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.

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.

scholarly journals A rationale for the use of anthropometric measurements and bioelectrical impedance analysis as efficacy criteria for summer camp healthcare

2019 ◽  
pp. 89-95 ◽  
Author(s):  
MYu Gavryushin ◽  
OV Sazonova ◽  
DO Gorbachev ◽  
LM Borodina ◽  
OV Frolova ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Bioelectrical Impedance Analysis ◽  
Healthy Lifestyle ◽  
Summer Camp ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Anthropometric Measurements ◽  
Summer Camps ◽  
Wide Range ◽  
Efficacy Criteria

The proportion of obese and overweight children is alarmingly high. This dictates the need for promoting healthy lifestyle and eating habits in children. Summer camps provide a wide range of activities to improve children’s health. However, methods used to assess children’s nutritional status during a camp session need to be analyzed in depth, and a rationale should be provided for the use of bioelectrical impedance analysis (BIA) and anthropometric measurements as efficacy criteria for summer camp healthcare. We examined 125 boys and 221 girls aged 8–15 years spending their summer holidays at 3 different camps. Measurements were taken twice: on days 1 and 2 upon arrival to a camp and 2 days before leaving for home. In each camp, both positive and negative health weight dynamics were observed. The overall weight dynamics in children from camps 1 and 2 were statistically insignificant (p = 0.415 and p = 0.585), in contrast to camp 3 where those changes were significant (p = 0.025). BIA revealed that less than 44.34% of children had gained skeletal muscle mass during their stay at the camp, whereas weight loss was associated with both decreased fat and skeletal muscle masses. BIA confirms the results of anthropometric measurements and also provides information about the diet offered to children and their level of physical activity. Therefore, the use of anthropometric measurements and BIA could be an informative method for assessing the efficacy of healthcare in summer camps.

scholarly journals A New Strategy to Integrate Heath–Carter Somatotype Assessment with Bioelectrical Impedance Analysis in Elite Soccer Players

Sports ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 142
Author(s):  
Francesco Campa ◽  
Tindaro Bongiovanni ◽  
Catarina N. Matias ◽  
Federico Genovesi ◽  
Athos Trecroci ◽  
...  
Keyword(s):  
Bioelectrical Impedance Analysis ◽  
Cross Validation ◽  
Predictive Ability ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Anthropometric Measurements ◽  
Fat Free Mass ◽  
Soccer Players ◽  
New Strategy ◽  
Soccer Teams

Easy-to-apply and quick methods for evaluate body composition are often preferred when assessing soccer teams. This study aimed to develop new equations for the somatotype quantification that would reduce the anthropometric measurements required by the Heath and Carter method, integrating the somatotype assessment to the bioelectrical impedance analysis (BIA). One hundred and seventy-six male elite soccer players (age 26.9 ± 4.5 years), registered in the Italian first division (Serie A), underwent anthropometric measurements and BIA. Endomorphy, mesomorphy, and ectomorphy were obtained according to the Heath and Carter method, while fat mass (FM) and fat free mass (FFM) estimated using a BIA-derived equation specific for athletes. The participants were randomly split into development (n = 117) and validation groups (n = 59, 1/3 of sample). The developed models including resistance2/stature, FM%, FFM, contracted arm and calf circumference, triceps, and supraspinal skinfolds had high predictive ability for endomorphy (R2 = 0.83, Standard Error of Estimate (SEE) = 0.16) mesomorphy (R2 = 0.80, SEE = 0.36), and ectomorphy (endomorphy (R2 = 0.87, SEE = 0.22). Cross validation revealed R2 of 0.80, 0.84, 0.87 for endomorphy, mesomorphy, and ectomorphy, respectively. The proposed strategy allows the integration of somatotype assessment to BIA in soccer players, reducing the number of instruments and measurements required by the Heath and Carter approach.

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.

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