Mental Disorders and Suicide Attempts in the Pregnancy and Postpartum Periods Compared with Non-Pregnancy: A Population-Based Study
Bibliographic record
Abstract
Objective: To compare the rate of mental disorders (i.e., mood and anxiety, substance use, psychotic disorders) and suicide attempts within the same group of women across the pre-pregnancy, pregnancy, and postpartum periods, and between this perinatal cohort and a non-perinatal reference group. Method: Data were from an administrative repository of residents in Manitoba, Canada. The perinatal cohort consisted of women aged 18 to 45 years who experienced >1 live birth pregnancy between 2011 and 2014 ( n = 45,362). Pre-pregnancy, pregnancy, and postpartum periods were defined over consecutive 40-week intervals. The non-perinatal cohort consisted of age-matched women with no pregnancies during the same period ( n = 139,705). A reference 40-week interval was defined from the individual’s birthdate in the year they entered the cohort. Rate ratios of diagnosed mental disorders were adjusted (aRR) for demographic factors, parity, and mental health history. Results: Within the perinatal cohort, pregnancy was associated with a lower rate of diagnosed mood or anxiety disorder, substance use disorder, and suicide attempt relative to pre-pregnancy (aRR range, 0.22-0.82). Pregnancy also had lower rates of all outcomes compared with the postpartum period (aRR, 0.44-0.87). Postpartum had a higher rate of psychotic disorder compared with pre-pregnancy (aRR, 1.61; 95% CI, 1.17-2.21), but a lower rate of mood or anxiety disorder and suicide attempt. Compared with non-perinatal women, pregnancy was associated with lower rates of all outcomes (aRR range, 0.25-0.87). Conclusions: Compared with a non-perinatal period, the rate of a diagnosed mental disorder is lower during pregnancy but begins to rise in the postpartum period, highlighting an important period for early identification and rapid access to intervention.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".