# Project 4: Virtual Public Health Precision Nutrition Laboratory > **NIH NIH U54** · GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY · 2022 · $242,501 ## Abstract 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. Ai... ## Key facts - **NIH application ID:** 10386502 - **Project number:** 1U54TR004279-01 - **Recipient organization:** GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY - **Principal Investigator:** Bruce Y Lee - **Activity code:** U54 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $242,501 - **Award type:** 1 - **Project period:** 2022-01-19 → 2026-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10386502 ## Citation > US National Institutes of Health, RePORTER application 10386502, Project 4: Virtual Public Health Precision Nutrition Laboratory (1U54TR004279-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10386502. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*