1935-LB: The Risk of Postpartum Depressive Symptoms in Immigrant Women with Recent Gestational Diabetes Mellitus
Bibliographic record
Abstract
Introduction and Objective: Postpartum depressive (PPD) symptoms are more common in patients with gestational diabetes mellitus (GDM), and immigrants may be particularly vulnerable due to socioeconomic stressors, cultural barriers, and limited healthcare access. However, the relationship between immigration status and PPD symptoms in this population remains unclear. This study examined the association between immigration status and PPD symptoms in patients with recent GDM, evaluating the influence of time since immigration and sociodemographic factors. Methods: This cross-sectional study analyzed baseline data from 327 patients with recent GDM who participated in a postpartum diabetes prevention trial in Toronto, Canada. We used multivariable logistic regression adjusting for sociodemographic and clinical factors to evaluate the association between self-reported immigration status (Canadian-born vs. immigrant), overall and by time since immigration (<10 years vs. ≥10 years), and PPD symptoms based on a score of ≥10 on the Edinburgh Postnatal Depression Scale. Results: The prevalence of PPD symptoms was 25.6% in immigrant patients with GDM compared to 18.2% in Canadian-born patients with GDM (adjusted odds ratio, AOR: 1.31, 95% confidence interval, CI 0.72,2.40), with no significant effect of time since immigration. In the subgroup of immigrants, the prevalence of PPD symptoms was 52.8% with a household income below C$60,000, which was significantly higher than those with an income over C$100,000 (prevalence 21.8%, AOR: 3.31, 95% CI 1.24,8.83). Conclusion: Postpartum depressive symptoms are common among immigrant patients with recent GDM, particularly among those with a low household income. These findings highlight the need to prioritize PPD screening and culturally tailored interventions that address socioeconomic barriers, as mental health disparities may affect engagement in postpartum diabetes prevention and long-term metabolic health. Disclosure N. Ahimsadasan: None. L. Lipscombe: None. W. Wu: None. I. Rahman: None.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".