Discovering Determinants of Food Intake by Application of Machine Learning to Complex, High-Dimensional Data

Summary

Background: Many people in the United States are overweight or obese. Researchers want to learn why some people can overeat and not gain weight, whereas others who do not overeat still gain weight. Objective: To study factors related to food intake that can lead to weight gain over time. Eligibility: Healthy adults aged 18 to 60 years. Design: Participants will have 6 to 8 clinic visits over 2 years. The first 3 or 4 study visits will be 1 week apart. Procedures during visits may include the following: Collection of blood, hair, urine, and stool samples. Measurement of the waist, neck, thighs, and other parts of the body. Dual energy x-ray absorption (DXA) scan: Participants will lie still on a padded table while they are scanned to measure body fat. Physical activity monitor: Participants will wear a monitor on the wrist for 2 weeks. Cognitive tests: Participants will perform tasks to measure attention, memory, and brain function. Continuous glucose monitor. Participants will wear a device that measures their blood glucose for 1 week. Mixed meal test and stomach emptying test. Participants will drink a breakfast shake and swallow a dose of acetaminophen. Blood will be drawn over the next 4 hours. Resting metabolic rate: Participants will wear a clear hood over their head while they rest for 20 minutes. The hood will measure the gases they breathe. Breakfast and lunch test. Participants will eat a standard breakfast. They will be allowed to select from foods and eat as much as they like at lunch. They will be asked how hungry or full they are. Questionnaires. Participants will answer questions about their health, sleep, physical activity, and eating.

Description