equations are available and utilized. The objective of this study was to create and cross-validate a new BIA body composition equation with representative healthy weight (HW), overweight (OW), and obese (OB) young children. Participants were 436 children who were 5-11 years of age. Dual-energy absorptiometry fat-free mass (FFM) was used as the criterion measure and a single frequency tetra-polar BIA device was used to create the new BIA equation. The new BIA equation explained 95.2% of the variance in FFM with no statistical shrinkage upon cross-validation. The use of this equation may help to identify effective intervention strategies to prevent or combat childhood obesity, and may assist in additional conditions or treatments where information concerning body composition measures would provide greater accuracy and sensitivity measures for preventing or combating disease.     

Reliability of Multifrequency Bioelectrical Impedance Analysis to Quantify Body Composition in Patients After Musculoskeletal Trauma

BackgroundChanges in body composition, especially loss of lean mass, commonly occur in the orthopedic trauma population due to physical inactivity and inadequate nutrition. The purpose of this study was to assess inter-rater and intra-rater reliability of a portable bioelectrical impedance analysis (BIA) device to measure body composition in an orthopedic trauma population after operative fracture fixation. BIA uses a weak electric current to measure impedance (resistance) in the body and uses this to calculate the components of body composition using extensively studied formulas.MethodsTwenty subjects were enrolled, up to 72 hours after operative fixation of musculoskeletal injuries and underwent body composition measurements by two independent raters. One measurement was obtained by each rater at the time of enrollment and again between 1-4 hours after the initial measurement. Reliability was assessed using intraclass correlation coefficients (ICC) and minimum detectable change (MDC) values were calculated from these results.ResultsInter-rater reliability was excellent with ICC values for body fat mass (BFM), lean body mass (LBM), skeletal muscle mass (SMM), dry lean mass (DLM), and percent body fat (PBF) of 0.993, 0.984, 0.984, 0.979, and 0.986 respectively. Intra-rater reliability was also high for BFM, LBM, SMM, DLM, and PBF, at 0.994, 0.989, 0.990, 0.983, 0.987 (rater 1) and 0.994, 0.988, 0.989, 0.985, 0.989 (rater 2). MDC values were calculated to be 4.05 kg for BFM, 4.10 kg for LBM, 2.45 kg for SMM, 1.21 kg for DLM, and 4.83% for PBF.ConclusionPortable BIA devices are a versatile and attractive option that can reliably be used to assess body composition and changes in lean body mass in the orthopedic trauma population for both research and clinical endeavors. Level of Evidence: III     

INDICES OF BODY CONDITION AND BODY COMPOSITION IN FEMALE ANTARCTIC FUR SEALS (ARCTOCEPHALUS GAZELLA)

An attempt was made to develop simple, inexpensive, rapid means of determining body composition in Antarctic fur seals ( Arctocephalus gazella ). Measurements of total body water ( TBW ) and total body lipid ( TBL ), obtained by hydrogen isotope dilution, were compared to the results of bioelectrical impedance analysis ( BIA ) and morphometric indices of body condition in 52 adult females. TBW was weakly correlated with BIA measurements of resistance ( v = -0.30, P < 0.03). Conductor volume (length2/resistance) was more highly correlated with TBW ( r = 0.75, P < 0.0001) and the inclusion of mass into the predictive equation improved the correlation further ( r = 0.95, P < 0.0001). A body condition index (mass/length) previously used in pinniped studies was positively correlated to TBL ( r = 0.77, P < 0.0001) validating its use as a relative index of condition. However, body mass alone was highly correlated to TBW ( r = 0.94, P < 0.0001) and appears to provide a simple, rapid means of estimating body composition in adult females. This technique may also be applicable to juvenile male Antarctic fur seals.     

Use of bioelectrical impedance to assess body composition changes at high altitude.

This study determined the feasibility of using bioelectrical impedance analysis (BIA) to assess body composition alterations associated with body weight (BW) loss at high altitude. The BIA method was also evaluated relative to anthropometric assessments. Height, BW, BIA, skinfold (SF, 6 sites), and circumference (CIR, 5 sites) measurements were obtained from 16 males (23-35 yr) before, during, and after 16 days of residence at 3,700-4,300 m. Hydrostatic weighings (HW) were performed pre- and postaltitude. Results of 13 previously derived prediction equations using various combinations of height, BW, age, BIA, SF, or CIR measurements as independent variables to predict fat-free mass (FFM), fat mass (FM), and percent body fat (%Fat) were compared with HW. Mean BW decreased from 84.74 to 78.84 kg (P less than 0.01). As determined by HW, FFM decreased by 2.44 kg (P less than 0.01), FM by 3.46 kg (P less than 0.01), and %Fat by 3.02% (P less than 0.01). The BIA and SF methods overestimated the loss in FFM and underestimated the losses in FM and %Fat (P less than 0.01). Only the equations utilizing the CIR measurements did not differ from HW values for changes in FFM, FM, and %Fat. It was concluded that the BIA and SF methods were not acceptable for assessing body composition changes at altitude.     

