Abstract
Objectives: The objective of this study was to examine the association between non-high-density lipoprotein cholesterol (non-HDL-C) to high-density lipoprotein cholesterol (HDL-C) ratio (NHHR) and chronic kidney disease (CKD) in Chinese adults with type 2 diabetes mellitus (T2DM). Methods: This study originated from a survey carried out in Zhejiang Province, located in eastern China, between March and November 2018. To explore the relationship between NHHR and CKD, a multivariable logistic regression model was employed. The dose-response relationship was assessed using restricted cubic spline (RCS) analysis, while generalized additive models (GAMs) were applied to examine the associations between NHHR and urinary albumin-to-creatinine ratio (UACR) as well as estimated glomerular filtration rate (eGFR). Subgroup analyses were performed across various demographic and clinical categories to assess the consistency of the NHHR-CKD association. The optimal NHHR cutoff for CKD diagnosis, its predictive accuracy, and its comparison with its components and HbA1c were determined through receiver operating characteristic (ROC) curve analysis. Results: The study enrolled 1756 participants, including 485 individuals with CKD and 1271 without CKD. Multivariable logistic regression revealed a significant positive association between NHHR and CKD, with each standard deviation (SD) increase in NHHR linked to a 23% higher odds of CKD (OR = 1.23, 95% CI: 1.09-1.37) after adjusting for potential confounders. When comparing quartiles, the fully adjusted ORs for Q2, Q3, and Q4 were 1.29 (0.92-1.79), 1.31 (0.94-1.83), and 1.87 (1.34-2.60), respectively, relative to Q1 (p for trend < 0.01). RCS analysis confirmed a linear dose-response relationship between NHHR and CKD in both sexes (p for nonlinearity > 0.05). GAMs indicated a significant positive correlation between NHHR and UACR (ρ = 0.109, p < 0.001) but no significant association with eGFR (ρ = -0.016, p = 0.502). Subgroup analyses demonstrated consistent associations across most subgroups, except for the 18-44 years age group, the well-controlled glycemic group, and the non-alcohol drinking group (p > 0.05). ROC curve analysis identified an optimal NHHR cutoff of 3.48 for CKD prediction, with an area under the curve (AUC) of 0.606 (95% CI: 0.577-0.635). Notably, NHHR outperformed its individual components and HbA1c in predictive performance. Conclusions: This study revealed a linear link between higher NHHR levels and increased CKD prevalence in Chinese T2DM patients. NHHR may also serve as a potential complementary biomarker for early CKD detection, though further prospective studies are needed to confirm its predictive value and clinical utility in high-risk T2DM populations.