Background
The TyG index is thought to be a trustworthy substitute indicator of insulin resistance. Increasing research evidence shows the correlation between TyG and various cardiovascular and cerebrovascular diseases and adverse prognosis. However, the effect of diabetes on the connection between TyG and hypertension has not been extensively studied. In order to identify high-risk individuals, our research aimed to investigate the potential relationship between the TyG index and the risk of hypertension in middle-aged and elderly Chinese individuals.
Methods
This study analyzed and collected information of the middle-aged and elderly population from the 2015 China Health and Retirement Longitudinal Study (CHARLS) database, and three groups were created based on the tertiles of TyG. First, the clinical characteristics of patients in different groups were analyzed univariately, and logistic regression analysis and RCS model were utilized to further clarify the relationship between the TyG index and hypertension. Finally, subgroup analysis was performed to distinguish the effects of different baseline characteristics on the connection between TyG and hypertension.
Results
9695 patients in all were enrolled, including 4548 males (46.9%) and 5147 females (53.1%). The incidence of hypertension in all patients was 33.7%. As displayed in Table 1, as the TyG index rises, the incidence of Diabetes, Heart disease, and Stroke in patients increased accordingly. Similarly, in terms of laboratory indicators, White blood cell, Platelets, Triglycerides, Uricacid, and Hbg increased with the rises of TyG; while the incidence of lung diseases, BUN, and HDL levels showed a downward trend. The RCS model showed that there was a nonlinear certain correlation between TyG and hypertension (p value < 0.001, nonlinear p = 0.008);Subgroup analysis showed that different baseline characteristics may influence the association between TyG and hypertension risk.
Conclusion
Our study's findings demonstrate a substantial correlation between TyG index and hypertension, showing a positive correlation in both adjusted and unadjusted logistic regression models, which may help identify individuals at risk for hypertension and have great potential through early improvement of blood pressure management. It has great potential to reduce the occurrence related to cardiovascular and cerebrovascular disorders.