Trajectories of Alcohol Use and Binge Drinking Among Pregnant Inuit Women
Bibliographic record
Abstract
BACKGROUND: This study investigated trajectories of alcohol use and binge drinking among Inuit women starting from a year before pregnancy until a year after delivery, examined transition rates between time periods, and established whether specific factors could be identified as predictors of changes in alcohol behaviors. METHODS: Drinking trajectories and movement among alcohol users and binge drinkers (i.e. non-binging and binging) were explored by Markov modeling across time periods. Two hundred and forty-eight Inuit women from Arctic Quebec were interviewed at mid-pregnancy, and at 1 and 11 months postpartum to obtain descriptive data on alcohol use during the year before pregnancy, the conception period, the pregnancy and the year after delivery. RESULTS: The proportions of drinkers and bingers were 73 and 54% during the year prior to pregnancy and 62 and 33% after delivery. Both alcohol use and binge drinking trajectories demonstrated a significant drop in prevalence between the year before conception to the conception period. We also noted high probabilities of becoming an abstainer or not binging at this time. However, up to 60% of women continued to drink alcohol during pregnancy. Women in couples and not consuming marijuana were more likely to decrease their binge drinking at conception. CONCLUSIONS: This study emphasizes the importance of including the period around conception in the definition of drinking patterns during pregnancy. The importance of considering alcohol consumption in a multidimensional way (personal, familial and social determinants) is also addressed while trying to minimize problems both for the fetus and the mother.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".