Risk and timing of postpartum depression in parents of twins compared to parents of singletons
Bibliographic record
Abstract
BACKGROUND: Parents of twins appear to be at increased risk of postpartum depression (PPD), yet little is known about the magnitude and timing of onset in the postpartum period compared to singleton parents. METHODS: We conducted a cohort study using the Danish nationwide health registers. We defined a study population of parents that is, mothers and fathers of all twin and singleton livebirths between 1997 and 2019. Postpartum depression was defined as incident depression diagnosis or a redeemed antidepressant prescription from childbirth through 365 days postpartum. We performed a parametric time-to-event analysis based on Poisson regression. The time scale was time since birth, modeled using restricted cubic splines. From this we estimated the hazard ratio (HR) representing the momentary risk, and the cumulative risk ratio (RR) over the first year postpartum, in twin compared to singleton parents. RESULTS: The study population was based on 27,095 twin and 1,350,046 singleton births. In adjusted analyses, the HR of twins compared to singletons was highest around 2 months postpartum (HR 1.28, 95% CI 1.10-1.49) for mothers, and around 6 months (1.20, 95% CI 1.02-1.42) for fathers. The 6 months adjusted cumulative RR of PPD in twins compared to singletons was 1.24 (95% CI 1.10-1.40) for mothers and 1.11 (95% CI 0.95-1.30) for fathers. CONCLUSIONS: Twin mothers had increased risk of PPD compared to singleton mothers, which was driven by an immediate increase after childbirth. The risk among twin fathers was not increased immediately after childbirth, but we found slightly elevated risk around 6 months postpartum. This could suggest diverse patterns of PPD symptomatology in twin parents compared to singleton parents and between mothers and fathers. Our findings underline parents of twins as a potentially vulnerable group to PPD and emphasize the need for increased awareness of their mental health.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".