New bioimpedance model accurately predicts lower limb muscle volume: validation by magnetic resonance imaging

Conventional bioimpedance analysis (BIA) methods now simplify the representation of lower limb geometry and electrical properties for body composition estimation. In the present study, a three-dimensional model of the lower limb was assembled by segmentation of magnetic resonance cross-sectional images (MRI) for adipose tissue, skeletal muscle, and bone. An electrical network was then associated with this model. BIA and MRI measurements were made in six lean subjects (3 men and 3 women, age 32.2 +/- 6.9 yr). Assuming 0.85 S/m for the longitudinal conductivity of the muscle, the model predicted in the examined subjects an impedance profile that conformed well to the BIA impedance profile; predicted and measured resistances were similar (261.3 +/- 7.7 vs. 249 +/- 9 Omega; P = not significant). The resistance profile provided, through a simpler model, muscle area estimates along the lower limb and total leg muscle volume (mean 4,534 cm(3) for men and 4,071 cm(3) for women) with a mean of the absolute value of relative error with respect to MRI of 6.2 +/- 3.9. The new approach suggests that BIA can reasonably estimate the distribution and volume of muscles in the lower extremities of lean subjects.     

Effect of physical training on body composition in Moscow adolescents

The influence of physical activity on body mass components has been studied using a sample of Moscow children. 195 girls and 259 boys of Russian ethnicity from 12 to 17 years old were investigated cross-sectionally in 2005 in different Moscow schools. According to the level of physical activity they were divided into three groups: 1-those who did not take part in regular physical exercise (44 boys and 50 girls); 2-those who took part in special sports programs in general education schools (82 boys and 82 girls); 3-students of special sports schools with a high sports ranking (133 boys and 63 girls). The program included anthropometric measurements, evaluation of sexual maturation indices, somatotypes, and "functional" traits (diastolic and systolic blood pressure, pulse rate, hand grip, etc). For the study of body composition, bioelectrical impedance analysis (BIA) was used. The estimates of body mass components were also calculated using the anthropometric measurements. For the fat component, the estimates obtained by BIA and the anthropometric methods were highly correlated: r=0.85-0.88. Age changes of BIA measurements and body components were analysed. With multiple regression analysis it was shown that BIA measurements are dependent on a great number of morphological and functional traits, with the most informative sets of traits being selected. The degree of physical activity has a strong effect on body components: the contents of fat-free mass (FFM) and total body water (TBW) significantly increase, and the fat mass (FM) in girls decreases.     

No apparent progress in bioelectrical impedance accuracy: validation against metabolic risk and DXA

Bioelectrical impedance (BIA) is quick, easy, and safe when quantifying fat and lean tissue. New BIA models (Tanita BC-418 MA, abbreviated BIA(8)) can perform segmental body composition analysis, e.g., estimate %trunkal fatness (%TF). It is not known, however, whether new BIA models can detect metabolic risk factors (MRFs) better than older models (Tanita TBF-300, abbreviated BIA(4)). We therefore tested the correlation between MRF and percentage whole-body fat (%BF) from BIA(4) and BIA(8) and compared these with the correlation between MRF and dual-energy X-ray absorptiometry (DXA, used as gold standard), BMI and waist circumference (WC). The sample consisted of 136 abdominally obese (WC >or= 88 cm), middle-aged (30-60 years) women. MRF included fasting blood glucose and insulin; high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides; high sensitive C-reactive protein, plasminogen activator inhibitor-1 (PAI-1), and fibrinogen; and alanine transaminase (ALT) liver enzyme. We found that similar to DXA, but in contrast to BMI, neither %BF BIA(4) nor %BF BIA(8) correlated with blood lipids or ALT. In the segmental analysis of %TF, BIA(8) only correlated with inflammatory markers, but not insulin, blood lipids, or ALT liver enzyme (in contrast to WC and %TF DXA). %TF DXA was associated with homeostatic model assessment insulin resistance (HOMA-IR) independently of WC (P = 0.03), whereas %TF BIA(8) was not (P = 0.53). Receiver-operating characteristic (ROC) curves confirmed that %TF BIA(8) did not differ from chance in the detection of insulin resistance (P = 0.26). BIA estimates of fatness were, at best, weakly correlated with obesity-related risk factors in abdominally obese women, even the new eight-electrode model. Our data support the continued use of WC and BMI.     

