The association between the cardiac metabolic index and rapid kidney function decline and CKD in individuals with different glucose metabolism statuses: results from the China health and retirement longitudinal study

临床营养学 脂多糖学 临床化学 医学 肾功能 中国 内科学 生物 索引(排版) 老年学 环境卫生 生理学 政治学 计算机科学 万维网 法学
作者
Wei‐Zhen Tang,Qin‐Yu Cai,Tai‐Hang Liu,Tsai‐Chung Li,Gang Zhu,Jiacheng Li,Kui Huang,Jin Xu,H-M. Hua,Rong Li
出处
期刊:Lipids in Health and Disease [BioMed Central]
卷期号:24 (1) 被引量:1
标识
DOI:10.1186/s12944-025-02572-z
摘要

The Cardiometabolic Index (CMI) is a new measure that combines fat distribution and lipid profiles. However, its relationship with rapid decline in renal function and the chronic kidney disease (CKD), especially in individuals with varying glucose metabolism, is still unclear. This study included 3,485 participants aged 45 and above from the China Longitudinal Study on Health and Retirement (CHARLS), with baseline assessments in 2011-2012 and follow-ups in 2015 and 2018. Participants were grouped into four categories (Q1-Q4) based on baseline CMI levels. The primary outcome was rapid decline in renal function, with CKD events also observed. Multivariable logistic models and restricted cubic spline (RCS) analysis were used to explore the relationship between baseline CMI levels and the risk of kidney disease in individuals with different glucose metabolism statuses. Nine machine learning models were developed using baseline CMI to validate its predictive ability for kidney disease risk. Finally, mediation causal analysis was conducted to examine whether the development of diabetes in the non-diabetic population serves as an important mediator in the relationship between CMI and kidney disease. During the follow-up period, a total of 173 participants (4.96%) experienced rapid decline in renal function, and 87 participants (2.50%) developed CKD. With increasing baseline CMI levels, the risk of rapid decline in renal function and CKD significantly increased. Among the various machine learning models for predicting kidney disease, logistic regression performed excellently, with AUCs exceeding 0.6, indicating the strong predictive ability of baseline CMI. For the primary outcome, multivariable logistic regression analysis showed that, in all participants, as well as in the normal glucose regulation (NGR) group and the prediabetes (Pre-DM) group, the incidence of rapid decline in renal function significantly increased across different CMI groups (P < 0.05), with trend RR values of 1.285(1.076,1.536), 1.308 (1.015, 1.685) and 1.566 (1.207, 2.031), respectively. However, this association was not observed in patients with diabetes (P for trend > 0.05). RCS analysis further indicated that higher baseline CMI levels were associated with a greater risk of rapid decline in renal function in all participants and in the non-diabetic population. A similar trend was observed for CKD. Finally, mediation causal analysis showed that the development of new-onset diabetes in the non-diabetic population may not be an important mediator in the relationship between CMI and kidney disease. Higher baseline CMI levels were significantly linked to rapid decline in renal function and CKD in middle-aged and elderly individuals, with the relationship varying by glucose metabolism status. CMI may serve as a useful indicator for predicting kidney disease risk, especially in non-diabetic population.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
NexusExplorer应助轻松的达采纳,获得10
1秒前
xiaobaiyang完成签到,获得积分10
2秒前
无昵称完成签到,获得积分10
2秒前
2秒前
tomorrow发布了新的文献求助10
2秒前
3秒前
云朵云朵飘呀飘完成签到,获得积分10
3秒前
日常K人发布了新的文献求助10
3秒前
科研小叶完成签到,获得积分10
3秒前
爆米花应助zzz采纳,获得10
4秒前
andjdd完成签到,获得积分10
4秒前
wenwen流发布了新的文献求助10
6秒前
6秒前
叶飞完成签到,获得积分10
6秒前
科研通AI6.1应助左安采纳,获得10
7秒前
7秒前
7秒前
8秒前
whr完成签到,获得积分10
8秒前
8秒前
静文发布了新的文献求助10
8秒前
虚心的访风完成签到,获得积分10
8秒前
Ava应助畅快的海白采纳,获得10
10秒前
10秒前
10秒前
10秒前
10秒前
10秒前
10秒前
10秒前
10秒前
王大大完成签到,获得积分10
10秒前
11秒前
11秒前
卡卡完成签到,获得积分20
12秒前
12秒前
13秒前
超级铅笔发布了新的文献求助10
13秒前
清脆巧蕊发布了新的文献求助10
14秒前
小蘑菇应助云纳采纳,获得10
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Adhesion Science: Principles & Practice 800
The Graphene Handbook (2019 Edition) 700
Signals, Systems, and Signal Processing 610
IEST-RP-CC018: Cleanroom Cleaning and Sanitization: Operating and Monitoring Procedures 600
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
Fundamentals of Modern Mathematics: A Practical Review (Dover Books on Mathematics) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6532250
求助须知:如何正确求助?哪些是违规求助? 8325147
关于积分的说明 17827663
捐赠科研通 5633576
什么是DOI,文献DOI怎么找? 2933093
邀请新用户注册赠送积分活动 1909697
关于科研通互助平台的介绍 1768686