Abuse: a risk factor for low birth weight? A systematic review and meta-analysis.
Bibliographic record
Abstract
BACKGROUND: Abuse during pregnancy is considered to be a potentially modifiable risk factor for low birth weight (LBW). We conducted a systematic review and meta-analysis to determine the strength of association between physical, sexual or emotional abuse during pregnancy and LBW. METHODS: We selected papers for review from an electronic search of MEDLINE (1966-1999), CINAHL (1982-1997) and the Cochrane Library. We retrieved articles using the following MeSH headings and keywords: "infant low birth weight," "fetus," "perinatal care," "pregnancy," "prenatal care," "infant mortality," "violence," "battered women," "spouse abuse," "infant morbidity," "antenatal" and "neonatal." When necessary, we contacted authors to obtain data that were not included in the published material. We analyzed the methodological quality of each eligible study and selected those of the highest quality for meta-analysis. RESULTS: We reviewed 14 studies, of which 8 were selected for meta-analysis. Using a fixed-effects model, we found that women who reported physical, sexual or emotional abuse during pregnancy were more likely than nonabused women to give birth to a baby with LBW (odds ratio 1.4, 95% confidence interval 1.1-1.8). INTERPRETATION: Abuse may be part of a complex interaction of factors that contribute to LBW.
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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 | 0.021 | 0.066 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.030 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 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".