Researchers analyzing data from the China Health and Retirement Longitudinal Study (CHARLS) have identified a significant association between a combined biomarker index and the development of cardiometabolic multimorbidity in middle-aged and older adults. The study, published in Cardiovascular Diabetology, examined the relationship between the combined C-reactive protein–triglyceride glucose index and frailty index (CTI-FI) and the incident onset of multiple cardiometabolic conditions. By integrating measures of inflammatory and metabolic burden with accumulated health deficits, the team sought to determine whether this composite index offers predictive insights beyond individual components.
The research team, led by Yiwen Lu and colleagues, included 5,586 participants who had CTI-FI measurements at Wave 1 (2011–2012) and Wave 3 (2015) of the CHARLS cohort. All participants were free of cardiometabolic multimorbidity through Wave 3, ensuring a clean baseline for assessing incident disease. Follow-up began at Wave 3 and continued through 2020, with a median follow-up period of 5.00 years. During this interval, 494 participants developed cardiometabolic multimorbidity, defined as the coexistence of at least two of three specific conditions: heart disease, stroke, and diabetes.
The CTI-FI was calculated by multiplying the C-reactive protein–triglyceride glucose index (CTI) by the frailty index (FI). This approach aims to summarize both inflammatory–metabolic burden and accumulated health deficits into a single metric. The study also examined time-weighted two-point mean CTI-FI and longitudinal exposure patterns derived using K-means clustering. These methods allowed the researchers to assess not only current levels of the index but also the trajectory of exposure over time, providing a more nuanced view of how changes in CTI-FI relate to disease risk.
Using Cox proportional hazards models and restricted cubic splines, the researchers found that higher CTI-FI levels were associated with a greater hazard of developing cardiometabolic multimorbidity. In fully adjusted models stratified by baseline cardiometabolic disease status, each one-standard-deviation increment in Wave 3 CTI-FI was associated with a hazard ratio of 1.342 (95% CI, 1.246–1.445). For the time-weighted two-point mean CTI-FI, the hazard ratio was 1.370 (95% CI, 1.273–1.476). These results indicate that both current and repeated measurements of the index are linked to increased risk.
When comparing the highest versus lowest quartiles of CTI-FI, the association was even more pronounced. The hazard ratio for the highest quartile compared to the lowest was 3.263 (95% CI, 2.316–4.599) for Wave 3 CTI-FI and 4.217 (95% CI, 2.938–6.053) for the time-weighted mean. Additionally, participants with a high-level longitudinal pattern of CTI-FI had a higher hazard of developing multimorbidity compared to those with a low-level pattern, with a hazard ratio of 2.072 (95% CI, 1.707–2.515).
The study also explored whether CTI-FI provided additional predictive value beyond the individual components. In model-fit comparisons, CTI contributed additional longitudinal information beyond the frailty index alone. However, the gains in discrimination were small, and neither CTI-FI nor its repeated-measurement summaries showed a consistent predictive advantage over corresponding FI-based models. This suggests that while the combined index is associated with disease risk, it may not significantly improve prediction beyond what is already captured by the frailty index alone.
Sensitivity analyses were conducted to address potential biases, including death as a competing event, interval-based outcome ascertainment, extreme exposure values, and selection related to exposure availability. The associations between CTI-FI and incident cardiometabolic multimorbidity remained consistent across these analyses, reinforcing the robustness of the findings. The study also included exploratory comparisons of model fit and predictive performance, including 3- and 5-year prediction measures and bootstrap internal validation, to further assess the utility of the index.
The authors conclude that higher CTI-FI across current and repeated-measurement dimensions is associated with incident cardiometabolic multimorbidity. These findings support the examination of inflammatory–metabolic burden alongside accumulated health deficits in studies of cardiometabolic disease progression. However, the clinical use of CTI-FI requires further validation, particularly given the absence of a consistent predictive advantage over the frailty index alone.
Subject of Research: Association between combined inflammation-frailty index and incident cardiometabolic multimorbidity
Article Title: Associations of the combined C-reactive protein–triglyceride glucose index and frailty index (CTI-FI) with incident cardiometabolic multimorbidity: a prospective cohort study
Article References: Lu, Y., Han, X., Jiang, D., Ma, Z., Feng, J., Zhang, J., Wang, C., Li, J., & Liang, Y. (2026). Associations of the combined C-reactive protein–triglyceride glucose index and frailty index (CTI-FI) with incident cardiometabolic multimorbidity: a prospective cohort study. Cardiovascular Diabetology. https://doi.org/10.1186/s12933-026-03381-z
Image Credits: AI Generated
DOI: 10.1186/s12933-026-03381-z
Keywords: cardiometabolic multimorbidity, frailty index, C-reactive protein, triglyceride glucose index, CHARLS, prospective cohort, inflammation, health deficits, cardiovascular disease, diabetes, stroke, risk prediction
Tags: C-reactive proteincardiometabolic multimorbidityCardiovascular diseaseCHARLSDiabetesfrailty indexhealth deficitsinflammationprospective cohortrisk predictionStroketriglyceride-glucose index
