984 resultados para Bioelectrical Impedance Analysis
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BACKGROUND/OBJECTIVES: (1) To cross-validate tetra- (4-BIA) and octopolar (8-BIA) bioelectrical impedance analysis vs dual-energy X-ray absorptiometry (DXA) for the assessment of total and appendicular body composition and (2) to evaluate the accuracy of external 4-BIA algorithms for the prediction of total body composition, in a representative sample of Swiss children. SUBJECTS/METHODS: A representative sample of 333 Swiss children aged 6-13 years from the Kinder-Sportstudie (KISS) (ISRCTN15360785). Whole-body fat-free mass (FFM) and appendicular lean tissue mass were measured with DXA. Body resistance (R) was measured at 50 kHz with 4-BIA and segmental body resistance at 5, 50, 250 and 500 kHz with 8-BIA. The resistance index (RI) was calculated as height(2)/R. Selection of predictors (gender, age, weight, RI4 and RI8) for BIA algorithms was performed using bootstrapped stepwise linear regression on 1000 samples. We calculated 95% confidence intervals (CI) of regression coefficients and measures of model fit using bootstrap analysis. Limits of agreement were used as measures of interchangeability of BIA with DXA. RESULTS: 8-BIA was more accurate than 4-BIA for the assessment of FFM (root mean square error (RMSE)=0.90 (95% CI 0.82-0.98) vs 1.12 kg (1.01-1.24); limits of agreement 1.80 to -1.80 kg vs 2.24 to -2.24 kg). 8-BIA also gave accurate estimates of appendicular body composition, with RMSE < or = 0.10 kg for arms and < or = 0.24 kg for legs. All external 4-BIA algorithms performed poorly with substantial negative proportional bias (r> or = 0.48, P<0.001). CONCLUSIONS: In a representative sample of young Swiss children (1) 8-BIA was superior to 4-BIA for the prediction of FFM, (2) external 4-BIA algorithms gave biased predictions of FFM and (3) 8-BIA was an accurate predictor of segmental body composition.
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Background/objectives:Bioelectrical impedance analysis (BIA) is used in population and clinical studies as a technique for estimating body composition. Because of significant under-representation in existing literature, we sought to develop and validate predictive equation(s) for BIA for studies in populations of African origin.Subjects/methods:Among five cohorts of the Modeling the Epidemiologic Transition Study, height, weight, waist circumference and body composition, using isotope dilution, were measured in 362 adults, ages 25-45 with mean body mass indexes ranging from 24 to 32. BIA measures of resistance and reactance were measured using tetrapolar placement of electrodes and the same model of analyzer across sites (BIA 101Q, RJL Systems). Multiple linear regression analysis was used to develop equations for predicting fat-free mass (FFM), as measured by isotope dilution; covariates included sex, age, waist, reactance and height(2)/resistance, along with dummy variables for each site. Developed equations were then tested in a validation sample; FFM predicted by previously published equations were tested in the total sample.Results:A site-combined equation and site-specific equations were developed. The mean differences between FFM (reference) and FFM predicted by the study-derived equations were between 0.4 and 0.6âeuro0/00kg (that is, 1% difference between the actual and predicted FFM), and the measured and predicted values were highly correlated. The site-combined equation performed slightly better than the site-specific equations and the previously published equations.Conclusions:Relatively small differences exist between BIA equations to estimate FFM, whether study-derived or published equations, although the site-combined equation performed slightly better than others. The study-derived equations provide an important tool for research in these understudied populations.
