Dietary behaviors are key modifiable risk factors in averting cardiovascular disease (CVD), the leading cause of morbidity, mortality, and disability in the United States (US). Despite national and local initiatives to promote healthy dietary behaviors, unhealthy diets remain a difficult, perplexing population health problem requiring initiatives and solutions at the community and population levels. Prior to investing in implementation, health practitioners and policymakers?often working with limited resources?need to compare the population health impact of different food policies and programs to then determine priorities. The goal of this project, Assessment of Policies through Prediction of Long-term Effects on Cardiovascular Disease Using Simulation (APPLE CDS), is to compare the effects of food policies and programs on CVD-related outcomes and health care costs for adults. This will be useful to aid local government and community organizations in priority setting and decision-making. Policy and program assessment will be conducted by combining agent- based modeling with an established health outcomes model. We assembled a team of experts in CVD, nutrition, public health, health economics, health policy, and computer simulation modeling who are committed to working together to identify realistic pathways that can be used to improve dietary behaviors.
The Specific Aims are to: (1) develop an agent-based model to assess and compare the impact of alternative food policies and programs on dietary behaviors, blood pressure, body mass index (BMI), and diabetes across different neighborhoods in NYC and (2) link the agent-based model with the well-established, validated NYC CVD Policy Model to project the long-term impact of different food policies and programs on cardiovascular disease outcomes (e.g., hypertension, coronary heart disease, stroke), quality-adjusted life years (QALYs), and health care costs. We will leverage the rich community-level health data on dietary behaviors collected by the NYC Department of Health and Mental Hygiene (DOHMH) to parameterize and validate the model. In addition, our close partnerships with the NYC DOHMH and a broad range of community-based organizations across the city will ensure that simulation results will be used to select and optimize implementation of the most cost-effective, neighborhood-specific food policies and programs to improve population health. Finally, the NYC experience can serve as an example by which other local health departments and community-based organizations may make more informed decisions for their own priority setting and program implementation.
This project will use computer simulation modeling to compare the effects of food policies and programs on CVD-related outcomes and health care costs for adults in New York City (NYC). The proposed research is relevant to public health because results will lead to specific recommendations that can be shared with the NYC Department of Health and Mental Hygiene and community-based organizations to help them select and adopt the most cost-effective, neighborhood-specific food policies and programs. Its broader impact lies in the fact that the NYC experience can serve as an example to other local health departments when it comes to making informed decisions related to program implementation to improve population health.
