29 resultados para Bioelectrical Impedance Analysis

em Université de Lausanne, Switzerland


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OBJECTIVES: Perioperative fluid accumulation determination is a challenge for the clinician. Bioelectrical impedance analysis (BIA) is a noninvasive method based on the electrical properties of tissues, which can assess body fluid compartments. The study aimed at assessing their changes in three types of surgery (thoracic, abdominal, and intracranial) requiring various regimens of fluid administration. DESIGN: Prospective descriptive trial. PATIENTS: A total of 26 patients scheduled for elective surgery were separated into three groups according to site of surgery: thoracic (n = 8), abdominal aortic (n = 8), and brain surgery (n = 10). SETTING: University teaching hospital. INTERVENTION: None. MEASUREMENTS: Whole body, segmental (arm, trunk, and legs) BIA at multiple frequency (0.5, 50, 100 kHz) was used to assess perioperative fluid accumulation after surgery. The fluid balances were calculated from the charts. RESULTS: The patients were aged 62+/-4 yrs. Fluid balances were 4.8+/-1.0 L, 4.1+/-0.5 L, and 1.9+/-0.3 L, respectively, in the three groups. In trunk surgery patients, fluid accumulation was detected as a drop in impedance in the operated area at all frequencies. In the operated area, there was an expansion of both intra- and extracellular compartments. A reduction in high frequencies' impedance in the legs was only detected after aortic surgery. Fluid accumulation and trunk impedance changes were strongly correlated. Neurosurgery only induced minor body fluid changes. CONCLUSIONS: Segmental BIA is able to detect and localize perioperative fluid accumulation. It may become a bedside tool to quantify and to localize fluid accumulation.

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The present study assessed the relative contribution of each body segment to whole body fat-free mass (FFM) and impedance and explored the use of segmental bioelectrical impedance analysis to estimate segmental tissue composition. Multiple frequencies of whole body and segmental impedances were measured in 51 normal and overweight women. Segmental tissue composition was independently assessed by dual-energy X-ray absorptiometry. The sum of the segmental impedance values corresponded to the whole body value (100.5 +/- 1.9% at 50 kHz). The arms and legs contributed to 47.6 and 43.0%, respectively, of whole body impedance at 50 kHz, whereas they represented only 10.6 and 34.8% of total FFM, as determined by dual-energy X-ray absorptiometry. The trunk averaged 10.0% of total impedance but represented 48.2% of FFM. For each segment, there was an excellent correlation between the specific impedance index (length2/impedance) and FFM (r = 0.55, 0.62, and 0.64 for arm, trunk, and leg, respectively). The specific resistivity was in a similar range for the limbs (159 +/- 23 cm for the arm and 193 +/- 39 cm for the leg at 50 kHz) but was higher for the trunk (457 +/- 71 cm). This study shows the potential interest of segmental body composition by bioelectrical impedance analysis and provides specific segmental body composition equations for use in normal and overweight women.

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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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BACKGROUND AND AIMS: little is known regarding the reproducibility of body fat measuring devices; hence, we assessed the between and within-device reproducibility, and the within-day variability of body fat measurements. METHODS: body fat percentage was measured twice on seventeen female students aged between 18 and 20 with a body mass index of 21.9 ± 2.5 kg/m2 (mean ± SD) using seven bipolar bioelectrical impedance devices. Each participant was also measured each hour between 7:00 and 22:00. RESULTS: the correlation between first and second measurements was very high (Spearman r between 0.985 and 1.000, p<0.001), as well as between devices (Spearman r between 0.916 and 0.991, p<0.001). Repeated measurements analysis showed no differences were between devices (p=0.59) or readings (first vs. second: p=0.74). Conversely, significant differences were found between assessment periods throughout the day, measurements made in the morning being lower than those made in the afternoon (F test for repeated values= 6.58, p<0.001). CONCLUSIONS: the between and within-device reproducibility for measuring body fat is high, enabling the use of multiple devices in a single study. Conversely, small but significant changes in body fat measurements occur during the day, urging body fat measurements to be performed at fixed times.

