Article(id=1259565965889626459, tenantId=1146029695717560320, journalId=1259198908832956435, issueId=1259565961842123095, articleNumber=null, orderNo=null, doi=10.16462/j.cnki.zhjbkz.2026.02.007, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1750953600000, receivedDateStr=2025-06-27, revisedDate=1760457600000, revisedDateStr=2025-10-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1778233527871, onlineDateStr=2026-05-08, pubDate=1770652800000, pubDateStr=2026-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1778233527871, onlineIssueDateStr=2026-05-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1778233527871, creator=13701087609, updateTime=1778233527871, updator=13701087609, issue=Issue{id=1259565961842123095, tenantId=1146029695717560320, journalId=1259198908832956435, year='2026', volume='30', issue='2', pageStart='125', pageEnd='242', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1778233526907, creator=13701087609, updateTime=1778233940379, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1259567696174301345, tenantId=1146029695717560320, journalId=1259198908832956435, issueId=1259565961842123095, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1259567696174301346, tenantId=1146029695717560320, journalId=1259198908832956435, issueId=1259565961842123095, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=177, endPage=182, ext={EN=ArticleExt(id=1259565966346805601, articleId=1259565965889626459, tenantId=1146029695717560320, journalId=1259198908832956435, language=EN, title=Association between frailty and incident multimorbidity in middl-aged and older adults in China, columnId=1259565965784789759, journalTitle=Chinese Journal of Disease Control and Prevention, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=
Objective

To examine the impact of frailty status on the risk of multimorbidity among middle-aged and older adults in China.

Methods

Utilizing the China Health and Retirement Longitudinal Study (CHARLS) database, data from 2011 were employed as the baseline for enrollment, and participants who completed follow-up assessments from 2013 to 2020 were matched by ID. The study included middle-aged and older adults aged 45 years and above who were free of multimorbidity at baseline. The questionnaire encompassed basic information, frailty assessments, and evaluations of chronic disease. The Cox regression model was applied to analyze the relationship between frailty and incident multimorbidity.

Results

A total of 4 832 participants were included in the study. The mean age of participants at baseline was (61.09±9.52) years, with 50.12% (2 422 individuals) being men. During the follow-up period, 2 502 individuals (51.78%) developed multimorbidity. The results of the Cox regression model, after adjusting for covariates, indicated that compared with robust individuals at baseline, those in the pre-frailty (HR=1.127, 95% CI: 1.035-1.227) and frailty (HR=1.363, 95% CI: 1.126-1.650) categories were at a higher risk of developing multimorbidity.

Conclusions

Frailty is associated with an increased risk of incident multimorbidity among middle-aged and older adults in China. Both pre-frailty and frailty significantly elevate the risk of multimorbidity. Frailty should be considered a crucial pre-interventional stage in the prevention of chronic diseases to mitigate the risk of multimorbidity.

, correspAuthors=null, authorNote=null, correspAuthorsNote=
SI Huaxin, E-mail:
, copyrightStatement=Copyright © 2026 Chinese Journal of Disease Control & Prevention. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xuelai YANG, Yemin YUAN, Huaxin SI), CN=ArticleExt(id=1259565970679521659, articleId=1259565965889626459, tenantId=1146029695717560320, journalId=1259198908832956435, language=CN, title=中国中老年人衰弱与慢性病共病发生风险的关联, columnId=1259565966174860033, journalTitle=中华疾病控制杂志, columnName=论著, runingTitle=null, highlight=null, articleAbstract=
目的

在中国中老年人群中,探讨衰弱状态对慢性病共病发生风险的影响。

方法

基于中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS)数据库,以2011年数据为基线,并以身份证号码(identification number, ID)匹配2013―2020年参与随访的研究对象,纳入≥45岁且基线无慢性病共病的中老年人,调查内容包括基本信息、衰弱状态和慢性病测量情况。采用Cox比例风险回归模型分析衰弱状态与慢性病共病风险的关联。

结果

共纳入4 832名研究对象,研究对象基线时年龄为(61.09±9.52)岁,其中男性2 422名(50.12%)。随访期间共2 502人(51.78%)发生了慢性病共病,调整协变量后的Cox比例风险回归模型结果显示,与基线处于健壮者相比,处于衰弱前期(HR=1.127, 95% CI: 1.035~1.227)和衰弱期者(HR=1.363, 95% CI: 1.126~1.650)发生慢性病共病的风险均较高。

