Article(id=1324077930715951208, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077868950631142, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202510069, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1760112000000, receivedDateStr=2025-10-11, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614378860, onlineDateStr=2026-11-02, pubDate=1771948800000, pubDateStr=2026-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614378860, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614378860, creator=13701087609, updateTime=1793614378860, updator=13701087609, issue=Issue{id=1324077868950631142, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='4', pageStart='577', pageEnd='768', issueExtLink='null', onlineDate='null', pubDate='1771948800000', pubDateStr='2026-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614364134, creator='13701087609', updateTime=1793614446224, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078213328142371, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077868950631142, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078213332336676, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077868950631142, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=707, endPage=712, ext={EN=ArticleExt(id=1324077931991019625, articleId=1324077930715951208, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between cardiovascular health and cognitive function trajectories among middle-aged and elderly Chinese adults, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the association between Cardiovascular Health (CVH) and cognitive function trajectories.

Methods

Data were obtained from five waves (2011-2020) of the China Health and Retirement Longitudinal Study (CHARLS), including participants aged ≥45 years. CVH was assessed using six indicators: tobacco exposure, sleep, body mass index (BMI), non-high-density lipoprotein cholesterol (non-HDL-C), blood glucose, and blood pressure. Group-based trajectory modeling was applied to identify trajectories of cognitive function, and multinomial logistic regression was used to evaluate the association between CVH and cognitive function trajectories.

Results

A total of 5 774 participants was included. Four cognitive trajectories were identified: low-declining, medium-declining, medium-stable and high-stable. Compared with the high-stable group, each one-point increase in CVH score was associated with a reduced risk of entering the low-decline, medium-decline, and medium-stable groups by approximately 1.4%, 0.8%, and 0.5%, respectively (all P<0.01). Tobacco exposure, sleep, and blood pressure were consistently associated with cognitive trajectories (P<0.05), while BMI and non-HDL-C showed significance in selected comparisons.

Conclusion

CVH in middle-aged and older adults is positively associated with cognitive function trajectories. Tobacco exposure, sleep, BMI, non-HDL-C, and blood pressure emerge as key influencing factors. Enhancing CVH, especially through midlife strategies focusing on modifiable lifestyle behaviors and metabolic indicators within an integrated “heart-brain prevention” framework, may represent a promising avenue to mitigate or delay cognitive decline.

, authors=Xia ZHANG1, Qin WANG1, Yu-ting LIANG1, Ming-lei FANG1, Lin-lin LI1, 2, Yan ZHANG3, Qi-rong QIN3, Fen HUANG4, Ye-huan SUN5, Jie LI1, authorsList=Xia ZHANG, Qin WANG, Yu-ting LIANG, Ming-lei FANG, Lin-lin LI, Yan ZHANG, Qi-rong QIN, Fen HUANG, Ye-huan SUN, Jie LI, authorCompany=null, correspAuthors=Jie LI, 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=1324077933614215276, articleId=1324077930715951208, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=中国中老年人心血管健康与认知功能发展轨迹的关联研究, columnId=1228016572640461823, journalTitle=现代预防医学, columnName=健康与社会行为, runingTitle=null, highlight=null, articleAbstract=
目的

探索心血管健康(CVH)与认知功能发展轨迹的关联。

方法

基于中国健康与养老追踪调查(CHARLS)2011—2020年五次调查数据,纳入45岁及以上人群。采用烟草暴露、睡眠、体质指数(BMI)、非高密度脂蛋白胆固醇(non-HDL-C)、血糖和血压6个指标评估CVH,利用组基轨迹模型识别认知功能发展轨迹,并通过多项式logistic回归分析探索CVH与其关系。

结果

共纳入5 774人,认知功能发展轨迹分为低水平下降组、中水平下降组、中水平持续组和高水平稳定组。与高水平稳定组相比,CVH评分每增加1分,个体进入低、中水平下降组及中水平持续组的风险分别降低约1.4%、0.8%和0.5%(均P<0.01)。其中,烟草暴露、睡眠、血压3个CVH指标与认知功能发展轨迹相关(P<0.05),BMI、non-HDL-C在部分轨迹组比较中存在统计学显著性(P<0.05)。

结论

中老年人CVH水平与认知功能发展轨迹呈正相关。烟草暴露、睡眠、BMI、non-HDL-C及血压是其中的影响因素。改善CVH水平,尤其是针对可干预的生活方式与代谢指标的中年期“心脑共防”,可能为延缓认知功能衰退提供潜在途径。

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李杰,E-mail:
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注:●1低水平下降组认知功能总分均值;▲2中水平下降组认知功能总分均值;◆3中水平持续组认知功能总分均值;■4高水平稳定组认知功能总分均值。

, figureFileSmall=D0T0/eFJlbZ8AUhfSdkJVQ==, figureFileBig=uCBEqJy/SCciZ5xKXb2GzA==, tableContent=null), ArticleFig(id=1324077941377872053, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077930715951208, language=EN, label=Table 1, caption=

