Assessment of Policies through Prediction of Long-term Effects on Cardiovascular Disease Using Simulation (APPLE CDS)

通过模拟预测对心血管疾病的长期影响来评估政策（APPLE CDS）

• 批准号: 10256739
• 负责人: Bian Liu
• 金额: $ 70.11万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10256739
• 关键词: Adopted; Adult; Behavior; Blood Pressure; Body mass index; Cardiovascular Diseases; Cities; Communities; Complex; Computer Simulation; Consumption; Coronary heart disease; Cost Savings; Cost of Illness; Data; Decision Making; Diabetes Mellitus; Disease Outcome; Eating; Ensure; Food; Food Policy; Geographic Locations; Goals; Government; Health; Health Care Costs; Health Planning; Health Status; Health behavior; Health behavior outcomes; Hypertension; Intervention; Investigation; Link; Local Government; Long-Term Effects; Mental Health; Modeling; Morbidity - disease rate; Neighborhoods; New York City; Outcome; Pathway interactions; Policies; Population; Population Characteristics; Public Health; Quality-Adjusted Life Years; Recommendation; Research; Research Project Grants; Resources; Restaurants; Risk Factors; Sodium; Stroke; System; Techniques; Unhealthy Diet; United States; Vendor; base; cardiometabolism; cardiovascular disorder prevention; cardiovascular health; community organizations; comparative effectiveness; contextual factors; cost effective; design; dietary; disability; discount; evidence base; experience; fast food; fruits and vegetables; health data; health economics; improved; income disparities; innovation; insight; model development; models and simulation; modifiable risk; mortality; novel; nutrition; population health; programs; public health research; simulation; success; warning label

Project Summary/Abstract 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 using agent-based modeling, an efficient, novel technique that has been underutilized in public health research. We assembled a team of experts in CVD, nutrition, public health, health economics, 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.

项目总结/摘要 饮食行为是避免心血管疾病（CVD）的主要可改变风险因素， 发病率，死亡率和残疾率在美国（US）。尽管国家和地方采取措施， 健康的饮食行为，不健康的饮食仍然是一个困难的，令人困惑的人口健康问题， 在社区和人口层面的倡议和解决办法。在投资实施之前，卫生 从业者和决策者--通常在有限的资源下工作--需要比较人口健康状况 不同的粮食政策和计划的影响，然后确定优先事项。这个项目的目标， 通过预测对心血管疾病的长期影响来评估政策 模拟（APPLE CDS），比较食品政策和项目对CVD相关结果的影响 和成人的医疗保健费用。这将有助于帮助地方政府和社区组织， 优先事项的确定和决策。政策和计划评估将使用基于代理人的 建模是一种有效的新技术，在公共卫生研究中未得到充分利用。我们组建了一个 心血管疾病、营养、公共卫生、卫生经济学和计算机模拟建模方面的专家团队， 致力于共同努力，以确定可用于改善饮食行为的现实途径。的 具体目标是：（1）开发一个基于代理人的模型来评估和比较替代食品的影响 政策和计划的饮食行为，血压，身体质量指数（BMI），和糖尿病， 纽约市的不同社区，（2）将基于代理的模型与完善的，经过验证的纽约市联系起来 心血管疾病政策模型，用于预测不同食品政策和计划对心血管疾病的长期影响 疾病结果（例如，高血压、冠心病、中风）、质量调整生命年（Qs）， 和医疗费用。我们将充分利用社区一级关于饮食行为的丰富健康数据， 纽约市卫生和心理卫生部（DOHMH）对模型进行参数化和验证。在 此外，我们与NYC DOHMH和广泛的社区组织建立了密切的伙伴关系 整个城市将确保模拟结果将用于选择和优化最 具有成本效益的、针对具体社区的食品政策和方案，以改善人口健康。最后 纽约市的经验可以作为一个例子，其他地方卫生部门和社区为基础的 各组织可以为自己的优先级设置和计划实施做出更明智的决定。