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Objective: to assess the between and within-device reproducibility, as well as within-day variability of body fat measurements. Methods: body fat percentage (%BF) was measured twice on seventeen female students aged between 18 and 20 with a body mass index of 21.9 22.6 kg/m2 (mean SD) using seven bipolar bioelectrical impedance devices (BF-306) according to the manufacturer's recommendations. Each student was also measured each hour between 7:00 and 22:00. Statistical analysis was conducted using a general linear model for repeated measurements. Results: the correlation between first and second measurements was very high (Pearson r between 0.985 and 1.000, p<0.001), as well as the correlation between devices (Pearson r between 0.986 and 0.999, all p<0.001). Repeated measurements analysis showed no differences were between devices (F test=0.83, p=0.59) or readings (first vs. second: F test=0.12, p=0.74). Conversely, significant differences were found between assessment periods throughout the day, measurements made in the morning being lower than those made in the afternoon. Assuming an overall daily average of 100 (based on all measurements), the values were 95.8 3.2 (mean SD) at 8:00 versus 101.3 3.0 at 20:00, corresponding to a mean change of 2.2 1.1 in %BF (F test for repeated values=6.58, p<0.001). Conclusions: the between and within-device reproducibility for measuring body fat is high, enabling the use of multiple devices in a single study. Conversely, small but significant changes in body fat measurements occur during the day, urging body fat measurements to be performed at fixed times.

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BACKGROUND: Little information is available on the validity of simple and indirect body-composition methods in non-Western populations. Equations for predicting body composition are population-specific, and body composition differs between blacks and whites. OBJECTIVE: We tested the hypothesis that the validity of equations for predicting total body water (TBW) from bioelectrical impedance analysis measurements is likely to depend on the racial background of the group from which the equations were derived. DESIGN: The hypothesis was tested by comparing, in 36 African women, TBW values measured by deuterium dilution with those predicted by 23 equations developed in white, African American, or African subjects. These cross-validations in our African sample were also compared, whenever possible, with results from other studies in black subjects. RESULTS: Errors in predicting TBW showed acceptable values (1.3-1.9 kg) in all cases, whereas a large range of bias (0.2-6.1 kg) was observed independently of the ethnic origin of the sample from which the equations were derived. Three equations (2 from whites and 1 from blacks) showed nonsignificant bias and could be used in Africans. In all other cases, we observed either an overestimation or underestimation of TBW with variable bias values, regardless of racial background, yielding no clear trend for validity as a function of ethnic origin. CONCLUSIONS: The findings of this cross-validation study emphasize the need for further fundamental research to explore the causes of the poor validity of TBW prediction equations across populations rather than the need to develop new prediction equations for use in Africa.

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Introduction: Growth is a central process in paediatrics. Weight and height evaluation are therefore routine exams for every child but in some situation, particularly inflammatory bowel disease (IBD), a wider evaluation of nutritional status needs to be performed. Objectives: To assess the accuracy of bio-impedance analysis (BIA) compared to the gold standard dual energy X-ray absorptiometry (DEXA) in estimating percentage body fat (fat mass; FM) and lean body mass (fat free mass; FFM) in children with inflammatory bowel disease (IBD). To compare FM and FFM levels between patients with IBD and healthy controls. Methods: Twenty-nine healthy controls (12 females; mean age: 12.7 ± 1.9 years) and 21 patients (11 females; 14.3 ± 1.3 years) were recruited from August 2011 to October 2012 at our institution. BIA was performed in all children and DEXA in patients only. Concordance between BIA and DEXA was assessed using Lin's concordance correlation and the Bland-Altman method. Between-group comparisons were made using analysis of variance adjusting for age. Results: BIA-derived FM% showed a good concordance with DEXA-derived values, while BIA-derived FFM% tended to be slightly higher than DEXA-derived values (table). No differences were found between patients and controls regarding body mass index (mean ± SD: 19.3 ± 3.3 vs. 20.1 ± 2.8 kg/m2, respectively; age-adjusted P = 0.08) and FM% (boys: 25.3 ± 10.2 vs. 22.6 ± 7.1%, for patients and controls, respectively; P = 0.20; girls: 28.2 ± 5.7 vs. 26.4 ± 7.7%; P = 0.91). Also, no differences were found regarding FFM% in boys (74.9 ± 10.2 vs. 77.4 ± 7.1%; P = 0.22) and girls (71.8 ± 5.6 vs. 73.5 ± 7.7%; P = 0.85). Conclusion: BIA adequately assesses body composition (FM%) in children with IBD and could advantageously replace DEXA, which is more expensive and less available. No differences in body composition were found between children with IBD and healthy controls.

