Prevalence and Associated Factors of Urinary Incontinence among Chinese Adolescents in Henan Province: A Cross-Sectional Survey
Bibliographic record
Abstract
Urinary incontinence is a common but understudied health problem in adolescents. This study aimed to investigate the prevalence of and associated factors for urinary incontinence in high-school-aged Chinese adolescents. A stratified two-stage cluster sampling procedure was adopted, yielding a sampling frame of 15,055 participants from 46 high schools in Henan province, China. Self-reported questionnaires were used to collect data. The urinary incontinence variable was assessed using the International Consultation of Incontinence Questionnaire-Short Form. The prevalence of urinary incontinence was 6.6%, with a female predominance (7.2% versus 6.0% in males; p < 0.05), and it increased with age, from 5.8% at 14-15 years to 12.3% at 19-20 years old (p < 0.001). The most common subtype of urinary incontinence was urgency urinary incontinence (4.4%), followed by stress urinary incontinence (1.7%) and mixed urinary incontinence (0.5%). Female sex, higher grades, more frequent sexual behavior, physical disease, chronic constipation, mental health problems, and residence in nonurban areas were significantly associated with higher odds of having urinary incontinence (p < 0.05). Public health programs, such as health education and school-based screening, should be established for early detection and appropriate management of urinary incontinence. Furthermore, individualized interventions targeting associated factors should be developed through collective efforts by adolescents, families, schools, and policymakers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".