Food addiction in a large non-clinical sample of Canadians
Bibliographic record
Abstract
Introduction The concept of food addiction emerged recently due to the similarities between food overconsumption patterns and addictive drugs. This concept is not yet included into ICD or DSM as it still needs to be further investigated. Relationship between obesity and food consumption as well as the psychological indicators of food addiction are of particular interest. Objectives To examine the prevalence of food addiction and its relationship to obesity, quality of life and multiple indicators of impulsivity. Methods Cross-sectional in-person assessment of 1432 community adults (age 38.93+/-13.7; 58% female). Measurements: Yale Food Addiction Scale 2.0, anthropometrics, body composition, World Health Organization Quality of Life scale, and impulsivity measures including impulsive personality traits, delay discounting, and behavioral inhibition. Results The prevalence of food addiction was 9.3% and substantially below that of obesity (32.7%). Food addiction was more prevalent among obese individuals and also was associated with higher BMI among non-obese participants. It was associated with significantly lower quality of life in all domains, and significantly higher impulsive personality traits, particularly negative and positive urgency. Conclusions In this general community sample, food addiction was present in slightly fewer than 1 in 10 individuals, approximately one-third the prevalence of obesity, but notably the food addiction has been mostly represented within the subsample of obese individuals. Food addiction was robustly associated with substantively lower quality of life and elevations in impulsivity, particularly in deficits in emotional regulation. These data suggest food addiction may be thought of as a subtype of obesity and, in non-obese individuals, possibly a prodrome. Disclosure No significant relationships.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".