A Potential Role for Insulin Treatment During Pregnancy in Reducing Postpartum Psychological Distress in Maternal Obesity: An Administrative Population Health Study
Bibliographic record
Abstract
Abstract Background: Obesity in pregnancy carries significant risks on mother and child. Studies have found an association between obesity and increased risk for peripartum depression, which has also been linked to decreased placental lactogen levels. In addition, women with obesity treated for gestational diabetes with insulin were found to have increased levels of placental lactogen. Treatment options exist for perinatal and postpartum depression however, they pose a risk to the developing offspring. Thus, prevention as well as markers for early identification of peripartum depression are needed. Methods: Administrative health data (2002/03-2018/19) housed at the Manitoba Centre for Health Policy were used to identify the association between insulin treatment in pregnancy and the risk of postpartum psychological distress (abbreviated here as PPD). This was effectuated in a cohort of women (age 15+ years) who gave birth (N=250,746) and had no pre-existing mood/anxiety disorders or diabetes (N=222,863 excluded). Women were then divided into two groups: lean (N=17,975) and with obesity (N=9,908), which was identified by a recorded maternal weight of >38 - <65.6 kg and ≥85 - <186 kg (respectively). The risk of PPD within one year after delivery with and without insulin treatment was assessed by Poisson regression analysis. Models were adjusted for maternal age group (at pregnancy start date) and area-level income (at delivery). Results: The unadjusted risk of PPD was higher in the obesity group (8.56%; 95% CI 8.00 - 9.15) than in the lean group (6.93%; 95% CI 6.56 - 7.33). When no insulin treatment was given during pregnancy, mothers with obesity had a significantly higher risk of PPD than the lean group (aRR 1.27; 95% CI 1.17-1.39; p<0.0001). However, when women with obesity and insulin treatment were compared to the lean group with no insulin treatment, no significant difference in the risk of PPD was observed between the groups (aRR 1.30; 95% CI 0.83-2.02; p=0.248). Conclusion: This is the first study to demonstrate a positive association between insulin treatment in pregnancy among women with obesity and reduced PPD rates, suggesting insulin as a preventative measure, and further supporting placental lactogen levels as a potential marker for early identification.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".