Baseline characteristics of the research subjects

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群
(n=5 774)
低CVH组
(n=344)
中CVH组
(n=3 534)
高CVH组
(n=1 896)
P值
性别(%)<0.001
男2 991249(8.32)2 113(70.65)629(21.05)
女2 78395(3.41)1 421(51.06)1 267(45.53)
年龄(%)<0.001
45~59岁3 754196(5.22)2 191(58.36)1 367(36.42)
60~74岁1 904141(7.41)1 256(65.97)507(26.62)
≥75岁1167(6.03)87(75.0)22(18.97)
婚姻状况(%)0.003
已婚5 280302(5.72)3 217(60.93)1 761(33.35)
其他49442(8.50)317(64.17)135(27.33)
教育水平(%)0.001
小学以下2 052136(6.63)1 242(60.53)674(32.84)
小学1 49283(5.56)952(63.81)457(30.63)
中学1 48986(5.78)930(62.46)473(31.76)
高中及以上74139(5.26)410(55.33)292(39.41)
居住地(%)0.007
农村3 578191(5.34)2 172(60.70)1 215(33.96)
城市2 196153(6.97)1 362(62.02)681(31.01)
慢性病(%)<0.001
否1 81153(2.93)995(54.94)763(42.13)
是3 963291(7.34)2 539(64.07)1 133(28.59)
饮酒(%)<0.001
否3 327133(4.00)1 861(55.94)1 333(40.06)
是2 447211(8.62)1 673(68.37)563(23.01)
家庭人均消费5 008.67(2 974.17,8 745)5 110.00(3 066,9 155)4 970.00(2 982,8 624)5 064.00(2 931.11,8 894)0.564
心理健康7.83±5.999.40±6.568.30±6.108.34±6.360.019
CVH评分72.68±14.0542.85±6.4567.44±7.8987.86±5.88<0.001
烟草暴露评分63.04±46.1825.15±40.9452.26±47.6889.99±27.39<0.001
睡眠评分70.61±32.2748.58±34.6966.13±33.0682.95±25.29<0.001
BMI评分87.84±19.5169.93±26.7986.54±20.0793.50±13.59<0.001
non-HDL-C评分66.17±30.2035.47±27.8361.60±29.4980.25±24.66<0.001
血糖评分88.80±23.7457.30±30.2987.22±24.9397.45±11.50<0.001
血压评分59.64±36.3920.71±22.3350.89±35.5283.01±25.05<0.001
), ArticleFig(id=1324077941474341046, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077930715951208, language=CN, label=表1, caption=

基线研究人群的基本特征

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群
(n=5 774)
低CVH组
(n=344)
中CVH组
(n=3 534)
高CVH组
(n=1 896)
P值
性别(%)<0.001
男2 991249(8.32)2 113(70.65)629(21.05)
女2 78395(3.41)1 421(51.06)1 267(45.53)
年龄(%)<0.001
45~59岁3 754196(5.22)2 191(58.36)1 367(36.42)
60~74岁1 904141(7.41)1 256(65.97)507(26.62)
≥75岁1167(6.03)87(75.0)22(18.97)
婚姻状况(%)0.003
已婚5 280302(5.72)3 217(60.93)1 761(33.35)
其他49442(8.50)317(64.17)135(27.33)
教育水平(%)0.001
小学以下2 052136(6.63)1 242(60.53)674(32.84)
小学1 49283(5.56)952(63.81)457(30.63)
中学1 48986(5.78)930(62.46)473(31.76)
高中及以上74139(5.26)410(55.33)292(39.41)
居住地(%)0.007
农村3 578191(5.34)2 172(60.70)1 215(33.96)
城市2 196153(6.97)1 362(62.02)681(31.01)
慢性病(%)<0.001
否1 81153(2.93)995(54.94)763(42.13)
是3 963291(7.34)2 539(64.07)1 133(28.59)
饮酒(%)<0.001
否3 327133(4.00)1 861(55.94)1 333(40.06)
是2 447211(8.62)1 673(68.37)563(23.01)
家庭人均消费5 008.67(2 974.17,8 745)5 110.00(3 066,9 155)4 970.00(2 982,8 624)5 064.00(2 931.11,8 894)0.564
心理健康7.83±5.999.40±6.568.30±6.108.34±6.360.019
CVH评分72.68±14.0542.85±6.4567.44±7.8987.86±5.88<0.001
烟草暴露评分63.04±46.1825.15±40.9452.26±47.6889.99±27.39<0.001
睡眠评分70.61±32.2748.58±34.6966.13±33.0682.95±25.29<0.001
BMI评分87.84±19.5169.93±26.7986.54±20.0793.50±13.59<0.001
non-HDL-C评分66.17±30.2035.47±27.8361.60±29.4980.25±24.66<0.001
血糖评分88.80±23.7457.30±30.2987.22±24.9397.45±11.50<0.001
血压评分59.64±36.3920.71±22.3350.89±35.5283.01±25.05<0.001
), ArticleFig(id=1324077941608558775, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077930715951208, language=EN, label=Table 2, caption=

Distribution of cognitive function trajectories across characteristics in middle-aged and older adults

