目的：探讨社区老年人群单核细胞/高密度脂蛋白胆固醇比值（monocyte to high-density lipoprotein cholesterol ratio，MHR）、甘油三酯-葡萄糖（triglyceride-glucose，TyG）指数与慢性肾脏病（chronic kidney disease, CKD）之间的相关性，并评估基于MHR、TyG指数联合尿酸、体质量指数（body mass index，BMI）及年龄构建的多元联合预测模型对老年CKD的预测价值。方法：收集2022年上海市浦东新区陆家嘴社区1 653例老年人群的临床资料及外周血检测数据，根据估算肾小球滤过率（estimated glomerular filtration rate，eGFR）将研究对象分为非CKD组[eGFR ≥ 60 mL/（min·1.73 m²）]和CKD组[eGFR< 60 mL/（min·1.73 m²）]。分析MHR-TyG联合预测模型对老年CKD的预测效能。结果：Logistic回归分析显示，年龄、BMI、尿酸、MHR及TyG指数均为CKD的独立危险因素（均P<0.05）。限制性立方样条（restricted cubic spline，RCS）曲线及中介效应分析表明，MHR与CKD的发病风险呈显著的非线性正相关（总体关联性检验P<0.001, 非线性检验P=0.016）。当MHR>0.3时，CKD的发病风险显著上升。MHR在BMI与CKD关系中的中介效应占比为23.88%，在年龄与CKD关系中为4.77%。受试者操作特征（receiver operating characteristic，ROC）曲线分析显示，MHR-TyG联合预测模型的曲线下面积（area under the curve， AUC）为0.826（95% CI: 0.793~0.859，P<0.001），灵敏度为79.1%，特异度为73.4%，预测效能优于任一单一指标。亚组分析提示，MHR在非高危人群（如BMI、尿酸和甘油三酯水平正常者）中仍具有显著的预测价值。结论：年龄、BMI、尿酸、MHR及TyG指数均为CKD的独立危险因素。由MHR-TyG联合年龄、BMI和尿酸构建的CKD风险预测模型具有良好的预测效能，且优于任一单一指标。

Objective To discuss the correlation among monocyte to high-density lipoprotein cholesterol ratio (MHR), triglyceride-glucose (TyG) index, and chronic kidney disease (CKD) in the community-dwelling elderly population, and to evaluate the predictive value of a multivariate joint prediction model based on MHR, TyG index combined with uric acid, body mass index (BMI), and age for CKD in the elderly. Methods Clinical data and peripheral blood test results were collected from a total of 1 653 elderly individuals in the Lujiazui community of Pudong New Area, Shanghai, in 2022. Based on the estimated glomerular filtration rate (eGFR), the study population was divided into a non-CKD group [eGFR≥60 mL/(min·1.73 m²)] and a CKD group [eGFR<60 mL/(min·1.73 m²)]. The predictive value of the combined MHR-TyG model for CKD in the elderly was analyzed. Results Logistic regression analysis showed that age, BMI, uric acid, MHR, and TyG index were all independent risk factors for CKD (all P<0.05). Restricted cubic spline (RCS) curves and mediation analysis demonstrated that MHR was significantly non-linearly and positively associated with the risk of CKD (P for overall<0.001, P for nonlinear=0.016). When MHR>0.3, the risk of CKD increased significantly. The proportion of the mediation effect of MHR was 23.88% in the relationship between BMI and CKD, and 4.77% in the relationship between age and CKD. Receiver operating characteristic (ROC) curve analysis showed that the combined MHR-TyG prediction model achieved an area under the curve (AUC) of 0.826 (95% CI: 0.793–0.859, P<0.001), with a sensitivity of 79.1% and a specificity of 73.4%, demonstrating predictive performance superior to any single indicator. Subgroup analysis suggested that MHR remained a significant predictor in non-high-risk populations, such as those with normal BMI, uric acid, and triglyceride levels. Conclusions Age, BMI, uric acid, MHR, and TyG index are all independent risk factors for CKD. The risk prediction model constructed by combining MHR-TyG with age, BMI, and uric acid has good predictive performance and is superior to any single indicator.