医学
体质指数
四分位数
累积发病率
混淆
内科学
入射(几何)
队列
置信区间
数学
几何学
作者
Yu Wang,Bing Chen,Chongsen Zang,Jie Hou
标识
DOI:10.3389/fendo.2025.1525078
摘要
Background Chronic kidney disease (CKD) has become a significant global public health challenge, which was reported to be highly correlated with the triglyceride glucose-body mass index (TyG-BMI). Nevertheless, literature exploring the association between changes in the TyG-BMI and CKD incidence is scant, with most studies focusing on individual values of the TyG-BMI. We aimed to investigate whether cumulative average in the TyG-BMI were associated with CKD incidence. Methods Data in our study were obtained from the China Health and Retirement Longitudinal Study (CHARLS), which is an ongoing nationally representative prospective cohort study. The exposure was the cumulative average TyG-BMI from 2011 to 2015. The TyG-BMI was calculated by the formula ln [TG (mg/dl) × FBG (mg/dl)/2] × BMI (kg/m 2 ), and the cumulative average TyG-BMI was calculated as follows: (TyG-BMI 2011 + TyG-BMI 2015 )/2. Logistic regressions were used to determine the association between different quartiles of cumulative average TyG-BMI and CKD incidence. Meanwhile, restricted cubic spline was applied to examine the potential nonlinear association of the cumulative average TyG-BMI and CKD incidence. In addition, subgroup analysis was used to test the robustness of results. Results Of the 6117 participants (mean [SD] age at baseline, 58.64 [8.61] years), 2793 (45.7%) were men. During the 4 years of follow-up, 470 (7.7%) incident CKD cases were identified. After adjusting for potential confounders, compared to the participants in the lowest quartile of cumulative average TyG-BMI, participants in the 3rd and 4th quartile had a higher risk of CKD onset. The ORs and 95%CIs were [1.509(1.147, 1.990)] and [1.452(1.085, 1.948)] respectively. In addition, restricted cubic spline showed the cumulative average TyG-BMI had a liner association ( p -nonlinear = 0.139). Conclusions The cumulative average in the TyG-BMI was independently associated with the risk of CKD in middle-aged and older adults. Monitoring long-term changes in the TyG-BMI may assist with the early identification of individuals at high risk of CKD.
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