Article(id=1324077918833484770, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077716676424398, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202509027, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1756742400000, receivedDateStr=2025-09-02, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614376027, onlineDateStr=2026-11-02, pubDate=1773072000000, pubDateStr=2026-03-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614376027, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614376027, creator=13701087609, updateTime=1793614376027, updator=13701087609, issue=Issue{id=1324077716676424398, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='5', pageStart='769', pageEnd='960', issueExtLink='null', onlineDate='null', pubDate='1773072000000', pubDateStr='2026-03-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614327830, creator='13701087609', updateTime=1793614418028, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078095132655884, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077716676424398, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078095132655885, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077716676424398, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=914, endPage=920, ext={EN=ArticleExt(id=1324077919026422755, articleId=1324077918833484770, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between physical activity and cardiometabolic multimorbidity among community-dwelling older adults, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the relationship between physical activity and cardiometabolic multimorbidity (CMM) among older adults in the community.

Methods

Using data from the 2020 China Health and Retirement Longitudinal Study(CHARLS), 9 076 older participants were included. Propensity score matching was employed to control for confounding factors in analyzing the association between physical activity and the number of cardiometabolic diseases. Multivariable logistic regression and restricted cubic spline models were used to evaluate the relationship between physical activity level (PAL) and CMM risk.

Results

Propensity score matching showed that sufficient physical activity was associated with an average reduction of 0.20 in the number of cardiometabolic diseases (ATT: -0.187~-0.225). Logistic regression indicated that a PAL ≥1 800 MET-min/week was significantly associated with lower CMM risk (1 800<PAL≤3 000: OR=0.814, 95% CI: 0.682-0.972; PAL≥3 000: OR=0.647, 95% CI: 0.572-0.732). The restricted cubic spline model revealed a nonlinear dose-response relationship between PAL and CMM risk (P for nonlinear <0.05). The risk of CMM decreased notably at a PAL around 3 800 MET min/week, and the association plateaued when PAL exceeded 8 000 MET min/week.

Conclusion

Physical activity is associated with a reduction in the number of cardiometabolic diseases. Maintaining an adequately high level of physical activity may have a positive effect on preventing CMM in older adults.

, authors=Ji-yi MA, Jia-lin WANG, Ying XIA, Qi AN, Ting LI, Fu-yu LI, Ying HUANG, Zi-qi AN, authorsList=Ji-yi MA, Jia-lin WANG, Ying XIA, Qi AN, Ting LI, Fu-yu LI, Ying HUANG, Zi-qi AN, authorCompany=null, correspAuthors=Jia-lin WANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, 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, fund=null), CN=ArticleExt(id=1324077927742186489, articleId=1324077918833484770, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=社区老年人体力活动与心血管代谢性共病的相关性分析, columnId=1228016572640461823, journalTitle=现代预防医学, columnName=健康与社会行为, runingTitle=null, highlight=null, articleAbstract=
目的

探讨体力活动与社区老年人心血管代谢性共病(cardiometabolic multimorbidity, CMM)的关系。

方法

基于2020年CHARLS的9 076名老年人数据,采用倾向得分匹配控制混杂,分析体力活动与疾病数量的关系;并利用多因素logistic回归和限制性立方样条评估体力活动水平(physical activity level , PAL)与CMM的关联。

结果

倾向得分匹配结果显示,充足的体力活动平均减少0.20个心血管代谢性疾病数量(ATT:-0.187~-0.225)。Logistic回归结果显示,当PAL≥1 800MET-min/week时,与较低的CMM风险显著相关(1 800<PAL≤3 000组:OR=0.814, 95% CI:0.682~0.972;PAL≥3 000组:OR=0.647,95% CI:0.572~0.732)。限制性立方样条提示,PAL与CMM风险之间存在非线性的剂量反应关系(P for nonlinear<0.05)。当PAL在3 800 MET-min/week处时,该活动水平与较低的CMM风险显著相关,PAL>8 000 MET-min/week时,关联强度趋于平稳。

结论

体力活动与心血管代谢性疾病数量减少有关,维持适量的高体力活动水平在预防老年人CMM方面具有积极意义。

, authors=马吉意, 王佳琳, 夏颖, 安琪, 李婷, 李馥余, 黄英, 安梓淇, authorsList=马吉意, 王佳琳, 夏颖, 安琪, 李婷, 李馥余, 黄英, 安梓淇, authorCompany=null, correspAuthors=王佳琳, authorNote=

马吉意(1996—),女,硕士在读,研究方向:临床护理

, correspAuthorsNote=
王佳琳,E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点,除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=76K+9r6ufhPg9DatgC57ZA==, magXml=BKrzrv9vHWhzvIiOLgDf2A==, pdfUrl=null, pdf=wLXO1AGxrfpNTvxj9myXeg==, pdfFileSize=886784, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=8EIX3HA65ur6A+Yf7TnCsg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=Yd9i3L1MjNvwr3in9qu2Iw==, mapNumber=null, fund=null)}, authors=[Author(id=1324077928283251710, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1324077928362943488, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, authorId=1324077928283251710, language=EN, stringName=Ji-yi MA, firstName=Ji-yi, middleName=null, lastName=MA, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1324077928471994368, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, authorId=1324077928283251710, language=CN, stringName=马吉意, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=成都中医药大学,四川 成都 610075, bio={"content":"

