Adverse Birth Outcomes Associated with Types of Eating Disorders: A Review
Bibliographic record
Abstract
At least 5% of women have an eating disorder (ED) during pregnancy. These EDs affect prepregnancy body mass index (BMI) and weight gain during pregnancy, factors associated with birth complications and adverse neonatal outcomes. This review contributes to the literature by examining several adverse birth outcomes associated with EDs and differentiates between past and present EDs. Of the 18 articles reviewed, EDs were associated with preterm birth in 5/14 (36%) and small-for-gestational-age in 5/8 (63%) studies. Anorexia Nervosa increases the odds of a low birth weight baby, particularly when women enter pregnancy with a low BMI. Binge Eating Disorder is positively associated with having a large-for-gestational-age infant, and Bulimia Nervosa is associated with miscarriage when symptomatic during pregnancy. Having a current ED increases the risk for adverse birth outcomes more than a past ED. Since the aetiology of adverse birth outcomes is multi-factorial, drawing conclusions about causal relationships between EDs and birth outcomes is problematic given the small number of studies reporting these outcomes. Resources should target preconception interventions that put EDs into remission and help women achieve a healthier BMI prior to pregnancy, as these have been consistently shown to improve birth outcomes.
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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) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".