, figureFileSmall=null, figureFileBig=null, tableContent=
变量低水平下降组
(n=438)
中水平下降组
(n=1 262)
中水平持续组
(n=2 360)
高水平稳定组
(n=1 714)
P值
性别(%)<0.001
男142(4.75)577(19.29)1 323(44.23)949(31.73)
女296(10.64)685(24.61)1 037(37.26)765(27.49)
年龄(%)<0.001
45~59岁182(5.19)649(18.50)1 431(40.79)1 246(35.52)
60~74岁216(10.28)555(26.42)874(41.60)456(21.70)
≥75岁40(24.24)58(35.15)55(33.33)12(7.28)
婚姻状况(%)<0.001
已婚367(6.95)1 104(20.91)2 184(41.36)1 625(30.78)
其他71(14.37)158(31.98)176(35.63)89(18.02)
教育水平(%)<0.001
小学以下376(18.32)786(38.30)712(34.70)178(8.68)
小学42(2.81)327(21.89)763(51.07)362(24.23)
中学16(1.07)126(8.46)663(44.53)684(45.94)
高中及以上4(0.54)23(3.11)222(30.04)490(66.31)
居住地(%)<0.001
农村348(9.73)921(25.74)1 490(41.64)819(22.89)
城市90(4.10)341(15.53)870(39.62)895(40.75)
慢性病(%)<0.001
否116(6.41)396(21.87)696(38.43)603(33.59)
是322(8.13)866(21.85)1 664(41.99)1 111(28.03)
饮酒(%)<0.001
否316(8.63)846(23.11)1 477(40.34)1 022(27.92)
是122(5.77)416(19.69)883(41.79)692(32.75)
家庭人均消费3 689.00
(2 379.67,5 967)
4 246.00
(2 595,7 152)
4 871.67
(2 962.89,8 574)
6 202.50
(3 463.33,10 136.25)
<0.001
心理健康10.65±6.509.20±6.368.05±5.905.81±5.03<0.001
CVH评分71.33±14.2472.47±13.9372.16±13.8373.90±14.330.007
CVH分组(%)0.003
低CVH组34(9.89)77(22.38)132(38.37)101(29.36)
中CVH组280(7.92)766(21.68)1 496(42.33)992(28.07)
高CVH组124(6.54)419(22.10)732(38.61)621(32.75)
烟草暴露评分69.58±44.3764.34±45.9960.34±46.7164.12±45.82<0.001
睡眠评分61.07±36.2365.17±34.5470.29±31.8877.48±28.38<0.001
BMI评分91.59±16.4290.03±17.9987.50±20.0085.74±20.31<0.001
non-HDL-C评分64.75±29.7967.42±30.4766.78±29.8364.77±30.580.042
血糖评分86.51±25.4588.58±23.9489.13±23.3489.08±23.670.155
血压评分54.47±37.9459.27±36.6358.94±36.6262.19±35.32<0.001
), ArticleFig(id=1324077941692444856, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077930715951208, language=CN, label=表2, caption=

不同特征中老年人认知功能轨迹分布

, figureFileSmall=null, figureFileBig=null, tableContent=
变量低水平下降组
(n=438)
中水平下降组
(n=1 262)
中水平持续组
(n=2 360)
高水平稳定组
(n=1 714)
P值
性别(%)<0.001
男142(4.75)577(19.29)1 323(44.23)949(31.73)
女296(10.64)685(24.61)1 037(37.26)765(27.49)
年龄(%)<0.001
45~59岁182(5.19)649(18.50)1 431(40.79)1 246(35.52)
60~74岁216(10.28)555(26.42)874(41.60)456(21.70)
≥75岁40(24.24)58(35.15)55(33.33)12(7.28)
婚姻状况(%)<0.001
已婚367(6.95)1 104(20.91)2 184(41.36)1 625(30.78)
其他71(14.37)158(31.98)176(35.63)89(18.02)
教育水平(%)<0.001
小学以下376(18.32)786(38.30)712(34.70)178(8.68)
小学42(2.81)327(21.89)763(51.07)362(24.23)
中学16(1.07)126(8.46)663(44.53)684(45.94)
高中及以上4(0.54)23(3.11)222(30.04)490(66.31)
居住地(%)<0.001
农村348(9.73)921(25.74)1 490(41.64)819(22.89)
城市90(4.10)341(15.53)870(39.62)895(40.75)
慢性病(%)<0.001
否116(6.41)396(21.87)696(38.43)603(33.59)
是322(8.13)866(21.85)1 664(41.99)1 111(28.03)
饮酒(%)<0.001
否316(8.63)846(23.11)1 477(40.34)1 022(27.92)
是122(5.77)416(19.69)883(41.79)692(32.75)
家庭人均消费3 689.00
(2 379.67,5 967)
4 246.00
(2 595,7 152)
4 871.67
(2 962.89,8 574)
6 202.50
(3 463.33,10 136.25)
<0.001
心理健康10.65±6.509.20±6.368.05±5.905.81±5.03<0.001
CVH评分71.33±14.2472.47±13.9372.16±13.8373.90±14.330.007
CVH分组(%)0.003
低CVH组34(9.89)77(22.38)132(38.37)101(29.36)
中CVH组280(7.92)766(21.68)1 496(42.33)992(28.07)
高CVH组124(6.54)419(22.10)732(38.61)621(32.75)
烟草暴露评分69.58±44.3764.34±45.9960.34±46.7164.12±45.82<0.001
睡眠评分61.07±36.2365.17±34.5470.29±31.8877.48±28.38<0.001
BMI评分91.59±16.4290.03±17.9987.50±20.0085.74±20.31<0.001
non-HDL-C评分64.75±29.7967.42±30.4766.78±29.8364.77±30.580.042
血糖评分86.51±25.4588.58±23.9489.13±23.3489.08±23.670.155
血压评分54.47±37.9459.27±36.6358.94±36.6262.19±35.32<0.001
), ArticleFig(id=1324077941793108153, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077930715951208, language=EN, label=Table 3, caption=

