Abstract
BACKGROUND: The growing global aging population and the high prevalence of oral diseases among the elderly significantly affect their quality of life. This study aimed to assess the current status of oral health literacy (OHL) among community-dwelling elderly individuals in urban China, analyze its associated factors and theoretical pathways, and provide a scientific basis for targeted oral health interventions. METHODS: Between December 2024 and April 2025, 346 community-dwelling elderly individuals in Shenzhen were recruited via a combined snowball and convenience sampling method. OHL was measured via the simplified Chinese version of the Health Literacy in Dentistry scale (HeLD-14). Multidimensional data were collected through a structured questionnaire and analyzed via descriptive statistics, the Mann‒Whitney U test, Spearman’s correlation, multivariate linear regression, and path analysis based on structural equation modeling. RESULTS: The median HeLD-14 score was 36.6 (P25-P75: 27–47), indicating a moderately low level of OHL. Multiple linear regression identified several significant predictors: education (B = 4.626, P < 0.001), monthly income (B = 2.475, P = 0.001), self-efficacy in oral health behavior (SEOH; B = 0.138, P < 0.001), social support rating scale (SSRS; B = 0.221, P < 0.001), oral health knowledge (B = 0.317, P = 0.002), and oral health attitudes (B = 0.365, P = 0.035), collectively explaining 66.3% of the variance (adjusted R² = 0.663). Path analysis revealed that education (β = 0.379, P < 0.001), SEOH (β = 0.383, P < 0.001), monthly income (β = 0.117, P < 0.001) and social support (β = 0.216, P < 0.001) were directly and positively associated with OHL. Additionally, SEOH acted as a mediator in the associations of oral health knowledge, attitudes, and social support with OHL. CONCLUSION: This is the first study to identify the mediating role of SEOH in relation to OHL among community-dwelling elderly individuals in urban China. OHL was found to be associated with a range of interrelated factors. Based on these associations, interventions could focus on populations with lower education and income, strengthen family and community support, and integrate oral health into chronic disease management at the community level.