Application of bioelectrical impedance analysis in prediction of light kid carcass and muscle chemical composition

Carcass data were collected from 24 kids (average live weight of 12.5±5.5 kg; range 4.5 to 22.4 kg) of Jarmelista Portuguese native breed, to evaluate bioelectrical impedance analysis (BIA) as a technique for prediction of light kid carcass and muscle chemical composition. Resistance (Rs, Ω) and reactance (Xc, Ω), were measured in the cold carcasses with a single frequency bioelectrical impedance analyzer and, together with impedance (Z, Ω), two electrical volume measurements (Vol_A and Vol_B, cm²/Ω), carcass cold weight (CCW), carcass compactness and several carcass linear measurements were fitted as independent variables to predict carcass composition by stepwise regression analysis. The amount of variation explained by Vol_A and Vol_B only reached a significant level (P<0.01 and P<0.05, respectively) for muscle weight, moisture, protein and fat-free soft tissue content, even so with low accuracy, with Vol_A providing the best results (0.326⩽R²⩽0.366). Quite differently, individual BIA parameters (Rs, Xc and Z) explained a very large amount of variation in dissectible carcass fat weight (0.814⩽R²⩽0.862; P<0.01). These individual BIA parameters also explained a large amount of variation in subcutaneous and intermuscular fat weights (respectively 0.749⩽R²⩽0.793 and 0.718⩽R²⩽0.760; P<0.01), and in muscle chemical fat weight (0.663⩽R²⩽0.684; P<0.01). Still significant but much lower was the variation in muscle, moisture, protein and fat-free soft tissue weights (0.344⩽R²⩽0.393; P<0.01) explained by BIA parameters. Still, the best models for estimation of muscle, moisture, protein and fat-free soft tissue weights included Rs in addition to CCW, and accounted for 97.1% to 99.8% (P<0.01) of the variation observed, with CCW by itself accounting for 97.0% to 99.6% (P<0.01) of that variation. Resistance was the only independent variable selected for the best model predicting subcutaneous fat weight. It was also selected for the best models predicting carcass fat weight (combined with carcass length, CL; R²=0.943; P<0.01) and intermuscular fat weight (combined with CCW; R²=0.945; P<0.01). The best model predicting muscle chemical fat weight combined CCW and Z, explaining 85.6% (P<0.01) of the variation observed. These results indicate BIA as a useful tool for prediction of light kids’ carcass composition.     

Reliability and validity of bioelectrical impedance in determining body composition

This study was designed to examine the reliability and validity of the bioelectrical impedance method (BIA) of measuring body composition and compare its accuracy with the results obtained by standard anthropometric methods BIA, skinfold fat, and hydrostatically measured percent fat (% fat) were obtained on 44 women and 24 men. Each subject was tested four times by two testers on two different days. Generalizability theory was used to estimate reliability and measurement error that considered both day-to-day and intertester error. The BIA, skinfold fat, and hydrostatic methods were all found to be reliable (Rxx = 0.957-0.987) with standard errors ranging from 0.9 to 1.5% fat. An additional 26 men (n = 50) and 38 women (n = 82) were tested once and combined with the data used for the reliability analysis to cross-validate BIA estimates of % fat with hydrostatically determined % fat. The cross-validation correlations for the BIA determinations of % fat ranged from 0.71 to 0.76, which were significantly lower than that obtained with the sum of seven (sigma 7) skinfolds equations (rxy = 0.92 for men and 0.88 for women). The correlations between the weight-to-height ratio body mass index (BMI) and hydrostatically determined % fat were 0.75 and 0.74 for men and women, respectively. The standard errors of estimate for the two BIA models ranged from 4.6 to 6.4% fat compared with 2.6 and 3.6% fat for the sigma 7 equations. The BIA method for measuring body composition was comparable to the BMI method, with height and weight accounting for most of the variance in the BIA equation.     

Bioelectrical Impedance Vector Analysis (BIVA) in Slovak population: application in a clinical sample

The purpose of this study is to provide new data on body composition in the Slovak population, particularly impedance vector components according to sex and age, relevant for bioelectrical impedance vector analysis (BIVA) in a clinical sample. The reference sample consisted of 1543 apparently healthy individuals (1007 females and 536 males), aged from 18 to 92 years and of 60 patients with Parkinson’s disease (PD) (26 females and 34 males), aged from 40 to 81 years. Bioelectrical parameters of resistance (R) and reactance (Xc) were measured with a monofrequency analyser (BIA 101). BIVA was used to analyse tissue electric properties in control subjects and patients with PD. The mean vector position differed significantly between PD patients and healthy controls in males of age subgroups 60–69 years and 70–79 years, respectively. These results were conterminous with significant Hotelling’s T²-test; 60–69 y T²=7.8, P=0.024 and 70–79 y T²=7.6, P=0.026. In the RXc-score graph three patients had values outside the 95% ellipse. Altered tissue electric properties were present in 23.5% of males and 15.4% of females. Distribution of impedance vector components in different age categories of healthy Slovak subjects are relevant to comparative population studies and to clinical practice.     