Multinomial logistic regression results for cognitive function trajectory groups

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调整低水平下降组VS高水平稳定组中水平下降组VS高水平稳定组中水平持续组VS高水平稳定组
OR值(95%CI)P值OR值(95%CI)P值OR值(95%CI)P值
模型1
CVH评分0.987(0.980~0.994)0.0010.993(0.988~0.998)0.0060.991(0.987~0.996)<0.001
CVH分组
低CVH组1.686(1.093~2.602)0.0181.130(0.819~1.558)0.4561.109(0.838~1.467)0.470
中CVH组1.414(1.119~1.786)0.0041.144(0.979~1.337)0.0891.279(1.119~1.462)<0.001
高CVH组1.000(ref)1.000(ref)1.000(ref)
烟草暴露评分1.003(1.001~1.005)0.0251.001(0.999~1.002)0.8950.998(0.997~1.001)0.010
睡眠评分0.984(0.981~0.987)<0.0010.988(0.985~0.990)<0.0010.992(0.990~0.994)<0.001
BMI评分1.017(1.011~1.024)<0.0011.012(1.008~1.016)<0.0011.004(1.001~1.007)0.006
non-HDL-C评分1.001(0.997~1.003)0.9881.003(1.001~1.005)0.0181.002(1.001~1.004)0.036
血糖评分0.996(0.992~1.001)0.0450.999(0.996~1.002)0.5671.001(0.997~1.003)0.949
血压评分0.994(0.991~0.997)<0.0010.998(0.996~0.999)0.0300.998(0.996~0.999)0.005
模型2
CVH评分0.982(0.974~0.990)<0.0010.990(0.985~0.996)0.0010.992(0.987~0.996)0.001
CVH分组
低CVH组2.212(1.398~3.501)0.0011.253(0.896~1.750)0.1871.083(0.812~1.444)0.587
中CVH组1.630(1.274~2.085)<0.0011.214(1.030~1.431)0.0211.258(1.094~1.447)0.001
高CVH组1.000(ref)1.000(ref)1.000(ref)
烟草暴露评分0.991(0.988~0.995)<0.0010.994(0.992~0.997)<0.0010.997(0.995~0.999)<0.001
睡眠评分0.986(0.983~0.990)<0.0010.989(0.987~0.991)<0.0010.993(0.991~0.995)<0.001
BMI评分1.019(1.012~1.025)<0.0011.012(1.008~1.016)<0.0011.003(1.001~1.007)0.031
non-HDL-C评分1.003(0.999~1.006)0.1361.004(1.002~1.006)0.0021.002(1.001~1.004)0.035
血糖评分0.998(0.993~1.002)0.2871.001(0.997~1.003)0.9191.001(0.998~1.003)0.695
血压评分0.997(0.994~1.001)0.0631.001(0.998~1.002)0.6870.998(0.997~1.001)0.090
模型3
CVH评分0.986(0.978~0.994)0.0010.992(0.988~0.996)<0.0010.995(0.991~0.998)0.002
CVH分组
低CVH组1.500(0.928~2.425)0.0981.045(0.824~1.326)0.6110.918(0.749~1.125)0.411
中CVH组1.544(1.192~2.00)0.0011.154(1.027~1.297)0.0161.144(1.038~1.260)0.007
高CVH组1.000(ref)1.000(ref)1.000(ref)
烟草暴露评分0.995(0.991~0.998)0.0020.997(0.996~0.999)<0.0010.999(0.997~1.001)0.016
睡眠评分0.993(0.990~0.997)<0.0010.994(0.992~0.996)<0.0010.996(0.995~0.998)<0.001
BMI评分1.014(1.007~1.021)<0.0011.007(1.005~1.010)<0.0011.002(0.999~1.004)0.118
non-HDL-C评分1.002(0.998~1.005)0.3831.003(1.001~1.005)<0.0011.002(1.001~1.004)0.004
血糖评分0.996(0.992~1.001)0.1080.998(0.996~1.001)0.0621.001(0.998~1.002)0.988
血压评分0.995(0.992~0.998)0.0010.998(0.996~0.999)0.0020.997(0.996~0.999)<0.001
), ArticleFig(id=1324077941902160058, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324077930715951208, language=CN, label=表3, caption=

