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)
基本信息
- 批准号:9762624
- 负责人:
- 金额:$ 77.38万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-08-15 至 2019-08-31
- 项目状态:已结题
- 来源:
- 关键词:AdoptedAdultBehaviorBlood PressureBody mass indexCardiovascular DiseasesCitiesCommunitiesComplexComputer SimulationConsumptionCoronary heart diseaseCost SavingsCost of IllnessDataDecision MakingDiabetes MellitusDietDisease OutcomeEatingEnsureFoodFood PolicyGoalsGovernmentHealthHealth Care CostsHealth PlanningHealth PolicyHealth StatusHealth behaviorHealth behavior outcomesHypertensionIncomeInterventionInvestigationLabelLinkLocal GovernmentLong-Term EffectsMental HealthModelingMorbidity - disease rateMunicipalitiesNeighborhoodsNew York CityOutcomePathway interactionsPoliciesPopulationPopulation CharacteristicsPublic HealthQuality-Adjusted Life YearsRecommendationResearchResearch Project GrantsResourcesRestaurantsRisk FactorsSodiumStrokeSystemUnhealthy DietUnited Statesbasecardiometabolismcardiovascular disorder preventioncardiovascular healthcommunity organizationscomparative effectivenesscontextual factorscost effectivedesigndisabilitydiscountevidence baseexperiencefast foodfruits and vegetableshealth datahealth disparityhealth economicsimprovedinnovationinsightmodel developmentmodels and simulationmodifiable riskmortalitynutritionpopulation healthprogramssimulationsuccess
项目摘要
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 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.
项目概要/摘要
饮食行为是预防心血管疾病(CVD)的关键可改变危险因素,心血管疾病是主要原因
美国 (US) 的发病率、死亡率和残疾情况。尽管国家和地方采取措施促进
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,需要
社区和人口层面的倡议和解决方案。在投资实施之前,卫生
从业者和政策制定者通常资源有限,需要比较人口健康状况
不同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),用于比较食品政策和计划对 CVD 相关结果的影响
以及成人的医疗保健费用。这将有助于帮助当地政府和社区组织
优先事项设定和决策。政策和计划评估将通过联合代理进行
基于已建立的健康结果模型的建模。我们组建了CVD专家团队,
营养学、公共卫生、卫生经济学、卫生政策和计算机模拟建模领域的研究人员
共同努力找出可用于改善饮食行为的现实途径。具体
目标是:(1) 开发基于代理的模型来评估和比较替代食品政策的影响
以及针对不同人群的饮食行为、血压、体重指数 (BMI) 和糖尿病的计划
纽约市的社区,以及 (2) 将基于代理的模型与成熟且经过验证的纽约市 CVD 联系起来
预测不同食品政策和计划对心血管疾病的长期影响的政策模型
结果(例如高血压、冠心病、中风)、质量调整生命年 (QALY) 和健康
护理费用。我们将利用纽约市收集的有关饮食行为的丰富社区级健康数据
健康和心理卫生部 (DOHMH) 对模型进行参数化和验证。此外,我们的
与 NYC DOHMH 以及全市范围广泛的社区组织建立密切合作关系
将确保模拟结果将用于选择和优化最具成本效益的实施,
旨在改善人口健康的针对特定社区的粮食政策和计划。最后,纽约的经历
可以作为其他地方卫生部门和社区组织的榜样
为自己的优先事项设定和计划实施做出更明智的决定。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yan Li其他文献
Modeling Fuzzy Data with Fuzzy Data Types in Fuzzy Database and XML Models
使用模糊数据库和 XML 模型中的模糊数据类型对模糊数据进行建模
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:1.2
- 作者:
Yan Li - 通讯作者:
Yan Li
Formal Mapping of Fuzzy XML Model into Fuzzy Conceptual Data Model
模糊XML模型到模糊概念数据模型的形式化映射
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Yan Li - 通讯作者:
Yan Li
Yan Li的其他文献
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{{ truncateString('Yan Li', 18)}}的其他基金
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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 - 财政年份:2018
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$ 77.38万 - 项目类别:
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)
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