Bioelectrical Impedance Analysis Models Research Articles

Çocuklarda Vücut Kompozisyonunun Belirlenmesi: Biyoelektrik İmpedans Analizi

Çocukluk döneminde vücut kompozisyonunun etkisi, yetişkinlik dönemi risk faktörleri hakkında bilgi vermektedir. Bu nedenle, çocukluk döneminde, vücut suyu, kemik kütlesi, yağ kütlesi ve yağsız vücut kütlesindeki değişimin takip edilmesi ve egzersizin bu değişimlere olan etkisi klinik sağlık ve spor bilimlerinin araştırma alanı olmuştur. Çocukların vücut ağırlığını oluşturan bileşenler farklı büyüme ve gelişim döneminde değişmektedir. Büyüme ve gelişme döneminde vücut kompozisyonu ölçülmesi ve değerlendirilmesinde, kullanışlı, geçerli ve güvenilir yöntemin seçilmesi en kritik noktadır. En doğru sonuca ulaşabilmek için kullanılan laboratuvar yöntemlerinin çoğu uzmanlık gerektirmektedir. Laboratuvar ortamı olmayan büyük çalışma gruplarının ölçümünde kolay saha yöntemleri tercih edilmektedir. Çoğu zaman kullanım kolaylığı ve taşınabilir olması nedeniyle bilimsel çalışmalarda sıklıkla Biyoelektrik İmpedans Analizi (BİA) seçilmektedir. Popülasyona uygun BİA modelinin ve formülünün belirlenmesiyle doğru ve kesin sonuçlar elde edilmesi oldukça kolaydır. Bu derlemede, çocukların neden yetişkinlerden farklılaştığı, ölçümlerde kullanılan yöntem ve geliştirilmiş formüllerin sınırlılıkları ortaya konulmuştur. Vücut kompozisyonu bileşenlerinin belirlenmesinde kullanılan yöntemlere ait çalışmalar tartışılmıştır. BİA’dan elde edilen ham verinin kullanımındaki yaklaşımlar ve modele ait yazılımdaki formül yerine popülasyona özel uygun regresyon formülünün seçimi ele alınmıştır. Bu derlemede ayrıca, oldukça özel bir grup olan sporcu çocuklardaki farklılıklar analiz edilmiştir. Ayrıca fizyolojik ve performans faktörlerini etkileyen yağ ve yağsız vücut kütlesinin belirlenmesinde doğru sonuçlara ulaşmak için hangi verilerin dikkate alınması gerektiği bu derlemede özetlenmiştir.

Energetic Status of Alaskan Chinook Salmon: Interpopulation Comparisons and Predictive Modeling Using Bioelectrical Impedance Analysis

AbstractAdult Pacific salmon Oncorhynchus spp. undertake energetically demanding migrations where they must have adequate energy reserves to survive to reach spawning locations and reproduce. Lethal proximate analysis provides insight into available energy stores (e.g., lipids), but the ability to monitor energetic status nonlethally may be useful for managers. Nonlethal monitoring may be more cost effective, reduce harm to sensitive populations, allow for more fish to be sampled, and assessments can be done relatively quickly. Chinook Salmon Oncorhynchus tshawytscha (N = 129) were sampled for proximate analysis from four populations in Alaska to examine variation in energetic status before and after spawning migration and to create predictive bioelectrical impedance analysis (BIA) models for this species. In addition to proximate analysis we tested the variability between two BIA devices (Q2 and CQR), whether BIA models were generalizable to a congener, Chum Salmon Oncorhynchus keta, and the feasibility of integrating BIA into field studies. The populations that were sampled at prespawning migration had higher %lipid (N = 77; mean = 43%) than those that were collected at postspawning migration (N = 52; mean = 20%). Total %lipid and %water was more accurately predicted based on BIA measurements that were made by using the Q2 device (RMSE = 5.33 and RMSE = 2.43, respectively) than on those that were made by using the CQR device measurements (RMSE = 6.27; RMSE = 2.66). The between‐species (Chinook Salmon to Chum Salmon RMSE = 19.47; Chum to Chinook RMSE = 7.69) models were less accurate than species‐specific models that were created for Chinook Salmon and Chum Salmon, suggesting that single‐species models should be used. We field‐tested the BIA model to predict %lipid and %water for Chinook Salmon on a remote Southeast Alaska river. The range of predicted values of %lipid and %water was similar to the results that are obtained via proximate composition from the other populations. Our results indicate that BIA could be a valuable tool for assessing the spatial and temporal patterns of energetic status for Chinook Salmon populations.