认知功能轨迹分组的多项式logistic回归分析结果

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调整低水平下降组VS高水平稳定组中水平下降组VS高水平稳定组中水平持续组VS高水平稳定组
OR值(95%CI)P值OR值(95%CI)P值OR值(95%CI)P值
模型1
CVH评分0.987(0.980~0.994)0.0010.993(0.988~0.998)0.0060.991(0.987~0.996)<0.001
CVH分组
低CVH组1.686(1.093~2.602)0.0181.130(0.819~1.558)0.4561.109(0.838~1.467)0.470
中CVH组1.414(1.119~1.786)0.0041.144(0.979~1.337)0.0891.279(1.119~1.462)<0.001
高CVH组1.000(ref)1.000(ref)1.000(ref)
烟草暴露评分1.003(1.001~1.005)0.0251.001(0.999~1.002)0.8950.998(0.997~1.001)0.010
睡眠评分0.984(0.981~0.987)<0.0010.988(0.985~0.990)<0.0010.992(0.990~0.994)<0.001
BMI评分1.017(1.011~1.024)<0.0011.012(1.008~1.016)<0.0011.004(1.001~1.007)0.006
non-HDL-C评分1.001(0.997~1.003)0.9881.003(1.001~1.005)0.0181.002(1.001~1.004)0.036
血糖评分0.996(0.992~1.001)0.0450.999(0.996~1.002)0.5671.001(0.997~1.003)0.949
血压评分0.994(0.991~0.997)<0.0010.998(0.996~0.999)0.0300.998(0.996~0.999)0.005
模型2
CVH评分0.982(0.974~0.990)<0.0010.990(0.985~0.996)0.0010.992(0.987~0.996)0.001
CVH分组
低CVH组2.212(1.398~3.501)0.0011.253(0.896~1.750)0.1871.083(0.812~1.444)0.587
中CVH组1.630(1.274~2.085)<0.0011.214(1.030~1.431)0.0211.258(1.094~1.447)0.001
高CVH组1.000(ref)1.000(ref)1.000(ref)
烟草暴露评分0.991(0.988~0.995)<0.0010.994(0.992~0.997)<0.0010.997(0.995~0.999)<0.001
睡眠评分0.986(0.983~0.990)<0.0010.989(0.987~0.991)<0.0010.993(0.991~0.995)<0.001
BMI评分1.019(1.012~1.025)<0.0011.012(1.008~1.016)<0.0011.003(1.001~1.007)0.031
non-HDL-C评分1.003(0.999~1.006)0.1361.004(1.002~1.006)0.0021.002(1.001~1.004)0.035
血糖评分0.998(0.993~1.002)0.2871.001(0.997~1.003)0.9191.001(0.998~1.003)0.695
血压评分0.997(0.994~1.001)0.0631.001(0.998~1.002)0.6870.998(0.997~1.001)0.090
模型3
CVH评分0.986(0.978~0.994)0.0010.992(0.988~0.996)<0.0010.995(0.991~0.998)0.002
CVH分组
低CVH组1.500(0.928~2.425)0.0981.045(0.824~1.326)0.6110.918(0.749~1.125)0.411
中CVH组1.544(1.192~2.00)0.0011.154(1.027~1.297)0.0161.144(1.038~1.260)0.007
高CVH组1.000(ref)1.000(ref)1.000(ref)
烟草暴露评分0.995(0.991~0.998)0.0020.997(0.996~0.999)<0.0010.999(0.997~1.001)0.016
睡眠评分0.993(0.990~0.997)<0.0010.994(0.992~0.996)<0.0010.996(0.995~0.998)<0.001
BMI评分1.014(1.007~1.021)<0.0011.007(1.005~1.010)<0.0011.002(0.999~1.004)0.118
non-HDL-C评分1.002(0.998~1.005)0.3831.003(1.001~1.005)<0.0011.002(1.001~1.004)0.004
血糖评分0.996(0.992~1.001)0.1080.998(0.996~1.001)0.0621.001(0.998~1.002)0.988
血压评分0.995(0.992~0.998)0.0010.998(0.996~0.999)0.0020.997(0.996~0.999)<0.001
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中国中老年人心血管健康与认知功能发展轨迹的关联研究
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张侠 1 , 王勤 1 , 梁雨婷 1 , 方明磊 1 , 李林林 1, 2 , 张燕 3 , 秦其荣 3 , 黄芬 4 , 孙业桓 5 , 李杰 1
现代预防医学 | 健康与社会行为 2026,53(4): 707-712
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现代预防医学 |健康与社会行为 2026 , 53 (4) : 707 -712
中国中老年人心血管健康与认知功能发展轨迹的关联研究
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张侠1, 王勤1, 梁雨婷1, 方明磊1, 李林林1, 2, 张燕3, 秦其荣3, 黄芬4, 孙业桓5, 李杰1
作者信息
  • 1.安徽医科大学公共卫生学院健康促进与行为科学系,安徽 合肥 230032
  • 2.宿州市疾病预防控制中心(宿州市卫生监督所)传染病预防控制科
  • 3.马鞍山市疾病预防控制中心慢病科
  • 4.安徽医科大学公共卫生学院流行病与卫生统计学系
  • 5.安徽医科大学附属巢湖医院
通讯作者:
李杰,E-mail:
作者简介:

