Zeng Zhihe, Xiao Zhaoyang
Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116027, China.
BMC Public Health. 2025 Jul 29;25(1):2581. doi: 10.1186/s12889-025-23868-w.
There is mixed evidence for an association between cardiometabolic risk factors and chronic kidney disease risk (CKD). This study aimed to determine whether different latent classes of cardiometabolic conditions were associated with chronic kidney disease risk.
Data from 7,195 participants in the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Latent class analysis was performed using data on obesity, high-density lipoprotein cholesterol, triglyceride, hypertension, diabetes, arthritis or rheumatism, and systemic inflammatory conditions and heart disease. Confounder-adjusted multiple logistic regressions were conducted to estimate CKD incidence by cardiometabolic latent classes. Sensitivity analyses were performed across cross-sectional and longitudinal samples, as well as derivation and validation cohorts.
Three cardiometabolic classes were identified: relatively healthy cardiometabolic (RHC) phenotype, metabolic syndrome (MetS) phenotype, and cardiovascular disease (CVD) phenotype, which accounted for 66.2%, 19.9%, and 13.8%, respectively. The incidence of CKD was 12.7% in the CVD group, 9.4% in the MetS group, and 5.9% in the RHC group. After adjusting for confounding factors, it was found that the metabolic syndrome type had a 54% increased risk of newly diagnosed CKD compared to the healthy heart type (OR = 1.54, 95% CI: 1.22-1.93), while the cardiovascular type increased by 104% (OR = 2.04, 95% CI: 1.61-2.57). Sensitivity analyses showed high consistency (> 90%) in class assignments, confirming model robustness.
Different cardiometabolic phenotypes are associated with an increased risk of new-onset CKD. Gender and age are important factors influencing the strength of this association. Phenotypic classification may improve CKD risk stratification and guide early prevention efforts.
关于心脏代谢危险因素与慢性肾脏病风险（CKD）之间的关联，证据并不一致。本研究旨在确定不同潜在类别的心脏代谢状况是否与慢性肾脏病风险相关。
对中国健康与养老追踪调查（CHARLS）中7195名参与者的数据进行分析。使用关于肥胖、高密度脂蛋白胆固醇、甘油三酯、高血压、糖尿病、关节炎或风湿病、全身炎症状况和心脏病的数据进行潜在类别分析。进行了混杂因素调整的多重逻辑回归，以估计心脏代谢潜在类别导致的CKD发病率。在横断面和纵向样本以及推导和验证队列中进行了敏感性分析。
确定了三种心脏代谢类别：相对健康的心脏代谢（RHC）表型、代谢综合征（MetS）表型和心血管疾病（CVD）表型，分别占66.2%、19.9%和13.8%。CKD的发病率在CVD组中为12.7%，在MetS组中为9.4%，在RHC组中为5.9%。在调整混杂因素后，发现代谢综合征类型与健康心脏类型相比，新诊断CKD的风险增加了54%（OR = 1.54，95%CI：1.22 - 1.93），而心血管类型增加了104%（OR = 2.04，95%CI：1.61 - 2.57）。敏感性分析显示类别分配的一致性很高（> 90%），证实了模型的稳健性。
不同的心脏代谢表型与新发CKD风险增加相关。性别和年龄是影响这种关联强度的重要因素。表型分类可能改善CKD风险分层并指导早期预防工作。