Development of Striped Bass Relative Condition Models with Bioelectrical Impedance Analysis and Associated Temperature Corrections

AbstractNutritional condition is a valuable metric in ecosystem‐based fisheries management. However, the need for lethal sampling for the most accurate indicators ethically and logistically limits sample sizes. Percent moisture has been recommended for management of Striped Bass Morone saxatilis. We sought to develop bioelectrical impedance analysis (BIA) models for five size‐classes of Striped Bass across three temperatures in a controlled laboratory setting. Results suggest that BIA is an accurate and robust method for estimating percent dry weight in Striped Bass, with model adjusted R2 values in the range of 0.70–0.89. Temperature correction models successfully removed a significant relationship (P < 0.0001) between temperature and BIA model residuals (P = 0.48). We recommend that these models be tested with independent data collected in a field setting.Received October 16, 2016; accepted April 5, 2017 Published online July 18, 2017

Seasonal Changes in Condition of Appalachian Brook Trout

AbstractReliable fish condition estimates help managers better understand ecosystem population dynamics. Therefore, our study objectives were to measure seasonal changes in percent dry weight and energy density (physiological‐based measures of condition) of stream‐dwelling Appalachian Brook Trout Salvelinus fontinalis, field‐validate bioelectrical impedance analysis (BIA) models, and compare reliability of BIA and morphometric‐based estimates of condition. Percent dry weight was highly correlated to energy density (R2 = 0.93; J/g wet weight = −1,803.5 + 286.43 ∙ [percent dry weight]), and the relationship was clearly different from those published previously for other salmonids. Significant seasonal changes in adult Brook Trout condition were observed and likely related to energy depletion from reproduction and changes in terrestrial invertebrate consumption. Adult percent dry weight peaked in early September and was lowest in February. Age‐0 fish did not have large changes in measured condition between summer and winter. Bioelectrical impedance analysis was able to estimate adult mean monthly percent dry weight reliably; however, it did not appear to outperform results from relative weight (Wr). Neither Wr nor predicted percent dry weight from BIA was a reliable estimator of condition for individual adult fish. The BIA model for age‐0 fish was unable to provide reliable predictions for either individual fish or monthly mean estimates, due in large part to the small range in measured condition. The BIA estimated monthly mean energy density more reliably than did Wr. Overall results of this study indicate that BIA did not perform appreciably better than Wr, which required much less effort to collect. Potential BIA model improvements may be possible by accounting for changes in skin temperature. Until improvements in the Brook Trout BIA models occur, their use should be limited to estimating mean energy density.Received August 16, 2016; accepted October 20, 2016 Published online January 12, 2017

Influence of Electrode Type and Location upon Bioelectrical Impedance Analysis Measurements of Brook Trout

AbstractIn recent years, bioelectrical impedance analysis (BIA) has started to develop into a low‐cost tool that can provide accurate estimates of fish condition. Past researchers have had success predicting mass‐based proximate condition components, but attempts to predict percent‐based components have not been as successful, suggesting that methodological improvements are needed. The percent dry weight (%DW) of a fish is a desirable value because energy density and body composition estimates can be obtained from it using previously developed or easily developable equations. The primary objective of this study was to determine the locations at which electrodes should be placed to provide the best estimates of %DW for brook trout Salvelinus fontinalis ranging from 140 to 330 mm (total length). A second objective was to determine the effect that electrode type has on the ability to predict %DW. Models developed using two electrode locations performed better than those with only one location. One set of measurements should be made by placing the electrodes along the dorsal midline (DML) of the fish. A second set should be made by placing one electrode on the dorsal midline directly in front of the dorsal fin and another on the ventral midline directly below the first electrode (DTVpre). On average, models developed using these locations explained 13.2% more of the variation in%DW than models developed using the same locations as previous researchers. Validation of the BIA models demonstrated that both subdermal needle (root mean square error [RMSE] = 1.34, R2 = 0.82) and less‐invasive external rod electrodes (RMSE = 1.37, R2 = 0.79) provided accurate estimates of %DW using the DML and DTVpre locations. More research is needed to determine whether these patterns hold true for smaller fish and species with distinctly different morphologies, bone structures, or scale types.