结论

中国中老年人衰弱与慢性病共病发生存在关联,衰弱前期和衰弱期均可增加慢性病共病发生风险。应将衰弱作为慢性病预防的重要前置环节,以降低慢性病共病风险。

, correspAuthors=null, authorNote=null, correspAuthorsNote=
司华新,E-mail:
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Metabolic impact of frailty changes diabetes trajectory[J]. Metabolites, 2023, 13(2): 295. DOI:10.3390/metabo13020295., articleTitle=null, refAbstract=null), Reference(id=1259565991902700147, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965889626459, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=14, rfOrder=13, authorNames=null, journalName=null, refType=null, unstructuredReference=Ward DD, Flint JP, Littlejohns TJ, et al. Frailty trajectories preceding dementia in the US and UK[J]. JAMA Neurol, 2025, 82(1): 61-71. 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DOI:10.1016/j.arr.2021.101498., articleTitle=null, refAbstract=null), Reference(id=1259565992313741953, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965889626459, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=16, rfOrder=15, authorNames=null, journalName=null, refType=null, unstructuredReference=Mielke N, Schneider A, Huscher D, et al. Gender differences in frailty transition and its prediction in community-dwelling old adults[J]. Sci Rep, 2022, 12(1): 7341. 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A:Kaplan-Meier生存曲线;B:风险人数表。

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Baseline characteristics of the participants grouped by multimorbidity

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特征
Characteristic
总样本
Total
(n=4 832)
未患慢性病共病组
No multimorbidity group
(n=2 330)
新发慢性病共病组
Incident multimorbidity group
(n=2 502)
t/χ2
值value
P
value
年龄/岁Age/years61.09±9.5260.67±9.9661.48±9.09-2.9430.003
性别Gender7.0480.008
  男性Male2 422(50.12)1 214(52.10)1 208(48.28)
  女性Female2 410(49.88)1 116(47.90)1 294(51.72)
婚姻状况Marital status0.8150.367
  在婚Married4 125(85.37)1 978(84.89)2 147(85.81)
  非在婚Unmarried707(14.63)352(15.11)355(14.19)
文化程度Educational level-2.2410.025
  文盲Illiteracy1 539(31.85)707(30.34)832(33.25)
  小学及以下Primary school or below1 993(41.25)972(41.72)1 021(40.81)
  初中及以上Middle school and above1 300(26.90)651(27.94)649(25.94)
居住地Place of residence0.8870.346
  城镇Town1 681(34.79)795(34.12)886(35.41)
  农村Countryside3 151(65.21)1 535(65.88)1 616(64.59)
吸烟Smoking2.4820.115
  否No3 212(66.47)1 523(65.36)1 689(67.51)
  是Yes1 620(33.53)807(34.64)813(32.49)
饮酒/(次·周-1) Drinking status/ (times·week-1)-2.5830.010
  从不None3 131(68.57)1 468(66.73)1 663(70.29)
  ≤1641(14.04)325(14.77)316(13.35)
  >1794(17.39)407(18.50)387(16.36)
衰弱状态Frailty status-3.3900.001
  健壮期Robust2 038(42.18)1 033(44.34)1 005(40.17)
  衰弱前期Pre-frail2 571(53.21)1 210(51.93)1 361(54.40)
  衰弱期Frail223(4.61)87(3.73)136(5.43)
), ArticleFig(id=1259565988425622060, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965889626459, language=CN, label=表1, caption=

