Urge to Eat and Body Mass Index: Exploring the Association with Diffuse and Defined Emotions
Bibliographic record
Abstract
Introduction: Emotional eating is more common in individuals with obesity and is a predictor of increased body mass index (BMI). This study aimed to identify the types of emotions associated with the urge to eat in subjects with varying BMI levels. METHODS: Adult participants were recruited as part of a validity study for a new questionnaire designed to assess an individual's relationship with their body. The emotional eating scale of the Dutch Eating Behavior Questionnaire (DEBQ), as well as questions on past and current eating disorders, body weight status and history, health, and sociodemographic data, were assessed through an online questionnaire. RESULTS: Six hundred participants were included, comprising 80.5% women. A total of 27.0% were living with overweight and 21.2% with obesity. The urge to eat was significantly more frequent in response to diffuse emotions than to defined emotions, independent of sex and BMI level. The frequency of emotional eating was positively associated with BMI for all emotions explored by the DEBQ. The defined emotion "depressed/discouraged" induced an urge to eat more often in individuals with obesity. "Feeling abandoned" was the diffuse emotion most associated with obesity (53.5% of subjects with obesity ate often or very often versus 28.6% of subjects with normal weight). CONCLUSION: This study highlights the need to explore diffuse emotions in subjects with obesity. .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".