External cross-validation of bioelectrical impedance analysis for the assessment of body composition in Korean adults.

Bioelectrical impedance analysis (BIA) models must be validated against a reference method in a representative population sample before they can be accepted as accurate and applicable. The purpose of this study was to compare the eight-electrode BIA method with DEXA as a reference method in the assessment of body composition in Korean adults and to investigate the predictive accuracy and applicability of the eight-electrode BIA model. A total of 174 apparently healthy adults participated. The study was designed as a cross-sectional study. FM, %fat, and FFM were estimated by an eight-electrode BIA model and were measured by DEXA. Correlations between BIA_%fat and DEXA_%fat were 0.956 for men and 0.960 for women with a total error of 2.1%fat in men and 2.3%fat in women. The mean difference between BIA_%fat and DEXA_%fat was small but significant (P < 0.05), which resulted in an overestimation of 1.2 ± 2.2%fat (95% CI: -3.2-6.2%fat) in men and an underestimation of -2.0 ± 2.4%fat (95% CI: -2.3-7.1%fat) in women. In the Bland-Altman analysis, the %fat of 86.3% of men was accurately estimated and the %fat of 66.0% of women was accurately estimated to within 3.5%fat. The BIA had good agreement for prediction of %fat in Korean adults. However, the eight-electrode BIA had small, but systemic, errors of %fat in the predictive accuracy for individual estimation. The total errors led to an overestimation of %fat in lean men and an underestimation of %fat in obese women.

Reliability of Bioelectrical Impedance Analysis for Estimating Whole‐Fish Energy Density and Percent Lipids

AbstractWe evaluated bioelectrical impedance analysis (BIA) as a nonlethal means of predicting energy density and percent lipids for three fish species: Yellow perch Perca flavescens, walleye Sander vitreus, and lake whitefish Coregonus clupeaformis. Although models that combined BIA measures with fish wet mass provided strong predictions of total energy, total lipids, and total dry mass for whole fish, including BIA provided only slightly better predictions than using fish mass alone. Regression models that used BIA measures to directly predict the energy density or percent lipids of whole fish were generally better than those using body mass alone (based on Akaike's information criterion). However, the goodness of fit of models that used BIA measures varied widely across species and at best explained only slightly more than one‐half the variation observed in fish energy density or percent lipids. Models that combined BIA measures with body mass for prediction had the strongest correlations between predicted and observed energy density or percent lipids for a validation group of fish, but there were significant biases in these predictions. For example, the models underestimated energy density and percent lipids for lipid‐rich fish and overestimated energy density and percent lipids for lipid‐poor fish. A comparison of observed versus predicted whole‐fish energy densities and percent lipids demonstrated that models that incorporated BIA measures had lower maximum percent error than models without BIA measures in them, although the errors for the BIA models were still generally high (energy density: 15‐18%; percent lipids: 82‐89%). Considerable work is still required before BIA can provide reliable predictions of whole‐fish energy density and percent lipids, including understanding how temperature, electrode placement, and the variation in lipid distribution within a fish affect BIA measures.

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.

