Longitudinal analysis of the association between parity, mode of delivery and urinary incontinence in midlife using the SWAN cohort data
Bibliographic record
Abstract
Parity increases the risk of urinary incontinence, but this risk differs by mode of delivery. This study evaluated the association between mode of delivery and prevalence of urge, stress, and mixed urinary incontinence in middle age. The association between mode of delivery and urinary incontinence subtypes was examined using data from the SWAN cohort. Women who experienced vaginal, cesarean, or combination deliveries were compared against nulliparous women. Women who delivered vaginally had a significantly higher prevalence of all subtypes of incontinence compared to women who were nulliparous or delivered via other modes. No significant differences in urinary incontinence were observed when comparing women who birthed vaginally, via cesarean, or combination to nulliparous women. However, in comparison to those who delivered via cesarean, women who delivered vaginally have significantly increased odds of experiencing stress urinary incontinence, and those who delivered via combination have significantly increased odds of experiencing mixed urinary incontinence. Urge urinary incontinence appears to be driven by aging, not childbearing. Compared to cesarean, vaginal deliveries increase the odds of stress and mixed urinary incontinence during middle age. Delivering via a combination of vaginal and cesarean sections increases the odds of mixed urinary incontinence during middle age.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".