Association between uric acid to high-density lipoprotein cholesterol ratio and chronic kidney disease in middle-aged and older adults: results from two nationally representative population-based study

尿酸与高密度脂蛋白胆固醇比值与中老年人慢性肾脏病之间的关联:两项具有全国代表性的人群研究结果

阅读:1

Abstract

Uric acid to high-density lipoprotein cholesterol ratio (UHR) is considered a novel marker of inflammation. The aim of this study was to investigate the association between the UHR and chronic kidney disease (CKD) in middle-aged and older adults. This study used data from the National Health and Nutrition Examination Survey (NHANES) and the China Health and Retirement Longitudinal Study (CHARLS). The association between UHR and CKD prevalence was analyzed using weighted multivariable logistic regression models. Restricted cubic spline (RCS) models were used to analyze nonlinear relationships. Weighted subgroup analyses were performed to validate the robustness of the findings. The diagnostic performance of UHR for CKD was evaluated using receiver operating characteristic (ROC) curves. This study included 10,968 participants from NHANES and 9,012 participants from CHARLS. The mean age of NHANES participants was 59.60 years (standard deviation [SD] = 10.97), with 5,575 men (50.83%). CHARLS participants had a mean age of 59.58 years (SD = 9.40), and 4,203 (46.64%) were men. Weighted logistic regression analysis revealed a positive association between UHR and CKD prevalence (CHARLS: OR = 1.83, 95% CI = 1.44-2.32, p < 0.001; NHANES: OR = 1.81, 95% CI = 1.58-2.07, p < 0.001). The RCS regression models demonstrated a significant nonlinear relationship between UHR and CKD. ROC analysis indicated that UHR demonstrated moderate CKD discrimination (CHARLS: AUC = 0.707; NHANES: AUC = 0.645). UHR is positively associated with an increased prevalence of CKD in middle-aged and older adults, and this association exhibits cross-ethnic consistency.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。