Children of parents with obesity are twice as likely to develop obesity themselves, however, some children at high familial risk are resilient to the disease (i.e., do not develop obesity themselves). Understanding the sources that promote this resilience could inform obesity prevention, however, currently these sources are poorly understood and have not been a strategic focus of prospective studies. Excess weight gain is ultimately due to overconsumption, therefore, understanding the cognitive mechanisms driving eating behavior is critical to successful prevention. This training plan builds upon my foundation in cognitive psychology to understand individual differences in pediatric ingestive behaviors that promote resiliency to obesity in settings of high familial obesity risk. Eating behaviors are learned through reinforcement (e.g., hedonic pleasure, parental feedback) and rely on habitual (i.e., sensitive to rewards) and goal-directed (i.e., relies on knowledge of the environment and goals16-18) systems. Building on my sponsor?s R01 study, which uses a prospective, family risk design to identify risks for excess weight gain among healthy, 7-8 year-olds, this proposal aims to 1) identify individual differences in food-related reinforcement learning that reduce susceptibility to laboratory overconsumption; and 2) characterize individual differences in reinforcement learning and eating behaviors that promote resiliency to excess gains in adiposity after 1 year. We hypothesize that greater reliance on goal- directed food-related reinforcement learning will decrease susceptibility to overconsumption and serve as a protective factor for excess weight gain after 1 year, particularly for children with high familial risk. To test this hypothesis, we will enroll 90, 7-8 year-old healthy weight children at two levels of obesity risk (i.e., 45 high-risk and 45 low-risk) based on parent weight status. Methods will include sophisticated analytical coding of video recorded laboratory test meals and eating in the absence of hunger, a novel reinforcement learning task, and anthropomorphic assessments of adiposity attained from dual x-ray absorptiometry (DXA; collected at baseline and 1 year follow-up). The primary innovations offered by this proposal are 1) the use of both prospective and family-risk designs, which will provide insight into the cognitive and behavioral factors that promote resiliency to excess weight gain during the vulnerable pre-adolescent period; and 2) the use of sophisticated statistical techniques to characterize a eating behaviors at a multi-item meal. In addition, a mentorship team with strengths in pediatric obesity, ingestive behavior, dynamic coding of self-regulation, and sophisticated quantitative analysis of individual differences will provide rigorous, inter-disciplinary training to advance my research career. The proposed study will contribute essential information to our understanding of the cognitive mechanisms supporting eating behavior and resiliency to obesity, which will highlight targets for prevention programs.
Parental obesity increases the risk that children will go on to develop obesity themselves, but the eating behaviors that may protect from this are unknown. Using a prospective, family-risk design will provide insight into the cognitive and behavioral factors that promote resiliency to excess laboratory consumption and weight gain in children, particularly for those with high familial risk. These findings will directly inform public health interventions by highlighting behavioral targets for obesity prevention programs.
