Nutrition for Precision Health Study Using Artificial Intelligence to Predict Individual Responses to Controlled Diets in Community and Residential Settings for Adults 18 and Older

What this Trial Is About

Researchers are studying how individual people respond to different diet patterns by using artificial intelligence and machine learning. The Nutrition for Precision Health NPH study includes a large group of adults who provide detailed health and lifestyle data, along with two smaller groups that follow specific diet plans under controlled conditions. The goal is to predict metabolic responses to meals by analyzing data from clinical, molecular, behavioral, environmental, and social factors. Participants in the study are divided into three modules. Module 1 is observational and collects baseline health data over 8 to 10 days. Module 2 involves 1,200 participants living in their own homes who follow three different diets each for about two weeks, with at least two weeks in between, while all meals are provided. Module 3 includes 150 participants who live in a residential research setting and follow the same three diets under full supervision. Both modules include meal tests to measure glucose, insulin, triglycerides, and GLP-1 responses. During the study, participants provide blood samples at multiple times after meal tests and wear devices to monitor activity and glucose levels. Data collected includes biospecimens, questionnaires, and physical measures. The study also compares various dietary assessment tools for accuracy and ease of use. The entire process for Modules 2 and 3 can last up to six months, including diet periods and washouts, with researchers measuring metabolic responses to better understand how diet affects health.

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