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in Journal of the American Veterinary Medical Association

Abstract

Objective—To develop morphometric equations for prediction of body composition and create a body fat index (BFI) system to estimate body fat percentage in overweight and obese cats.

Design—Prospective evaluation study.

Animals—76 overweight or obese cats ≥ 1 year of age.

Procedures—Body condition score (BCS) was determined with a 5-point scale, morphometric measurements were made, and dual-energy x-ray absorptiometry (DEXA) was performed. Visual and palpation-based evaluation of various body regions was conducted, and results were used for development of the BFI system. Best-fit multiple regression models were used to develop equations for predicting lean body mass and fat mass from morphometric measurements. Predicted values for body composition components were compared with DEXA results.

Results—For the study population, prediction equations accounted for 85% of the variation in lean body mass and 98% of the variation in fat mass. Values derived from morphometric equations for fat mass and lean mass were within 10% of DEXA values for 55 of 76 (72%) and 66 of 76 (87%) cats, respectively. Body fat as a percentage of total body weight (ie, body fat percentage) predicted with the BCS and BFI was within 10% of the DEXA value for 5 of 39 (13%) and 22 of 39 (56%) cats, respectively.

Conclusions and Clinical Relevance—The BFI system and morphometric equations were considered accurate for estimation of body composition components in overweight and obese cats of the study population and appeared to be more useful than BCS for evaluation of these patients. Further research is needed to validate the use of these methods in other feline populations. (J Am Vet Med Assoc 2014;244:1285–1290)

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in Journal of the American Veterinary Medical Association

Abstract

Objective—To develop morphometric equations for prediction of body composition and create a body fat index (BFI) to estimate body fat percentage in overweight and obese dogs.

Design—Prospective evaluation study.

Animals—83 overweight or obese dogs ≥ 1 year of age.

Procedures—Body condition score (BCS) was assessed on a 5-point scale, morphometric measurements were made, and visual and palpation-based assessments and dual-energy x-ray absorptiometry (DEXA) were performed. Equations for predicting lean body mass, fat mass, and body fat as a percentage of total body weight (ie, body fat percentage) on the basis of morphometric measurements were generated with best-fit statistical models. Visual and palpation-based descriptors were used to develop a BFI. Predicted values for body composition components were compared with DEXA-measured values.

Results—For the study population, the developed morphometric equations accounted for 98% of the variation in lean body mass and fat mass and 82% of the variation in body fat percentage. The proportion of dogs with predicted values within 10% of the DEXA values was 66 of 83 (80%) for lean body mass, 56 of 83 (68%) for fat mass, and 56 of 83 (67%) for body fat percentage. The BFI accurately predicted body fat percentage in 25 of 47 (53%) dogs, whereas the value predicted with BCS was accurate in 6 of 47 (13%) dogs.

Conclusions and Clinical Relevance—Morphometric measurements and the BFI appeared to be more accurate than the 5-point BCS method for estimation of body fat percentage in overweight and obese dogs. Further research is needed to assess the applicability of these findings to other populations of dogs. (J Am Vet Med Assoc 2014;244:1279–1284)

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in Journal of the American Veterinary Medical Association

Abstract

Objective—To quantitatively determine echogenicity of the liver and renal cortex in clinically normal cats.

Animals—17 clinically normal adult cats.

Procedure—3 ultrasonographic images of the liver and the right kidney were digitized from video output from each cat. Without changing the ultrasound machine settings, an image of a tissue-equivalent phantom was digitized. Biopsy specimens of the right renal cortex and liver were obtained for histologic examination. Mean pixel intensities within the region of interest (ROI) on hepatic, renal cortical, and tissue-equivalent phantom ultrasonographic images were determined by histogram analysis. From ultrasonographic images, mean pixel intensities for hepatic and renal cortical ROI were standardized by dividing each mean value by the mean pixel intensity from the tissue-equivalent phantom.

Results—The mean (± SD) standardized hepatic echogenicity value was 1.06 ± 0.02 (95% confidence interval, 1.02 to 1.10). The mean standardized right renal cortical echogenicity value was 1.04 ± 0.02 (95% confidence interval, 1.01 to 1.08). The mean combined standardized hepatic and renal cortical echogenicity value was 1.02 ± 0.05 (95% confidence interval, 0.99 to 1.04).

Conclusions and Clinical Relevance—Quantitative determination of hepatic and renal cortical echogenicity in cats is feasible, using histogram analysis, and may be useful for early detection of diffuse parenchymal disease and for serially evaluating disease progression. (Am J Vet Res 2000;61:1016–1020)

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in American Journal of Veterinary Research
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in Journal of the American Veterinary Medical Association