马吉意(1996—),女,硕士在读,研究方向:临床护理

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马吉意(1996—),女,硕士在读,研究方向:临床护理

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Front Cardiovasc Med, 2022,9: 966217., articleTitle=Effects of potential risk factors on the development of cardiometabolic multimorbidity and mortality among the elders in China, refAbstract=null), Reference(id=1324077946650107995, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, doi=null, pmid=null, pmcid=null, year=2024, volume=19, issue=1, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[26], rfOrder=27, authorNames=Xiao X, Beach J, Senthilselvan A, journalName=PLOS One, refType=null, unstructuredReference=Xiao X, Beach J, Senthilselvan A. Prevalence and determinants of multimorbidity in the Canadian population[J]. PLOS One, 2024, 19(1): e0297221., articleTitle=Prevalence and determinants of multimorbidity in the Canadian population, refAbstract=null), Reference(id=1324077946729799772, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, doi=null, pmid=null, pmcid=null, year=2023, volume=31, issue=2, pageStart=101, pageEnd=105, url=null, language=null, rfNumber=[27], rfOrder=28, authorNames=郭丹, 丁若溪, 何平, journalName=中国慢性病预防与控制, refType=null, unstructuredReference=郭丹,丁若溪,何平.中国老年人心血管代谢性共病的患病情况及影响因素研究[J].中国慢性病预防与控制,2023,31(2):101-105., articleTitle=中国老年人心血管代谢性共病的患病情况及影响因素研究, refAbstract=null), Reference(id=1324077946817880157, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, doi=null, pmid=null, pmcid=null, year=2023, volume=31, issue=2, pageStart=101, pageEnd=105, url=null, language=null, rfNumber=[27], rfOrder=29, authorNames=Guo D, Ding RX, He P, journalName=Chinese Journal of Prevention and Control of Chronic Diseases, refType=null, unstructuredReference=Guo D, Ding RX, He P. Prevalence and influencing factors of cardiometabolic multmorbidity in Chinese elderly[J]. Chinese Journal of Prevention and Control of Chronic Diseases, 2023, 31(2): 101-105. (In Chinese), articleTitle=Prevalence and influencing factors of cardiometabolic multmorbidity in Chinese elderly, refAbstract=null), Reference(id=1324077946889183326, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, doi=null, pmid=null, pmcid=null, year=2023, volume=107, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[28], rfOrder=30, authorNames=Qin K, Bai SG, Chen WQ, journalName=Archives of Gerontology and Geriatrics, refType=null, unstructuredReference=Qin K, Bai SG, Chen WQ, et al. Association of comorbid depression and obesity with cardiometabolic multimorbidity among middle-aged and older Chinese adults: A cohort study[J]. Archives of Gerontology and Geriatrics, 2023, 107: 104912., articleTitle=Association of comorbid depression and obesity with cardiometabolic multimorbidity among middle-aged and older Chinese adults: A cohort study, refAbstract=null), Reference(id=1324077946964680799, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, doi=null, pmid=null, pmcid=null, year=2020, volume=11, issue=null, pageStart=1, pageEnd=21, url=null, language=null, rfNumber=[29], rfOrder=31, authorNames=Hendriks HFJ, journalName=Annual Review of Food Science and Technology, refType=null, unstructuredReference=Hendriks HFJ. Alcohol and human health: what is the evidence?[J].Annual Review of Food Science and Technology, 2020, 11: 1-21., articleTitle=Alcohol and human health: what is the evidence?, refAbstract=null)], funds=[Fund(id=1324077941113626684, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, awardId=2024BS015, language=CN, fundingSource=成都市哲学社会科学规划项目(2024BS015), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324077928182588410, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, xref=null, ext=[AuthorCompanyExt(id=1324077928195171323, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, companyId=1324077928182588410, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China), AuthorCompanyExt(id=1324077928207754236, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, companyId=1324077928182588410, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=成都中医药大学,四川 成都 610075)])], figs=[ArticleFig(id=1324077936877379630, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=EN, label=Figure 1, caption=Flowchart of screening and exclusion criteria for participants, figureFileSmall=YXyUuuHuSQYXMVEBZHnbnw==, figureFileBig=8EIX3HA65ur6A+Yf7TnCsg==, tableContent=null), ArticleFig(id=1324077936944488495, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=CN, label=图1, caption=受访者筛选和排除标准流程图, figureFileSmall=YXyUuuHuSQYXMVEBZHnbnw==, figureFileBig=8EIX3HA65ur6A+Yf7TnCsg==, tableContent=null), ArticleFig(id=1324077937372307504, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=EN, label=Figure 2, caption=Propensity score distributions of the treatment and control groups before and after matching, figureFileSmall=Xl5qf35bStZlm1khg5Egjg==, figureFileBig=k+oGaxyarAY/6pnIajE5+w==, tableContent=null), ArticleFig(id=1324077937653325873, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=CN, label=图2, caption=匹配前后处理组和对照组的倾向得分分布, figureFileSmall=Xl5qf35bStZlm1khg5Egjg==, figureFileBig=k+oGaxyarAY/6pnIajE5+w==, tableContent=null), ArticleFig(id=1324077937745600562, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=EN, label=Figure 3, caption=Dose-response relationship between physical activity level and CMM, figureFileSmall=0cdylhjRS+A1152T1eevsQ==, figureFileBig=lJ8RdtZgjG1udaFnsMOAsg==, tableContent=null), ArticleFig(id=1324077938186002483, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=CN, label=图3, caption=PAL与CMM的剂量反应关系, figureFileSmall=0cdylhjRS+A1152T1eevsQ==, figureFileBig=lJ8RdtZgjG1udaFnsMOAsg==, tableContent=null), ArticleFig(id=1324077938500575284, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=EN, label=Table 1, caption=

