<![CDATA[Background: The world, including Thailand, has become an aged society where maintaining physical function is essential for older adults to live independently. Objectives: This study aimed to explore the factors associated with physical function and analyze the structural model of physical function in Thai older adults in urban areas. Methods: The structural equation model was developed based on social cognitive theory and a review of relevant literature. The study was conducted between 2020 and 2024. A multistage random sampling method was used for sample selection. The study included 302 older adults who met the inclusion criteria. The instruments used were 1) a demographic questionnaire; 2) the Physical Activity Scale for Elderly (PASE); 3) the Physical functions (Physical Performance Test; PPT and hand grip strength); 4) the Self-Efficacy for Physical Activity Scale (SEPAS); 5) the Outcome Expectations for Physical Activity Scale (OEPAS); 6) ahealth literacy questionnaire; 7) the Thai version of the Mini-Mental State Evaluation (MMSE-Thai 2002); and 8) the Social Support Questionnaire (SSQ). Data were analyzed using descriptive statistics, multivariate multiple regression analysis (MMRA), and structural equation modeling (SEM). Results: Most of the sample (81.5%) were female, and 46.69% were married. Using MMRA, the overall results showed that age and self-efficacy for physical activity predicted both physical activity and physical function. For individual indicators of physical activity, R² ranged from 5.8% (leisure-time) to 12.0% (work-related); for physical function indicators, R² ranged from 7.1% (handgrip) to 13.5% (physical performance). Cognitive ability was significantly associated with physical function (β = 0.15, p < 0.05 for handgrip), whereas its association with physical performance was statistically significant but of negligible practical magnitude (β = 0.03, p = 0.044). In MMRA, age was a significant negative predictor of physical activity across all categories, whereas self-efficacy was a positive predictor of leisure-time activity, not household or work-related activities. In SEM, health literacy showed a significant direct path to physical activity, and physical activity mediated the health literacy–physical function relationship. Conclusion: The findings indicate that health literacy, age, and self-efficacy for physical activity are found related to physical activity and physical function. These factors may inform nursing intervention design. But given the limited explanatory power of the current model, caution should be exercised when applying these findings in clinical practice.]]>
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