Association Between Alcohol use in Pregnancy and Preeclampsia or Hypertension in Pregnancy: A Systematic Review
Bibliographic record
Abstract
Abstract BackgroundTo summarize evidence on the association of maternal alcohol consumption during pregnancy with preeclampsia (PE) or hypertensive disorders of pregnancy (HDP).Methods We searched PubMed, EMBASE, PsycINFO, and Cochrane Central Register of Controlled Trials databases. We included original studies that presented relative risks, odds ratios, or data to calculate the risks for the association of alcohol consumption during pregnancy with PE or HDP. We used the Newcastle-Ottawa Scale to assess study quality. We conducted a random-effects meta-analysis to calculate the pooled association of gestational alcohol use with PE or HDP.ResultsThirty-seven articles met the criteria for inclusion. The total study population was 4,434,003 women with 170,481 cases of PE and 467,055 women with 41,708 cases of HDP. For all included studies, there was no significant association between alcohol consumption during pregnancy and incidence of PE (OR=0.93, 95%CI: 0.73-1.20), with statistical significant heterogeneity (I2=91%, P<0.00001). Among the subgroup of prospective cohort studies, the pooled results showed that alcohol consumption during pregnancy had a protective effect on PE (OR=0.64, 95% CI: 0.54-0.76), and with no statistical heterogeneity (I2 =0%, P=0.56). The results from the subgroup of retrospective cohort and case-control studies showed that alcohol consumption during pregnancy was not associated with PE, with odds ratios of 1.07 (0.65-1.74) and 1.02 (0.64-1.61), respectively, and with statistically significant heterogeneity. The pooled OR for the association between alcohol consumption during pregnancy and HDP was 0.98 (95% CI: 0.75-1.29), with considerable heterogeneity (I2=90% P<0.00001).ConclusionOverall, there is no apparent association of alcohol consumption during pregnancy with PE or HDP. In prospective cohort studies, an evident protective effect is likely due to residual confounding. Further studies should consider alternative designs such as mendelian randomization, which can overcome some of the limitations of conventional prospective studies.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".