Examining the Relationship Between Eating Disorders and Gestational Weight Gain: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Pregnant women face significant changes in their body image, weight, and overall appearance, potentially leading to the development of an eating disorder or exacerbation of a pre-existing eating disorder during pregnancy. Despite the known risks of insufficient or excess gestational weight gain (GWG), few studies have examined the relationship between eating disorders and GWG. The objective of this study was to examine the relationship between GWG and eating disorders in women with anorexia nervosa, bulimia nervosa, and binge eating disorder. DATA SOURCES: CINAHL, Embase, PsycInfo, and PubMed. STUDY SELECTION: A search strategy was developed and entered into CINAHL, Embase, PsycInfo, and PubMed for studies published since 1994 that included participants with a singleton pregnancy; a clinical diagnosis of anorexia nervosa, bulimia nervosa, or binge eating disorder; and ≥18 years of age. DATA EXTRACTION AND SYNTHESIS: Titles and abstracts were reviewed, followed by full-text review and a quality assessment. An integrated approach was undertaken, including line-by-line coding of eligible papers, development of preliminary descriptive themes based on these codes, and amalgamation of the themes to describe the relationship between eating disorders and GWG. A total of 1471 articles were identified, 14 of which met the inclusion criteria for the study. Three themes emerged: body image concerns, fear of GWG and postpartum weight retention, and prioritizing the health of the baby. CONCLUSION: The identified themes inform the relationship between anorexia nervosa, bulimia nervosa, and binge eating disorder and guideline-discordant GWG. These findings are relevant for persons who provide prenatal care to patients with previous or current eating disorders.
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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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".