中国全科医学 ›› 2023, Vol. 26 ›› Issue (29): 3608-3615.DOI: 10.12114/j.issn.1007-9572.2023.0186

所属专题: 老年人群健康最新文章合集 老年问题最新文章合集

• 慢性病共病专题研究 • 上一篇    下一篇

中国老年人慢性病多病共存模式的研究

潘晔1, 刘志辉2, 胡倩倩3, 王留义2,*()   

  1. 1.450004 河南省郑州市,河南省中西医结合医院
    2.450003 河南省郑州市,河南省人民医院全科医学科
    3.450003 河南省郑州市,河南大学人民医院
  • 收稿日期:2023-02-24 修回日期:2023-05-10 出版日期:2023-10-15 发布日期:2023-05-26
  • 通讯作者: 王留义

  • 作者贡献:王留义提出研究选题方向和总体研究目标,对研究进行可行性分析,对文章整体负责,监督管理;潘晔负责数据清洗、处理和统计学分析、R语言编程、绘制图表;潘晔、刘志辉、胡倩倩负责结果分析与解释,撰写论文初稿;潘晔、刘志辉负责论文的修订。
  • 基金资助:
    河南省中医药科学研究专项课题(2023ZYZD13); 河南省中医药文化与管理研究项目(TCM2023005)

Patterns of Coexistence of Multiple Chronic Conditions among Chinese Elderly

PAN Ye1, LIU Zhihui2, HU Qianqian3, WANG Liuyi2,*()   

  1. 1. Henan Integrative Medicine Hospital, Zhengzhou 450004, China
    2. Department of General Practice, Henan Provincial People's Hospital, Zhengzhou 450003, China
    3. Henan University People's Hospital, Zhengzhou 450003, China
  • Received:2023-02-24 Revised:2023-05-10 Published:2023-10-15 Online:2023-05-26
  • Contact: WANG Liuyi

摘要: 背景 随着人口老龄化及寿命延长,慢性病的多病共存日益普遍。疾病种类多且病情复杂,为老年人健康管理提出挑战。共病模式作为研究的必要问题,国内研究相对缺乏。 目的 研究中国老年人常见慢性病的多病共存模式,帮助政策制定者、研究人员和临床医生更好地了解多病共存现状。 方法 选取中国健康养老追踪调查(CHARLS)2018年数据中60岁及以上被访者,选择人口特征学部分数据及健康状况的14种慢性病数据。采用关联规则、聚类分析、主成分分析、潜在类别分析4种方法对中国老年人的共病模式进行探索,并对比不同方法所得结果。 结果 最终共纳入10 800例被访者数据。4种方法所得模式有所差异,但存在一致性的共病模式:(1)高血压、糖尿病或血糖升高、血脂异常;(2)慢性肺部疾患和哮喘;(3)关节炎或风湿病、胃部疾病或消化系统疾病;(4)中风、与记忆相关的疾病。 结论 不同方法得到的一致性的共病模式所包含的慢性病病因关系关联明显;4种方法得到的共病模式存在差异的原因是包含的病因关系复杂,且方法的原理不同。

关键词: 慢性病, 慢性病共病, 共病现象, 关联规则, 系统聚类, 潜在类别分析

Abstract:

Background

With the aging and longer survival of the population, comorbid chronic diseases is increasingly common. The variety and complexity of diseases pose challenges to the health management of the elderly. There is a relative lack of multimorbidity pattern researches in China, which are necessary issues for research.

Objective

To investigate the patterns of coexistence of common multiple chronic conditions among the elderly in China, in order to help policymakers, researchers, and clinicians better understand the current status of multimorbidity among Chinese elderly.

Methods

Data on the demographic characteristics and health status of 14 chronic diseases were extracted from the respondents aged 60 years and above in the China Health and Retirement Longitudinal Study (CHARLS) 2018, association rules, cluster analysis, principal component analysis, latent class analysis were used to explore the multimorbidity patterns of Chinese elderly, and the results of different methods were compared.

Results

The data from a total of 10 800 respondents were eventually included, there were differences among the patterns obtained by four methods. However, the consistent multimorbidity patterns were identified: hypertension, diabetes or elevated blood glucose, dyslipidemia; chronic lung disease and asthma; arthritis or rheumatism, stomach diseases or digestive diseases; stroke, memory-related diseases.

Conclusion

The consistent patterns obtained by different methods contain chronic diseases with significant relationships of etiologies. The reasons of differences in results are complex etiologic relationships and different method principles.

Key words: Chronic disease, Multiple chronic conditions, Comorbidity, Association rules, Clustering analysis, Latent class analysis