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

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.