Multicenter cohort study reveals: composite inflammatory indexs are associated with increased risk of diabetes in patients with hypertension

Background: Patients with hypertension commonly exhibit a persistent chronic inflammatory state. Accumulating evidence suggests that inflammation can induce insulin resistance, which is a key pathological mechanism in the development of diabetes. However, whether composite inflammatory indices are independently associated with the risk of incident diabetes in hypertensive patients remains insufficiently supported by current evidence. Methods: Multivariable-adjusted Cox proportional hazards regression models were used to assess the associations between composite inflammatory indices and the risk of incident diabetes in patients with hypertension. Kaplan-Meier (KM) curves were generated to visually depict the cumulative incidence of diabetes across different levels of these inflammatory indices. Furthermore, comparative analyses were conducted to identify the most predictive composite inflammatory marker. Results: Cox regression analysis revealed that elevated composite inflammatory indices were significantly associated with an increased risk of incident diabetes in patients with hypertension. KM curves further demonstrated that individuals with higher inflammatory levels exhibited a significantly higher cumulative incidence of diabetes during follow-up compared to those with lower levels. Moreover, comparative analyses among the inflammatory markers identified the inflammatory burden index (IBI) as the most effective predictor of diabetes risk. Conclusion: This study demonstrates that elevated composite inflammatory indices are closely associated with an increased risk of future diabetes in patients with hypertension, with a notable threshold effect. These findings suggest that actively controlling inflammatory levels may help reduce the risk of diabetes in this population. Furthermore, the IBI holds promise as a simple and accessible risk assessment tool for screening and early identification of individuals at high risk for diabetes.