Patterns of menstrual disturbance in eating disorders
Bibliographic record
Abstract
OBJECTIVE: To describe menstrual disturbance in eating disorders (ED). METHOD: We describe menstrual history in 1,705 women and compare eating, weight, and psychopathological traits across menstrual groups. RESULTS: Menstrual dysfunction occurred across all eating disorder subtypes. Individuals with normal menstrual history and primary amenorrhea reported the highest and lowest lifetime body mass index (BMI), respectively. Normal menstruation and oligomenorrhea groups reported greater binge eating, vomiting, and appetite suppressant use. Amenorrhea was associated with lower caloric intake and higher exercise. Harm avoidance, novelty seeking, perfectionism, and obsessionality discriminated among menstrual status groups. No differences in comorbid Axis I and II disorders were observed. CONCLUSION: Menstrual dysfunction is not limited to any eating disorder subtype. BMI, caloric intake, and exercise were strongly associated with menstrual function. Menstrual status is not associated with comorbidity. Menstrual irregularity is an associated feature of all ED rather than being restricted to AN only.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".