Obesity, Overnutrition, Overweight
Conditions
Keywords
Genetics, Fat Intake, Weight Control, Appetite Control, Natural History
Brief summary
The prevalence of obesity in the United States has reached alarming proportions with 33% of adults over the age of 20 being overweight. Obesity is more than twice as prevalent, however, in the Pima Indians of Arizona. Although there have been a number of advances in our understanding of the genetics of obesity, the environmental influences on the genetic expression of obesity requires further investigation. In an effort to understand some of the influences on the high prevalence of obesity in the Pima Indians, the present study was designed to investigate eating behaviors and food preferences, most especially the preference for high fat foods, in sib-pairs of Pima Indians who have been previously genotyped in our genomic scan for loci linked to diabetes/obesity. Most specifically, we will utilize several questionnaires and methods of assessing eating behavior and the preference for high fat foods to create a food intake phenotype. In addition, we will study Caucasians so that comparisons can be made between these two groups. We will make these evaluations by assessing eating behavior, food preferences including usual fat intake and preferences for high fat foods, body image perceptions, and energy expenditure. It is hoped that the data gathered from this study will elucidate some of the risk factors for the development of obesity among the Pima Indians....
Detailed description
The prevalence of obesity in the United States has reached alarming proportions with 33% of adults over the age of 20 being overweight. In some populations, obesity is even more prevalent. Although there have been a number of advances in our understanding of the genetics of obesity, the environmental influences on the genetic expression of obesity requires further investigation. In an effort to understand some of the influences on the high prevalence of obesity, the present study was designed to investigate what drives how much people eat. More specifically, we will try to understand what drives food intake utilizing 1) questionnaires that assess eating behavior, 2) measurements in blood, urine or fat tissue, and 3) genotypic associations to investigate the various factors that control what and how much people eat. We will make these evaluations by assessing eating behavior, food preferences including usual fat intake and preferences for high fat foods, body image perceptions, and energy expenditure. It is hoped that the data gathered from this study will elucidate some of the risk factors for the development of obesity.
Interventions
None listed
Sponsors
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Study design
Observational model
ECOLOGIC_OR_COMMUNITY
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
No
Inclusion criteria
* Inclusion Criteria: 1. Healthy, as determined by medical history, physical examination, and laboratory tests. 2. 18-65 years old 3. Non-diabetic status
Exclusion criteria
1. Hypo- or hyper-thyroid 2. Blood pressure greater than 160/95 3. Cardiovascular disease 4. Gallbladder disease 5. Alcohol and/or current use of drugs (more than 2 drinks per day and regular use of drugs such as amphetamines, cocaine, or heroin) 6. Psychiatric conditions or behavior that would be incompatible with safe and successful participation in this study, including claustrophobia and eating disorders such as anorexia or bulimia nervosa 8\. Use of medications affecting metabolism and appetite 9\. Pregnancy 10\. Current use of nicotine products, including tobacco, electronic cigarettes, and nicotine replacement therapies that exceed Very Low Dependence on the Fagerstr(SqrRoot)(Delta)m Test for Nicotine Dependence Tool (score greater than 2). Subjects may be excluded or withdrawn from the study if they have any conditions not specifically mentioned above that may interfere with the collection of the food intake. This includes such issues as not following study and unit policies and procedures, diagnosis of contraindications following admission, and development of illness/infection unrelated to the study. For example, volunteers who do not comply with the vending machine protocol (i.e., share food, do not record what they eat, eat outside of room, etc) may be withdrawn from the study.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Ad libitum food intake | Baseline, up to day 3 | Ad libitum food intake measured in kcal/day averaged over 3 days |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORSusanne M Votruba, Ph.D.
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Outcome results
None listed