Accuracy of Consumer Grade Bioelectrical Impedance Analysis Devices Compared to Air Displacement Plethysmography

PURPOSE: The aim of this study was to compare body composition measures between consumer grade models of bioelectrical impedance analysis (BIA), skin folds and a criterion methodology, air displacement plethysmography (ADP). METHODS: Eighty-two female volunteers ranging from 19–67 years (31.96 ± 1.39) enrolled in this study. Body composition was assessed by seven site skin folds (SKF), ADP, Tetrapolar BIA (TBIA), and five consumer grade BIA devices: finger to finger (FF), hand to hand (HH) and three different leg to leg (LL1, LL2, LL3) models. In addition, LL3 was analyzed using the athletic (LL3a) and non-athletic modes (LL3b). This study was approved by the Institutional Review Board for Human Subjects at Eastern Washington University. RESULTS: The participants represented a wide range of percentage body fat (BF) as assessed by ADP (8.40 to 47.10, mean = 26.15 ± 0.93 SEE). No difference in estimating percent body fat was found between ADP and SKF, TBIA, FF, HH, LL1, LL2 and LL3a (r=0.862, 0.553, 0.775, 0.771, 0.765, 0.791, 0.798, respectively; p<0.001). A significant difference in estimating percent body fat was found between ADP and LL3b (r=0.051, p<0.001, SEE = 8.42). Bland-Altman plots of the differences between % fat by ADP and BIA versus average % fat by the two methods showed no systematic differences for SKF and six BIA models (mean differences ± SD: SKF, 1.92 ± 4.25; TBIA, 0.73 ± 7.3; FF, −1.55 ± 5.34, HH, 1.37 ± 5.35; LL1, −4.70 ± 5.40, LL2, −3.72 ±5.12 andLL3a, 1.70 ± 5.07; p<0.05). Systematic differences were found for the LL3b BIA model (mean difference ± SD = −6.11 ±31.40). CONCLUSIONS: Skin fold measures were found to be the most reliable simple method of estimating body composition. Of the all BIA machines tested, the strongest relationship was found in the LL models with the LL3 in athletic mode being the most reliable. For the most affordable models, the LL2 model was the most reliable when comparing to ADP.

Comparison of Three Consumer Grade Bioelectrical Impedance Analyses Devices and Skinfold Measurements

Many techniques to assess body composition require expensive equipment or trained technicians. Bioelectrical impedance analysis (BIA) is an indirect, simple method to assess body composition and there are several inexpensive consumer models on the market. PURPOSE: The aim of this study was to evaluate the accuracy of three consumer BIA models, compared with percent body fat as assessed by 7 site skin fold thickness (7SKF). In addition this study examined the relationship between BIA and body fat distribution. METHODS: One-hundred and four male (n=52) and female (n=52) volunteers ranging from 18–62 years (29.13 ± 1.42) enrolled in this study. Anthropometric measures included height, weight, waist to hip ratio, skinfolds [9 different sites both left and right side] and percentage body fat, as assessed by 7SKF and consumer BIA devices; hand to hand (HH), leg to leg (LL), and fingers to fingers (FF). Physical activity data was assessed using a self report physical activity questionnaire. All participants were required to adhere to standard BIA and skin-fold testing guidelines. This study was approved by the Institutional Review Board at Linfield College. RESULTS: There were no significant differences between percent body fat as assessed by HH (20.58 ± 0.89) and 7SKF (20.28 ± 0.71). Percent fat as assessed by FF (23.37 ± 0.76) and LL (23.13 ± 0.83) were significantly higher than 7SKF (p ≥ 0.01). All three consumer BIA devices correlated (r ranged from 0.812 to 0.853, p<0.01) with SKF, with the HH method having the highest correlation. All three consumer BIA devices were more strongly correlated with 7SKF in those reporting less cardiovascular physical activity (r ranged from 0.889 to 0.927, p<0.01). The LL had a strongest correlation to the sum of upper skinfold measures and the HH had the strongest correlation to lower skin fold measures (r= 0.817, 0.858, respectively, p<0.01). CONCLUSIONS: This data suggest that the HH is the most accurate of the consumer models studied. These results suggest further research to determine the influence of the amount of physical activity on the accuracy of consumer grade BIA analysis devices.