不同慢性病共病分组的研究对象基线特征分布

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特征
Characteristic
总样本
Total
(n=4 832)
未患慢性病共病组
No multimorbidity group
(n=2 330)
新发慢性病共病组
Incident multimorbidity group
(n=2 502)
t/χ2
值value
P
value
年龄/岁Age/years61.09±9.5260.67±9.9661.48±9.09-2.9430.003
性别Gender7.0480.008
  男性Male2 422(50.12)1 214(52.10)1 208(48.28)
  女性Female2 410(49.88)1 116(47.90)1 294(51.72)
婚姻状况Marital status0.8150.367
  在婚Married4 125(85.37)1 978(84.89)2 147(85.81)
  非在婚Unmarried707(14.63)352(15.11)355(14.19)
文化程度Educational level-2.2410.025
  文盲Illiteracy1 539(31.85)707(30.34)832(33.25)
  小学及以下Primary school or below1 993(41.25)972(41.72)1 021(40.81)
  初中及以上Middle school and above1 300(26.90)651(27.94)649(25.94)
居住地Place of residence0.8870.346
  城镇Town1 681(34.79)795(34.12)886(35.41)
  农村Countryside3 151(65.21)1 535(65.88)1 616(64.59)
吸烟Smoking2.4820.115
  否No3 212(66.47)1 523(65.36)1 689(67.51)
  是Yes1 620(33.53)807(34.64)813(32.49)
饮酒/(次·周-1) Drinking status/ (times·week-1)-2.5830.010
  从不None3 131(68.57)1 468(66.73)1 663(70.29)
  ≤1641(14.04)325(14.77)316(13.35)
  >1794(17.39)407(18.50)387(16.36)
衰弱状态Frailty status-3.3900.001
  健壮期Robust2 038(42.18)1 033(44.34)1 005(40.17)
  衰弱前期Pre-frail2 571(53.21)1 210(51.93)1 361(54.40)
  衰弱期Frail223(4.61)87(3.73)136(5.43)
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Cox regression analysis of the association between frailty status and multimorbidity risk

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变量
Variable
模型1 Model 1模型2 Model 2模型3 Model 3
HR值value
(95% CI)
P
value
HR值value
(95% CI)
P
value
HR值value
(95% CI)
P
value
衰弱状态Frailty status
  健壮期Robust1.0001.0001.000
  衰弱前期Pre-frail1.158(1.067~1.257)< 0.0011.130(1.040~1.227)0.0041.127(1.035~1.227)0.006
  衰弱期Frail1.548(1.294~1.851)< 0.0011.406(1.168~1.692)< 0.0011.363(1.126~1.650)0.001
年龄/岁Age/years1.011(1.007~1.016)< 0.0011.011(1.006~1.016)< 0.001
性别Gender
  男性Male1.0001.000
  女性Female1.071(0.982~1.167)0.1201.031(0.921~1.154)0.595
婚姻状况Marital status
  在婚Married1.0001.000
  非在婚Unmarried0.930(0.825~1.049)0.2400.920(0.813~1.041)0.187
文化程度Educational level
  文盲Illiteracy1.0001.000
  小学及以下Primary school or below0.965(0.874~1.065)0.4750.957(0.865~1.060)0.399
  初中及以上Middle school and above0.981(0.868~1.107)0.7510.979(0.865~1.109)0.742
居住地Place of residence
  城镇Town1.0001.000
  农村Countryside0.932(0.857~1.015)0.1050.934(0.865~1.019)0.125
吸烟Smoking
  否No1.000
  是Yes0.993(0.893~1.106)0.904
饮酒/(次·周-1) Drinking status/(times·week-1)
  从不None1.000
  ≤10.929(0.818~1.054)0.252
  >10.924(0.816~1.047)0.216
), ArticleFig(id=1259565988903772726, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965889626459, language=CN, label=表2, caption=

