A simple, reliable tool for owners to assess the body condition of their dog or cat.

Numerous methods exist for quantifying body composition and body fat mass in companion animals. In a clinical setting, the most widely accepted and practical method of body condition evaluation is condition scoring using visual assessment and palpation (1). All such systems attempt to partition a body composition continuum into a finite number of categories. Currently, 3 main systems exist, all of which use similar visual and palpable characteristics, but which differ by the number of integer categories within the scoring system (e.g., 5 points, 6 points, and 9 points) (2–8). The most widely accepted system is the 9-integer scale system, which has previously been shown to correlate well with body fat mass determined by dual-energy X-ray absorptiometry (DXA) (2–4). To aid decision making, a series of animal silhouettes are also provided that illustrate the visual characteristics for a typical (e.g., Labrador morphology) dog and cat. Scores determined by different operators have also been shown to correlate well (2–4), although a degree of expertise is required, rendering this system less accessible to untrained pet owners. S.H.A.P.E (Size, Health And Physical Evaluation) is a new algorithm-based system that uses similar visual and palpable characteristics as existing scoring systems (see http://www.petslimmers.com/shape.htm). A series of questions are followed that direct the operator to examine the animal in a sequential fashion. The questions instruct the operator to perform examinations that will determine the presence and amount of subcutaneous fat (over the ribcage and spine, etc.), and the amount of abdominal fat (by determining the presence and degree of abdominal tuck). Ultimately, 1 of 7 categories of body condition is chosen, each of which is assigned an alphabetical character from A (underweight) to G (obese). Letters were chosen for this new system to avoid confusion with current body condition score systems. This approach is designed to minimize interoperator variability and expertise required, allowing owners to evaluate their animals in the home and consult the veterinarian accordingly. The aim of the current study was to assess the performance of the algorithm system in predicting body composition in dogs and cats, and to acquire preliminary data on how the system performed in the hands of both experienced and inexperienced operators.