The prediction of ham composition by bioelectrical impedance analysis

2013 ◽  
Vol 53 (10) ◽  
pp. 1119
Author(s):  
A. Mateos ◽  
C. J. López-Bote ◽  
I. Ovejero ◽  
M. A. Latorre ◽  
A. Daza
Keyword(s):  
Linear Regression ◽  
Bioelectrical Impedance Analysis ◽  
Subcutaneous Fat ◽  
Inverse Function ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Regression Equations ◽  
Intermuscular Fat ◽  
Total Fat ◽  
Predicted Values

The objective of this preliminary experiment was to study whether bioelectrical impedance analysis (BIA) can accurately predict the components of fresh pig hams. The trimmed right hams from 20 Iberian barrows were used. Six measures of resistance and reactance were taken by a bioelectrical impedance analyser. Simple and multiple regression equations were calculated for estimating bone, lean, intermuscular fat (IF), subcutaneous fat (SF), total fat (TF) and skin weights and percentages with respect to ham weight (HW). The HW accounted for 22% (P < 0.05) and 35% (P < 0.01) in the variations in lean and skin percentages, respectively. The ham compactness index (HCI), calculated as HW (in g)/(ham length, in cm)2, accounted for 20% (P < 0.05) and 38% (P < 0.01) in the variations in SF and TF percentages, respectively. The HW and BIA variables accounted for 60% (P < 0.001) of the variation in skin percentage; the HCI and BIA measures accounted for 79% (P < 0.0001), 66% (P < 0.001) and 78% (P < 0.0001) of the variation in lean, IF and SF percentages; and BIA variables accounted for 72% (P < 0.0001) of the variation in bone percentage. To determine the accuracy of the calculated regression equations, five additional trimmed fresh hams from Iberian barrows were used. Actual and predicted values were compared. The HW accurately predicted lean weight and skin percentage in linear regression equations, and HCI adequately predicted SF and TF weights in simple linear regression equations, and also SF percentage in inverse function. The additional inclusion of HW, HCI or BIA variables in the regression models did not improve the accuracy of the equations. It is concluded that BIA might be applied to predict the components of fresh hams but more studies are needed to determine whether levels of accuracy and precision are sufficient for this method to be used in practice.

Estimation of body composition changes during weight cycling by bioelectrical impedance analysis in rats

1993 ◽  
Vol 74 (5) ◽  
pp. 2092-2098 ◽  
Author(s):  
J. Ilagan ◽  
V. Bhutani ◽  
P. Archer ◽  
P. K. Lin ◽  
K. L. Jen
Keyword(s):  
Body Composition ◽  
Body Weight ◽  
Bioelectrical Impedance Analysis ◽  
Subcutaneous Fat ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Weight Cycling ◽  
High Fat ◽  
Ad Libitum ◽  
Ad Libitum Feeding

The effects of body weight cycling (WC) in rats on body composition (BC) and feeding efficiency were studied. The usefulness of estimating BC by bioelectrical impedance analysis (BIA) was also examined. Female Sprague-Dawley rats were divided into high-fat ad libitum feeding, either noncycling or cycling, or restricted feeding (75% of control feed) cycling groups. Control rats were fed a regular laboratory ad libitum diet and did not cycle. All rats were killed at the end of week 61. A BIA unit was used at each stage of WC to obtain resistance and reactance readings. Final BC was determined by chemical analysis. On the basis of the final chemical analysis and BIA measurements, an equation was established and applied to estimate BC at each stage of WC: fat-free mass (g) = 0.38 x body wt (g) + 13.8 x [length (cm)2/resistance] + 70.9 (r = 0.95, P < 0.001). High-fat ad libitum feeding induced rapid body weight and fat gains as well as an elevated feeding efficiency and an internal fat-to-subcutaneous fat ratio, regardless of whether the rats cycled. This change in fat mass was clearly detected by the BIA. Although rats fed restricted diets had similar body weights as did control rats, they had a significantly higher internal fat-to-subcutaneous fat ratio. Thus, not only the amount of food but also the composition of the diet is important for proper weight management. The BIA method is capable of detecting the body fat mass change during WC.

scholarly journals Bioelectrical Impedance Analysis Versus Quantitative Computer Tomography and Anthropometry for The Assessment of Body Composition Parameters in China

2020 ◽  
Author(s):  
Qian Qin ◽  
Yang Yang ◽  
Jingfeng Chen ◽  
Yaojun Jiang ◽  
Ang Li ◽  
...  
Keyword(s):  
Body Composition ◽  
Linear Regression ◽  
Computer Tomography ◽  
Visceral Fat ◽  
Regression Models ◽  
Bioelectrical Impedance Analysis ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Linear Regression Models ◽  
Quantitative Computer Tomography

