Comprehensive Association of C-reactive Protein-Triglyceride Glucose Index with 14 New-Onset Chronic Diseases: Evidence from the China Health and Retirement Longitudinal Study

Background The rising burden of multimorbidity in aging populations underscores the need for efficient screening tools. While the Triglyceride-Glucose (TyG) index and Cardiometabolic Index (CMI) are established markers for metabolic risk, they fail to capture chronic low-grade inflammation, a pivotal pathological driver. We aimed to evaluate the C-reactive Protein-Triglyceride Glucose Index (CTI)—a novel composite marker integrating inflammation and metabolic status—and assess its prospective association with 14 new-onset chronic diseases. Methods This prospective cohort study utilized data from the China Health and Retirement Longitudinal Study (CHARLS, 2011–2020). A total of 9,194 participants aged ≥ 45 years with complete baseline biomarker data were included. The CTI was calculated as 0.412 × ln(CRP [mg/L]) + ln(TG [mg/dL] × FPG [mg/dL]) / 2. We employed multivariable Cox proportional hazards models and restricted cubic splines (RCS) to estimate hazard ratios (HRs) and dose-response relationships for 14 incident diseases. Robustness was verified via sensitivity analyses (2-year lag) and subgroup stratifications. Results During the 9-year follow-up, elevated baseline CTI was independently associated with an increased risk of diabetes (HR 1.86, 95% CI 1.67–2.06), stroke (HR 1.42, 95% CI 1.23–1.64), dyslipidemia (HR 1.36, 95% CI 1.25–1.48), and liver disease (HR 1.16, 95% CI 1.01–1.33) after full adjustment. Notably, CTI demonstrated superior predictive value for stroke compared to traditional metabolic indices. These associations remained robust in lag analyses. Subgroup analyses revealed that the predictive value was more pronounced in individuals aged < 60 years and females. Crucially, CTI showed a stronger association with stroke risk in non-obese participants (BMI < 24 kg/m²; HR 1.59) compared to the obese population (HR 1.35). No significant associations were found for non-metabolic conditions (e.g., cancer, arthritis), indicating biological specificity. Conclusion The CTI serves as a robust and accessible biomarker capturing the dual burden of immunometabolic dysregulation. It effectively predicts risks for diabetes, dyslipidemia, liver disease, and particularly stroke . Our findings highlight the utility of CTI in identifying "hidden" cardiovascular risks in non-obese individuals, supporting its incorporation into routine health screenings for older adults.