Use of a novel morphometric method and body fat index system for estimation of body composition in overweight and obese dogs

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…