Association of obesity and lipid indexes with rapid kidney function decline and the progression to chronic kidney disease: a study from a large longitudinal cohort among middle-aged and older adults in China.

Background: Obesity and lipid abnormalities are recognized as important risk factors for rapid kidney function decline (RKFD) and chronic kidney disease (CKD). However, studies on the association between obesity and lipid indices with RKFD and CKD are still lacking. This study aims to investigate the association between obesity and lipid indexes with RKFD and CKD, and further explore their predictive value. Methods: Data from the China Health and Retirement Longitudinal Study (CHARLS) were used in this study. The obesity and lipid indexes used in this study included non-invasive anthropometric indexes and invasive anthropometric indexes. Multivariate logistic regression models with covariate adjustment were employed to assess association between obesity and lipid indexes and RKFD or progression to CKD. Restricted cubic spline (RCS) regression analyses were performed to characterize potential nonlinear relationships. Predictive performance was quantified through receiver operating characteristic (ROC) curve analysis. Subgroup analysis was performed based on hypertension, diabetes, or cardiovascular disease (CVD) status of the participants. Results: A total of 3,829 participants were included in this study. Of these, 192 participants developed RKFD and 60 progressed to CKD. Logistic regression after adjusting for confounders revealed significant associations between 11 indexes and RKFD, and 4 indexes standard deviation increases associated with CKD. RCS curve analysis demonstrated that 9 indexes had linear relationship with the risk of progression to RKFD though WHtR, BRI and TyG-BRI had non-linear relationship. Moreover, LAP had a linear relationship with the risk of CKD, whereas VAI had a nonlinear relationship. ROC analysis revealed TyG as the superior RKFD predictor and CVAI as the optimal CKD progression indicator. In subgroup analysis, the association between partial indexes and progression to CKD was more significant in subjects with hypertension (TyG-CVAI) or without CVD (C-index, RFM, TyG-RFM). Conclusion: This study comprehensively analyzed the associations between 20 obesity and lipid indexes and both RKFD and CKD. We proved that multiple obesity and lipid indexes were associated with RKFD and CKD. Compared with non-invasive anthropometric indexes, invasive anthropometric indexes have a more significant association with RKFD and CKD and have higher predictive value.