Participant characteristics [n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人数
(n=9 076)
CMD数量(种)Z/H值P值
0(n=2 994)1(n=2 662)2(n=1 726)3(n=1 104)≥4(n=590)
体力活动8.285<0.001
否1 645(18.10)430(26.14)466(28.33)349(21.22)252(15.32)148(9.00)
是7 431(81.90)2 564(34.50)2 196(29.55)1 377(18.53)852(11.47)442(5.95)
年龄(岁)47.041<0.001
60~695 860(64.60)2 058(35.12)1 692(28.87)1 077(18.38)686(11.70)347(5.92)
70~792 676(29.50)764(28.55)780(29.15)559(20.90)350(13.08)223(8.34)
≥80540(6.00)172(31.85)190(35.19)90(16.67)68(12.59)20(3.70)
性别-8.740<0.001
男4 460(49.10)1 638(36.73)1 303(29.21)815(18.27)466(10.45)238(5.34)
女4 616(50.90)1 356(29.37)1 359(29.44)911(19.73)638(13.82)352(7.63)
教育程度22.9780.001
文盲2 560(28.20)860(33.60)801(31.29)468(18.28)280(10.94)151(5.89)
小学4 109(45.30)1 401(34.09)1 178(28.67)765(18.62)497(12.10)268(6.52)
中学1 482(16.30)466(31.44)436(29.42)293(19.77)181(12.21)106(7.15)
高中及以上925(10.20)267(28.86)247(26.70)200(21.62)146(15.78)65(7.03)
婚姻状况-4.254<0.001
在婚7 167(79.00)2 440(34.04)2 073(28.92)1 369(19.10)850(11.86)435(6.07)
不在婚1 909(21.00)554(29.02)589(30.86)357(18.69)254(13.31)155(8.12)
居住地-8.664<0.001
农村5 991(66.00)2 088(34.85)1 826(30.48)1 123(18.74)616(10.28)338(5.64)
城市3 085(34.00)906(29.37)836(27.09)603(19.55)488(15.82)252(8.17)
饮酒9.942<0.001
否6 036(66.50)1 836(30.42)1 728(28.63)1 207(20.00)800(13.25)465(7.70)
是3 040(33.50)1 158(38.10)934(30.72)519(17.07)304(9.99)125(4.11)
吸烟6.389<0.001
否5 289(58.30)1 636(30.93)1 538(29.08)1 026(19.39)699(13.22)390(7.37)
是3 787(41.70)1 358(35.86)1 124(29.68)700(18.48)405(10.69)200(5.28)
身体疼痛-14.917<0.001
无3 671(40.50)1 478(40.26)1 103(30.05)607(16.53)336(9.15)147(4.00)
有5 405(59.60)1 516(28.05)1 559(28.84)1 119(20.70)768(14.21)443(8.19)
睡眠时长(h)46.151<0.001
≤65 617(61.90)1 741(31.00)1 633(29.07)1 097(19.53)721(12.84)425(7.57)
6~81 457(16.10)550(37.75)419(28.76)266(18.25)143(9.81)79(5.42)
≥82 002(22.10)703(35.12)610(30.47)363(18.13)240(11.99)86(4.29)
自评健康状况747.139<0.001
很好911(10.00)472(51.81)262(28.76)116(12.73)50(5.49)11(1.21)
好1 006(11.10)476(47.32)303(30.12)143(14.21)62(6.16)22(2.19)
一般4 564(50.30)1 537(33.68)1 440(31.55)859(18.82)507(11.11)221(4.84)
不好1 925(21.20)401(20.83)481(24.99)460(23.89)360(18.69)223(11.59)
很不好670(7.40)108(16.12)176(26.27)148(22.09)125(18.66)113(16.87)
生活满意度38.886<0.001
极其满意395(4.40)121(30.63)130(32.91)89(22.53)36(9.11)19(4.81)
非常满意3 021(33.30)1 069(35.38)877(29.03)575(18.99)327(10.82)173(5.72)
比较满意4 722(52.00)1 546(32.74)1 394(29.52)876(18.55)588(12.45)318(6.73)
不太满意672(7.40)191(28.42)193(28.72)128(19.05)108(16.07)52(7.74)
非常不满意266(2.90)67(25.19)68(25.56)58(21.80)45(16.92)28(10.53)
抑郁-11.050<0.001
无5 365(59.10)1 936(36.09)1 643(30.62)954(17.78)579(10.80)253(4.72)
有3 711(40.90)1 058(28.51)1 019(27.46)772(20.80)525(14.15)337(9.08)
), ArticleFig(id=1324077938601238581, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=CN, label=表1, caption=

