Cholesterol, high-density lipoprotein, and glucose index versus triglyceride-glucose index in predicting cardiovascular disease risk: a cohort study
- PMID: 40065297
- PMCID: PMC11895360
- DOI: 10.1186/s12933-025-02675-y
Cholesterol, high-density lipoprotein, and glucose index versus triglyceride-glucose index in predicting cardiovascular disease risk: a cohort study
Abstract
Background: Cardiovascular disease (CVD) represents a significant global health challenge, characterized by high incidence rates and substantial morbidity and mortality. A newer index, the Cholesterol, High-Density Lipoprotein, and Glucose (CHG) index, has been proposed as a potential diagnostic tool for metabolic disorders but has not been investigated for its ability to predict CVD risk. This study aims to evaluate the predictive efficacy of the CHG index in comparison to the well-established Triglyceride-Glucose (TyG) index.
Methods: In this cohort study, 6249 adults aged 45 and older were recruited from the CHARLS database, with data collected from 2011 to 2020. CVD events were tracked over a nine-year follow-up. The TyG and CHG indices were calculated, and their relationships with CVD risk were assessed using univariate and multivariate Cox regression models. Additionally, restricted cubic spline (RCS) analysis was performed to further explore these associations. Receiver operating characteristic (ROC) analysis was conducted to compare the predictive performance of both indices, and subgroup analysis evaluated their applicability in different populations.
Results: Among the 6249 participants, 1667 (26.68%) developed CVD during the nine-year follow-up. In unadjusted Cox regression models, the TyG index had a hazard ratio (HR) of 1.18 (95% confidence interval CI 1.10-1.27, p < 0.001), while the CHG index showed a higher HR of 1.35 (95% CI 1.21-1.51, p < 0.001). In the adjusted models, the relationship still persisted. The RCS models showed that the TyG index exhibited a non-linear relationship with the risk of CVD, while the CHG index demonstrated a positive linear correlation. ROC curve analysis revealed comparable predictive performance for both indices. The subgroup analysis indicated that there was no interaction between the subgroups and the both indices (p for interaction > 0.05).
Conclusions: An elevated CHG index is significantly correlated with an increased risk of CVD, demonstrating a linear relationship. Furthermore, it exhibits predictive capabilities comparable to those of the TyG index in assessing CVD risk.
Trial registration: Not applicable.
Keywords: Cardiovascular disease; Cholesterol, high-density lipoprotein, glucose index; Risk assessment; Triglyceride–glucose index.
© 2025. The Author(s).
Conflict of interest statement
Declarations. Ethics approval and consent to participate: The CHARLS study was conducted in line with the principles stated in the Declaration of Helsinki and received approval from the Institutional Review Board of Peking University (IRB00001052-11015). Prior to their involvement in the CHARLS study, all participants gave their written informed consent. The research adhered to the STROBE guidelines for reporting observational studies in epidemiology. Competing interests: The authors declare no competing interests.
Figures
References
-
- Li Y, Cao GY, Jing WZ, Liu J, Liu M. Global trends and regional differences in incidence and mortality of cardiovascular disease, 1990–2019: findings from 2019 global burden of disease study. Eur J Prev Cardiol. 2023;30:276–86. - PubMed
-
- Center For Cardiovascular Diseases The Writing Committee Of The Report On, Cardiovascular H. Diseases in China N. Report on cardiovascular health and diseases in China 2023: an updated summary. Biomed Environ Sci. 2024;37:949–92. - PubMed
-
- Teo KK, Rafiq T. Cardiovascular risk factors and prevention: a perspective from developing countries. Can J Cardiol. 2021;37:733–43. - PubMed
-
- Artola Arita V, Beigrezaei S, Franco OH. Risk factors for cardiovascular disease: the known unknown. Eur J Prev Cardiol. 2024;31:e106–7. - PubMed
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Medical
