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

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          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.

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          Is the impedance index (ht2/R) significant in predicting total body water?

          C Fjeld, D Schoeller, L Danford … (1992)
          We investigated the general utility of bioelectrical impedance analysis (BIA) and the implications of BIA theory in populations of various ages from infancy to adulthood by developing a single impedance equation. Four subject data sets representing 62 adults, 37 prepubertal children, 44 preschool children, and 32 premature low-birth-weight neonates were combined. Subjects were randomly divided into a development group (n = 116) and a cross-validation group (n = 59). The single best predictor of total body water (TBW) was height2/resistance (ht2/R), which explained 99% of the variation in TBW (SEE = 1.67 kg). The addition of weight reduced the SEE to 1.41 kg. A significant bias was only seen in the preschool children. These results were confirmed in the cross-validation group and the best prediction formula was TBW = 0.59 ht2/R + 0.065 wt + 0.04. We conclude that the impedance index (ht2/R) is a significant predictor of TBW and that there is some improvement in prediction of TBW by inclusion of a weight term.
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            A simplified approach to analysing bio-electrical impedance data in epidemiological surveys.

            J. Williams, B. Cole, Aneesh B Singhal … (2007)
            Bio-electrical impedance analysis (BIA) is widely used to estimate body composition. It is simple, quick and cheap, but less accurate than other methods. It has potential epidemiological value, but has conventionally required validation before application. To develop a simple method of expressing weight, height and impedance data that avoids the need for population-specific validation equations in order to facilitate epidemiological application. Body composition was measured using the four-component model in young adults (43 males, 90 females). Impedance (R) was measured hand-foot and foot-foot. Lean mass and fat mass were adjusted for height to give lean mass index (LMI) and fat mass index (FMI). Based on theoretical principles, we generated the index 1/R, which provides an index of body water adjusted for height. Sex-specific regression models were used to investigate the relationships between (a) 1/R and LMI, and (b) body mass index (BMI) adjusted for 1/R and FMI. The success of this approach was evaluated in relation to the conventional BIA approach, using correlation analysis. 1/R was a highly significant predictor of LMI. BMI adjusted for 1/R was a significant predictor of FMI. Our approach performed as well as the conventional approach for LMI, but not for FMI. Direct use of BIA data, rather than their combination with population-specific equations for the prediction of total body water, proved successful at ranking individuals of both sexes in terms of LMI and FMI. The index 1/R may prove particularly valuable in epidemiological studies where ranking of LMI is required.
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              Effects of feeding regimens on bodyweight, composition and condition score in cats following ovariohysterectomy.

              John D Watson, Richard Stack, G Moxham … (2001)
              The effects of ovariohysterectomy on bodyweight, composition and condition score were evaluated in 49 cats that were fed ad libitum and 11 cats that had their food allowances controlled with the aim of maintaining a stable bodyweight. In cats fed ad libitum, bodyweight increased by an average of 31 per cent in the 12 months following ovariohysterectomy compared with 3.1 per cent over the 12 months before surgery, and this was largely due to increased body fat content. There was no difference in weight gain between cats fed dry or canned foods, but weight gain was inversely related to age and bodyweight at the time of neutering. Mean bodyweight increased by 7.5 per cent in the controlled feeding group, compared with 3.6 per cent over the 12 months before surgery, and individual bodyweights were maintained to within 10 per cent of pre-neutering values in nine cats. The other two cats experienced substantial weight gain (+20 per cent and +36 per cent), despite being fed only 40 kcal/kg/day. There were no significant changes in body composition of cats with controlled dietary allowances and their condition scores were significantly lower than those of cats fed ad libitum. The results confirm a link between ovariohysterectomy and the development of obesity in cats with free access to food, and indicate that substantial reductions in energy intake are required to prevent weight gain in such cats.
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                Author and article information

                Journal
                Journal ID (nlm-ta): BMC Vet Res
                Journal ID (iso-abbrev): BMC Vet. Res
                Title: BMC Veterinary Research
                Publisher: BioMed Central
                ISSN (Electronic): 1746-6148
                Publication date Collection: 2012
                Publication date (Electronic): 10 July 2012
                Volume: 8
                Page: 111
                Affiliations
                [1 ]Veterinary Hospital, Veterinary and Zootechny School, Federal University of Goiás, Goias State, Brazil
                [2 ]College of Agrarian and Veterinarian Sciences, University of Jaboticabal, São Paulo State, Brazil
                [3 ]Faculty of Medicine of Ribeirão Preto, University of São Paulo, São Paulo State, Brazil
                [4 ]Department of Zootechny, Federal University of Minas Gerais, Minas Gerais State, Brazil
                Article
                Publisher ID: 1746-6148-8-111
                DOI: 10.1186/1746-6148-8-111
                PMC ID: 3413556
                PubMed ID: 22781317
                SO-VID: 199d10b7-d239-4dfa-a726-5dac71345f64
                Copyright © Copyright ©2012 Borges et al.; licensee BioMed Central Ltd.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 22 May 2010
                Date accepted : 10 July 2012
                Categories
                Subject: Research Article

                ScienceOpen disciplines: Veterinary medicine
                Data availability:
                ScienceOpen disciplines: Veterinary medicine

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