Project 4: Virtual Public Health Precision Nutrition Laboratory
项目4:虚拟公共卫生精准营养实验室
基本信息
- 批准号:10386502
- 负责人:
- 金额:$ 24.25万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-01-19 至 2026-12-31
- 项目状态:未结题
- 来源:
- 关键词:Adaptive BehaviorsAddressAdherenceAdoptionAffectAreaArtificial IntelligenceBehaviorBiological ProcessChronicComplexComputer ModelsDataData SetDecision MakingDietEatingEconomicsEnvironmentEthical IssuesExposure toFamilyFeedbackFoodFood AccessFriendsGoalsHealthIndividualInformaticsIntakeInterventionLaboratoriesLos AngelesMaintenanceModelingNew YorkNutrientNutritionalPathway interactionsPatternPersonsPhenotypePhysical environmentPoliciesPrecision HealthProcessPublic HealthRecommendationSamplingSkinSocial EnvironmentSocial NetworkSystemTestingTimebasebuilt environmentcomputerized toolsdietaryfood environmentfood insecurityinnovationneglectnovelnutritionprecision nutritionprogramsresponsesocialtoolvirtualvirtual humanvirtual laboratory
项目摘要
Abstract-Project 4: Virtual Public Health Precision Nutrition Laboratory
When it comes to better understanding and addressing precision nutrition, it is important to consider
what happens "above the skin" as well as under. Factors operating “above the skin” represent impacts from
outside an individual’s body that can influence their nutrition and health. This includes facets of the social, built,
and broader macro-environments that an individual is exposed to, such as influences from friend/family social
networks, food access, and local policies. Evidence shows that factors outside a person can affect their diet
and their capacity for dietary change. Studies also show how factors outside a person get “under the skin,”
affecting biological processes that matter to nutrient processing and long-term chronic health conditions. At the
same time, biological processes and health conditions can affect factors outside a person. Neglecting factors
outside a person may limit the impact of precision nutrition due to an incomplete understanding of mechanisms
and inaccurate intervention approaches that introduce bias and worsen disparities. Thus, precision nutrition
should consider how diets fit with phenotypes that are defined based on individual-level factors as well as
social, built, and macro-environments people are exposed to in order to narrow the intervention-implementation
gap. Nutrition recommendations may need to be tailored to the contexts in which people live and eat, and the
contexts in which people live and eat may need to be intervened upon to support adherence to dietary
recommendations. Therefore, the goal of this proposed project is to develop and utilize the Project 3:
The Virtual Human for Precision Nutrition (Project 4), which like the Virtual Human for Precision
Nutrition (Project 3) could serve as a "virtual laboratory" to test different diets on different
types/groups of people and better understand and predict the resulting responses. The difference is that
while the Virtual Human agent-based model (ABM) will focus on the individual and everything under their skin,
the Virtual Public Health Precision Nutrition Laboratory will incorporate the key factors and processes outside
the individual. This will include the person's exposure to social, economic, and built environments. These
different influences on dietary behaviors form feedback loops and interactions that require the model to
represent autonomous decision making and complex, adaptive behaviors. Aim 1 will develop ABMs of sample
New York State (NYS) and Los Angeles (LA) areas to simulate how physical environments may affect different
people's nutrient intake, dietary behaviors, ability to follow particular diets, and resulting health over time. Aim
2 will incorporate into the ABMs computational representations of different agents' social environments, to
simulate how these affect their diet, nutrient intake, adherence to dietary recommendations, and resulting
health over time. Aim 3 will demonstrate how the ABM can be used to evaluate how much different peoples’
diets may need to be tailored to their social, economic, and built environment and what other policies and
interventions may be needed to facilitate adherence to a given diet.
项目4:虚拟公共卫生精准营养实验室
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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{{ truncateString('Bruce Y Lee', 18)}}的其他基金
Simulating the Spread and Control of Multiple MDROs Across a Network of Different Nursing Homes
模拟多个 MDRO 在不同疗养院网络中的传播和控制
- 批准号:
10549492 - 财政年份:2023
- 资助金额:
$ 24.25万 - 项目类别:
Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems (AIMINGS) Center
营养指导和系统人工智能、建模和信息学 (AIMINGS) 中心
- 批准号:
10386497 - 财政年份:2022
- 资助金额:
$ 24.25万 - 项目类别:
Project 3: The Virtual Human for Precision Nutrition
项目 3:精准营养虚拟人
- 批准号:
10552681 - 财政年份:2022
- 资助金额:
$ 24.25万 - 项目类别:
Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems (AIMINGS) Center
营养指导和系统人工智能、建模和信息学 (AIMINGS) 中心
- 批准号:
10552675 - 财政年份:2022
- 资助金额:
$ 24.25万 - 项目类别:
Project 4: Virtual Public Health Precision Nutrition Laboratory
项目4:虚拟公共卫生精准营养实验室
- 批准号:
10552687 - 财政年份:2022
- 资助金额:
$ 24.25万 - 项目类别:
Project 3: The Virtual Human for Precision Nutrition
项目 3:精准营养虚拟人
- 批准号:
10386501 - 财政年份:2022
- 资助金额:
$ 24.25万 - 项目类别:
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