A Narrative Review of Binge Eating and Addictive Behaviors: Shared Associations with Seasonality and Personality Factors
Bibliographic record
Abstract
Binge-eating disorder and seasonal affective disorder were first described as clinically relevant conditions in very close temporal proximity a few decades ago. Both disorders have a higher prevalence rate in woman than in men, are characterized by a high proneness-to-stress and manifest heightened responsiveness to high-calorie, hyper-palatable foods. In recent years, a compelling body of evidence suggests that foods high in sugar and fat have the potential to alter brain reward circuitry in a manner similar to that seen when addictive drugs like alcohol and heroin are consumed in excess. These findings have led to suggestions that some cases of compulsive overeating may be understood as an addiction to sweet, fatty, and salty foods. In this paper, it is proposed that high seasonality is a risk factor for binge eating, especially in those characterized by anxious and impulsive personality traits - associations that could only occur in an environment with a superfluity of, and easy access to, rich and tasty foods. Given the well-established links between binge eating and addiction disorders [Ref. (1-3) for reviews], it is also suggested that seasonality, together with the same high-risk psychological profile, exacerbates the likelihood of engaging in a broad range of addictive behaviors. Data from a community sample (n = 412) of adults tested these models using linear regression procedures. Results confirmed that symptoms of binge eating and other addictive behaviors were significantly inter-correlated, and that seasonality, gender, and addictive personality traits were strong statistical predictors of the variance in binge-eating scores. Seasonality and addictive personality traits also accounted for a significant proportion of the variance in the measure of addictive behaviors. Conclusions are discussed in the context of brain reward mechanisms, motivational alternations in response to chronic over-consumption, and their relevance for the treatment of excessive appetitive behaviors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".