Objective: Evidence regarding the association between the total cholesterol, high-density lipoprotein, and glucose (CHG) index and diabetic retinopathy (DR) remains limited. This study aimed to explore the relationship between CHG and the prevalence of DR and evaluate its discriminative ability for DR. Methods: This cross-sectional study analyzed data from 1,909 individuals with diabetes mellitus (DM), aged 45–90 years, whose information was collected between August and December 2011. To determine the association between CHG and DR, binary logistic regression models were employed. The discriminative ability of CHG for DR was assessed using receiver operating characteristic (ROC) analysis. Additionally, a series of sensitivity analyses and subgroup analyses were conducted. Results: After multivariable adjustment, binary logistic regression analysis showed that each 0.1−unit increase in CHG was associated with a 14.2% higher prevalence of DR (OR = 1.142; 95% CI: 1.081–1.206). Additionally, CHG demonstrated the highest area under the curve (AUC) for discriminating DR (0.6673, 95% CI: 0.6287–0.7059), outperforming triglyceride-glucose body mass index (TyG-BMI, 0.4958, 95% CI: 0.4548–0.5368), triglyceride to high-density lipoprotein cholesterol ratio (THR, 0.5118, 95% CI: 0.4704–0.5532), and triglyceride-glucose index (TyG, 0.5720, 95% CI: 0.5314–0.6125). Sensitivity analysis and subgroup analyses further confirmed the reliability of these results. Conclusion: This study demonstrates that elevated CHG is independently and positively associated with DR in adults with DM. Moreover, CHG shows a certain discriminative ability for DR and may have potential utility in DR assessment.

Objective: Research on the relationship between Total Cholesterol, High-Density Lipoprotein, and Glucose (CHG) index and diabetes mellitus (DM) risk remains limited. This study aims to investigate the association between CHG and DM incidence. Methods: This retrospective cohort study included 8,844 participants who underwent comprehensive health examinations at Shenzhen Kuichong People’s Hospital between 2018 and 2023. The maximum individual follow-up duration reached 5 years, with a median (interquartile range) follow-up period of 2.72 (2.58–4.78) years. Cox proportional hazards regression models were used to evaluate the association between CHG and DM risk. ROC analysis was conducted to evaluate the predictive capability of CHG for DM. Finally, subgroup analyses and sensitivity analyses were performed to further verify the stability of these findings. Results: After multivariate adjustment, the CHG index was independently associated with increased DM risk, with an HR of 1.150 (95% CI: 1.098–1.204) per 0.1 unit increase in CHG. Furthermore, ROC curve analysis demonstrated that CHG had the highest AUC (0.7377) for predicting DM risk, compared to TC (0.5375), HDL-c (0.6105), and FPG (0.6761). The stability of these results was further validated through sensitivity and subgroup analyses. Conclusion: This study found an independent positive relationship between CHG and DM risk. Additionally, CHG demonstrates a certain predictive value for DM risk. This helps clinicians identify high-risk individuals for DM early and provides a new perspective for optimizing clinical prevention and management of DM.

Objective: Currently, there is limited research on the relationship between the atherogenic index of plasma (AIP) and the risk of prediabetes (pre-DM). This study aims to explore the potential link between AIP and the risk of progression from normoglycemia to pre-DM.Methods: In this retrospective cohort analysis, a total of 8,295 individuals receiving routine medical examinations at Kuichong People’s Hospital in Shenzhen between January 2018 and December 2023 were enrolled. The Cox proportional hazards regression model assessed the association between AIP and the risk of progression from normoglycemia to pre-DM, with restricted cubic splines functions used to assess non-linear relationships. Additionally, a competing risk Cox model was used, treating the progression from normoglycemia to diabetes (DM) as a competing event for pre-DM. Finally, the subgroup and sensitivity analyses confirmed the robustness of the findings.Results: After multivariable adjustment, each 0.1-unit increase in AIP was associated with an 11.5% increase in the risk of progression from normoglycemia to pre-DM [hazard ratio (HR) = 1.115; 95% confidence interval (CI): 1.065–1.167]. The competing risk Cox model showed that the sub-distribution hazard ratio for the association between AIP and the risk of pre-DM was 1.09 (95% CI: 1.04–1.14). Additionally, a non-linear association was observed in men, with an inflection point at 0.513. Below this threshold, each 0.1-unit increase in AIP was associated with an HR of 1.204 (95% CI: 1.098–1.321). In women, the relationship was linear.Conclusion: This study demonstrated that elevated AIP was positively associated with the risk of progression from normoglycemia to pre-DM, with a significant sex difference in this relationship. This provides a reference for individualized risk stratification and management strategies for different sex populations and offers new perspectives for optimizing strategies to prevent pre-DM and DM.

Objective: Research on the association between TyG-GGT index and diabetes mellitus (DM) risk remains scarce. This study aimed to investigate the relationship between TyG-GGT and DM incidence. Methods: This retrospective cohort investigation enrolled 8,678 participants who underwent comprehensive health screenings at Kuichong People’s Hospital in Shenzhen from 2018 through 2023. Cox proportional hazards regression models were employed to assess the association between TyG-GGT and DM risk, and Cox proportional hazards regression model with restricted cubic spline functions was used to evaluate non-linear relationships. Subgroup analyses and sensitivity analyses further verified the stability of these findings. Finally, receiver operating characteristic (ROC) curve methodology and time-dependent ROC analysis were performed to determine the predictive capacity of TyG-GGT for incident DM within a 5-year period. Results: Following multivariable adjustments, higher TyG-GGT levels were found to be associated with elevated DM risk, demonstrating an HR of 1.116 (95% CI: 1.041-1.196) per 50-unit increase in TyG-GGT. Additionally, a non-linear association between them was observed, exhibiting a threshold value at 380. When below this inflection point, the HR per 50-unit increase in TyG-GGT was 1.723 (95% CI: 1.500-1.979), while above this value the association was not statistically significant. Additionally, in predicting DM risk, TyG-GGT had the highest AUC value (0.732), while the AUC values of TG (0.635), GGT (0.649), FPG (0.660), and TyG (0.675) were all lower than this value. Time-dependent ROC analysis revealed that the AUC values of TyG-GGT remained stable between 0.7292-0.7338 over a prediction horizon of 1.0 to 5.0 years. The stability of these results was further corroborated via sensitivity analysis. Conclusion: This study found that TyG-GGT demonstrated an independent positive association and non-linear relationship with DM risk, with an inflection point at 380. TyG-GGT below 380 was associated with higher observed DM risk. Additionally, TyG-GGT exhibits discriminatory performance for DM risk assessment and may serve as a clinically useful predictor, thereby aiding clinicians in early identification of high-risk individuals and providing a novel perspective for optimizing clinical prevention and management of DM.