衰弱状态与慢性病共病风险关联的Cox回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量
Variable
模型1 Model 1模型2 Model 2模型3 Model 3
HR值value
(95% CI)
P
value
HR值value
(95% CI)
P
value
HR值value
(95% CI)
P
value
衰弱状态Frailty status
  健壮期Robust1.0001.0001.000
  衰弱前期Pre-frail1.158(1.067~1.257)< 0.0011.130(1.040~1.227)0.0041.127(1.035~1.227)0.006
  衰弱期Frail1.548(1.294~1.851)< 0.0011.406(1.168~1.692)< 0.0011.363(1.126~1.650)0.001
年龄/岁Age/years1.011(1.007~1.016)< 0.0011.011(1.006~1.016)< 0.001
性别Gender
  男性Male1.0001.000
  女性Female1.071(0.982~1.167)0.1201.031(0.921~1.154)0.595
婚姻状况Marital status
  在婚Married1.0001.000
  非在婚Unmarried0.930(0.825~1.049)0.2400.920(0.813~1.041)0.187
文化程度Educational level
  文盲Illiteracy1.0001.000
  小学及以下Primary school or below0.965(0.874~1.065)0.4750.957(0.865~1.060)0.399
  初中及以上Middle school and above0.981(0.868~1.107)0.7510.979(0.865~1.109)0.742
居住地Place of residence
  城镇Town1.0001.000
  农村Countryside0.932(0.857~1.015)0.1050.934(0.865~1.019)0.125
吸烟Smoking
  否No1.000
  是Yes0.993(0.893~1.106)0.904
饮酒/(次·周-1) Drinking status/(times·week-1)
  从不None1.000
  ≤10.929(0.818~1.054)0.252
  >10.924(0.816~1.047)0.216
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中国中老年人衰弱与慢性病共病发生风险的关联
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杨学来 1 , 袁叶敏 2, 3 , 司华新 2, 3
中华疾病控制杂志 | 论著 2026,30(2): 177-182
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中华疾病控制杂志 | 论著 2026, 30(2): 177-182
中国中老年人衰弱与慢性病共病发生风险的关联
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杨学来1, 袁叶敏2, 3, 司华新2, 3
作者信息
  • 1中日友好医院医改和医疗发展办公室,北京 100029
  • 2北京大学公共卫生学院,北京 100191
  • 3北京大学中国卫生发展研究中心,北京 100191

通讯作者:

司华新,E-mail:
Association between frailty and incident multimorbidity in middl-aged and older adults in China
Xuelai YANG1, Yemin YUAN2, 3, Huaxin SI2, 3
Affiliations
  • 1Medical Reform and Medical Development Office, China-Japan Friendship Hospital, Beijing 100029, China
  • 2School of Public Health, Peking University, Beijing 100191, China
  • 3China Center for Health Development Studies, Beijing 100191, China
出版时间: 2026-02-10 doi: 10.16462/j.cnki.zhjbkz.2026.02.007
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目的

在中国中老年人群中,探讨衰弱状态对慢性病共病发生风险的影响。

方法

基于中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS)数据库,以2011年数据为基线,并以身份证号码(identification number, ID)匹配2013―2020年参与随访的研究对象,纳入≥45岁且基线无慢性病共病的中老年人,调查内容包括基本信息、衰弱状态和慢性病测量情况。采用Cox比例风险回归模型分析衰弱状态与慢性病共病风险的关联。

结果

共纳入4 832名研究对象,研究对象基线时年龄为(61.09±9.52)岁,其中男性2 422名(50.12%)。随访期间共2 502人(51.78%)发生了慢性病共病,调整协变量后的Cox比例风险回归模型结果显示,与基线处于健壮者相比,处于衰弱前期(HR=1.127, 95% CI: 1.035~1.227)和衰弱期者(HR=1.363, 95% CI: 1.126~1.650)发生慢性病共病的风险均较高。

结论

中国中老年人衰弱与慢性病共病发生存在关联,衰弱前期和衰弱期均可增加慢性病共病发生风险。应将衰弱作为慢性病预防的重要前置环节,以降低慢性病共病风险。

慢性病共病  /  衰弱  /  队列研究  /  中老年人
Objective

To examine the impact of frailty status on the risk of multimorbidity among middle-aged and older adults in China.

Methods

Utilizing the China Health and Retirement Longitudinal Study (CHARLS) database, data from 2011 were employed as the baseline for enrollment, and participants who completed follow-up assessments from 2013 to 2020 were matched by ID. The study included middle-aged and older adults aged 45 years and above who were free of multimorbidity at baseline. The questionnaire encompassed basic information, frailty assessments, and evaluations of chronic disease. The Cox regression model was applied to analyze the relationship between frailty and incident multimorbidity.

Results

A total of 4 832 participants were included in the study. The mean age of participants at baseline was (61.09±9.52) years, with 50.12% (2 422 individuals) being men. During the follow-up period, 2 502 individuals (51.78%) developed multimorbidity. The results of the Cox regression model, after adjusting for covariates, indicated that compared with robust individuals at baseline, those in the pre-frailty (HR=1.127, 95% CI: 1.035-1.227) and frailty (HR=1.363, 95% CI: 1.126-1.650) categories were at a higher risk of developing multimorbidity.

