Epidemiology of Postpartum Depressive Symptoms among Canadian Women: Regional and National Results from a Cross-Sectional Survey
Bibliographic record
Abstract
OBJECTIVES: To describe national and regional prevalence rates for significant depressive symptoms in women after 12 weeks during the postpartum period, and to identify predictors of postpartum depressive symptoms during this later time period. METHODS: Data from the Maternity Experiences Survey of the Canadian Perinatal Surveillance System were analyzed. Participants completed a computer-assisted telephone interview between 5 and 14 months during the postpartum period (n = 6421). Depressive symptomatology was measured using the Edinburgh Postnatal Depression Scale (EPDS ≥ 13). Proportions and odds ratios with 95% confidence intervals were calculated using bootstrap methods to account for sample design and weighting adjustments. RESULTS: About 8% of Canadian women exhibited depressive symptoms past 12 weeks during the postpartum period. Prevalence rates varied between regions. In multivariable analysis, previous history of depression (OR 1.87; 95% CI 1.43 to 2.45, P < 0.001), low household income (OR 1.64; 95% CI 1.27 to 2.11, P < 0.001), low postpartum social support (OR 3.95; 95% CI 2.77 to 5.62, P < 0.001), stressful life events (OR 2.43; 95% CI 1.88 to 3.15, P < 0.001), interpersonal violence (OR 1.40; 95% CI 1.04 to 1.87, P = 0.02), and poor self-perceived maternal health (OR 4.48; 95% CI 3.15 to 6.38, P < 0.001) were independently associated with postpartum depressive symptoms. Regional differences in correlates of postpartum depressive symptoms were found. CONCLUSIONS: The finding that depression rates are elevated throughout the first postpartum year is important because of the known negative impact of postpartum depression (PPD). Targeted public health interventions may be needed to reduce the prevalence of PPD and its associated impact.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".