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Objectives: This study aimed to analyze multi-level data on the impact of individual and regional urban environmental factors on adult obesity using representative nationwide data. Methods: The study included 158,203 urban adults who participated in the 2023 Community Health Survey. Multilevel logistic regression analysis was conducted to examine the influence of individual and community-level urban environmental factors on adult obesity. In this research, individuals with a BMI of at least 25 kg/m² were considered obese, in line with the WHO Asia–Pacific classification and the Korean Society for the Study of Obesity’s clinical guidelines. Results: At the individual level, gender, education level, age, residence, subjective health status, chronic diseases, alcohol consumption, walking, and smoking were found to influence obesity. At the regional level, higher park area ratio (OR=0.994, 95% CI: 0.991-0.998) and public transportation use (OR=0.997, 95% CI: 0.996-0.999) were associated with a lower risk of obesity, while higher numbers of bars (OR=1.015, 95% CI: 1.002-1.029) were associated with a higher risk of obesity. Conclusions: Obesity is a multidimensional problem influenced not only by an individual's lifestyle and health, but also by the physical and social environment of the community. This suggests that obesity prevention and management policies should expand beyond individual behavioral modification to a comprehensive approach that includes improving the urban environment and expanding community health infrastructure.