张侠(1991—),女,硕士在读,研究方向:公共卫生(健康教育与健康促进)

Association between cardiovascular health and cognitive function trajectories among middle-aged and elderly Chinese adults
Xia ZHANG1, Qin WANG1, Yu-ting LIANG1, Ming-lei FANG1, Lin-lin LI1, 2, Yan ZHANG3, Qi-rong QIN3, Fen HUANG4, Ye-huan SUN5, Jie LI1
Affiliations
  • Department of Health Promotion and Behavioral Sciences, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China
出版时间: 2026-02-25 doi: 10.20043/j.cnki.MPM.202510069
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目的

探索心血管健康(CVH)与认知功能发展轨迹的关联。

方法

基于中国健康与养老追踪调查(CHARLS)2011—2020年五次调查数据,纳入45岁及以上人群。采用烟草暴露、睡眠、体质指数(BMI)、非高密度脂蛋白胆固醇(non-HDL-C)、血糖和血压6个指标评估CVH,利用组基轨迹模型识别认知功能发展轨迹,并通过多项式logistic回归分析探索CVH与其关系。

结果

共纳入5 774人,认知功能发展轨迹分为低水平下降组、中水平下降组、中水平持续组和高水平稳定组。与高水平稳定组相比,CVH评分每增加1分,个体进入低、中水平下降组及中水平持续组的风险分别降低约1.4%、0.8%和0.5%(均P<0.01)。其中,烟草暴露、睡眠、血压3个CVH指标与认知功能发展轨迹相关(P<0.05),BMI、non-HDL-C在部分轨迹组比较中存在统计学显著性(P<0.05)。

结论

中老年人CVH水平与认知功能发展轨迹呈正相关。烟草暴露、睡眠、BMI、non-HDL-C及血压是其中的影响因素。改善CVH水平,尤其是针对可干预的生活方式与代谢指标的中年期“心脑共防”,可能为延缓认知功能衰退提供潜在途径。

认知功能  /  心血管健康  /  中老年人  /  发展轨迹
Objective

To investigate the association between Cardiovascular Health (CVH) and cognitive function trajectories.

Methods

Data were obtained from five waves (2011-2020) of the China Health and Retirement Longitudinal Study (CHARLS), including participants aged ≥45 years. CVH was assessed using six indicators: tobacco exposure, sleep, body mass index (BMI), non-high-density lipoprotein cholesterol (non-HDL-C), blood glucose, and blood pressure. Group-based trajectory modeling was applied to identify trajectories of cognitive function, and multinomial logistic regression was used to evaluate the association between CVH and cognitive function trajectories.

Results

A total of 5 774 participants was included. Four cognitive trajectories were identified: low-declining, medium-declining, medium-stable and high-stable. Compared with the high-stable group, each one-point increase in CVH score was associated with a reduced risk of entering the low-decline, medium-decline, and medium-stable groups by approximately 1.4%, 0.8%, and 0.5%, respectively (all P<0.01). Tobacco exposure, sleep, and blood pressure were consistently associated with cognitive trajectories (P<0.05), while BMI and non-HDL-C showed significance in selected comparisons.

Conclusion

CVH in middle-aged and older adults is positively associated with cognitive function trajectories. Tobacco exposure, sleep, BMI, non-HDL-C, and blood pressure emerge as key influencing factors. Enhancing CVH, especially through midlife strategies focusing on modifiable lifestyle behaviors and metabolic indicators within an integrated “heart-brain prevention” framework, may represent a promising avenue to mitigate or delay cognitive decline.

