Accuracy and reliability of total body electrical conductivity (TOBEC) for determining body composition of rats in experimental studies

Rc, Bell; Aj, Lanou; Frongillo, E A; Levitsky, David A.; Tc, Campbell

doi:10.1016/0031-9384(94)90240-2

Cited by 21 publications

(7 citation statements)

References 15 publications

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“…A crucial consequence of this is the limited usefulness of derived calibration curves. Measurements carried out in the same manner in different experiments may fail to predict body chemical composition accurately, (Bear et al, 1993;Bellinger and Williams, 1993;Skagen et al, 1993;Bell et al, 1994;Trocki et al, 1995) and underlines the empirical nature of the TOBEC method. Factors responsible include the size, shape and dimensions of an individual in relation to the volume of the measurement chamber.…”

Section: Discussionmentioning

confidence: 91%

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Evaluation of the non invasive tobec (total body electrical conductivity) procedure for prediction of chemical components of male broilers with special consideration of dietary protein level

Dänicke

Halle²,

Jeroch³

1997

Archiv für Tierernaehrung

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TOBEC (total body electrical conductivity) measurement as a non invasive procedure for the estimation of body chemical composition was used to calculate calibration curves for the prediction of crude protein mass (CPM), crude water mass (CWM), crude ash mass (CAM) and fat-free mass (FFM) of male broiler chickens. A growth experiment with 3 protein levels (130, 230 and 330 g CP/kg diet, isoenergetic with 13.3 MJ AMEN/kg) was combined with TOBEC measurements and body chemical analysis in order to obtain the values necessary for calibration. A total of 196 TOBEC measurements and body chemical analysis were undertaken in time intervals of two days beginning with batch until day 17 of age. Different dietary protein levels resulted in marked differences in body weights and body chemical compositions but in similar TOBEC-responses for a given mass of FFM, CPM, CAM or CWM. Values for birds fed a diet with 130 g CP/kg diet tended to be more variable. Linear broken relationships were found between FFM, CPM, CAM and CWM, respectively and TOBEC values (E#). A set of different regression equations is given and yielded high proportions of variance accounted for the piece wise regression model (R2 ranged from 0.83 to 0.99). In spite of these high determinations the prediction of crude fat mass (CFM) by subtracting the FFM from the body weight resulted in most cases in weak determinations between observed and predicted CFM (R2 ranged from 0.38 to 0.86). The highest R2 was observed when the E# was expressed per unit metabolic body weight to the power of 0.67 and regressed on FFM expressed to the same power. In conclusion, FFM, CPM and CWM may be predicted reasonably well by TOBEC. However, these high determinations are not high enough to predict CFM accurately. In addition, the application of such regressions to an individual bird seems to be impossible. Assessment for groups of animals should be possible if errors of estimation, standard deviations and differences to be detected are taken into account in the calculation of the number of birds necessary for the TOBEC measurements.

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Section: Discussionmentioning

confidence: 91%

“…Studies on laboratory rats yielded only a weak correlation between actual BW and TOBEC-predicted FFM (Morbach and Brans, 1992;Stenger and Bielajew, 1995;Trocki et al, 1995). In addition, Bell et al (1994) found BW to be higher correlated to TOBEC than FFM and questioned the method in general.…”

Section: Introductionmentioning

confidence: 85%

Evaluation of the non invasive tobec (total body electrical conductivity) procedure for prediction of chemical components of male broilers with special consideration of dietary protein level

Dänicke

Halle²,

Jeroch³

1997

Archiv für Tierernaehrung

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“…Recent reports have questioned the reliability of total body electrical conductivity in the determination of fat mass and fat-free mass in Fischer F344 rats (30) and in Sprague-Dawley rats (31). However, others have compared direct carcass analysis to tetrapolar bioelectrical impedance analysis in female Sprague-Dawley rats (32), and to dual energy X-ray absorptiometry in male Fischer F344 rats (33), and have suggested that these two methods may be appropriate for the estimation of in vivo body composition in rats during periods of weight stability (32) and during aging (33).…”

Section: Discussionmentioning

confidence: 99%

Effect of Age on Protein Conservation during Very‐Low‐Energy Diet in Obese Sprague‐Dawley Rats

