Background: The objective of the study was to estimate the prevalence of multimorbidity and to analyze the factors related to multimorbidity using multilevel analysis.Methods: The data from the 2017 National Health and Welfare Survey was used. In total, 27,960 families and 65,781 participants were analyzed. Multilevel logistic regression analysis with 2-levels was performed to assess independent risk factors for the multimorbidity.Results: Of 14,353 participants analyzed, 20.4% (95% confidence interval (CI): 20.1, 20.7) of those showed multimorbidity. 59% were females; 74.4% were 56-66 years, 68.7% had primary school level education, and 63.8% were reported being married. Multilevel multiple logistic regression results showed that the prevalence of multimorbidity was higher in females (adjusted OR (AOR): 1.2, 95% CI: 1.1, 1.3), older participants had higher risk of multimorbidity than younger people (p value for trend <0.01), married (AOR: 1.2; 95% CI: 1.0, 1.4), widowed or divorced (AOR: 1.3; 95% CI: 1.1, 1.5).Conclusions: A high prevalence of multimorbidity in older patients was found. Tailored disease prevention programs and health care provider are needed to design and service for multimorbidity patients.