Conclusions

Frailty is associated with an increased risk of incident multimorbidity among middle-aged and older adults in China. Both pre-frailty and frailty significantly elevate the risk of multimorbidity. Frailty should be considered a crucial pre-interventional stage in the prevention of chronic diseases to mitigate the risk of multimorbidity.

Multimorbidity  /  Frailty  /  Cohort studies  /  Middle-aged and older adults
杨学来, 袁叶敏, 司华新. 中国中老年人衰弱与慢性病共病发生风险的关联. 中华疾病控制杂志, 2026 , 30 (2) : 177 -182 . DOI: 10.16462/j.cnki.zhjbkz.2026.02.007
Xuelai YANG, Yemin YUAN, Huaxin SI. Association between frailty and incident multimorbidity in middl-aged and older adults in China[J]. Chinese Journal of Disease Control and Prevention, 2026 , 30 (2) : 177 -182 . DOI: 10.16462/j.cnki.zhjbkz.2026.02.007
随着我国人口老龄化进程加速,中老年人群的健康问题已成为公共卫生领域的核心议题。慢性病共病指个体同时患≥2种慢性疾病,我国约30%的中老年人患有慢性病共病,且该患病率随年龄增长逐渐上升,由45~ < 60岁中年人的17.6%上升至≥80岁老年人的40.2%[1]。慢性病共病增加中老年人的死亡风险[2],已成为严重的公共卫生负担。因此,预防慢性病共病发生对优化健康管理和减轻公共卫生负担具有重要意义。
衰弱作为一种反映生理储备下降和多系统功能紊乱的临床综合征,在中老年人群中普遍存在,较小的应激事件(如轻度感染、小手术、跌倒等)即可引起健康状况的急剧下降[3],增加中老年人失能、死亡等风险[4]。Meta分析显示,社区衰弱人群中约72%患有慢性病共病[5],而在慢性病共病人群中约18%和49%分别处于衰弱期和衰弱前期[6]。一项在欧洲中老年人中开展的纵向研究表明,衰弱增加慢性病共病发生风险,提示应进行早期衰弱监测以预防慢性病共病的发生[7]。我国研究者也指出应将衰弱作为慢性病共病管理的突破点[8],然而国内关于衰弱与慢性病共病的研究仍处于起步阶段,尚缺乏中老年人群衰弱对慢性病共病长期影响的系统性证据。因此,本研究拟使用中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS)2011―2020年5轮全国性追踪数据,探讨衰弱与慢性病共病风险的前瞻性关联,以期为中老年人群慢性病共病的预防和管理提供科学依据。
CHARLS是一项针对中国≥45岁中老年人的全国代表性队列,本研究使用CHARLS数据,于2011年开展基线调查,随后分别于2013年、2015年、2018年和2020年进行4次追踪调查,具体研究设计和方法见文献[9]。本研究为前瞻性研究,使用2011年调查作为基线数据,2013―2020年调查作为随访期。研究人群的纳入标准:(1)≥45岁中老年人(16 931人);(2)基线无慢性病共病者(10 448人)。排除标准:(1)基线因数据缺失而无法定义衰弱状态的研究对象(5 424人);(2)随访期间慢性病共病数据缺失的研究对象(192人)。最终,本研究共纳入4 832名研究对象。调查各个阶段(抽样、调查员培训和实地入户等)都进行了严格的质量控制,研究已通过北京大学生物医学伦理委员会批准(伦理批件号:IRB00001052-11015),所有研究对象均在调查前签署了知情同意书。数据经研究者申请并获得使用许可。