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The nutritional status of cystic fibrosis (CF) patients has to be regularly evaluated and alimentary support instituted when indicated. Bio-electrical impedance analysis (BIA) is a recent method for determining body composition. The present study evaluates its use in CF patients without any clinical sign of malnutrition. Thirty-nine patients with CF and 39 healthy subjects aged 6-24 years were studied. Body density and mid-arm muscle circumference were determined by anthropometry and skinfold measurements. Fat-free mass was calculated taking into account the body density. Muscle mass was obtained from the urinary creatinine excretion rate. The resistance index was calculated by dividing the square of the subject's height by the body impedance. We show that fat-free mass, mid-arm muscle circumference and muscle mass are each linearly correlated to the resistance index and that the regression equations are similar for both CF patients and healthy subjects.

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Nutrition assessment is important during chronic respiratory insufficiency to evaluate the level of malnutrition or obesity and should include body composition measurements. The appreciation of fat-free and fat reserves in patients with chronic respiratory insufficiency can aid in designing an adapted nutritional support, e.g., nutritional support in malnutrition and food restriction in obesity. The purpose of the present study was to cross-validate fat-free and fat mass obtained by various bioelectric impedance (BIA) formulas with the fat-free and fat mass measured by dual-energy X-ray absorptiometry (DXA) and determine the formulas that are best suited to predict the fat-free and fat mass for a group of patients with severe chronic respiratory insufficiency. Seventy-five patients (15 women and 60 men) with chronic obstructive and restrictive respiratory insufficiency aged 45-86 y were included in this study. Body composition was calculated according to 13 different BIA formulas for women and 12 for men and compared with DXA. Because of the variability, calculated as 2 standard deviations, of +/- 5.0 kg fat-free mass for women and +/- 6.4 kg for men for the best predictive formula, the use of the various existing BIA formulas was considered not clinically relevant. Therefore disease-specific formulas for patients with chronic respiratory insufficiency should be developed to improve the prediction of fat-free and fat mass by BIA in these patients.

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OBJECTIVE: To determine reference values for fat-free mass index (FFMI) and fat mass index (FMI) in a large Caucasian group of apparently healthy subjects, as a function of age and gender and to develop percentile distribution for these two parameters. DESIGN: Cross-sectional study in which bioelectrical impedance analysis (50 kHz) was measured (using tetrapolar electrodes and cross-validated formulae by dual-energy X-ray absorptiometry in order to calculate FFMI (fat-free mass/height squared) and FMI (fat mass/height squared). SUBJECTS: A total of 5635 apparently healthy adults from a mixed non-randomly selected Caucasian population in Switzerland (2986 men and 2649 women), varying in age from 24 to 98 y. RESULTS: The median FFMI (18-34 y) were 18.9 kg/m(2) in young males and 15.4 kg/m(2) in young females. No difference with age in males and a modest increase in females were observed. The median FMI was 4.0 kg/m(2) in males and 5.5 kg/m(2) in females. From young to elderly age categories, FMI progressively rose by an average of 55% in males and 62% in females, compared to an increase in body mass index (BMI) of 9 and 19% respectively. CONCLUSIONS: Reference intervals for FFMI and FMI could be of practical value for the clinical evaluation of a deficit in fat-free mass with or without excess fat mass (sarcopenic obesity) for a given age category, complementing the classical concept of body mass index (BMI) in a more qualitative manner. In contrast to BMI, similar reference ranges seems to be utilizable for FFMI with advancing age, in particular in men.

