High rates of food insecurity and unhealthy diets – including overconsumption of highly-processed, unhealthy foods that are cheaper than their healthier, minimally processed counterparts -- are remarkably consistent across U.S. cities, particularly in many Black, Latino and low-income neighborhoods with low access to healthy food retailers and an abundance of unhealthy food options. First, we will use group model building to systematically engage academic, policy, and community stakeholders to build capacity for systems thinking, develop and refine a “map” of the multilevel factors that drive poor access and affordability of healthy foods in cities. The need for this work is motivated by the lack of an existing conceptual framework that explicates the dynamic mechanisms via which obesogenic environments are reinforced and perpetuated in many American neighborhoods. Previous research and existing conceptual frameworks have identified myriad influences on diet, but a more specific and dynamic conceptual framework can advance understanding of how low access to healthy food retail, the higher price of healthy foods, and resource constraints of low-income households work in combination to reinforce obesogenic environments. Second, we will implement an agent-based simulation model (ABM) to examine how high density of unhealthy food outlets, the lower price of unhealthy foods, and limited food budgets constraints work in combination to constrain food choices of low-income households. The ABM bridges lines of research conducted by our group and others that have used ABM to examine how food access and food prices separately affect diets. By integrating these separate modeling paradigms, we can examine how diet disparities emerge due to intersecting disadvantage in food access and affordability. In the ABM, individual-agents in a virtual city make a series of daily decisions about where to shop for food, what types of food to purchase, and what to eat. Each decision is based on simple rules that reflect influences on food purchasing and diet, including household food budgets; travel costs to food stores; between-store variation in price, inventory, and quality; and the prices of 12 nutritionally important food categories (e.g., protein, whole grains) and 6 beverage categories. We use gold standard data regarding household income and food spending, food prices and purchasing, and diet. We will use the ABM to assess the impact of changes to (i.e., scaling up and scaling back) eligibility and benefits of federal food assistance and housing policies, two of the nation’s most prominent safety net programs intended to mitigate some of the worse impacts of poverty. The ABM is grounded in the Philadelphia context, but the research questions and findings are highly relevant to persistently high rates of food insecurity, unhealthy diets, and diet-related chronic diseases in essentially all U.S. cities.