Multi-level Modular Agent-Based Computational Modeling of Childhood Obesity

Research Question
This project will both develop a multi-level methodology (modular agent-based computational modeling) and apply it to the study of childhood obesity. This will improve our understanding of the complex and multilevel determinants of childhood obesity and will inform design of more effective multilevel interventions that consider the range of biological, family, community, socio-cultural, environmental, policy, and macro-level economic factors that influence diet in children. Our central research focus is the interaction between "below the skin" determinants such as neurobiology, psychology, and genetics with "above the skin" determinants such as food environment, social influence, and family. The initial phase of our work explores these factors and their impact on eating behavior through the lens of the reward pathway.

Modeling Approach
We are developing and applying a modular multi-level extension of the core methodology of agent-based computational modeling (ABM). Our principal focus is on eating behavior and obesity outcomes in early childhood (ages 0 to 7). Our "modular" approach is designed to allow separate consideration of several levels of analysis, while permitting straightforward integration of the "modules" to study multilevel feedbacks and interactions. The modular ABM will examine five levels of influence expected to modulate the complex biology/environment interactions influencing eating behaviors and body weight (BMI): genes, neurobiology, psychological predisposition, family, and social/food environment. Our modeling approach will blend theoretical modeling with empirical model testing using existing longitudinal cohort data. The principal initial data source will be the MAVAN (Maternal Adversity , Vulnerability, and Neurodevelopment) study based in Canada, a sample of mothers and their child observed in a longitudinal within-subject design from the time of pregnancy and birth. The complete multi-level ABM model will enable subsequent exploration of potential policy design of interventions, as well as projection of the implications of identified trends.


Principal Investigator

Laurette Dubé, PhD
Founding Chair and Scientific Director
The McGill World Platform for Health and Economic Convergence
McGill University


Ross A. Hammond, PhD
Center on Social Dynamics and Policy Senior Fellow, Economic Studies
The Brookings Institution

Robert Levitan, PhD
Department of Psychiatry
University of Toronto