Discovering Determinants of Food Intake by Application of Artificial Intelligence to Complex, High-Dimensional Data
Healthy Volunteer
What this study involves
The registry does not currently label this study as recruiting. Ask about its status before planning a screening visit.
- Study type
- Observational
- Phase
- Not applicable / not listed
- Age range
- 18 years - 60 years
- Sex eligible
- All sexes
- Healthy volunteers
- Not accepted
- Participants
- 800 Estimated
These are starting points, not an eligibility decision. The research team must review the full requirements.
About the research
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.
Read the full description
Study Description:
The study will be an outpatient study with 6-7 total visits, 3-4 completed at baseline and 3 follow-up visits, occurring over 2 years. We will collect broad, multiscale data (e.g., clinical, genetic, microbiome, energy expenditure, physical activity, psychosocial). Then, we will apply artificial intelligence algorithms with the goal of identifying novel determinants of food intake.
Objectives:
Primary Objective:
To identify novel determinants of objectively measured ad libitum energy intake using broad, multiscale data.
Secondary Objectives:
1. To investigate whether determinants of ad libitum energy intake predict changes in weight, adiposity, and markers of metabolic health.
2. To determine associations of metabolic measures with psychosocial, hormonal, or other metabolic markers
3. To identify novel determinants of ad libitum self-reported energy and nutrient intake
Endpoints:
Primary Endpoint: Energy intake during ad libitum meal test, including total energy and macronutrient specific energy intake (e.g., carbohydrate, fat, protein) measured during the initial baseline period (visit 3). The potential determinants (broad multiscale data) will be collected during visits 1, 2, and 3.
Secondary Endpoints:
1. Measures at 0.5, 1, and 2 years of body weight, BMI, fat mass, body fat percentage, HbA1c, and fasting glucose, lipids, insulin, and c-peptide.
2. Psychosocial measures (visits 1-6), metabolic measures (e.g., fasting glucose, HbA1c, lipids, insulin, and c-peptide), resting metabolic rate, total energy expenditure, and physical activity
3. Energy and nutrient intake from ASA-24. The potential determinants (broad multiscale data) will be collected during visits 1, 2, and 3.
Who may be able to participate?
The list below is the sponsor’s full registry wording. It can include conditions, prior treatment, test results and other requirements. A match in search does not mean you qualify.
- INCLUSION CRITERIA:
To be eligible to participate in this study, an individual must meet all the following criteria:
1. Stated willingness to comply with all study procedures and availability for the duration of the study
2. Age 18 to 60
3. In good general health as evidenced by medical history and physical exam
EXCLUSION CRITERIA:
An individual who meets any of the following criteria will be excluded from participation in this study:
1. Weight \>=204 kg (\>=450 pounds, maximum weight of the iDXA machine as per manufacturer s manual), or weight \<45.4 kg (\<100 pounds, minimum weight allowed based on the NIH guidelines of blood drawing for research purposes)
