Evaluating community-driven cardiovascular health policy changes in the United States using agent-based modeling.
Academic Article
Overview
Research
Identity
Additional Document Info
Other
View All
Overview
abstract
Comprehensive smoke-free policy is a strategy to prevent cardiovascular disease (CVD) at a population-level; however, evaluating their long-term outcomes is difficult. This study used an agent-based model to estimate long-term impacts of a comprehensive smoke-free policy, as it was implemented in two communities, Arlington and Mesquite, Texas. The model predicted the percentage of myocardial infarction (MI), stroke, and diabetes in the population 10 and 20years following policy adoption. In Arlington, the percentage of the population with these conditions each decreased by approximately 0.5% over 20years; in Mesquite, the percentage of the population with diabetes, myocardial infarction (MI), and stroke decreased by 1.1%, 0.6%, and 0.3%, respectively, after 20years. The results were statistically significant (p<0.001). As an evaluation strategy, agent-based modeling can help researchers and practitioners estimate the potential long-term effects of policies and garner intervention support for implementation.