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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

DXA, bioelectrical impedance, ultrasonography and biometry for the estimation of fat and lean mass in cats during weight loss

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Author(s):
Borges, Naida C. [1] ; Vasconcellos, Ricardo S. [2] ; Carciofi, Aulus C. [2] ; Goncalves, Karina N. V. [2] ; Paula, Francisco J. A. [3] ; Faria Filho, Daniel E. [4] ; Canola, Julio C. [2]
Total Authors: 7
Affiliation:
[1] Univ Fed Goias, Vet Hosp, Vet & Zootechny Sch, Goiania, Go - Brazil
[2] Univ Jaboticabal, Coll Agr & Vet Sci, Jaboticabal, SP - Brazil
[3] Univ Sao Paulo, Fac Med Ribeirao Preto, BR-05508 Sao Paulo - Brazil
[4] Univ Fed Minas Gerais, Dept Zootechny, Belo Horizonte, MG - Brazil
Total Affiliations: 4
Document type: Journal article
Source: BMC Veterinary Research; v. 8, JUL 10 2012.
Web of Science Citations: 7
Abstract

Background: Few equations have been developed in veterinary medicine compared to human medicine to predict body composition. The present study was done to evaluate the influence of weight loss on biometry (BIO), bioimpedance analysis (BIA) and ultrasonography (US) in cats, proposing equations to estimate fat (FM) and lean (LM) body mass, as compared to dual energy x-ray absorptiometry (DXA) as the referenced method. For this were used 16 gonadectomized obese cats (8 males and 8 females) in a weight loss program. DXA, BIO, BIA and US were performed in the obese state (T0; obese animals), after 10% of weight loss (T1) and after 20% of weight loss (T2). Stepwise regression was used to analyze the relationship between the dependent variables (FM, LM) determined by DXA and the independent variables obtained by BIO, BIA and US. The better models chosen were evaluated by a simple regression analysis and means predicted vs. determined by DXA were compared to verify the accuracy of the equations. Results: The independent variables determined by BIO, BIA and US that best correlated (p < 0.005) with the dependent variables (FM and LM) were BW (body weight), TC (thoracic circumference), PC (pelvic circumference), R (resistance) and SFLT (subcutaneous fat layer thickness). Using Mallows'Cp statistics, p value and r(2), 19 equations were selected (12 for FM, 7 for LM); however, only 7 equations accurately predicted FM and one LM of cats. Conclusions: The equations with two variables are better to use because they are effective and will be an alternative method to estimate body composition in the clinical routine. For estimated lean mass the equations using body weight associated with biometrics measures can be proposed. For estimated fat mass the equations using body weight associated with bioimpedance analysis can be proposed. (AU)