Decomposition Analysis of the Prevalence of Denture Use Between Rural and Urban Older Individuals With Edentulism in China: Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: Edentulism impacts the physical health and quality of life of older individuals. The prevalence, influencing factors, and differences in terms of edentulism in urban and rural areas of China are unclear. OBJECTIVE: This study investigated the denture-wearing conditions and causes affecting older patients with edentulism in urban and rural areas of China and analyzed the differences. METHODS: This cross-sectional study included the data of 5139 older individuals (age>65 years) with edentulism obtained from 23 Chinese provinces in 2018. Participants were divided into urban and rural groups based on their household registration. Factors influencing denture use in both groups were explored using binary logistic regression, while factors influencing differences in denture wearing in both groups were explored using the Fairlie decomposition model. RESULTS: Of the 5139 participants, 67.05% (808/1205) from urban areas and 51.12% (2011/3934) from rural areas wore dentures. In the urban group, participants with a higher level of education (1-6 years: odds ratio [OR] 2.093, 95% CI 1.488-2.945; ≥7 years: OR 2.187, 95% CI 1.565-3.055) or who exercised (OR 2.840, 95% CI 2.016-3.999) preferred wearing dentures, but individuals with BMI<18.5 kg/m2 (OR 0.558, 95% CI 0.408-0.762) or widowed (OR 0.618, 95% CI 0.414-0.921) did not. In the rural group, a higher level of education (1-6 years: OR 1.742, 95% CI 1.429-2.123; ≥7 years: OR 1.498, 95% CI 1.246-1.802), living alone (OR 1.372, 95% CI 1.313-1.663), exercise (OR 1.612, 95% CI 1.340-1.940), high economic status (OR 1.234, 95% CI 1.035-1.472), residence in the eastern area (OR 2.045, 95% CI 1.723-2.427), presence of chronic diseases (1 disease: OR 1.534, 95% CI 1.313-1.793; ≥2 diseases: OR 1.500, 95% CI 1.195-1.882) were positively associated and age≥80 years (OR 0.318, 95% CI 0.247-0.408), BMI<18.5 kg/m2 (OR 0.692, 95% CI 0.590-0.813), and widowed (OR 0.566, 95% CI 0.464-0.690) or other marital status (OR 0.600, 95% CI 0.392-0.918) were negatively associated with denture use. The Fairlie decomposition model revealed that the number of chronic diseases (16.34%), education level (11.94%), region of residence (11.00%), annual income (10.55%), exercise (6.81%), and age (-0.92%) were the main factors responsible for differences between urban and rural edentulism and could explain the difference in the denture-wearing rate (58.48%) between both groups. CONCLUSIONS: Older individuals with edentulism with a higher education level and who exercise are more willing to wear dentures, while those with BMI<18.5 kg/m2 show a decreased willingness to wear dentures in both urban and rural areas in China. Controlling the number of chronic diseases, improving the education level and annual income, cultivating good exercise habits, and bridging the gap between the economic status of the east and west can narrow the differences in denture wearing among urban and rural older individuals with edentulism.
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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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,001 |
| 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 ».