Alcohol Use Disorder Comorbidity in Eating Disorders
Bibliographic record
Abstract
BACKGROUND: Eating disorders and alcohol use disorders (AUDs) commonly co-occur, although the patterns of comorbidity differ by eating disorder subtype. Our aim was to explore the nature of the co-morbid relation between AUDs and eating disorders in a large and phenotypically well-characterized group of individuals. METHOD: We compared diagnostic and personality profiles of 97 women with lifetime anorexia nervosa only, 282 women with lifetime bulimia nervosa only, and 293 women with a lifetime history of both anorexia nervosa and bulimia nervosa or anorexia nervosa with binge eating (ANBN) (DSM-IV criteria). All individuals were participants in a multicenter study of the genetics of anorexia nervosa and bulimia nervosa. We explored pattern of onset, Axis I and II comorbidity, and personality characteristics of individuals with and without AUDs by eating disorder subtype. Personality characteristics were assessed with the Multidimensional Perfectionism Scale, the Temperament and Character Inventory, and the Barratt Impulsivity Scale. RESULTS: Alcohol use disorders were significantly more prevalent in women with ANBN and bulimia nervosa than in women with anorexia nervosa (p =.0001). The majority of individuals reported primary onset of the eating disorder, with only one third reporting the onset of the AUD first. After eating disorder subtype was controlled for, AUDs were associated with the presence of major depressive disorder, a range of anxiety disorders, and cluster B personality disorder symptoms. In addition, individuals with AUDs presented with personality profiles marked by impulsivity and perfectionism. CONCLUSIONS: Individuals with eating disorders and AUDs exhibit phenotypic profiles characterized by both anxious, perfectionistic traits and impulsive, dramatic dispositions. These traits mirror the pattern of control and dyscontrol seen in individuals with this comorbid profile and suggest that anxiety modulation may be related to alcohol use in this group.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".