Abstract Objectives: The study evaluated the bioelectrical impedance analysis (BIA) device against the body composition parameters measured by anthropometry and quantitative computer tomography (QCT) to assess its reliability and accuracy among Chinese adults.Methods: Body composition parameters (waist circumstance [WC], body weight, body mass index [BMI] and visceral fat area [VFA]) were measured in 1,379 subjects (20-81 years old), both manually and by BIA, and in 1,317 of 1,379 subjects by QCT. The correlation coefficients were calculated between these measurements. Linear regression models were used to estimate each parameter based on the BIA measurements. Multivariate linear regression models were applied to calculate the correlation among VFA, WC and BMI. The concordance correlation coefficient from the Bland-Altman plots were calculated for VFA between QCT and BIA. Results: High correlation was observed for WC, weight and BMI (adjusted R2=0.78, 0.99 and 0.99) between BIA and anthropometry, and for VFA between BIA and QCT in both sex (adjusted R2=0.549 and 0.462). The multivariate regression models were established for the accurate prediction of QCT-VFA using WC and BMI (adjusted R2=0.603). In addition, a strong consistency of VFA measurement was found between BIA and QCT.Conclusion: Body composition parameters could be accurately determined in clinic using simple measurements of BIA. WC is more reliable as a predictor of visceral fat in the metabolic syndrome. Being non-invasive, accurate and free of radiation, BIA can be used as a safe and convenient tool in scientific research and clinical practice for the quick measurement of anthropometric parameters.

Measurement of total and visceral fat mass in young adult women: a comparison of MRI with anthropometric measurements with and without bioelectrical impedance analysis

2020 ◽  
Vol 93 (1110) ◽  
pp. 20190874
Author(s):  
Matthias F. Froelich ◽  
Marina Fugmann ◽  
Charlotte Lütke Daldrup ◽  
Holger Hetterich ◽  
Eva Coppenrath ◽  
...  
Keyword(s):  
Linear Regression ◽  
Predictive Value ◽  
Regression Models ◽  
Bioelectrical Impedance Analysis ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Anthropometric Measurements ◽  
Linear Regression Models ◽  
Multivariable Model ◽  
Hip Circumference

Objective: MRI is established for measurement of body fat mass (FM) and abdominal visceral adipose tissue (VAT). Anthropometric measurements and bioelectrical impedance analysis (BIA) have been proposed as surrogates to estimation by MRI. Aim of this work is to assess the predictive value of these methods for FM and VAT measured by MRI. Methods: Patients were selected from cohort study PPS-Diab (prediction, prevention and subclassification of Type 2 diabetes). Total FM and VAT were quantified by MRI and BIA together with clinical variables like age, waist and hip circumference and height. Least-angle regressions were utilized to select anthropometric and BIA parameters for their use in multivariable linear regression models to predict total FM and VAT. Bland–Altman plots, Pearson correlation coefficients, Wilcoxon signed-rank tests and univariate linear regression models were applied. Results: 116 females with 35 ± 3 years and a body mass index of 25.1 ± 5.3 kg/m2 were included into the analysis. A multivariable model revealed weight (β = 0.516, p < 0.001), height (β = −0.223, p < 0.001) and hip circumference (β = 0.156, p = 0.003) as significantly associated with total FM measured by MRI. A additional multivariable model also showed a significant predictive value of FMBIA (β = 0.583, p < 0.001) for FM. In addition, waist circumference (β = 0.054, p < 0.001), weight (β = 0.016, p = 0.031) in one model and FMBIA (β = 0.026, p = 0.018) in another model were significantly associated with VAT quantified by MRI. However, deviations reached more than 5 kg for total FM and more than 1 kg for VAT. Conclusion: Anthropometric measurements and BIA show significant association with total FM and VAT. Advances in knowledge: As these measurements show significant deviations from the absolute measured values determined by MRI, MRI should be considered the gold-standard for quantification.

The effects of genotype, sex and feeding regimen on pig carcass development: 2. Tissue weight distribution and fat partition between depots

1979 ◽  
Vol 93 (2) ◽  
pp. 349-358 ◽  
Author(s):  
A. J. Kempster ◽  
D. G. Evans
Keyword(s):  
Weight Distribution ◽  
Subcutaneous Fat ◽  
Carcass Composition ◽  
Regression Equations ◽  
Fat Depots ◽  
Tissue Weight ◽  
Intermuscular Fat ◽  
Feeding Regimen ◽  
Regression Slopes ◽  
Total Fat

SUMMARYDissection data for 1006 carcasses taken from the first 2 years of the Meat and Livestock Commission's (MLC) Commercial Pig Evaluation (CPE) were used to examine the growth of tissue weights in joints relative to the corresponding total tissue weight in carcass, and the growth of fat depots relative to total fat over the carcass weight range, 46–92 kg. Growth relationships were examined using a linear allometric model. Differences in tissue weight distribution between genotypes (pigs from different companies in CPE), sexes (barrows and gilts) and feeding regimens (restricted and ad libitum feeding) were examined at constant lean, bone or fat weight as appropriate, common allometric regression slopes being assumed.Lean and bone showed the same pattern of development. Relative growth was lowest in the proximal limb joints (ham and hand) increasing inwards to the joints of the back. With minor differences, the same pattern was found for subcutaneous fat and intermuscular fat. Fat depots differed considerably in their growth relative to total fat: intermuscular fat grew more slowly (allometric growth coefficient, b = 0·87), subcutaneous fat at the same rate and perinephric and retroperitoneal fat (flare fat) more rapidly (b = 1·24).Significant differences were recorded between genotypes in lean distribution and in the distribution of fat depots. However, the differences were small and of little commercial importance. There were also differences in fat partition between genotypes, flare fat being the most variable depot.Sex and feeding regimen also influenced tissue distribution and fat partition.The results are discussed in relation to the robustness of regression equations for predicting overall carcass composition from subcutaneous fat measurements and sample joint dissections.

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