Witzel Angela L, Kirk Claudia A, Henry George A, Toll Philip W, Brejda John J, Paetau-Robinson Inke
Small Animal Clinical Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996.
J Am Vet Med Assoc. 2014 Jun 1;244(11):1285-90. doi: 10.2460/javma.244.11.1285.
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.
Prospective evaluation study.
76 overweight or obese cats ≥ 1 year of age.
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.
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.
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.
建立用于预测身体成分的形态测量方程，并创建一个体脂指数（BFI）系统来估计超重和肥胖猫的体脂百分比。
前瞻性评估研究。
76只年龄≥1岁的超重或肥胖猫。
采用5分制确定身体状况评分（BCS），进行形态测量，并进行双能X线吸收法（DEXA）检测。对各个身体部位进行视觉和触诊评估，结果用于开发BFI系统。使用最佳拟合多元回归模型从形态测量数据中建立预测瘦体重和脂肪量的方程。将身体成分各部分的预测值与DEXA结果进行比较。
对于研究群体，预测方程解释了瘦体重85%的变异和脂肪量98%的变异。76只猫中，分别有55只（72%）和66只（87%）猫的形态测量方程得出的脂肪量和瘦体重值在DEXA值的10%以内。用BCS和BFI预测的体脂占总体重的百分比（即体脂百分比），分别有39只猫中的5只（13%）和22只（56%）的结果在DEXA值的10%以内。
BFI系统和形态测量方程被认为能够准确估计研究群体中超重和肥胖猫的身体成分各部分，并且在评估这些猫时似乎比BCS更有用。需要进一步研究以验证这些方法在其他猫群体中的应用。