参与者特征[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人数
(n=9 076)
CMD数量(种)Z/H值P值
0(n=2 994)1(n=2 662)2(n=1 726)3(n=1 104)≥4(n=590)
体力活动8.285<0.001
否1 645(18.10)430(26.14)466(28.33)349(21.22)252(15.32)148(9.00)
是7 431(81.90)2 564(34.50)2 196(29.55)1 377(18.53)852(11.47)442(5.95)
年龄(岁)47.041<0.001
60~695 860(64.60)2 058(35.12)1 692(28.87)1 077(18.38)686(11.70)347(5.92)
70~792 676(29.50)764(28.55)780(29.15)559(20.90)350(13.08)223(8.34)
≥80540(6.00)172(31.85)190(35.19)90(16.67)68(12.59)20(3.70)
性别-8.740<0.001
男4 460(49.10)1 638(36.73)1 303(29.21)815(18.27)466(10.45)238(5.34)
女4 616(50.90)1 356(29.37)1 359(29.44)911(19.73)638(13.82)352(7.63)
教育程度22.9780.001
文盲2 560(28.20)860(33.60)801(31.29)468(18.28)280(10.94)151(5.89)
小学4 109(45.30)1 401(34.09)1 178(28.67)765(18.62)497(12.10)268(6.52)
中学1 482(16.30)466(31.44)436(29.42)293(19.77)181(12.21)106(7.15)
高中及以上925(10.20)267(28.86)247(26.70)200(21.62)146(15.78)65(7.03)
婚姻状况-4.254<0.001
在婚7 167(79.00)2 440(34.04)2 073(28.92)1 369(19.10)850(11.86)435(6.07)
不在婚1 909(21.00)554(29.02)589(30.86)357(18.69)254(13.31)155(8.12)
居住地-8.664<0.001
农村5 991(66.00)2 088(34.85)1 826(30.48)1 123(18.74)616(10.28)338(5.64)
城市3 085(34.00)906(29.37)836(27.09)603(19.55)488(15.82)252(8.17)
饮酒9.942<0.001
否6 036(66.50)1 836(30.42)1 728(28.63)1 207(20.00)800(13.25)465(7.70)
是3 040(33.50)1 158(38.10)934(30.72)519(17.07)304(9.99)125(4.11)
吸烟6.389<0.001
否5 289(58.30)1 636(30.93)1 538(29.08)1 026(19.39)699(13.22)390(7.37)
是3 787(41.70)1 358(35.86)1 124(29.68)700(18.48)405(10.69)200(5.28)
身体疼痛-14.917<0.001
无3 671(40.50)1 478(40.26)1 103(30.05)607(16.53)336(9.15)147(4.00)
有5 405(59.60)1 516(28.05)1 559(28.84)1 119(20.70)768(14.21)443(8.19)
睡眠时长(h)46.151<0.001
≤65 617(61.90)1 741(31.00)1 633(29.07)1 097(19.53)721(12.84)425(7.57)
6~81 457(16.10)550(37.75)419(28.76)266(18.25)143(9.81)79(5.42)
≥82 002(22.10)703(35.12)610(30.47)363(18.13)240(11.99)86(4.29)
自评健康状况747.139<0.001
很好911(10.00)472(51.81)262(28.76)116(12.73)50(5.49)11(1.21)
好1 006(11.10)476(47.32)303(30.12)143(14.21)62(6.16)22(2.19)
一般4 564(50.30)1 537(33.68)1 440(31.55)859(18.82)507(11.11)221(4.84)
不好1 925(21.20)401(20.83)481(24.99)460(23.89)360(18.69)223(11.59)
很不好670(7.40)108(16.12)176(26.27)148(22.09)125(18.66)113(16.87)
生活满意度38.886<0.001
极其满意395(4.40)121(30.63)130(32.91)89(22.53)36(9.11)19(4.81)
非常满意3 021(33.30)1 069(35.38)877(29.03)575(18.99)327(10.82)173(5.72)
比较满意4 722(52.00)1 546(32.74)1 394(29.52)876(18.55)588(12.45)318(6.73)
不太满意672(7.40)191(28.42)193(28.72)128(19.05)108(16.07)52(7.74)
非常不满意266(2.90)67(25.19)68(25.56)58(21.80)45(16.92)28(10.53)
抑郁-11.050<0.001
无5 365(59.10)1 936(36.09)1 643(30.62)954(17.78)579(10.80)253(4.72)
有3 711(40.90)1 058(28.51)1 019(27.46)772(20.80)525(14.15)337(9.08)
), ArticleFig(id=1324077938689318966, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=EN, label=Table 2, caption=

Results of ordered logistic regression analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
变量粗模型模型1模型2
β β β
体力活动-0.405***0.049-0.403***0.049-0.299***0.050
性别0.391***0.0410.191***0.059
年龄0.112***0.0310.078*0.032
婚姻状况0.0720.0480.0830.049
教育程度0.148***0.0230.181**0.023
居住地0.266***0.0430.388***0.044
吸烟-0.0320.055
饮酒-0.209***0.044
身体疼痛0.238***0.043
生活满意度-0.072**0.025
睡眠时长-0.0170.023
自评健康状况0.478***0.023
抑郁0.138**0.044
N9 0769 0769 076
R20.0030.0080.04
), ArticleFig(id=1324077938915811383, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=CN, label=表2, caption=

