Prevalence and Associated Factors of Fecal Incontinence and Double Incontinence among Rural Elderly in North China
Bibliographic record
Abstract
Fecal and double incontinence are known to be more prevalent among the rural elderly. Yet, there have been few studies on their epidemic condition among Chinese rural elders. This study estimated the prevalence and correlates of fecal and double incontinence in rural elderly aged 65 years and over in North China. A multisite cross-sectional survey was conducted in 10 villages, yielding a sampling frame of 1250 residents. Fecal and urinary incontinence assessments were based on the self-reported bowel health questionnaire and the International Consultation on Incontinence Questionnaire-Short Form, respectively. The concomitant presence of fecal and urinary incontinence in the same subject was defined as double incontinence. The prevalence of fecal and double incontinence was 12.3% and 9.3%, respectively. Factors associated with fecal incontinence included urinary incontinence, lack of social interaction, traumatic brain injury, cerebrovascular disease, and poverty. Physical activities of daily living dependence, traumatic brain injury, lack of social interaction, and poor sleep quality were associated with higher odds of having double incontinence, whereas tea consumption was correlated with lower odds. Individualized intervention programs should be developed targeting associated factors and high-risk populations. These intervention programs should be integrated into existing public health services for the rural elderly to facilitate appropriate prevention and management of incontinence.
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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 | 0.000 | 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 | 0.000 | 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".