Nonlinear mixed models of growth curves from domestic shorthair cats in a breeding colony, housed in a seasonal facility to predict obesity.

Obesity is highly prevalent in pet cats (Felis silvestris catus) and is associated with several comorbidities, yet very little is understood about the early life risk factors. The aim of this study was to develop a mathematical model that describes growth in cats, to determine which early life variables were associated with being overweight in adulthood and to identify when during life the overweight phenotype developed in a colony of cats. We used pedigree, birth and growth data of 212 colony cats that were fed ad libitum from weaning. A nonlinear mixed-effects model was fitted to the body weight data to describe growth curves. A subset of 146 cats that had reached 9 years of age was used to evaluate the body weight curves to 9 years, and candidate early life predictors of peak weight were evaluated using logistic regression. In contrast with other species, candidates such as maternal factors, birth weight and litter size were not significant risk factors for adult obesity. Male sex, body weight around 15 weeks of age and being born during the increasing photoperiod were significantly associated with being overweight at 9 years. The growth equation created can be used to predict peak body weight, when sex and season of birth are included. Thus, the trajectory to obesity is determined early in life in cats, and early intervention appears essential to prevent obesity in pet cats.