Association between gestational diabetes mellitus and depression in parents: a retrospective cohort study
Bibliographic record
Abstract
PURPOSE: The aim of this study was to examine the association between gestational diabetes mellitus (GDM) and depression incidence in mothers and fathers during prenatal and postnatal periods. PATIENTS AND METHODS: Matched pairs (GDM vs no GDM) of randomly selected mothers with singleton live births (matched by age group, delivery year, and health region) and their partners (Quebec, Canada; cohort inception 1990-2007) were assessed for a composite outcome of depression/self-harm/suicide using a health administrative database. We examined the association of GDM and the composite outcome in the following three nonoverlapping periods: 1) 24 weeks gestation up to delivery; 2) delivery up to 1 year postpartum; and 3) 1 year postpartum to study end (March 31, 2012). We used stratified Cox proportional regression hazards models, with three models in mothers and three models in fathers, corresponding to each of the time periods of interest. RESULTS: In the 58,400 mothers, women with GDM had a nearly twofold greater risk (adjusted HR: 1.82, 95% CI 1.28, 2.59) of being diagnosed with depression compared to those without GDM during the prenatal period. In the first year postpartum, there was no conclusive difference observed between the two groups of mothers (adjusted HR: 1.05, 95% CI 0.84, 1.30). Beyond the first year postpartum, there was an 8% increased risk (adjusted HR: 1.08, 95% CI 1.03, 1.14) of depression in women with a history GDM compared to those without. A total of 63,384 fathers were included in our analyses, and no association between GDM in one's partner and depression was found during any of the three time periods evaluated. CONCLUSION: GDM is associated with an increased risk of depression in women particularly during pregnancy highlighting the need to screen for depression and provide supportive interventions during this period.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".