有序logistic回归分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量粗模型模型1模型2
β β β
体力活动-0.405***0.049-0.403***0.049-0.299***0.050
性别0.391***0.0410.191***0.059
年龄0.112***0.0310.078*0.032
婚姻状况0.0720.0480.0830.049
教育程度0.148***0.0230.181**0.023
居住地0.266***0.0430.388***0.044
吸烟-0.0320.055
饮酒-0.209***0.044
身体疼痛0.238***0.043
生活满意度-0.072**0.025
睡眠时长-0.0170.023
自评健康状况0.478***0.023
抑郁0.138**0.044
N9 0769 0769 076
R20.0030.0080.04
), ArticleFig(id=1324077938999697464, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=EN, label=Table 3, caption=

Average treatment effect of physical activity on the number of cardiometabolic diseases among older adults

, figureFileSmall=null, figureFileBig=null, tableContent=
方法处理组对照组ATT标准误差
K 近邻匹配1.2511.439-0.187***0.042
卡尺匹配1.2511.438-0.187***0.042
核匹配1.2511.477-0.225***0.037
半径匹配1.2511.456-0.204***0.037
), ArticleFig(id=1324077940694196281, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=CN, label=表3, caption=

体力活动对老年CMD数量的平均处理效应

, figureFileSmall=null, figureFileBig=null, tableContent=
方法处理组对照组ATT标准误差
K 近邻匹配1.2511.439-0.187***0.042
卡尺匹配1.2511.438-0.187***0.042
核匹配1.2511.477-0.225***0.037
半径匹配1.2511.456-0.204***0.037
), ArticleFig(id=1324077940786470970, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=EN, label=Table 4, caption=

Logistic regression results for the association between physical activity level and cardiometabolic multimorbidity risk

, figureFileSmall=null, figureFileBig=null, tableContent=
变量人数病例数OR(95%CI)P值
PAL(MET-min/week)
<600(参照)1 6457491.00
≥600~<1 2004421790.834(0.665~1.044)0.114
≥1 200~<1 8001 2695590.971(0.830~1.137)0.724
≥1 800~<3 0008763600.814(0.682~0.972)0.023
≥3 0004 8441 5730.647(0.572~0.732)<0.001
N9 076
R20.08
), ArticleFig(id=1324077940861968443, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077918833484770, language=CN, label=表4, caption=

不同PAL与CMM风险关联的logistic 回归分析结果

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变量人数病例数OR(95%CI)P值
PAL(MET-min/week)
<600(参照)1 6457491.00
≥600~<1 2004421790.834(0.665~1.044)0.114
≥1 200~<1 8001 2695590.971(0.830~1.137)0.724
≥1 800~<3 0008763600.814(0.682~0.972)0.023
≥3 0004 8441 5730.647(0.572~0.732)<0.001
N9 076
R20.08
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社区老年人体力活动与心血管代谢性共病的相关性分析
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马吉意 , 王佳琳 , 夏颖 , 安琪 , 李婷 , 李馥余 , 黄英 , 安梓淇
现代预防医学 | 健康与社会行为 2026,53(5): 914-920
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现代预防医学 |健康与社会行为 2026 , 53 (5) : 914 -920
社区老年人体力活动与心血管代谢性共病的相关性分析
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马吉意, 王佳琳 , 夏颖, 安琪, 李婷, 李馥余, 黄英, 安梓淇
作者信息
  • 成都中医药大学,四川 成都 610075
通讯作者:
王佳琳,E-mail:
作者简介:

马吉意(1996—),女,硕士在读,研究方向:临床护理

Association between physical activity and cardiometabolic multimorbidity among community-dwelling older adults
Ji-yi MA, Jia-lin WANG , Ying XIA, Qi AN, Ting LI, Fu-yu LI, Ying HUANG, Zi-qi AN
Affiliations
  • Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
出版时间: 2026-03-10 doi: 10.20043/j.cnki.MPM.202509027
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目的

探讨体力活动与社区老年人心血管代谢性共病(cardiometabolic multimorbidity, CMM)的关系。

方法

基于2020年CHARLS的9 076名老年人数据,采用倾向得分匹配控制混杂,分析体力活动与疾病数量的关系;并利用多因素logistic回归和限制性立方样条评估体力活动水平(physical activity level , PAL)与CMM的关联。

结果

倾向得分匹配结果显示,充足的体力活动平均减少0.20个心血管代谢性疾病数量(ATT:-0.187~-0.225)。Logistic回归结果显示,当PAL≥1 800MET-min/week时,与较低的CMM风险显著相关(1 800<PAL≤3 000组:OR=0.814, 95% CI:0.682~0.972;PAL≥3 000组:OR=0.647,95% CI:0.572~0.732)。限制性立方样条提示,PAL与CMM风险之间存在非线性的剂量反应关系(P for nonlinear<0.05)。当PAL在3 800 MET-min/week处时,该活动水平与较低的CMM风险显著相关,PAL>8 000 MET-min/week时,关联强度趋于平稳。

结论

体力活动与心血管代谢性疾病数量减少有关,维持适量的高体力活动水平在预防老年人CMM方面具有积极意义。

心血管代谢性共病  /  体力活动  /  倾向得分匹配  /  限制性立方样条  /  CHARLS数据
Objective

To explore the relationship between physical activity and cardiometabolic multimorbidity (CMM) among older adults in the community.