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Determination of fat-free mass (FFM) and fat mass (FM) is of considerable interest in the evaluation of nutritional status. In recent years, bioelectrical impedance analysis (BIA) has emerged as a simple, reproducible method used for the evaluation of FFM and FM, but the lack of reference values reduces its utility to evaluate nutritional status. The aim of this study was to determine reference values for FFM, FM, and %FM by BIA in a white population of healthy subjects, to observe the changes in these values with age, and to develop percentile distributions for these parameters. Whole-body resistance of 1838 healthy white men and 1555 women, aged 15-64 y, was determined by using four skin electrodes on the right hand and foot. FFM and FM were calculated according to formulas validated for the subject groups and analyzed for age decades. This is the first study to present BIA-determined age- and sex-specific percentiles for FFM, FM, and %FM for healthy subjects, aged 15-64 y. Mean FM and %FM increased progressively in men and after age 45 y in women. The results suggest that any weight gain noted with age is due to a gain in FM. In conclusion, the data presented as percentiles can serve as reference to evaluate the normality of body composition of healthy and ill subject groups at a given age.
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Objective: In chronic renal failure patients under hemodialysis (HD) treatment, the availability of simple, safe, and effective tools to assess body composition enables evaluation of body composition accurately, in spite of changes in body fluids that occur in dialysis therapy, thus contributing to planning and monitoring of nutritional treatment. We evaluated the performance of bioelectrical impedance analysis (BIA) and the skinfold thickness sum (SKF) to assess fat mass (FM) in chronic renal failure patients before (BHD) and after (AHD) HD, using air displacement plethysmography (ADP) as the standard method. Design: This single-center cross-sectional trial involved comparing the FM of 60 HD patients estimated BHD and AHD by BIA (multifrequential; 29 women, 31 men) and by SKF with those estimated by the reference method, ADP. Body fat-free mass (FFM) was also obtained by subtracting the total body fat from the individual total weight. Results: Mean estimated FM (kg [%]) observed by ADP BHD was 17.95 +/- 0.99 kg (30.11% +/- 1.30%), with a 95% confidence interval (CI) of 16.00 to 19.90 (27.56 to 32.66); mean estimated FM observed AHD was 17.92 +/- 1.11 kg (30.04% +/- 1.40%), with a 95% CI of 15.74 to 20.10 (27.28 to 32.79). Neither study period showed a difference in FM and FFM (for both kg and %) estimates by the SKF method when compared with ADP; however, the BIA underestimated the FM and overestimated the FFM (for both kg and %) when compared with ADP. Conclusion: The SKF, but not the BIA, method showed results similar to ADP and can be considered adequate for FM evaluation in HD patients. (C) 2012 by the National Kidney Foundation, Inc. All rights reserved.
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Objective The aim of the present study was to determine the impedance of Wistar rats treated with high-fat and high-sucrose diets and correlate their biochemical and anthropometric parameters with chemical analysis of the carcass. Methods Twenty-four male Wistar rats were fed a standard (AIN-93), high-fat (50% fat) or high-sucrose (59% of sucrose) diet for 4 weeks. Abdominal and thoracic circumference and body length were measured. Bioelectrical impedance analysis was used to determine resistance and reactance. Final body composition was determined by chemical analysis. Results Higher fat intake led to a high percentage of liver fat and cholesterol and low total body water in the High-Fat group, but these changes in the biochemical profile were not reflected by the anthropometric measurements or bioelectrical impedance analysis variables. Anthropometric and bioelectrical impedance analysis changes were not observed in the High-Sucrose group. However, a positive association was found between body fat and three anthropometric variables: body mass index, Lee index and abdominal circumference. Conclusion Bioelectrical impedance analysis did not prove to be sensitive for detecting changes in body composition, but body mass index, Lee index and abdominal circumference can be used for estimating the body composition of rats.
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Conventional bioimpedance spectrometers measure resistance and reactance over a range of frequencies and, by application of a mathematical model for an equivalent circuit (the Cole model), estimate resistance at zero and infinite frequencies. Fitting of the experimental data to the model is accomplished by iterative, nonlinear curve fitting. An alternative fitting method is described that uses only the magnitude of the measured impedances at four selected frequencies. The two methods showed excellent agreement when compared using data obtained both from measurements of equivalent circuits and of humans. These results suggest that operational equivalence to a technically complex, frequency-scanning, phase-sensitive BIS analyser could be achieved from a simple four-frequency, impedance-only analyser.