Preconception mental health and the relationship between antenatal depression or anxiety and gestational diabetes mellitus: a population-based cohort study
Bibliographic record
Abstract
Abstract Background Antenatal depression and anxiety are highly prevalent conditions that have been associated with increased risk for myriad adverse outcomes. Current literature exploring the connection between antenatal mental health and gestational diabetes mellitus (GDM) is limited, presenting conflicting evidence. We sought to evaluate the association between antenatal depression/anxiety (DEP-ANX) and GDM using population-based, administrative data, accounting for aspects of preconception mental health. Methods In this population-based retrospective cohort study, we included all singleton births in British Columbia, Canada from April 1, 2000, to December 31, 2014. We identified instances of DEP-ANX from outpatient and inpatient records that included relevant diagnostic codes and stratified our cohort by preconception DEP-ANX persistence. Logistic regression models were run to estimate odds of GDM given antenatal DEP-ANX. Models were adjusted for the birthing person’s socio-demographics and pregnancy characteristics. Using an expanded cohort, we ran conditional logistic regression models that matched birthing people to themselves (in a subsequent pregnancy) based on discordance of exposure and outcome. Results Out of the 228,144 births included in this study, 43,664 (19.1%) were to birthing people with antenatal health service use for DEP-ANX. There were 4,180 (9.6%) cases of GDM among those antenatal exposure to DEP-ANX compared to 15,102 (8.2%) among those without exposure (SMD 0.049). We observed an unadjusted odds ratio (OR) of 1.19 (95% CI: 1.15 – 1.23) and fully adjusted OR of 1.15 (95% CI: 1.11 – 1.19) overall. Apparent risk for GDM given antenatal DEP-ANX was highest among the no DEP-ANX history stratum, with a fully adjusted OR of 1.24 (95% CI: 1.15 – 1.34). Associations estimated by matched sibling analysis were non-significant (fully adjusted OR 1.19 [95% CI: 0.86 – 1.63]). Conclusions Results from this population-based study suggest an association between antenatal DEP-ANX and GDM that varied based on mental health history. Our analysis could suggest that incident cases of DEP-ANX within pregnancy are more closely associated with GDM compared to recurring or chronic cases.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".