Johnson

Yang

et al. 1998

Obesity Research

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JOHNSON, JULIA A, CHOON-HIE YU, MEI-UlH YANG, F. XAVIER PI-SUNYER. Effect of age on protein conservation during very-low-energy diet in obese SpragueDawley rats. Obes. Res. 1998;6:448--457. Objective: To examine the effect of age on body protein losses occurring during severe energy restriction in obesity. Research Methods and Procedures: Weanling (young) Sprague-Dawley rats (YR) were fed a high fat (35% energy) diet (HFD) until mean body weight approached that of a group of chow-fed retired breeder (aged) rats (AR). Both groups were then fed HFD for an additional 2 weeks, after which selected controls from YR and AR groups were killed for baseline carcass analysis. Remaining rats were fed a very-low-energy diet (VLED, 33% kcal of HFD) for 3 weeks and then killed for carcass analysis. Results: YR had greater fat stores before VLED, and lost proportionately more fat and less protein during VLED than did AR. Weight loss composition during VLED was 66.7% fat, 11.1% protein, and 22.2% water in YR, and 39.4% fat, 26.2% protein, and 34.3% water in AR. Greater YR fat loss during VLE]j (70.6 ± 30.4 vs. 32.6 ± 29.1 gin AR; mean ± SD) was paralleled by significantly larger decreases in epididymal and retroperitoneal fat pad weights, mean adipocyte size, and lipoprotein lipase activity. Greater protein loss in AR (21.6 ± 13.9 g vs. 11.8 ± 10.7 g in YR) coincided with larger decreases in visceral organ weights and serum thyroxine and triiodothyronine. Energy expenditure changes during VLED were similar between groups. Discussion: Dietary obese young rats appear better able 448 OBESITY RESEARCH Vol. 6 No.6 Nov. 1998 than aged rats to conserve body protein while losing body fat during severe energy restriction.

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“…For example, the apparent accuracy of a measure of lean body mass of small animals using total body electrical conductivity was attributable to the measure's relation to total body weight and not to lean body mass as the developers of the instrument had assumed. 10 Therefore, attribution of accuracy can only be achieved by careful study design and availability of other measures and information, and it is demonstrated by comparison with competing measures and examination of alternative explanations. 8 Measures can be categorized according to a hierarchy of accuracy: definitive, reference, and field (ie, routine).…”

Section: Research Snapshotmentioning

confidence: 99%

“…17 Total body electrical conductivity, in which a quantity reported by the machine is used to predict lean body mass, provides an example of calibration. 10 Furthermore, food records or 24-hour dietary recalls for multiple days have been used to calibrate dietary intake from food frequency questionnaires. 17…”

Section: Research Snapshotmentioning

confidence: 99%

Establishing Validity and Cross-Context Equivalence of Measures and Indicators

Frongillo

Baranowski

Subar

et al. 2019

Journal of the Academy of Nutrition and Dietetics

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Quantitative research depends on using measures to collect data that are valid (ie, reflect well the phenomena of interest) and perform equivalently across contexts. Demonstrating validity and cross-context equivalence requires specifically designed studies, but many such studies have problems that have limited their usefulness. This article explains validity and cross-context equivalence of measures (and important related concepts) and clarifies how to establish them. Validation is the process of determining whether a measure or indicator is suitable for providing useful analytical measurement for a given purpose and context. Cross-context equivalence means that a measure performs comparably across contexts. Four types of equivalence are construct, item, measurement, and scalar. Establishing validity and cross-context equivalence requires representing mathematically the errors (ie, imprecision, undependability, and inaccuracy) of a measure and using appropriate statistical methods to quantify these errors. Studies aiming to provide evidence about the validity of a measure need to clarify the purpose and context for use of that measure. Choose one of the two conceptual systems for validation; obtain data to establish the extent to which the measure is well constructed, reliable, and accurate; and use analytic methods beyond simple correlations to provide a basis for making reasoned judgment about whether the measure provides useful analytic measurement for the particular purpose(s) and context. Establishing accuracy of a measure requires having available other measures known to be accurate as comparators; in the case that no other measure understood to be more accurate is available, then the study will be able to establish agreement rather than validity.

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Accuracy and reliability of total body electrical conductivity (TOBEC) for determining body composition of rats in experimental studies

Cited by 21 publications

References 15 publications

Evaluation of the non invasive tobec (total body electrical conductivity) procedure for prediction of chemical components of male broilers with special consideration of dietary protein level

Evaluation of the non invasive tobec (total body electrical conductivity) procedure for prediction of chemical components of male broilers with special consideration of dietary protein level

Effect of Age on Protein Conservation during Very‐Low‐Energy Diet in Obese Sprague‐Dawley Rats

Establishing Validity and Cross-Context Equivalence of Measures and Indicators

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