Cognitive function  /  Cardiovascular health  /  Middle-aged and elderly adults  /  Development trajectories
张侠, 王勤, 梁雨婷, 方明磊, 李林林, 张燕, 秦其荣, 黄芬, 孙业桓, 李杰. 中国中老年人心血管健康与认知功能发展轨迹的关联研究. 现代预防医学, 2026 , 53 (4) : 707 -712 . DOI: 10.20043/j.cnki.MPM.202510069
Xia ZHANG, Qin WANG, Yu-ting LIANG, Ming-lei FANG, Lin-lin LI, Yan ZHANG, Qi-rong QIN, Fen HUANG, Ye-huan SUN, Jie LI. Association between cardiovascular health and cognitive function trajectories among middle-aged and elderly Chinese adults[J]. Modern Preventive Medicine, 2026 , 53 (4) : 707 -712 . DOI: 10.20043/j.cnki.MPM.202510069
当前,神经系统疾病已成为全球公共健康挑战[1],我国现存阿尔茨海默病及其他痴呆患者达1 699.08万例,40岁以上人群患病率随年龄增长呈指数上升[2],探索可干预因素显得尤为迫切[3]。心血管健康(Cardiovascular Health,CVH)是由美国心脏协会(American Heart Association,AHA)提出的综合健康概念,旨通过健康行为与生理指标8个维度即“生命八要素”(Life’s Essential 8,LE8)评估个体的整体心血管状态[4]。既往研究提示CVH与认知障碍有关,但多基于国外人群,且未考虑认知功能的动态变化[5]。本研究使用中国健康与养老追踪调查(China Health and Retirement Longitudinal Study,CHARLS)数据[6],较早关注我国中老年人CVH指标与认知功能发展轨迹之间的关联,为中老年人认知障碍干预提供理论依据。
本研究基于2011年至2020年CHARLS数据,选取了在这期间参与了五次调查的45岁及以上人群。研究总样本为25 873名受访者,其中,符合五次调查且年龄≥45岁的个体为10 434人。剔除以下不符合条件的个体后,本研究最终纳入5 774名受试者:①基线及随访期间认知功能评估缺失≥2次;②基线已诊断为痴呆者;③CVH信息不全者。
2022年,AHA在更新指南中将“睡眠”纳入评估体系,形成了CVH的框架“LE8”,即均衡饮食、定期锻炼、避免吸烟、良好睡眠、健康体重及控制血脂、血糖和血压[4]。既往已有多项国内外研究采用“修改版”CVH指数[7-9],结果表明,即使部分指标缺失,改良版CVH仍能有效预测心血管疾病及相关健康结局[8-9]。在中国人群研究(包括CHARLS)中,也有大量基于睡眠、血压、血糖、血脂及吸烟等单项或组合指标的研究,为构建改良版CVH提供了实证依据[10-12]。鉴于CHARLS缺乏可比性较强的饮食与锻炼数据,本研究在六项可测指标基础上构建了改良版CVH指数,包括:烟草暴露、睡眠、体质指数(Body Mass Index,BMI)、非高密度脂蛋白胆固醇(Non-high-density Lipoprotein Cholesterol,non-HDL-C)、血糖和血压,并通过敏感性分析验证模型稳定性。各指标按AHA标准转化为0~100分,综合CVH得分取六项指标的均值,分为高(80~100分)、中(50~79分)和低(0~49分)三个等级,得分越高,代表整体心血管健康状况越佳[4]。
采用CHARLS认知功能评估模块,从心智状况(总分11分)与情景记忆能力(总分10分)两个维度进行量化[6]。心智状况评估包含:日期认知:回答调查当天的年、月、日、季节及星期,共5分;计算能力:执行五次“100减7”递减计算,共5分;画图能力:临摹几何图形,正确复现计1分。情景记忆能力包含:词组即时回忆:主试朗读10个词汇后立即复述,正确计1分共10分;延时回忆:5分钟后再次复述,共10分,最终得分取两次均值[6]。
研究控制以下协变量:年龄、性别、居住地、婚姻状况、受教育水平、慢性病、饮酒、家庭人均消费及心理健康。
采用SPSS 25.0和STATA 18.0进行统计分析,符合正态分布的连续变量以均值±标准差表示,不符合的采用中位数和四分位数描述;分类变量以频数及百分比描述。其对应的多组间比较分别采用方差分析、K-W检验和卡方检验。认知功能发展轨迹采用组基轨迹模型(Group-Based Trajectory Model,GBTM)分析。模型筛选标准:(1)贝叶斯信息标准(Bayesian Information Criterion,BIC)和赤池信息准则(Akaike Information Criterion,AIC)绝对值最小;(2)平均后验概率>0.7;(3)各轨迹亚组样本量占比≥5%[13]。统计推断采用多项式logistic回归分析。所有分析采用双侧检验,显著性阈值设定为α=0.05。
研究纳入5 774名≥45岁的中老年人群,多来自农村(61.97%),91.44%的研究对象已婚,68.64%的患有慢性病,平均CVH评分为72.68±14.05分。与低CVH组相比,中、高CVH组的烟草暴露、睡眠、BMI、non-HDL-C、血压、血糖评分更高(P<0.05),心血管健康状况更好。详见表1。
根据GBTM模型结果最终确定4条中老年人认知功能发展轨迹。其中,第1组为“低水平下降组”,第2组为“中水平下降组”,第3组为“中水平持续组”,第4组为“高水平稳定组”。详见图1。
