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: 10089006
• 负责人: Yan Li
• 金额: $ 89.71万
• 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 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10089006
• 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; Diet; 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; Income; Intervention; Investigation; Label; 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; disability; discount; evidence base; experience; fast food; fruits and vegetables; health data; health economics; improved; innovation; insight; model development; models and simulation; modifiable risk; mortality; novel; nutrition; population health; programs; public health research; simulation; success

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.

项目摘要/摘要 饮食行为是避免心血管疾病（CVD）的关键可修改风险因素，这是主要原因 美国的发病，死亡率和残疾（美国）。尽管国家和地方倡议促进 健康的饮食行为，不健康的饮食仍然是一种困难，令人困惑的人口健康问题 社区和人口水平的计划和解决方案。在投资实施之前 从业者和政策制定者（通常使用有限的资源）需要比较人口健康 不同的食品政策和计划的影响，以确定优先级。这个项目的目标， 通过使用长期对心血管疾病的影响评估政策的评估 模拟（Apple CD）是要比较食品政策和计划对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 优先设定和决策。政策和计划评估将使用基于代理的代理人进行 建模是一种高效，新颖的技术，在公共卫生研究中未被充分利用。我们组装了一个 CVD，营养，公共卫生，健康经济学和计算机模拟建模专家团队 致力于确定可用于改善饮食行为的现实途径。这 具体目的是：（1）开发基于代理的模型来评估和比较替代食品的影响 有关饮食行为，血压，体重指数（BMI）和糖尿病的政策和计划 纽约市的不同社区和（2）将基于代理的模型与已建立的，已验证的纽约 CVD政策模型，以预测不同食品政策和计划对心血管的长期影响 疾病结局（例如高血压，冠心病，中风），质量调整的终身年份（Qalys）， 和医疗保健费用。我们将利用有关饮食行为的丰富社区级健康数据 纽约市卫生与精神卫生部（DOHMH）以参数化和验证该模型。在 此外，我们与纽约DOHMH的密切合作伙伴关系和广泛的社区组织 整个城市将确保模拟结果将用于选择和优化最多的实现 具有成本效益的社区特定食品政策和计划，以改善人口健康。最后， 纽约市的经验可以作为其他当地卫生部门和社区的榜样 组织可以为自己的优先设置和计划实施做出更明智的决定。