456Mode of delivery and urinary incontinence in middle age: longitudinal analysis of the SWAN cohort
Bibliographic record
Abstract
Abstract Background Urinary Incontinence (UI) is the involuntary loss of urine. Multiparity increases risk of UI, but this risk differs by mode of delivery. This study evaluated the association of mode of delivery (vaginal/cesarean) and prevalence of urge, stress, and mixed UI in middle age. Methods Using longitudinal data (baseline through visit ten collected annually) from the SWAN (Study of Women Across the Nation) cohort, the association between mode of delivery and UI subtypes was examined. We employed conditional mixed-effect logistic regression modelling, adjusting for baseline age, race, parity, smoking, diabetes, marital status, income, and body mass index. Menopausal status, hormone-replacement therapy use, and hysterectomy status were considered as time-varying and subject-specific covariates. A composite variable of mode of delivery was created to account for total pregnancies per participant, and women who experienced only vaginal (n = 2110) or caesarean (n = 379) deliveries were included. Results For women delivering vaginally vs cesarean, the baseline mean age (years) was 46.0(95%CI:45.9-46.1) and 45.6(95%CI:45.3-45.9), and proportion of perimenopausal women was 46.7%(95%CI:44.6-48.9) and 41.6%(95%CI:36.8-46.7). Women who deliver vaginally vs cesarean had an odds ratio (95% confidence interval) of 0.93(0.61-1.41), 1.46(1.04-2.05), and 1.58(1.21-2.05) for urge, stress, and mixed UI respectively. Conclusions The present study found vaginal deliveries increased odds of stress and mixed UI in middle age, but not urge UI. Key Messages Women have the most contact with health-care systems right after delivery; this is the optimal timing for increased awareness of UI in middle age and provision of interventions, including pelvic floor therapy, for women delivering vaginally.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".