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OBJECTIVE: Low and high body mass index (BMI) values have been shown to increase health risks and mortality and result in variations in fat-free mass (FFM) and body fat mass (BF). Currently, there are no published ranges for a fat-free mass index (FFMI; kg/m(2)), a body fat mass index (BFMI; kg/m(2)), and percentage of body fat (%BF). The purpose of this population study was to determine predicted FFMI and BFMI values in subjects with low, normal, overweight, and obese BMI. METHODS: FFM and BF were determined in 2986 healthy white men and 2649 white women, age 15 to 98 y, by a previously validated 50-kHz bioelectrical impedance analysis equation. FFMI, BFMI, and %BF were calculated. RESULTS: FFMI values were 16.7 to 19.8 kg/m(2) for men and 14.6 to 16.8 kg/m(2) for women within the normal BMI ranges. BFMI values were 1.8 to 5.2 kg/m(2) for men and 3.9 to 8.2 kg/m(2) for women within the normal BMI ranges. BFMI values were 8.3 and 11.8 kg/m(2) in men and women, respectively, for obese BMI (>30 kg/m(2)). Normal ranges for %BF were 13.4 to 21.7 and 24.6 to 33.2 for men and women, respectively. CONCLUSION: BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.

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ABSTRACT: BACKGROUND: The prevalence of obesity has increased in societies of all socio-cultural backgrounds. To date, guidelines set forward to prevent obesity have universally emphasized optimal levels of physical activity. However there are few empirical data to support the assertion that low levels of energy expenditure in activity is a causal factor in the current obesity epidemic are very limited. METHODS: The Modeling the Epidemiologic Transition Study (METS) is a cohort study designed to assess the association between physical activity levels and relative weight, weight gain and diabetes and cardiovascular disease risk in five population-based samples at different stages of economic development. Twenty-five hundred young adults, ages 25-45, were enrolled in the study; 500 from sites in Ghana, South Africa, Seychelles, Jamaica and the United States. At baseline, physical activity levels were assessed using accelerometry and a questionnaire in all participants and by doubly labeled water in a subsample of 75 per site. We assessed dietary intake using two separate 24-h recalls, body composition using bioelectrical impedance analysis, and health history, social and economic indicators by questionnaire. Blood pressure was measured and blood samples collected for measurement of lipids, glucose, insulin and adipokines. Full examination including physical activity using accelerometry, anthropometric data and fasting glucose will take place at 12 and 24 months. The distribution of the main variables and the associations between physical activity, independent of energy intake, glucose metabolism and anthropometric measures will be assessed using cross-section and longitudinal analysis within and between sites. DISCUSSION: METS will provide insight on the relative contribution of physical activity and diet to excess weight, age-related weight gain and incident glucose impairment in five populations' samples of young adults at different stages of economic development. These data should be useful for the development of empirically-based public health policy aimed at the prevention of obesity and associated chronic diseases.

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BACKGROUND: Normal weight obesity (NWO) is defined as an excessive body fat associated with a normal body mass index (BMI < 25 kg/m(2)), but its prevalence in the general population is unknown. AIM OF THE STUDY: To assess the prevalence of NWO in Switzerland according to different cut points used to define excess body fat. METHODS: Cross-sectional study including 3,213 women and 2,912 men aged 35-75 years. Body fat was assessed by bioelectrical impedance analysis and prevalence of NWO was assessed using four previously published definitions for excess body fat. RESULTS: Percent body fat increased with age: in men, the values (mean +/- SD) were 20.2 +/- 5.4, 23.0 +/- 5.4, 26.3 +/- 5.2 and 28.2 +/- 4.6 for age groups 35-44, 45-54, 55-64 and 65-75 years, respectively; the corresponding values for women were 29.9 +/- 7.8, 33.1 +/- 7.4, 36.7 +/- 7.5 and 39.6 +/- 6.9. In men, prevalence of NWO was <1% irrespective of the definition used. Conversely, in women, a 1- to 20-fold difference (from 1.4 to 27.8%) in NWO prevalence was found. The prevalence of NWO increased with age when age-independent cut points were used in women, but not in men. CONCLUSIONS: Prevalence of NWO is low in the general population and higher in women than in men. The prevalence is highly dependent on the criteria used to define excess body fat, namely in women. The use of gender- and age-specific cut points to define excess body fat is better than fixed or gender-specific only cut points.