Epidemiology of anorexia nervosa in a French community-based sample of 39,542 adolescents
Bibliographic record
Abstract
Purpose: To assess the prevalence of DSM-IV anorexia nervosa criteria, anorexia nervosa and subthreshold subgroups, and their incidence between the ages of 12 and 17 years using Cole’s international thinness cut-offs, and to characterize these anorexic adolescents by parental socioeconomic status and whether or not they reported receiving treatment. Method: In all, a representative sample of 39,542 French adolescents (19,658 girls and 19,884 boys) was recruited in a cross-sectional study in 2008. Anorexia nervosa DSM-IV diagnosis was determined by a self-administered questionnaire. Results: Among females, 0.5% (n = 105) met criteria for anorexia nervosa between the ages of 12 and 17 years, whereas among males, the prevalence was 0.03% (n = 6). In females, the prevalence of sub-threshold anorexia nervosa was found to be between 1.2% (n = 216) and 3.3% (n = 618); more than 75% were of the restrictive subtype. The highest incidence of anorexia nervosa was at 16 years. There was also a greater prevalence of sub-threshold anorexia nervosa subgroups among subjects with high parental socioeconomic status. More than half of the female adolescents who met the anorexia nervosa criteria reported receiving treatment for their disorder, versus 23% to 40% of the adolescents in the sub-threshold subgroups (P sample of adolescents. Using Cole’s international thinness cut-off could improve international comparability among studies. Adolescents from the higher socioeconomic categories were more likely to be anorexic.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".