Associations of cumulative exposure and dynamic trajectories of the C-reactive protein-triglyceride-glucose index with incident stroke in middle-aged and older Chinese adults: a longitudinal analysis based on CHARLS.

Background: The C-Reactive Protein-Triglyceride-Glucose Index (CTI) has been proposed as a novel biomarker for insulin resistance and inflammation. However, research on the relationship between CTI changes and stroke is limited. This study aims to investigate the association between changes in CTI and stroke risk.

Methods: Participants were drawn from the China Health and Retirement Longitudinal Study (CHARLS). Stroke was defined as self-reported stroke. K-means clustering analysis was used to classify CTI changes, and cumulative CTI (cuCTI) was calculated as follows: (CTI₂₀₁₂ + CTI₂₀₁₅)/2 × time. To assess the association between CTI and stroke risk, Cox regression and restricted cubic spline (RCS) regression models were applied.

Results: A total of 4,364 participants were included in the study, among whom 323 (7.4%) experienced a stroke. The risk of stroke increased with higher levels of cuCTI. In the multivariable-adjusted model, Cox regression analysis showed that, compared with the lowest quartile (Q1), participants in the highest quartile (Q4) had a significantly increased risk of stroke by 103% (HR = 1.90, 95% CI: 1.30-2.78, P < 0.001). Furthermore, stroke risk increased progressively across ascending cuCTI quartiles (P for trend < 0.001). RCS analysis demonstrated a linear association between cuCTI and stroke risk (for nonlinearity, p < 0.001). K-means clustering identified three distinct trajectories of CTI variation. Participants with moderate and elevated CTI levels (HR = 1.53, 95% CI: 1.17-2.00, P = 0.001) and those with high CTI levels showing a slow increasing trend (HR = 1.75, 95% CI: 1.25-2.48, P < 0.001) had a significantly higher risk of stroke.

Conclusion: This study demonstrates that both cuCTI and CTI changes are associated with stroke risk in middle-aged and older adults, particularly for those with consistently high CTI levels, which are linked to a significantly increased stroke risk. Monitoring long-term CTI changes and maintaining relatively low levels may help prevent stroke in this population.