Triglyceride to high-density lipoprotein ratio as a predictor for 10-year cardiovascular disease in individuals with diabetes in Thailand.

Background: Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide. The triglyceride to high-density lipoprotein cholesterol (TG/HDL) ratio has emerged as a potential marker for CVD risk. However, its predictive value for high 10-year predicted Cardiovascular (CV) risk remains unclear; This study evaluates the predictive value of the TG/HDL-C ratio for 10-year cardiovascular risk using the Framingham Heart Study (FHS) risk prediction model in individuals with Type 2 Diabetes Mellitus (T2DM).

Methods: A cross-sectional study was conducted on 61,004 adults from 2014,2015, and 2018 aged 30-74 years with T2DM, without a history of CVD. The FHS model was used to estimate 10-year predicted CV risk, and high CVD risk was defined as ≥ 20%. ROC curve analysis was used to determine the optimal TG/HDL cutoff for high 10-year predicted CV risk in the overall population and age-specific subgroups. Logistic regression was performed to find the association between TG/HDL and high 10-year predicted CV risk, adjusting for potential confounders.

Results: The optimal TG/HDL-C cutoff was 2.52 (AUC = 0.618, 95% CI: 0.612-0.624), with 67% sensitivity and 50% specificity. Higher TG/HDL were associated with increased odds of high predicted CVD risk in a dose-dependent manner, with an adjusted odds ratio (AOR) of 5.16 (95% CI: 4.86-5.49) in the highest TG/HDL quartile (> 4.91). Age-stratified analysis identified lower cutoffs for older adults (≥ 60 years: 2.42, AUC = 0.694) than younger individuals (< 60 years: 2.98, AUC = 0.636), indicating stronger predictive performance in older adults.

Conclusions: The TG/HDL ratio is significantly associated with 10-year predicted CVD risk in T2DM with age-specific differences in predictive value. The lower cutoff for older adults (2.42) suggests even modest elevations indicate increased risk. These findings support TG/HDL integration into routine CVD risk assessments and highlight the importance of age-specific cutoffs for improved risk stratification.