Estimation of human body composition by electrical impedance methods: a comparative study

This study 1) further validated the relationship between total body electrical conductivity (TOBEC) and densitometrically determined lean body mass (LBMd) and 2) compared with existing body composition techniques (densitometry, total body water, total body potassium, and anthropometry) two new electrical methods for the estimation of LBM: TOBEC, a uniform current induction method, and bioelectrical impedance analysis (BIA), a localized current injection method. In a sample of 75 male and female subjects ranging from 4.9 to 54.9% body fat the correlation between LBMd and LBM predicted from TOBEC by use of a previously developed regression equation was extremely strong (r = 0.962), thus confirming the validity of the TOBEC method. LBM predicted from BIA by use of prediction equations provided with the instrument also correlated with LBMd (r = 0.912) but overestimated LBM compared with LBMd in obese subjects. However, no such systematic error was apparent when new prediction equations derived from this heterogeneous sample of subjects were applied. Thus the TOBEC and BIA methods, which are based on the differing electrical properties of lean tissue and fat and which are convenient, rapid, and safe, correlate well with more cumbersome human body composition techniques.     

Percentage of total body fat as estimated by three automatic bioelectrical impedance analyzers

The present study aimed to compare the accuracy of estimating the percentage of total body fat (%TBF) among three bioelectrical impedance analysis (BIA) devices: a single-frequency BIA with four tactile electrodes (SF-BIA4), a single-frequency BIA with eight tactile electrodes (SF-BIA8) and a multi-frequency BIA with eight tactile electrodes (MF-BIA8). Dual-energy x-ray absorptiometry (DXA) and hydrostatic weighing (HW) were used as references for the measured values. Forty-five healthy college student volunteers (21 males: 172.9 +/- 5.5 cm and 65.8 +/- 9.1 kg and 24 females: 160.7 +/- 6.6 cm, 52.6 +/- 6.2 kg) were the subjects. Correlation coefficients between the BIA measurements and the references were calculated. The standard error of estimation (SEE) was calculated by regression analysis when estimating the reference measures (DXA and HW) from the predictor (SF-BIA4, SF-BIA8 and MF-BIA8). The differences in %TBF between the reference and the predictor, calculated by the reference minus the predictor, were plotted against the %TBF measured by the references. The MF-BIA 8 here showed the highest correspondence to the reference and the least estimation error compared with the other BIA methods. It is considered that there is a limit to directly estimate FFM from a regression equation using impedance, weight, height and age as independent variables, and that %TBF can be more accurately estimated by measuring segmental impedances using eight electrodes and multi-frequency electric currents and then estimating total body water from these impedances.     

Reliability and variability of bioimpedance measures in normal adults: effects of age, gender, and body mass

This study aimed to analyze the reliability and evaluate the causes of variability of bioimpedance parameters. Direct measures were analyzed because they are not affected by inappropriate prediction models. Resistance (R), reactance (Xc), and phase angle (PA) were determined at three fixed frequencies (5, 50, and 100 kHz) in 653 normal Germans (244 males and 409 females), aged 20-90 years, using a phase-sensitive whole-body tetrapolar bioimpedance analyzer (BIA 2000-M, Data Input, Germany). From these values, six bioimpedance ratios were calculated (R(5)/R(50), R(5)/R(100), Xc(5)/Xc(50), Xc(5)/Xc(100), PA(5)/PA(50), and PA(5)/PA(100)). Reliability of duplicate measurements, as determined by technical error, is high. ANOVA for repeated measurements yields a significant frequency main effect (within-subjects factor) and significant effects of age and gender (between-subject factors) on variation of resistance, reactance, and phase angle. Multiple regression analyses indicate independent effects of age, gender, and body mass index on variability of resistance, reactance, and phase angle at the three frequencies. Gender primarily influences variation in resistance (smaller values in males), whereas age mainly affects variations in reactance and phase angle (smaller values in older adults). Obesity is associated with smaller resistance (at all frequencies) and smaller reactance (high frequencies), but larger phase-angle values (low frequency). The study shows that variability of direct bioimpedance measures depends on age, gender, and body mass characteristics of the study population. The potential benefit for using both low and high frequencies in R measures is to differentiate between extra- and intracellular fluid spaces, which may be altered during human growth and aging.