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: 10386502
• 负责人: Bruce Y Lee
• 金额: $ 24.25万
• 依托单位: GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY
• 依托单位国家: 美国
• 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: https://reporter.nih.gov/project-details/10386502
• 关键词: Adaptive Behaviors; Address; Adherence; Adoption; Affect; Area; Artificial Intelligence; Behavior; Biological Process; Chronic; Complex; Computer Models; Data; Data Set; Decision Making; Diet; Eating; Economics; Environment; Ethical Issues; Exposure to; Family; Feedback; Food; Food Access; Friends; Goals; Health; Individual; Informatics; Intake; Intervention; Laboratories; Los Angeles; Maintenance; Modeling; New York; Nutrient; Nutritional; Pathway interactions; Pattern; Persons; Phenotype; Physical environment; Policies; Precision Health; Process; Public Health; Recommendation; Sampling; Skin; Social Environment; Social Network; System; Testing; Time; base; built environment; computerized tools; dietary; food environment; food insecurity; innovation; neglect; novel; nutrition; precision nutrition; programs; response; social; tool; virtual; virtual human; virtual laboratory

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.

摘要项目 4：虚拟公共卫生精准营养实验室 当谈到更好地理解和解决精准营养问题时，重要的是要考虑 “皮肤之上”和之下发生的情况“皮肤之上”的因素代表了来自以下因素的影响。 个人体外可能会影响他们的营养和健康，这包括社会、建筑、 以及个人所接触的更广泛的宏观环境，例如来自朋友/家人社交的影响 有证据表明，个人以外的因素也会影响他们的饮食。 以及他们改变饮食的能力 研究还表明，外部因素如何“深入皮肤”。 影响对营养加工和长期慢性健康状况至关重要的生物过程。 同时，生物过程和健康状况也会影响人以外的因素。 由于对机制的不完全理解，体外可能会限制精准营养的影响 不准确的干预方法会引入偏见并加剧差异，因此，精准营养。 应考虑饮食如何适应基于个体水平因素以及 人们所接触的社会、建筑和宏观环境，以缩小干预实施范围 营养建议可能需要根据人们的生活和饮食环境以及情况进行调整。 可能需要对人们的生活和饮食环境进行干预，以支持对饮食的坚持 因此，本项目的目标是开发和利用项目 3： 精准营养虚拟人（项目 4），类似于精准营养虚拟人 营养（项目3）可以作为一个“虚拟实验室”来测试不同人群的不同饮食习惯 不同类型/群体的人并更好地理解和预测结果的反应。 而基于虚拟人代理的模型（ABM）将关注个人及其皮肤下的一切， 虚拟公共卫生精准营养实验室将整合外部的关键因素和流程 这将包括该人接触的社会、经济和建筑环境。 对饮食行为的不同影响形成反馈循环和相互作用，需要模型 目标 1 将开发样本 ABM。 纽约州 (NYS) 和洛杉矶 (LA) 地区模拟物理环境如何影响不同地区 人们的营养摄入量、饮食行为、遵循特定饮食的能力以及随着时间的推移而产生的健康目标。 2 将把不同智能体社交环境的计算表示纳入 ABM 中，以 模拟这些因素如何影响他们的饮食、营养摄入、对饮食建议的遵守以及由此产生的结果 目标 3 将展示如何使用 ABM 来评估不同人群的健康程度。 饮食可能需要根据他们的社会、经济和建筑环境以及其他政策和环境进行调整 可能需要采取干预措施来促进对特定饮食的坚持。