Relationship between the Body Fat Content Assessed by a Bioelectrical Impedance Analysis and Metabolic Syndrome-Related Blood Parameters

2009 ◽  
Vol 67 (6) ◽  
pp. 323-330
Author(s):  
Mami Matsushita ◽  
Kumiko Watanabe ◽  
Masayuki Saito
2021 ◽  
Vol 8 ◽  
Author(s):  
Kathrin Heine ◽  
Viktoria Kichmann ◽  
Miriam K. von Kuhlberg ◽  
Ingrid Vervuert ◽  
Lisa Bachmann ◽  
...  

This study analyzed skeletal development, body condition, and total body fat development of growing heifers. A total of 144 female primiparous Holstein cattle from four commercial dairy farms with different degrees of stillbirth rates were examined during the rearing period. This included measurements in body condition, fat tissue, metabolic, and endocrine factors. Pelvic measurements and the sacrum height were analyzed to assess skeletal development. The body condition was classified via body condition scoring, bioelectrical impedance analysis (BIA), back fat thickness measurements, and the body mass. For the first time, BIA was used as an appropriate method to evaluate the fat tissue content of cattle throughout the rearing period. This analysis technique can be performed on heifers aged 8–15 months. Throughout that period, the fat content decreased while the skeletal development increased. In addition, high free fatty acid concentrations in serum of the animals with high frame development were found, supporting our hypothesis that stored energy of body fat deposits is used for skeletal growth. Furthermore, we were able to demonstrate complex endocrine relationships between fat metabolism and skeletal growth by using specific markers, such as leptin, insulin growth factor-1 (IGF-1), and estradiol (E2). Food analysis showed high crude protein (CP) levels in the total mixed ration above recommendation for daily protein intake of all farms. However, there was a positive correlation between CP and the body frame measurements in our study. In summary, we established a novel regression formula for BIA analysis (“BIA-Heine”) in heifers to evaluate the body composition throughout different ages and physiological stages in the development of heifers. This special formula allows the evaluation of fat tissue without a whole-body analysis and therefore provides an innovative technique for animal welfare support.


2021 ◽  
pp. 30-34
Author(s):  
O. A. Nikitinskaya ◽  
N. V. Toroptsova

Obesity is a risk factor for many chronic diseases. Several research methods are used to determine the amount of body fat, including the «gold standard» dual-energy X-ray absorptiometry (DXA). The bioelectrical impedance analysis (BIA) method is an alternative for assessing body composition that does not require special conditions for placement and examination, but the accuracy of its results depends on the hydration of the body.Objective. To compare the results of determining the percentage of body fat using multi-frequency (MF) BIA and DXA.Material and methods. The study included 20 volunteers (11 women and 9 men) aged 26 to 70 years without serious metabolic, cardiovascular or endocrine diseases. Two repeated measurements were performed using the MF-BIA method on the MS FIT device and the DXA method on the Lunar Prodigy Advance device.Results. There were no significant differences in the average percentage of body fat in repeated measurements by MF-BIA and DXA methods, and the intra-group correlation coefficients (r2 ) were 0.999 and 0.997, respectively. A high and significant correlation in percentage of body fat was found between the MF-BIA and DXA (r = 0.973, p < 0.001). The average difference between the results of these two methods was 0.1243%. Differences in percentage of body fat that exceeded two or more standard deviations were detected less than in 5% cases, so the data on body fat content estimated using DXA and BIA are consistent and can be considered almost equal.Conclusion. Our study has shown that the MS FIT body composition device using the MF-BIA method can be an alternative to DXA for assessing the percentage of body fat without introducing additional formulas to recalculate the data obtained.


2002 ◽  
Vol 140 (6) ◽  
pp. 681-687 ◽  
Author(s):  
Dorothy J. VanderJagt ◽  
Paul Harmatz ◽  
Ajovi B. Scott-Emuakpor ◽  
Elliot Vichinsky ◽  
Robert H. Glew

2020 ◽  
Vol 14 (6) ◽  
pp. 519-523
Author(s):  
Yi-Chen Lee ◽  
Yi-Hsuan Lee ◽  
Pei-Ni Chuang ◽  
Chia-Sheng Kuo ◽  
Chia-Wen Lu ◽  
...  

1992 ◽  
Vol 79 (5) ◽  
pp. 421-423 ◽  
Author(s):  
K. C. H. Fearon ◽  
R. A. Richardson ◽  
J. Hannan ◽  
S. Cowan ◽  
W. Watson ◽  
...  

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