Methods

Using data from the 2020 China Health and Retirement Longitudinal Study(CHARLS), 9 076 older participants were included. Propensity score matching was employed to control for confounding factors in analyzing the association between physical activity and the number of cardiometabolic diseases. Multivariable logistic regression and restricted cubic spline models were used to evaluate the relationship between physical activity level (PAL) and CMM risk.

Results

Propensity score matching showed that sufficient physical activity was associated with an average reduction of 0.20 in the number of cardiometabolic diseases (ATT: -0.187~-0.225). Logistic regression indicated that a PAL ≥1 800 MET-min/week was significantly associated with lower CMM risk (1 800<PAL≤3 000: OR=0.814, 95% CI: 0.682-0.972; PAL≥3 000: OR=0.647, 95% CI: 0.572-0.732). The restricted cubic spline model revealed a nonlinear dose-response relationship between PAL and CMM risk (P for nonlinear <0.05). The risk of CMM decreased notably at a PAL around 3 800 MET min/week, and the association plateaued when PAL exceeded 8 000 MET min/week.

Conclusion

Physical activity is associated with a reduction in the number of cardiometabolic diseases. Maintaining an adequately high level of physical activity may have a positive effect on preventing CMM in older adults.

Cardiometabolic multimorbidity  /  Physical activity  /  Propensity score matching  /  Restricted cubic spline  /  CHARLS
马吉意, 王佳琳, 夏颖, 安琪, 李婷, 李馥余, 黄英, 安梓淇. 社区老年人体力活动与心血管代谢性共病的相关性分析. 现代预防医学, 2026 , 53 (5) : 914 -920 . DOI: 10.20043/j.cnki.MPM.202509027
Ji-yi MA, Jia-lin WANG, Ying XIA, Qi AN, Ting LI, Fu-yu LI, Ying HUANG, Zi-qi AN. Association between physical activity and cardiometabolic multimorbidity among community-dwelling older adults[J]. Modern Preventive Medicine, 2026 , 53 (5) : 914 -920 . DOI: 10.20043/j.cnki.MPM.202509027
共病是指个体同时患有两种及以上慢性病。2024年数据显示,中国约半数老人正受共病困扰[1],其中心血管代谢性共病(cardiometabolic multimorbidity, CMM)最为常见[2],指同时患有两种及以上心血管代谢性疾病(cardiometabolic disease,CMD),如糖尿病、心脏病、高血压等。研究表明,与健康人群或单一CMD患者相比,CMM患者死亡风险增加3.7~6.9倍,预期寿命缩短,且家庭及社会负担显著增加[3]。体力活动(physical activity)作为经济有效的慢性病防控手段,具有多重健康益处[4-5]。然而,既往研究多聚焦单一疾病[6-7],较少关注体力活动与疾病数量的关联。此外,老年人体力活动行为易受人口学特征、健康状况与生活方式等因素影响,传统观察性研究难以有效控制此类混杂,易产生选择偏倚。倾向得分匹配(propensity score matching, PSM)可通过平衡处理组与对照组的基线特征来模拟随机试验,提高效应估计的准确性[8]。因此,本研究基于中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS)数据,采用PSM方法控制选择偏倚,量化社区老年人体力活动与CMD数量的关系,并探讨其与CMM的关联,以期为该人群的体力活动管理与干预提供实证依据。
本研究数据来源于CHARLS 2020年第五波数据。该数据调查范围覆盖全国28个省的150个县级单位以及450个社区(村),样本具有全国代表性。
