Prevalence and Risk Factors of Urinary Incontinence Among Elderly Adults in Rural China
Notice bibliographique
Résumé
PURPOSE: The purpose of this study was to explore the prevalence of urinary incontinence (UI) and several subtypes: (stress, urge, and mixed UI) and the influence of multiple factors on the likelihood of UI. DESIGN: Epidemiological study based on cross-sectional data collection. SUBJECTS AND SETTING: The sample comprised 1279 inhabitants 65 years and older residing in 10 villages randomly selected from the Shanxi province, located in North China. METHODS: The presence and types of UI were assessed using the International Consultation of Incontinence Questionnaire-Short Form. Sociodemographic parameters were also recorded, along with data on lifestyle, bowel function, and medical conditions. The Activity of Daily Living Scale and Mini-Mental State Examination instruments were used to evaluate physical and cognitive functions, respectively. A multivariate logistic regression model with the backward method was employed to identify factors associated with UI. RESULTS: The prevalence of any UI among the rural Chinese elderly 65 years and older was 46.8%, with a female predominance (56.3% in females vs 35.0% in males). The most common incontinence subtype in women was mixed UI (n = 170, 24.0%), followed by stress UI (n = 131, 18.5%) and urge UI (n = 97, 13.7%). The most prevalent form of UI in males was urge UI (n = 190, 33.2%), followed by stress UI (n = 5, 0.9%) and mixed UI (n = 5, 0.9%). Less than one quarter of respondents (17%, n = 102) of participants with UI had consulted a doctor. Multivariate analysis found that poorer physical function, poor quality of sleep, and fecal incontinence were common factors associated with UI in both women and men. In women, higher body mass index and constipation were also independent correlates, as were poor vision and heart disease in men. Poorer physical function was associated with all UI subtypes. For female stress UI, poorer cognitive status, tea drinking, and hypertension also emerged as independent risk factors. Heart disease was an independent risk factor in both female and male urge UI; as was consumption of a non-plant-based diet for female mixed and urge UI; nonfarmer and traumatic brain injury for female urge UI; and poor vision and fecal incontinence in male urge UI. CONCLUSIONS: Chinese rural citizens showed a high UI prevalence, but only a small proportion had consulted a health care provider. Physical function decline was the most important contributor to UI among participants. Individualized intervention programs targeting modifiable risk factors among high-risk populations should be developed.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».