Cross Validation of Fat-Free Mass Prediction Models for Elite Female Gymnasts

The purpose of this investigation was to evaluate three bioelectrical impedance analysis (BIA) prediction models for fat-free mass (FFM) using the U.S. National Women’s Gymnastics team (N = 48; age = 15.8 ± 1.8 years). One model had been developed recently using dual-energy x-ray absorptiometry (DEXA) as the criterion measure, whereas the other two used hydrodensitometry. In this investigation, FFM predictions were compared with measures obtained via DEXA. FFM measured by DEXA averaged 40.5 ± 7.4 kg (± SD), whereas values generated using the three BIA models were within 0.8 kg of this actual measure. Validity coefficients for all models were high (Rxy = .95-98). FFM prediction error was lowest with the model using DEXA as the criterion measure (1.3 kg) compared with the other two (1.9 and 2.4 kg). All BIA models underpredicted FFM in the heaviest girls, and the Lohman and Van Loan et al. models overpredicted FFM in the lightest girls. Whereas prediction error was significantly correlated to the girls’ bone mineral density in all BIA models, this relationship was strongest in the two that were developed using hydrodensitometry.

The Validity of Bioelectrical Impedance Models in Clinical Populations

Bioelectrical impedance analysis (BIA) is the most commonly used body composition technique in published studies. Herein we review the theory and assumptions underlying the various BIA and bioelectrical impedance spectroscopy (BIS) models, because these assumptions may be invalidated in clinical populations. Single-frequency serial BIA and discrete multifrequency BIA may be of limited validity in populations other than healthy, young, euvolemic adults. Both models inaccurately predict total body water (TBW) and extracellular water (ECW) in populations with changes in trunk geometry or fluid compartmentalization, especially at the level of the individual. Single-frequency parallel BIA may predict body composition with greater accuracy than the serial model. Hand-to-hand and leg-to-leg BIA models do not accurately predict percent fat mass. BIS may predict ECW, but not TBW, more accurately than single-frequency BIA. Segmental BIS appears to be sensitive to fluid accumulation in the trunk. In general, bioelectrical impedance technology may be acceptable for determining body composition of groups and for monitoring changes in body composition within individuals over time. Use of the technology to make single measurements in individual patients, however, is not recommended. This has implications in clinical settings, in which measurement of individual patients is important.

Bioelectrical impedance analysis models for prediction of total body water and fat-free mass in healthy and HIV-infected children and adolescents , ,

Bioelectrical impedance analysis (BIA) is an attractive method of measuring pediatric body composition in the field, but the applicability of existing equations to diverse populations has been questioned. The objectives were to evaluate the performance of 13 published pediatric BIA-based predictive equations for total body water (TBW) and fat-free mass (FFM) and to refit the best-performing models. We used TBW by deuterium dilution, FFM by dual-energy X-ray absorptiometry, and BIA-derived variables to evaluate BIA models in a cross-sectional study of 1291 pediatric subjects aged 4-18 y, from several ethnic backgrounds, including 54 children with HIV infection and 627 females. The best-performing models were refitted according to criterion values from this population, cross-validated, and assessed for performance. Additional variables were added to improve the predictive accuracy of the equations. The correlation between predicted and criterion values was high for all models tested, but bias and precision improved with the refitted models. The 95% limits of agreement between predicted and criterion values were 16% and 11% for TBW and FFM, respectively. Bias was significant for some subgroups, and there was greater loss of precision in specific age groups and pubertal stages. The models with additional variables eliminated bias, but the limits of agreement and the loss of precision persisted. This study confirms that BIA prediction models may not be appropriate for individual evaluation but are suitable for population studies. Additional variables may be necessary to eliminate bias for specific subgroups.

Segmental bioelectrical impedance analysis in children aged 8-12 y: 2. The assessment of regional body composition and muscle mass.

