Hormonal and Dietary Characteristics in Obese Human Subjects with and without Food Addiction
Bibliographic record
Abstract
The concept of food addiction (FA) is a potentially important contributing factor to the development of obesity in the general population; however, little is known about the hormonal and dietary differences between obesity with and without FA. Therefore, the aim of our study was to explore potential biomarkers, including various hormones and neuropeptides, which regulate appetite and metabolism, and dietary components that could potentially differentiate obesity with and without FA. Of the 737 adults recruited from the general Newfoundland population, 58 food-addicted and non-food-addicted overweight/obese individuals (FAO, NFO) matched for age, sex, BMI and physical activity were selected. A total of 34 neuropeptides, gut hormones, pituitary polypeptide hormones and adipokines were measured in fasting serum. We found that the FAO group had lower levels of TSH, TNF-α and amylin, but higher levels of prolactin, as compared to NFO group. The total calorie intake (per kg body weight), the dietary intake of fat (per g/kg body weight, per BMI and per percentage of trunk fat) and the percent calorie intake from fat and carbohydrates (g/kg) was higher in the FAO group compared to the NFO group. The FAO subjects consumed more sugar, minerals (including sodium, potassium, calcium and selenium), fat and its components (such as saturated, monounsaturated and trans fat), omega 3 and 6, vitamin D and gamma-tocopherol compared to the NFO group. To our knowledge, this is the first study indicating possible differences in hormonal levels and micro-nutrient intakes between obese individuals classified with and without food addiction. The findings provide insights into the mechanisms by which FA could contribute to obesity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".