Objective To identify risk factors associated with renal impairment in early-onset type 2 diabetes mellitus （EOT2DM） through a multidimensional assessment， so as to provide a scientific basis for establishing an early warning system and optimizing clinical intervention strategies. Methods This retrospective study recruited 541 patients diagnosed with EOT2DM who were admitted to the Department of Endocrinology at the Jiangsu Provincial Hospital of Traditional Chinese Medicine from August 2024 to August 2025. The participants were stratified into two groups according to the presence of abnormal renal impairment indicators： an EOT2DM group with renal impairment （n = 241） and an EOT2DM group without renal impairment （n = 300）. Clinical data were collected and underwent univariate analysis. Variables with a P-value < 0.05 in the univariate analysis， as well as variables with established clinical significance according to previous literature （even if P ≥ 0.05）， were included in a least absolute shrinkage and selection operator （LASSO） logistic regression model to remove redundant variables. Subsequently， multivariate logistic regression analysis was carried out. The optimal cut-off values for significant continuous variables were identified by calculating the Youden's index. Based on these cut-offs， continuous variables were dichotomized into high-risk （≥ cutoff） and low-risk （< cutoff） groups. After covariance adjustment， the adjusted odds ratios （ORs） and their 95% confidence intervals （CIs） were computed to accurately quantify the independent association between the level of each risk variable and the risk of renal impairment in EOT2DM. Receiver Operating Characteristic （ROC） curves were drawn， and the discriminatory ability of each risk factor was evaluated by the area under the ROC curve. Results Multivariate logistic regression analysis has identified six risk factors： sTM （OR = 1.789， AUC = 0.702）， TG （OR = 2.647， AUC = 0.602）， UA （OR = 1.693， AUC = 0.637）， LDL-C （OR = 1.942， AUC = 0.562）， WHR （OR = 2.364， AUC = 0.566）， and carotid plaque （OR = 1.872， AUC = 0.607）. After further refining the strength of the association by using cutoff values， the following four risk factors were determined： sTM， TG， WHR， and carotid plaque. Conclusions Elevated sTM， TG， WHR， and the presence of carotid plaque are independent risk factors for renal impairment in patients with EOT2DM. Among these， sTM demonstrated superior accuracy for renal impairment in EOT2DM and may be more suitable as a clinical assessment tool.