本研究的纳入标准:受访者必须年满60岁并有户籍。排除标准:变量缺失、回答不知道或拒绝回答。经过筛选变量和数据清洗后保留了9 076个样本,见图1。
本研究中,CMD包含高血压、糖尿病、心脏病、脑卒中和血脂异常五类,依据患者自我报告的医生诊断进行定义。根据同时患有上述疾病的数量(0、1、2、3和≥4种),将受访者分为五组。将患有至少两种CMD者定义为CMM,其余为非CMM。
CHARLS记录了参与者每周至少进行10 min的体力活动类型、天数以及持续时间。活动分为三类:(1)剧烈体力活动:耕作、负重骑行等,代谢当量(metabolic equivalent, MET)赋值为8.0;(2)中等强度体力活动:疾走、打太极拳等,MET为4.0;(3)低强度体力活动:如日常步行、居家移动等,MET为3.3[9]。每日活动持续时间经中间值转换为20、75、180和240 min。总体力活动水平(physical activity level, PAL)根据国际体力活动问卷(International Physical Activity Questionnaire, IPAQ)标准,计算为MET ×每日活动时长(min)×每周活动天数[10]。IPAQ已在中国人群中得到验证和应用,具有良好的信效度[11]。参考IPAQ标准[10],本研究将PAL ≥600 MET-min/week定义为活动充足组(即体力活动组),低于该值则为活动不足组(非体力活动组);PAL进一步分为低水平(<600 MET-min/week)、中等水平(600~3 000 MET-min/week)和高水平(>3 000 MET-min/week)。为增强结果可比性,参考既往研究[12],本研究将体力活动分为五个组别:PAL≤600、600≤PAL<1 200、1 200≤PAL<1 800、1 800≤PAL<3 000、PAV≥3 000,单位为MET-min/week。
基于既往文献[13],本研究调整了以下可能影响体力活动与CMD关系的混杂变量。(1)身体疼痛:依据“身体哪些部位感到疼痛?”的回答,报告任一部位疼痛即定义为存在疼痛。(2)睡眠时长:按自我报告每晚实际睡眠时间,划分为<6 h、6~8 h和>8 h[13]。(3)自评健康状况:基于“现在的身体情况怎么样?”的回答,选项为“很好,好,一般,不好,很不好”。(4)生活满意度:基于“您对自己的生活是否感到满意?”的回答,选项为“极其满意,非常满意,比较满意,不太满意,一点也不满意”。(5)抑郁:CHARLS问卷中,使用流行病学研究中心抑郁量表-10项(CESD-10)评估,得分≥10分的参与者被认为有抑郁症状[14]。同时还调整年龄、性别、教育程度、婚姻状况、居住地、吸烟及饮酒等协变量。
采用stata 17.0软件进行统计分析。分类变量以频数(%)形式描述,组间比较分别使用Wilcoxon秩和检验(二分类)与Kruskal-Wallis检验(多分类)。使用有序logistic回归来评估体力活动与CMD数量的关系。此外,PSM用于控制受访者的选择偏倚,为了确保估计的准确性,使用最近邻匹配、半径匹配和核匹配来检验结果的稳健性。随后,使用logistic回归比值比(odds ratio, OR)来分析PAL与CMM之间的关联,并运用R 4.1.0软件绘制限制性立方样条图,探讨总PAL与CMM之间的剂量-反应关系,检验水准α=0.05。
PSM具体通过三个步骤实现[8]:
(1)基于logit模型估计个体参与体力活动的概率(即倾向得分)。P(Xi)为个体i的倾向得分。
(2)依据倾向得分对处理组与对照组进行匹配。采用1:3近邻匹配并设置0.01卡钳值,通过平衡性检验确保匹配后两组协变量分布无显著差异(标准化偏差<10%)。
(3)基于匹配样本计算体力活动的平均处理效应(average treatment effect on the treated,ATT)。其中Di为二元变量(Di=1表示体力活动组,Di=0表示非体力活动组);Y1i为处理组老年人的CMD数量,Y0i为对照组老年人的CMD数量。
本研究共纳入9 076名参与者,平均年龄为(68.22±6.14)岁,CMM患病率为37.7%。不同疾病数量的组间,所有社会人口学及健康相关因素均存在差异(P<0.05)。与患病数量较少者相比,患病数量更多的老年人更可能体力活动不足、高龄为女性、居住在城市、不饮酒、不吸烟、更可能伴有身体疼痛、睡眠时长过短、自评健康差、生活满意度低及有抑郁症状。见表1。
有序logistic回归分析满足平行回归假设(Brant检验,P>0.05)。分析构建了三个模型:粗模型未调整变量;模型1调整人口学变量(年龄、性别、教育、婚姻、居住地);模型2进一步纳入健康相关变量(疼痛、饮酒、吸烟、睡眠、生活满意度、自评健康状况、抑郁)。模型2结果显示,体力活动与疾病数量呈负相关(β=-0.299, sx= 0.05, P<0.001)。性别、年龄、教育程度、居住地、身体疼痛、自评健康状况、饮酒及抑郁与疾病数量显著相关(P<0.05),见表2。在后续PSM分析中,上述显著变量均作为控制变量纳入。
总样本共9 076例,其中处理组7 431例,对照组1 645例。匹配后9 018例(99.4%)纳入分析,其中处理组7 374例,对照组1 644例,样本损失率(0.64%)较低,匹配效率良好。匹配前,两组倾向得分分布存在偏移,匹配后,核密度曲线基本重叠,协变量分布得到有效平衡,见图2。平衡检验显示,所有变量标准化均数差均<10%,且组间差异无统计学意义(P>0.05),符合匹配质量要求。表明PSM有效减少了混杂偏倚,增强了组间可比性。
采用四种匹配方法(K近邻、卡尺、半径与核匹配)估计体力活动的ATT,并验证其与疾病数量关联的稳健性。如表3所示,所有方法均得到一致且显著的结果(ATT范围:-0.187~-0.225)。表明在控制混杂因素后,体力活动平均可减少约0.2个疾病数量。
多因素logistic回归分析显示,与参照组(PAL<600MET-min/week)相比,较高的PAL与较低的CMM风险相关,1 800≤PAL<3 000组OR=0.814(95% CI:0.682~0.972)、PAL≥3 000组OR=0.647(95% CI: 0.572~0.732)。见表4。
