Acute care related to cannabis use during pregnancy after the legalization of nonmedical cannabis in Ontario
Bibliographic record
Abstract
BACKGROUND: Cannabis use during pregnancy is increasing, but the contribution of cannabis legalization to these trends is unclear. We sought to determine whether health service utilization related to cannabis use during pregnancy increased after the legalization of nonmedical cannabis in October 2018 in Ontario, Canada. METHODS: In this population-based, repeated cross-sectional study, we evaluated changes in the number of pregnant people who received acute care (emergency department visit or admission to hospital) between January 2015 and July 2021 among all people eligible for the province's public health coverage. We used segmented regression to compare changes in the quarterly rate of pregnant people with acute care related to cannabis use (primary outcome) with the quarterly rates of acute care for mental health conditions or for noncannabis substance use (control conditions). We identified risk factors associated with acute care for cannabis use and the risk of adverse neonatal outcomes using multivariable logistic regression models. RESULTS: The mean quarterly rate of acute care for cannabis use during pregnancy increased from 11.0 per 100 000 pregnancies before legalization to 20.0 per 100 000 pregnancies after legalization (incidence rate ratio [IRR] 1.82, 95% confidence interval [CI] 1.44-2.31), while acute care for mental health conditions decreased (IRR 0.86, 95% CI 0.78-0.95) and acute care for noncannabis substance use did not change (IRR 1.03, 95% CI 0.91-1.17). Legalization was not associated with an immediate change, but the quarterly change in rates of pregnancies with acute care for cannabis use increased by 1.13 (95% CI 0.46-1.79) per 100 000 pregnancies after legalization. Pregnant people with acute care for cannabis use had greater odds of having received acute care for hyperemesis gravidarum during their pregnancy than those without acute care for cannabis use (30.9% v. 2.5%, adjusted odds ratio [OR] 9.73, 95% CI 8.01-11.82). Pregnancies with acute care for cannabis use had greater odds of newborns being born preterm (16.9% v. 7.2%, adjusted OR 1.93, 95% CI 1.45-2.56) and of requiring care in the neonatal intensive care unit (31.5% v. 13.0%, adjusted OR 1.94 95% CI 1.54-2.44) than those without acute care for cannabis use. INTERPRETATION: The rate of acute care related to cannabis use during pregnancy almost doubled after legalization of nonmedical cannabis, although absolute increases were small. These findings highlight the need to consider interventions to reduce cannabis use during pregnancy in jurisdictions pursuing legalization.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 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".