代谢因素与中老年人群慢性肝病发病风险关系:一项基于CHARLS数据的队列研究

肝脏 ›› 2026, Vol. 31 ›› Issue (6): 873-878.

代谢因素与中老年人群慢性肝病发病风险关系:一项基于CHARLS数据的队列研究

包荟伟, 姜思雨, 郭克芬, 袁刘远

201104 上海上海市老年医学中心心电图科(包荟伟),消化科(姜思雨,袁刘远),心内科(郭克芬)

收稿日期:2026-02-25 出版日期:2026-06-30 发布日期:2026-07-29
通讯作者: 姜思雨,Email:Jiang.siyu@zsgmc.sh.cn
基金资助:
上海市老年医学中心青年项目(YQ2025-008)

Association between metabolic factors and the risk of chronic liver disease in middle-aged and older adults: a cohort study based on CHARLS data

Bao Huiwei¹, Jiang Siyu², Guo Kefen³, Yuan Liuyuan²

1. Department of Electrocardiography, Shanghai Geriatric Medical Center, Shanghai 201104, China;
2. Department of Gastroenterology and Hepatology, Shanghai Geriatric Medical Center, Shanghai 201104, China;
3. Department of Cardiology, Shanghai Geriatric Medical Center, Shanghai 201104, China

Received:2026-02-25 Online:2026-06-30 Published:2026-07-29
Contact: Jiang Siyu

摘要/Abstract

摘要： 目的探讨代谢综合征及其评分动态变化轨迹与中国中老年人群慢性肝病发病风险的关系。方法基于中国健康与退休追踪研究(CHARLS)2011—2020年数据,纳入8 479名既往未患慢性肝病的中老年人群(≥45岁)。采用Cox比例风险回归模型分析慢性肝病发生的独立危险因素。通过k-means聚类算法识别2011—2015年代谢综合征评分的变化轨迹,采用Kaplan-Meier曲线评估不同代谢综合征评分变化轨迹与慢性肝病发生的关系。结果随访9年间,共839例(9.90%)参与者新发生慢性肝病。多因素Cox回归显示基线诊断代谢综合征(HR=1.24,95%CI:1.07~1.43,P=0.004)、基线时较高的代谢综合征评分(HR=1.19,95%CI:1.11~1.27,P<0.001)和2015年较高的代谢综合征评分(HR=1.16,95%CI:1.05~1.28,P=0.004)是慢性肝病发生的独立危险因素。进一步绘制2011—2015年代谢综合征评分变化轨迹,并基于轨迹变化曲线将人群分为三组:高基线改善组、稳定组、低基线恶化组。Kaplan-Meier曲线显示,高基线改善组人群9年内慢性肝病累积发病率最高(12.74% vs. 7.88% vs. 7.46%, P=0.002)。结论代谢综合征评分升高显著增加中老年人群慢性肝病发病风险,监测评分动态变化并对人群进行危险分层可指导临床诊疗,降低肝病发生风险。

关键词: 代谢综合征, 慢性肝病, 中老年人, CHARLS, 队列研究

Abstract: Objective To explore the association of metabolic syndrome and dynamic trajectories of metabolic syndrome scores with the risk of chronic liver disease among middle-aged and older adults in China. Methods Based on data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, 8 479 middle-aged and elderly individuals (≥45 years) without a prior history of chronic liver disease were included. The Cox proportional hazards regression model was used to analyze the independent risk factors for the occurrence of chronic liver disease. The k-means clustering algorithm was applied to identify trajectories of changes in metabolic syndrome scores from 2011 to 2015, and Kaplan-Meier curves were used to evaluate the relationship between different metabolic syndrome score trajectories and the occurrence of chronic liver disease. Results During the 9-year follow-up period, a total of 839 participants (9.90%) newly developed chronic liver disease. Multivariate Cox regression analysis showed that a baseline diagnosis of metabolic syndrome (HR=1.24, 95% CI: 1.07~1.43, P=0.004), a higher baseline metabolic syndrome score (HR=1.19, 95% CI: 1.11-1.27, P<0.001), and a higher metabolic syndrome score in 2015 (HR=1.16, 95% CI: 1.05~1.28, P=0.004) were independent risk factors for the occurrence of chronic liver disease. The trajectories of metabolic syndrome score changes from 2011 to 2015 were further plotted, and based on the trajectory curves, the population was divided into three groups: the high-baseline improvement group, the stable group, and the low-baseline deterioration group. Kaplan-Meier curves showed that the high-baseline improvement group had the highest cumulative incidence of chronic liver disease within 9 years (12.74% vs. 7.88% vs. 7.46%, P=0.002). Conclusion An elevated metabolic syndrome score significantly increases the risk of chronic liver disease in the middle-aged and older adults. Monitoring the dynamic changes of the score and stratifying the population by risk can guide clinical diagnosis and treatment and reduce the risk of liver disease.

Key words: Metabolic syndrome, Chronic liver disease, Middle-aged and elderly, CHARLS, Cohort study

包荟伟, 姜思雨, 郭克芬, 袁刘远. 代谢因素与中老年人群慢性肝病发病风险关系:一项基于CHARLS数据的队列研究[J]. 肝脏, 2026, 31(6): 873-878.

Bao Huiwei, Jiang Siyu, Guo Kefen, Yuan Liuyuan. Association between metabolic factors and the risk of chronic liver disease in middle-aged and older adults: a cohort study based on CHARLS data[J]. Chinese Hepatolgy, 2026, 31(6): 873-878.

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