Amirhossein Yadegar, Fatemeh Mohammadi, Shima Loni, Sepideh Yadegar, Ali Mohammadi Naeini, Amirhossein Tayebi, Mahsa Abbaszadeh, Soghra Rabizadeh, Alireza Esteghamati, Manouchehr Nakhjavani, Sahar Karimpour Reyhan
The observed nonlinear associations between nontraditional lipid indices and poor glycemic control highlight the close interplay between atherogenic dyslipidemia and glycemic dysregulation. As these indices are derived from routinely measured lipid parameters, they can act as practical complementary tools for identifying individuals at higher risk of poor glycemic control, especially in settings where HbA1c measurement is limited or not cost-effective. Further research is required to confirm these findings and determine causal relationships.
BACKGROUND: This study investigated the association between poor glycemic control, defined as HbA1c ≥ 7.5%, and multiple nontraditional lipid indices, including AC, AIP, LCI, TG/HDL-C ratio, CRI-I, and CRI-II, and to evaluate their diagnostic performance for identifying poor glycemic control.
METHODS: In this cross-sectional study, 6424 individuals diagnosed with Type 2 diabetes (T2D) who visited a diabetes clinic from 2014 to 2024 were included. The relationships between nontraditional lipid indices and poor glycemic control were evaluated using RCS models and multivariable logistic regression. Diagnostic performance was examined using ROC analysis.
RESULTS: Nontraditional lipid indices were significantly elevated in patients with poor glycemic control (p < 0.001). In RCS models, significant nonlinear associations were observed between all lipid indices and poor glycemic control, with progressively higher odds of HbA1c ≥ 7.5% as index values increased (p for nonlinearity < 0.05). When analyzed as continuous variables, all indices were positively associated with poor glycemic control, with AIP showing the strongest association (OR = 2.25 [1.84-2.76]). Individuals in higher quartiles of each lipid index had significantly greater odds of poor glycemic control compared with those in the first quartile. All indices showed modest discriminatory ability (AUCs ≥ 0.684) for poor glycemic control, with AIP demonstrating the highest AUC (0.687 [0.657-0.718]). However, no statistically significant differences in AUC were detected among the indices.
CONCLUSIONS: The observed nonlinear associations between nontraditional lipid indices and poor glycemic control highlight the close interplay between atherogenic dyslipidemia and glycemic dysregulation. As these indices are derived from routinely measured lipid parameters, they can act as practical complementary tools for identifying individuals at higher risk of poor glycemic control, especially in settings where HbA1c measurement is limited or not cost-effective. Further research is required to confirm these findings and determine causal relationships.