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

项目摘要/摘要 饮食行为是避免心血管疾病(CVD)的关键可改变的危险因素，心血管疾病是主要原因 美国(US)的发病率、死亡率和残疾。尽管国家和地方采取了促进 健康的饮食行为，不健康的饮食仍然是一个难题，困扰着人们的健康要求 社区和人口层面的倡议和解决方案。在投资实施之前，健康 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，然后确定优先事项。这个项目的目标是， 通过预测心血管疾病的长期影响来评估政策 模拟(Apple CDS)，是比较食品政策和计划对心血管疾病相关结果的影响 以及成年人的医疗保健费用。这将有助于帮助当地政府和社区组织 优先次序的设定和决策。将使用基于代理的方式进行政策和计划评估 建模，一种在公共卫生研究中一直未得到充分利用的有效的新技术。我们组装了一个 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，确定可用于改善饮食行为的现实途径。这个 具体目标是：(1)开发一个基于代理的模型来评估和比较替代食品的影响 关于饮食行为、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公认的、经过验证的纽约市联系起来 心血管疾病政策模型预测不同食品政策和计划对心血管疾病的长期影响 疾病结局(如高血压、冠心病、中风)、质量调整寿命年(QALY)、 和医疗保健费用。我们将利用由以下机构收集的丰富的社区健康数据 纽约市卫生和精神卫生部门(DOHMH)对该模型进行参数化和验证。在……里面 此外，我们与纽约市DOHMH和广泛的社区组织的密切合作伙伴关系 全市将确保使用模拟结果来选择和优化MOST 具有成本效益的、针对特定社区的食品政策和计划，以改善人口健康。最后， 纽约市的经验可以作为其他地方卫生部门和社区的榜样 组织可以为自己的优先顺序设置和计划实施做出更明智的决定。

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.