Maternal Alcohol Use, Adverse Neonatal Outcomes and Pregnancy Complications in British Columbia, Canada: A Population-based Study
Bibliographic record
Abstract
Abstract BackgroundThe current study aimed to estimate the prevalence of alcohol use identified as a risk factor during pregnancies by the antenatal care providers, resulting in live births in British Columbia (BC) and to examine associations between alcohol use, adverse neonatal outcomes, and pregnancy complications.MethodsThis population-based cross-sectional study utilized linked obstetrical and neonatal records within the BC Perinatal Data Registry (BCDPR), for deliveries that were discharged between January 1, 2015 and March 31, 2018. The main outcome measures were alcohol use identified as a risk factor during pregnancy, associated maternal characteristics, pregnancy complications, and adverse neonatal outcomes. Estimates for the period and fiscal year prevalence were calculated. Chi-square tests were used to compare adverse neonatal outcomes and pregnancy complications by alcohol use during pregnancy. Logistic regression was used to examine the association between alcohol use during pregnancy and adverse neonatal outcomes and pregnancy complications, after adjusting for identified risk factors.ResultsA total of 144,779 linked records within the BCDPR were examined. The period prevalence of alcohol use during pregnancy identified as a risk factor was estimated to be 1.1% and yearly prevalence was 1.1%, 1.1%, 1.3% and 0.9% from the 2014/2015 fiscal year to 2017/2018, respectively. Indicated alcohol use was associated with younger maternal age, fewer antenatal visits, being nulliparous, a history of mental illness, substance use and smoking. Alcohol-exposed neonates had greater odds of being diagnosed with low birth weight (aOR = 1.25; 95% CI: 1.01, 1.53), other respiration distress of newborn (aOR = 2.57; 95% CI: 1.52, 4.07), neonatal difficulty in breastfeeding (aOR = 1.97; 95% CI: 1.27, 2.92) and unspecified feeding problems (aOR = 2.06; 95% CI: 1.31, 3.09)ConclusionsThe prevalence of alcohol use during pregnancy identified as a risk factor, estimated in this study, was comparable to the previous estimates within BCDPR. Prenatal alcohol exposure was associated with notable differences in maternal and neonatal characteristics and adverse neonatal outcomes. More consistent and thorough screening and prevention efforts targeting alcohol use in pregnancy are urgently needed in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".