限制性立方样条分析中选取4个结,分别位于第5、35、65和第95百分位数,在调整了人口学变量和健康相关因素后,结果显示PAL与CMM风险之间存在非线性的剂量反应关系(P for nonlinear<0.05)。当PAL在约1 800 MET-min/week时,CMM风险开始下降,并在3 800 MET-min/week处出现明显拐点,该活动水平与较低的CMM风险相关,当PAL达到8 000 MET-min/week时,CMM风险下降趋势趋于平稳。见图3。
运动干预对CMD具有多方面的保护作用。早期研究证实体育锻炼可降低心血管等慢性病患者过早死亡风险[5],并有助于缓解抑郁、焦虑,提升生活质量与社会联结[15]。基于CHARLS数据,本研究发现,在控制混杂因素后,规律体力活动与老年CMM负荷降低相关,平均减少约0.2种疾病(ATT:-0.187~-0.225),这与既有研究相互印证[16-17]。作用机制可能在于规律体力活动可以通过增强脂肪酸氧化能力,减少内脏脂肪堆积,改善胰岛素敏感性及糖脂代谢稳态;还可改善血流介导的血管舒张功能,增加冠状动脉血流储备,提升心肌灌注[18]。这些机制协同作用,共同缓解了CMD的发生发展。
本研究采用多因素logistic回归和限制性立方样条分析发现,PAL与CMM风险之间呈显著非线性负相关。Logistic回归结果显示,当PAL≥1 800 MET-min/week时,CMM的风险显著降低;限制性立方样条模型进一步揭示了PAL与CMM风险之间存在剂量-反应关系,当PAL达到约3 800 MET-min/week时,其与CMM风险的负向关联程度开始显著。两种分析结果的差异可能与统计方法的特征有关,分组logistic回归反映区间平均效应,而限制性立方样条模型能更精细刻画连续变化趋势[19]。本研究结果提示,适度提升PAL有助于降低CMM风险,且当PAL达到约3 800 MET-min/周时,健康获益更为显著。本研究观察到的PAL高于世界卫生组织推荐的最低活动量[20],但与部分既往研究[18,21]结果相近。例如,一项队列研究发现,在患有三种及以上慢性病的老年人中,较高的PAL与较低的多病患病率关联尤为明显[18]。这可能是因为多病共存涉及复杂的病理机制,需要更高的活动水平才能观察到显著的关联效应。此外,本研究发现PAL与CMM风险之间的关系呈非线性特征,当PAL达到约8 000 MET-min/week时,风险下降趋势趋于平稳,提示进一步增加活动量未必能带来额外的保护效应,该结果与既往部分研究结论存在共性[22-23]。有研究认为,过量活动可能通过诱发氧化应激等机制,部分抵消其积极影响[24]。因此,倡导规律、适量的较高水平体力活动,有助于更有效地防控CMM。然而,目前关于最佳活动区间与安全上限的证据仍不充分,未来需在中国人群中进行更深入的研究,以明确适宜的PAL范围及其长期健康效应。
有序logistic回归发现,高龄、女性、城市居住、较高教育程度及抑郁状态与老年人患CMM风险升高相关。年龄增长伴随的器官与代谢功能衰退可增加患病风险[25]。女性风险较高可能与绝经后雌激素变化影响脂代谢有关[26]。城市居民、较高教育程度者与CMM的高风险关联,可能与医疗可及性高导致的检出偏倚有关,这一发现与部分中低收入国家研究一致[25,27],但与发达国家常见的社会经济地位负相关模式不同[26],提示关联可能存在地域差异。有研究指出,抑郁可通过促进炎症、影响神经内分泌等机制增加CMM风险[28]。此外,研究观察到饮酒与较低的CMM风险相关,此结果与Han等人[29]研究提示适度饮酒具有保护作用的发现相符,但其关系仍需进一步探讨。因此,建议对高龄、女性、抑郁等高风险老年群体开展针对性健康管理,并鼓励规律体力活动,以降低CMM负担。
本研究存在以下局限性。一方面,横断面设计无法确定因果关系。另一方面,体力活动与睡眠时长均依赖自我报告,可能存在回忆偏倚,且未能纳入静坐时间这一潜在混杂因素;此外,饮酒仅以二分类评估,无法反映实际饮酒模式,可能造成暴露错误分类;在方法学上,由于疾病病因复杂,logistic回归的解释力度有限。未来建议采用前瞻性设计,结合客观测量,以深入探讨体力活动与CMM的长期关系。
本研究表明,规律体力活动与老年人CMD数量呈负相关,当每周总体力活动量达到3 800 MET-min及以上时,与较低的CMM患病风险显著相关。该结果提示维持较高PAL在预防老年人CMM方面具有积极意义,可为老年群体健康管理策略的制定提供参考依据。
  • 成都市哲学社会科学规划项目(2024BS015)
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2026年第53卷第5期
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doi: 10.20043/j.cnki.MPM.202509027
  • 接收时间:2025-09-02
  • 首发时间:2026-11-02
  • 出版时间:2026-03-10
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  • 收稿日期:2025-09-02
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成都市哲学社会科学规划项目(2024BS015)
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    成都中医药大学,四川 成都 610075

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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
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