2. Unstable weight (+/-5%) within past 6 months as determined by volunteer self-report.
3. Current use of medications, dietary supplements, or alternative therapies known to alter energy metabolism
4. Inability to consume provided food based on food allergy or intolerance or other food restrictions (e.g., kosher, vegan, or vegetarian)
5. Current pregnancy, or recent pregnancy within past 6 months or currently lactating
6. History or clinical manifestation of:
6i. Diabetes, including fasting glucose \>= 126 mg/dl or HbA1c \>= 6.5%, or history
6ii. Surgery for treatment of obesity
6iii. Endocrine disorders, such as Cushing s disease, pituitary disorders, or hypo- and hyperthyroidism (TSH \<0.1 or \>= 10 uIU/mL)
6iv. Pulmonary disorders including chronic obstructive pulmonary disease or other lung disease that which would limit ability to follow the protocol
6v. History of coronary artery disease, heart failure, arrhythmias, and peripheral artery disease that which would limit ability to follow the protocol
6vi. Liver disease, including cirrhosis, active hepatitis B or C based on history, and AST or ALT \>= 3x normal
6vii. Gastrointestinal disease including Crohn's disease, ulcerative colitis, celiac disease, or other malabsorptive disorders by history
6viii. Hematologic disorders including significant anemia (male hemoglobin \< 13.0 g/dL or female hemoglobin \< 11.0 g/dL)
6ix. Renal disease including abnormal kidney function (eGFR \<60 mL/min/1.73m\^2)
6x. Central nervous system disease, including cerebrovascular accidents, dementia, and neurodegenerative disorders by history
6xi. Cancer requiring treatment in the past 5 years, except for nonmelanoma skin cancers or cancers that have clearly been cured
6xii. Infectious disease such as active tuberculosis, HIV (by self-report), chronic coccidiomycosis or other chronic infections that might influence appetite
6xiii. Diagnosis of binge eating disorder, anorexia, or major psychiatric disorders including depression, schizophrenia, and psychosis
6xiv. Menopausal transition (late) to early postmenopause (e.g., \>= 2 skipped cycles and an interval of amenorrhea \>= 60 days and \<12 months)
7\. Alcohol abuse as defined by \>= 8-point score on the Alcohol Use Disorders Identification Test (AUDIT) questionnaire interview
8\. Inability to provide informed consent
9\. Any disorder, unwillingness, or inability not specifically mentioned above may serve as criteria for exclusion at the discretion of the investigators, such as those that jeopardize the safety of the participant or others, or would interfere with completion of study procedures
Study population
800 males and females, age 18-60 years who are in good health
Understand screeningTreatment, groups and participation
The registry may describe treatments and study duration without a complete visit calendar. Ask the study team for the exact schedule, procedures, risks, costs and alternatives. Keep your usual care plan unless your treating clinician tells you otherwise.
- Assignment
- Not reported
- Masking
- Not reported
1
800 males and females, age 18-60 years who are in good health
What researchers are measuring
Outcome measures describe what is being studied. They are not proof that a treatment works.
Primary measures
To identify novel determinants of objectively measured ad libitum energy intake using broad, multiscale data.
Time frame: 24-28 months
Energy intake during ad libitum meal test, including total energy and macronutrient specific energy intake (e.g., carbohydrate, fat, protein) measured during the initial baseline period (visit 3). The potential determinants (broad multiscale data) will be collected during visits 1, 2, and 3.
Secondary measures
To investigate whether determinants of ad libitum energy intake predict changes in weight, adiposity, and markers of metabolichealth
Time frame: 24-48 months
Measures at 0.5, 1, and 2 years of body weight, BMI, fat mass,body fat percentage, HbA1c, and fasting glucose, lipids, insulin,and c-peptide.
To determine associations of metabolic measures with psychosocial, hormonal, or other metabolic markers
Time frame: 24-48 months
Psychosocial measures (visits 1-6), metabolic measures (e.g., fasting glucose, HbA1c, lipids, insulin, and c-peptide), resting metabolic rate, total energy expenditure, and physical activity
To identify novel determinants of ad libitum self-reported energy and nutrient intake
Time frame: 24-28 months
Energy and nutrient intake from ASA-24. The potential determinants (broad multiscale data) will be collected during visits 1, 2, and 3
Review the complete result tables and limitations in the official record.
Open official results ↗Research locations (1)
The overall study status and a local site’s status can differ. Confirm that location’s availability before traveling.
1 locations
NIDDK, PhoenixPhoenix, Arizona, United StatesStatus unknown
Study team and timeline
- Lead sponsor
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
- Study start
- Nov 15, 2026 Estimated
- Primary completion
- Jul 1, 2037 Estimated
- Study completion
- Jul 1, 2037 Estimated
- First posted
- Jun 10, 2026 Actual
- Last updated
- Nov 10, 2026 Actual
Official study contacts
Official study title
Discovering Determinants of Food Intake by Application of Machine Learning to Complex, High-Dimensional Data
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Source: ClinicalTrials.gov API v2. Information is submitted by sponsors and investigators. NLM does not approve the safety or science of all listed studies. Registry disclaimer.
Retrieved: Nov 12, 2026 · Last registry update: Nov 10, 2026