采用衰弱表型量表(frailty phenotype, FP)测量衰弱水平。包括疲乏、握力不足、步速缓慢、身体活动量低和体重下降5个指标。本研究采用吴晨凯教授修订并验证的CHARLS数据FP指标构建方法[10],纳入含有4项或5项指标的样本进行分析。疲乏采用“我觉得我无法继续我的生活”和“我觉得做任何事都很费劲”进行测量,研究对象在任一问题上回答为“有时或者有一半时间”或者“大多数时间”被判为疲乏;握力不足根据两只手的最大握力值经性别和体质量指数(body mass index, BMI)调整后低于总体的20%来判定;步速缓慢基于2次2.5 m步行测试的步速平均值低于总体(经过性别和身高调整)的20%来判定;自我报告通常没有连续步行≥10 min/周者被视为身体活动量低;体重下降的判断标准为前一年自我报告体重减少≥5 kg或BMI≤18.5 kg/m2。上述5项指标中符合1项计1分,总分为0~5分,衰弱状态分为3组:健壮期(0分)、衰弱前期(1~ < 3分)、衰弱期(≥3分)。
慢性病种类包括高血压、血脂异常、糖尿病或血糖升高、恶性肿瘤、慢性肺部疾病、肝脏疾病、心脏病、卒中、肾脏疾病、消化系统疾病、情感及精神障碍、与记忆相关疾病、关节炎或风湿病和哮喘。研究对象被询问“您是否被医生诊断出患有以上慢性病?”,若回答“是”,则被认定患有此种慢性病。本研究的终点事件为慢性病共病。生存时间根据基线调查时间(2011年)至随访期内(2013―2020年)慢性病共病首次发生时间计算。
包括基线时年龄、性别、婚姻状况(在婚、非在婚)、文化程度(文盲、小学及以下、初中及以上)、居住地(城镇、农村)、吸烟(是/否)和饮酒(从不、≤1次/周、>1次/周)。
采用Stata 16.0软件进行数据分析。计量资料采用x±s表示,组间比较采用t检验;计数资料采用频数及构成比(%)表示,有序分类变量的组间比较采用秩和检验,其他类型变量的组间比较采用χ2检验。采用Kaplan-Meier生存曲线和log-rank检验比较组间的慢性病共病发生情况。应用Cox比例风险回归模型分析衰弱与慢性病共病风险的关联,模型1未调整任何协变量,模型2调整了基线年龄、性别、婚姻状况、文化程度和居住地,模型3进一步调整吸烟和饮酒状况。模型结果以风险比(hazard ratio, HR)和95% CI进行展示。检验水准α=0.05。
共纳入4 832名基线无慢性病共病者,平均年龄为(61.09±9.52)岁。2013―2020年,共有2 502人(51.78%)出现了新发慢性病共病。基线特征的比较分析显示,与未患慢性病共病者相比,新发慢性病共病者年龄更大、女性比例更高、文化程度更低,且从不饮酒和衰弱者的比例更高(均P < 0.05)。见表 1
本研究总样本的中位生存时间为7.00(95% CI: 6.82~7.18)年,在不同基线衰弱状态上,健壮期、衰弱前期和衰弱期中老年人的中位生存时间分别为9.00(因共病事件数较少,未能估计95% CI)年、7.00(95% CI: 6.75~7.25)年、7.00(95% CI: 6.74~7.26)年,经log-rank检验显示差异有统计学意义(χ2 =36.337, P < 0.001)。见图 1
模型1仅纳入衰弱状态构建单因素Cox比例风险回归模型,结果显示,在未控制其他协变量时,相较于健壮期,基线处于衰弱前期(HR=1.158, 95% CI: 1.067~1.257)、衰弱期(HR=1.548, 95% CI: 1.294~1.851)的中老年人新发慢性病共病的风险更高。模型2进一步纳入年龄、性别、婚姻状况、文化程度、居住地构建多因素Cox比例风险回归模型,发现基线处于衰弱前期(HR=1.130, 95% CI: 1.040~1.227)和衰弱期(HR=1.406, 95% CI: 1.168~1.692)的中老年人更有可能发生慢性病共病。模型3进一步调整吸烟和饮酒变量后,衰弱前期(HR=1.127, 95% CI: 1.035~1.227)和衰弱期(HR=1.363, 95% CI: 1.126~1.650)对慢性病共病发生的影响仍有统计学意义。此外,年龄与慢性病共病风险呈正相关(HR=1.011, 95% CI: 1.006~1.016)。见表 2