不同性别、年龄、婚姻状况、受教育水平、居住地、慢性病、饮酒、家庭人均消费、心理健康等认知功能轨迹组间均存在统计学差异(P<0.05)。CVH总体评分、CVH分组及烟草暴露、睡眠、BMI、non-HDL-C、血压在不同认知功能轨迹分组中也存在统计学差异(P<0.05)。详见表2。
以“高水平稳定组”为参照,在校正年龄、性别、居住地等(模型3)混杂因素后,CVH评分每增加1分,进入低水平下降组的风险降低约1.4%(OR=0.986,95% CI:0.978~0.994),进入中水平下降组的风险降低约0.8%(OR=0.992,95% CI:0.988~0.996),进入中水平持续组的风险降低约0.5%(OR=0.995,95% CI:0.991~0.998),差异均具有统计学意义(P<0.01)。在各组成指标中,烟草暴露、睡眠和血压与认知功能轨迹表现出稳定的显著关联(P<0.05)。详见表3。
由于本研究仅包含LE8指标中的6项,为验证主要结果的稳健性,分别采用仅包含4项指标的CVH评分,及赋予不同权重的替代评分进行重复分析。结果显示,各模型中CVH与认知功能轨迹的关联方向及显著性保持一致,提示研究结果具有良好的稳健性。
本研究基于中国中老年人群长达10年的纵向随访,系统分析了中老年人CVH与认知功能发展轨迹的关系。结果显示,整体CVH水平与较佳的认知功能轨迹呈正相关,这与美国[5,14-15]、英国[16]和法国[17]等的研究结果一致[18]。研究识别出四种认知功能发展轨迹:低水平下降组、中水平下降组、中水平持续组和高水平稳定组,CVH评分较高的中老年人更可能归类为认知功能高水平稳定组。认知功能并非随年龄变化呈单一线性,而是受健康行为、代谢状态及社会经济因素等多重影响[19-21]。
从总体CVH水平来看,CVH评分越高,出现不良认知轨迹的风险越低。调整混杂因素后,中CVH组仍与多种不良认知轨迹显著相关(P<0.05),而低CVH组未达显著水平(P>0.05)。这可能与低CVH组样本量较小、统计功效不足或模型过度调整中介变量有关[22-23]。也可能存在阈值效应,即维持中等及以上水平的CVH可获得显著的认知保护,而极差健康状态下,认知功能下降可能更多由其他病理过程主导[24]。
在CVH的各组成指标中,烟草暴露、睡眠和血压与认知功能发展轨迹的关联相对稳定(P<0.05)。非吸烟者及睡眠充足者更可能维持认知稳定,这与既往研究中吸烟和睡眠紊乱可通过氧化应激、炎症反应及脑血管损伤促进认知退化的机制一致[25-26]。同时,即使在多变量调整后,高血压仍是痴呆的独立危险因素,这与现有研究一致,强化血压管理可能降低认知衰退风险[27-28]。
BMI、non-HDL-C在部分轨迹组比较中有统计学意义(P<0.05),且表现出一定的“肥胖悖论”[11]。类似结果亦见于部分亚洲人群研究,认为适度脂肪储备可能在老年期对神经退行性损伤具有代偿作用[11,29]。non-HDL-C与认知功能的正向关联可能反映营养状态差异或反向因果效应,过高或过低均会增加认知损害发生概率[30]。相较之下,血糖与认知功能轨迹未见显著关联,这与部分西方研究不一致[31],需进一步验证。
基于本研究结果,建议将CVH监测纳入我国中老年人群常规体检与慢病管理体系,进一步推动“LE8”理念的本土化实践[21]。在具体干预上,应优先强化控烟、改善睡眠及血压管理,以行为干预与代谢调控为核心,强化中年期预防[32]。此外,还需关注老年期“肥胖悖论”现象,倡导“代谢健康型体重”,避免营养不良[11,30],推动“心脑共防,一体化管理”的老龄健康策略落地,以促进认知障碍的早期预防与进程延缓。
本研究具有一定优势,较早关注国内中老年人CVH与认知功能,采用全国代表性样本、连续认知测量并充分控制混杂因素。然而仍存在局限性:其一,由于CHARLS问卷限制,仅使用基线CVH,且未纳入饮食和锻炼指标,可能无法充分反映长期动态变化;其二,认知功能量表、睡眠等基于问卷调查,尚需客观指标进一步验证;其三,校正因素无法包括所有潜在影响因素。未来仍需开展更多高质量研究以丰富完善中国人群CVH与认知功能关系的证据基础。
尽管存在上述不足,本研究结果提示,提升CVH水平对延缓认知衰退和促进健康老龄化具有重要公共卫生意义。未来应进一步加强控烟、血压管理、改善睡眠及优化代谢状况等综合干预措施,以维持中老年人群的心血管与认知双重健康,助力实现积极老龄化目标。
  • 国家自然科学基金青年项目(82504536)
  • 安徽省卫生健康科研项目委省共建青年项目(AHWJ2024Aa30196)
  • 安徽医科大学公共卫生学院高峰学科项目(2024GWXTRZ001)
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2026年第53卷第4期
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doi: 10.20043/j.cnki.MPM.202510069
  • 接收时间:2025-10-11
  • 首发时间:2026-11-02
  • 出版时间:2026-02-25
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  • 收稿日期:2025-10-11
基金
国家自然科学基金青年项目(82504536)
安徽省卫生健康科研项目委省共建青年项目(AHWJ2024Aa30196)
安徽医科大学公共卫生学院高峰学科项目(2024GWXTRZ001)
作者信息
    1.安徽医科大学公共卫生学院健康促进与行为科学系,安徽 合肥 230032
    2.宿州市疾病预防控制中心(宿州市卫生监督所)传染病预防控制科
    3.马鞍山市疾病预防控制中心慢病科
    4.安徽医科大学公共卫生学院流行病与卫生统计学系
    5.安徽医科大学附属巢湖医院

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