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Effect of high contents of dietary animal-derived protein or carbohydrates on canine faecal microbiota
Authors:Ingrid Hang  Teemu Rinttila  Jürgen Zentek  Anu Kettunen  Susanna Alaja  Juha Apajalahti  Jaana Harmoinen  Willem M de Vos  Thomas Spillmann
Institution:1. Veterinary Hospital, Veterinary and Zootechny School, Federal University of Goi??s, Goias State, Brazil
2. College of Agrarian and Veterinarian Sciences, University of Jaboticabal, S?o Paulo State, Brazil
3. Faculty of Medicine of Ribeir?o Preto, University of S?o Paulo, S?o Paulo State, Brazil
4. Department of Zootechny, Federal University of Minas Gerais, Minas Gerais State, Brazil
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.
Keywords:
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