Lipid-based atherogenic indices and their relationship with cardiovascular disease risk in an African population of type 2 diabetes mellitus patients

Background Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), driven largely by atherogenic dyslipidaemia. Conventional lipid parameters such as total and low-density lipoprotein cholesterol (LDL-C) inadequately reflect the complex lipid disturbances that characterize T2DM. Composite lipid-based indices offer inexpensive and integrative measures of cardiovascular risk, but their predictive utility in African populations remains poorly characterized. This study investigated the association between multiple atherogenic indices and 10-year estimated CVD risk in Nigerian adults with T2DM. Methods In this analytical cross-sectional study, 197 adults with T2DM aged 40–74 years without established CVD were included in the final analysis from an endocrinology clinic in Makurdi, Nigeria. Sociodemographic, clinical, and fasting lipid data were collected. Ten-year CVD risk was estimated using the World Health Organization (WHO) risk prediction chart for Western sub-Saharan Africa. Several atherogenic indices were derived, and a series of hierarchical multiple regression analyses was used to determine their comparative incremental predictive value beyond traditional risk factors like age, systolic blood pressure, diabetes duration, anti-lipid therapy, and anti-hypertensive therapy. Receiver operating characteristic (ROC) analysis assessed their discriminatory performance for elevated CVD risk (≥ 10%). Results Traditional risk factors accounted for 72.4% of the variance in estimated 10-year CVD risk. Non–high-density lipoprotein cholesterol (non-HDL-C) demonstrated the strongest incremental predictive value, explaining an additional 6.2% of the variance (ΔR² = 0.062, p < 0.001), yielding a final R² of 77.2%. Other cholesterol-based ratios (CRI-II, CRI-I) added minor, significant value, but triglyceride-centric indices like the Atherogenic Index of Plasma (AIP) did not. However, none of the indices alone demonstrated significant discriminative power in ROC analysis. Conclusions In this study population, non-HDL-C significantly enhances the prediction of 10-year CVD risk beyond conventional factors, outperforming other cholesterol-based ratios. Triglyceride-centric indices, including AIP, offered no significant incremental value. Therefore, incorporating this low-cost index into existing risk assessment frameworks could strengthen early identification of high-risk individuals in resource-limited settings.