本研究发现,基线衰弱期可增加慢性病共病的发生风险,与既往研究结果类似。Hanlon等[11]分析了英国生物样本库共计493 737名中老年人的数据,发现衰弱与慢性病共病相关。另一项基于欧洲健康、老龄化和退休调查2011―2015年22 786名中老年人数据开展的研究显示,随着时间的推移,衰弱与慢性病共病间存在双向关联,衰弱可以预测慢性病共病发生,反之亦然[7]。衰弱增加慢性病共病发生风险的机制包括以下方面:首先,衰弱常伴随慢性炎症,体内促炎性细胞因子(如白细胞介素6、肿瘤坏死因子等)水平升高,可损伤血管内皮细胞、干扰胰岛素信号通路,进而增加心血管病、糖尿病等慢性病风险[12]。其次,衰弱状态下内分泌系统紊乱,下丘脑-垂体-肾上腺轴功能异常导致皮质醇分泌节律紊乱,干扰机体代谢并增加心血管病和糖尿病共病风险[13]。最后,衰弱个体氧化应激失衡,自由基生成与清除失衡导致体内氧化应激产物蓄积,损伤细胞大分子,引发心血管病、神经退行性疾病等[14]
此外,本研究发现,衰弱前期同样会增加中老年人慢性病共病的发生风险,凸显了衰弱前期是一个关键的干预窗口,为慢性病共病预防工作提供了新的有力证据。从生理角度来看,衰弱前期个体的身体功能虽未明显受损,但已开始出现衰退迹象,此时进行针对性干预更容易取得良好效果[15]。Mielke等[16]对社区老年人的衰弱状态转变进行纵向研究,发现约42%的研究对象存在衰弱状态的转变,虽然大部分转变是向更严重的衰弱状态发展,但也有部分向较轻的衰弱状态转变,这一现象表明衰弱是可逆的。而且,相较于衰弱者,处于衰弱前期者更有可能向健壮期转变[16]。鉴于此,应更加重视衰弱前期的早期识别。
本研究为“以衰弱为共病管理突破点”提供了关键证据[8],提示应将早期衰弱识别和管理融入慢性病共病防治过程中。在公共卫生政策层面,建议将衰弱评估纳入基本公共卫生服务项目,通过早期识别高危个体实现慢性病共病一级预防;定期开展针对基层医疗卫生人员的衰弱防治培训,提高其对衰弱的认识和管理能力。同时,加强健康教育宣传,提高中老年人对衰弱危害的认知度并增强自我防范意识,使其主动参与健康管理和生活方式的改善。在疾病预防体系中,应将衰弱作为慢性病预防的重要前置环节来抓,构建涵盖全生命周期的预防保健服务体系,在中青年时期积极开展健康教育,倡导戒烟限酒、合理膳食、规律运动等健康行为,从而降低中老年时期衰弱和慢性病共病的风险,以促进健康老龄化,减轻家庭和社会的疾病负担。
相较于以往多关注单一慢性病与衰弱关系的研究,本研究从多病共存的角度出发,涵盖心血管病、代谢性疾病、神经系统疾病等多种慢性病类别,在反映疾病负担总体水平的同时,更全面地揭示了衰弱对中老年人健康的影响,为老年人健康管理提供了新的视角。本研究存在的局限性:(1)慢性病是通过自我报告来定义的,某些研究对象可能由于记忆不清存在回忆偏倚;(2)本研究排除了基线因数据缺失而无法定义衰弱状态的研究对象,可能存在选择偏倚,衰弱和慢性病共病的真实关联强度可能被低估;(3)由于数据限制,本研究未能涵盖所有可能的慢性病类型和相关影响因素,如遗传因素、环境暴露等。未来研究可在此基础上进一步完善研究设计和数据收集,以更全面深入地揭示两者之间的关联和作用机制。
综上所述,中国中老年人群伴有衰弱期或衰弱前期发生慢性病共病的风险较高。研究结果提示,应将衰弱作为慢性病预防的重要前置环节,加强衰弱的早期识别,对衰弱前期和衰弱期的中老年人积极进行干预,以预防慢性病共病的发生,助力健康老龄化。
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2026年第30卷第2期
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doi: 10.16462/j.cnki.zhjbkz.2026.02.007
  • 接收时间:2025-06-27
  • 首发时间:2026-05-08
  • 出版时间:2026-02-10
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  • 收稿日期:2025-06-27
  • 修回日期:2025-10-15
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    1中日友好医院医改和医疗发展办公室,北京 100029
    2北京大学公共卫生学院,北京 100191
    3北京大学中国卫生发展研究中心,北京 100191

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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