Abstract
BACKGROUND: Visceral obesity contributes to hypertension through pathways of insulin resistance and inflammation. The joint association of C-reactive protein-triglyceride-glucose index (CTI), which integrates these pathways, and anthropometric indices with incident hypertension remains unclear, especially across different baseline blood pressure. METHODS: The data for this study were obtained from the China Health and Retirement Longitudinal Study (CHARLS) across the 2011 to 2020 survey waves. Participants were stratified based on the median values of anthropometric indices and CTI. The associations with incident hypertension risk were evaluated using Kaplan-Meier curves, multivariable Cox regression, and restricted cubic spline (RCS) methods. Predictive performance was assessed by receiver operating characteristic (ROC) curve analysis, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Mediation and interaction analyses were conducted to explore potential mediating effects and the robustness of the findings. RESULTS: Among 4,735 eligible participants, the median age was 56 years, and 46.04% were male. During the 9-year follow-up period, 1,852 participants (39.37%) developed hypertension. Cox regression analysis revealed that Compared with subjects with lower levels of both anthropometric indices and CTI, those with higher levels of both exhibited the highest risk of hypertension. Individuals with both BRI and CTI above the median consistently exhibited the highest risk of hypertension across all subgroups: HR = 1.51, 95% CI: 1.33-1.71 in the total population; HR = 1.58, 95% CI: 1.29-1.93 in the normal BP group; and HR = 1.45, 95% CI: 1.23-1.71 in the elevated BP group. After incorporating anthropometric indices and CTI into the basic model, the predictive performance for hypertension was significantly improved. The integrated model of BRI and CTI demonstrated the best overall predictive performance (AUC = 0.747). Mediation analysis revealed that CTI significantly mediated the association between anthropometric indices and hypertension. CONCLUSION: These anthropometric indices and CTI effectively predicted hypertension risk across populations with different baseline blood pressures, both independently and in combination. Among all evaluations, the combination of BRI and CTI emerged as the optimal approach, most robustly associated with incident hypertension and providing the greatest improvement in risk discrimination and reclassification.