To investigate the potential of segmental bioelectrical impedance analysis (BIA) for assessing regional composition and muscle mass in children. Strengths of relationships were determined between (a) BIA indices of trunk, limbs or limb segments and (b) segment fat or fat-free mass (FFM) assessed using dual-energy X-ray absorptiometry (DXA); the extent of agreement was established between two independent models, based on DXA and BIA, of limb muscle and adipose tissue (AT) mass. Eighteen boys and 19 girls aged 8-12 y. BIA and anthropometry of trunk, whole limbs, limb segments and defined sections were used to calculate segmental impedance indices and specific resistivities; segment fat and FFM were obtained using DXA; muscle and AT masses of limbs, segments and sections were estimated using DXA and BIA models, and by anthropometry. Segmental BIA indices were significantly related to composition of the segments assessed using DXA; although substantial bias was observed, there was fairly good agreement (low 95% limits of agreement) between the BIA and DXA models of muscle mass and estimates from each were similarly categorised in tertiles, as were estimates of AT. Segmental BIA appears to have potential for assessing in children the composition of body segments, as obtained using DXA, and the masses of muscle and AT in whole limbs, limb segments and defined sections.

Bioelectrical impedance methods in clinical research: a follow-up to the NIH Technology Assessment Conference.

In 1994, the National Institutes of Health (NIH) convened a Technology Assessment Conference "to provide physicians with a responsible assessment of bioelectrical impedance analysis (BIA) technology for body composition measurement." In 1997, Serono Symposia USA, Inc., organized an invited panel of scientists and clinicians, with extensive research and clinical experience with BIA, to provide an update. Panel members presented reviews based on their own work and published studies for the intervening years. Updates were provided on the single and multifrequency BIA methods and models; continued clinical research experiences; efforts toward establishing population reference norms; and the feasibility of establishing guidelines for potential diagnostic use of BIA in a clinical setting. This report provides a summary of the panel's findings including a consensus on several technical and clinical issues related to the research use of BIA, and those areas that are still in need of additional study.

Single- and multifrequency models for bioelectrical impedance analysis of body water compartments

The 1994 National Institutes of Health Technology Conference on bioelectrical impedance analysis (BIA) did not support the use of BIA under conditions that alter the normal relationship between the extracellular (ECW) and intracellular water (ICW) compartments. To extend applications of BIA to these populations, we investigated the accuracy and precision of seven previously published BIA models for the measurement of change in body water compartmentalization among individuals infused with lactated Ringer solution or administered a diuretic agent. Results were compared with dilution by using deuterium oxide and bromide combined with short-term changes of body weight. BIA, with use of proximal, tetrapolar electrodes, was measured from 5 to 500 kHz, including 50 kHz. Single-frequency, 50-kHz models did not accurately predict change in total body water, but the 50-kHz parallel model did accurately measure changes in ICW. The only model that accurately predicted change in ECW, ICW, and total body water was the 0/infinity-kHz parallel (Cole-Cole) multifrequency model. Use of the Hanai correction for mixing was less accurate. We conclude that the multifrequency Cole-Cole model is superior under conditions in which body water compartmentalization is altered from the normal state.

Bioelectrical impedance analysis measurements of total body water and extracellular water in healthy elderly subjects.

To address whether: (1) bioelectrical impedance analysis (BIA) can provide precise and accurate estimates of total body water (TBW) and extracellular water (ECW) in healthy elderly subjects, that display age-induced changes in body composition, (2) BIA models are improved by introducing variables related to geometrical body-shape and osmolarity. Cross-validation of available BIA models and models developed in the study. 58 healthy elderly subjects (31 women, 27 men, 66.8+/-4.7 y, mean +/- s.d.) BIA at 5, 50 and 100 kHz, 18O labelled water measurements of TBW, Br measurements of ECW, anthropometric variables, plasma osmolarity. Published BIA models for estimating TBW, entail various degrees of bias. Precise models (SEE of the models 0.8 L at 100 kHz, 1.0 L at 50 kHz) involving height2/resistance, weight, gender, circumferences and plasma osmolarity were established with data from 30 subjects chosen at random. Cross-validation of an independent group (n = 28) showed no bias (-1.5+/-3.2 L at 100 kHz, -1.4+/-3.2 L at 50 kHz, P = NS). We conclude that BIA models with increased accuracy and precision for predicting ECW and TBW can be derived in healthy elderly subjects. Repeated measures had a mean difference of 0.2+/-1.2 L.