Prevalence, Incidence, and Persistence of Postpartum Depression, Anxiety, and Comorbidity among Chinese Immigrant and Nonimmigrant Women: A Longitudinal Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Our objectives were to examine the prevalence and incidence of postpartum depressive, anxiety, and comorbid symptoms over the first postpartum year; the persistence of these symptoms; and the prevalence stratified by immigration status. METHOD: We conducted a longitudinal cohort study in Ontario, Canada. Participants were 571 Chinese recent immigrant, nonrecent immigrant, and Canadian-born women with live births in 2011 to 2014. Participants were assessed at 4, 12, and 52 weeks postpartum for the presence of possible and high depressive symptomatology (Edinburgh Postnatal Depression Scale [EPDS] >9 and >12, respectively), anxiety symptomatology (State-Trait Anxiety Inventory [STAI] >40), and comorbid symptomatology (EPDS >9 and STAI >40). Prevalence and incidence with 95% confidence intervals were calculated. RESULTS: Prevalence rates were highest at 4 weeks and decreased across time, with possible depressive symptomatology most prevalent at most time points. Incidence rates at 12 and 52 weeks were generally similar. Of those with possible symptomatology at 4 weeks, 42.0% or less continued to have symptomatology at 12 weeks and 17.4% or less at 52 weeks. There were no differences in prevalence of any type of symptomatology between immigrant and Canadian-born Chinese women at 4 weeks, but at 12 and 52 weeks, most types of symptomatology were more common among recent and nonrecent immigrants. CONCLUSION: Our findings suggest that Chinese immigrant women are a high-risk group for postpartum depressive and anxiety symptomatology. Future research should identify cultural and psychosocial factors associated with immigration that could be addressed in the system of care for postpartum immigrant women.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".