Artificial intelligence as an analytic approximation to evaluate associations between Parental Feeding Behaviors and Excess Weight in Colombian Preschoolers.

Artificial intelligence as an analytic approximation to evaluate associations between Parental Feeding Behaviors and Excess Weight in Colombian Preschoolers. Br J Nutr. 2020 Sep 28;:1-27 Authors: Gamboa-Delgado EM, Amaya-Castellanos CI, Bahamonde A Abstract Parental practices can affect children's weight and body mass index and may even be related to a high prevalence of obesity. Therefore, the aim of this study was to evaluate the relationship between parents' practices related to feeding their children and excess weight in preschoolers in Bucaramanga, Colombia, using artificial intelligence as an analytical and novel approximation. A Cross-sectional study was carried out between September and December 2017. Sample included preschoolers who attended child development institutions belonging to the Colombian Institute for Family Wellbeing (Instituto Colombiano de Bienestar Familiar (ICBF, Spanish acronym)) in Bucaramanga and the metropolitan area (sample size n=384). Outcome variable was excess weight, defined as body mass index for age. Main independent variable was parental feeding practices. Confounding variables that were analyzed included sociodemographic characteristics, food consumption, and the physical activity of the children. All equipment used for the anthropometric measurements was calibrated. Logistic regression was used to predict the effect of parental practices on the excess weight of the children, and the area under ...
Source: The British Journal of Nutrition - Category: Nutrition Authors: Tags: Br J Nutr Source Type: research