This study investigates the relationship between diabetes mellitus, systemic inflammation, and overactive bladder (OAB) using data from six cycles of the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. The study included 23,863 participants, with a median age of 49.7 years. Key findings include: 1. **Association Between Diabetes and OAB**: Participants with diabetes had a 77% higher prevalence of OAB compared to those without diabetes. 2. **Diabetes-Related Markers and OAB**: Higher levels of diabetes-related markers (glycohemoglobin, fasting glucose, and insulin) were associated with increased odds of OAB, with a monotonic increase in odds as the quartiles of these markers increased. 3. **Inflammatory Markers and OAB**: White blood cells and neutrophils were significantly correlated with OAB, with white blood cells mediating the association between diabetes-related markers and OAB. 4. **Machine Learning Model**: The XGBoost model identified glycohemoglobin as the most important indicator for predicting OAB. 5. **Subgroup Analysis**: The association between diabetes and OAB was more pronounced in younger participants and those with higher education levels. The study concludes that diabetes mellitus and diabetes-related markers are significantly associated with OAB, and systemic inflammation plays a crucial mediating role in this relationship. These findings provide valuable insights for further research and clinical management of OAB in diabetic patients.This study investigates the relationship between diabetes mellitus, systemic inflammation, and overactive bladder (OAB) using data from six cycles of the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. The study included 23,863 participants, with a median age of 49.7 years. Key findings include: 1. **Association Between Diabetes and OAB**: Participants with diabetes had a 77% higher prevalence of OAB compared to those without diabetes. 2. **Diabetes-Related Markers and OAB**: Higher levels of diabetes-related markers (glycohemoglobin, fasting glucose, and insulin) were associated with increased odds of OAB, with a monotonic increase in odds as the quartiles of these markers increased. 3. **Inflammatory Markers and OAB**: White blood cells and neutrophils were significantly correlated with OAB, with white blood cells mediating the association between diabetes-related markers and OAB. 4. **Machine Learning Model**: The XGBoost model identified glycohemoglobin as the most important indicator for predicting OAB. 5. **Subgroup Analysis**: The association between diabetes and OAB was more pronounced in younger participants and those with higher education levels. The study concludes that diabetes mellitus and diabetes-related markers are significantly associated with OAB, and systemic inflammation plays a crucial mediating role in this relationship. These findings provide valuable insights for further research and clinical management of OAB in diabetic patients.