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Article(id=1241023851476349181, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202409204, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1725897600000, receivedDateStr=2024-09-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812743300, onlineDateStr=2026-03-18, pubDate=1737734400000, pubDateStr=2025-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812743300, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812743300, creator=13701087609, updateTime=1773812743300, updator=13701087609, issue=Issue{id=1241023847537897695, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='2', pageStart='193', pageEnd='384', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812742361, creator=13701087609, updateTime=1773812823817, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024189247845056, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024189247845057, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=342, endPage=348, ext={EN=ArticleExt(id=1241023851807699207, articleId=1241023851476349181, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study on the association between biological aging and cognitive function in middle-aged and elderly Chinese, columnId=1228016573156360233, journalTitle=Modern Preventive Medicine, columnName=Disease Control and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the association between biological aging and cognitive function in middle-aged and elderly Chinese.

Methods

The subjects were health check-up personnel over 45 years old from a top three hospital. The general demographic characteristics, covariates and cognitive function status were collected by questionnaire and Montreal cognitive assessment (MoCA). Multivariate linear regression and logistic regression were used to analyze biological aging index (BAI) and biological aging type (BAT) association with MoCA score and risk of mild cognitive impairment (MCI). Subgroup analysis was conducted by the middle-aged group (45-64 years old) and the elderly group (65 years old and above) to explore whether the correlation between biological aging and cognitive function was different in different age groups.

Results

A total of 407 participants were included in this study. The average MoCA score was 23.30±4.30, and the detection rate of MCI was 41.5%. BAI was negatively correlated with MoCA score, and the regression coefficient after adjusting for covariates was -0.135 (95%CI: -0.229--0.042). Compared with those with delayed aging, subjects with premature aging had lower cognitive function scores (β=-0.882，95%CI：-1.566--0.198) and a higher risk of MCI (OR=1.736，95%CI：1.072-2.833). Subgroup analysis found that the association was still present in the middle-aged group, but not in the elderly group.

Conclusion

There is a negative correlation between biological aging and cognitive function in middle-aged and elderly people, and the cognitive function of subjects with premature aging is worse. This effect is more significant in middle-aged group, suggesting that individuals with premature aging should be identified in middle age or even earlier and that intervention measures should be taken to prevent or delay the occurrence of dementia.

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目的

探讨中老年人生物学衰老和认知功能的关系。

方法

研究对象来自某三甲医院的45岁以上体检人员，通过问卷和蒙特利尔认知评估量表（Montreal cognitive assessment，MoCA）收集一般人口学特征、协变量以及认知功能状况，采用多因素线性回归、logistic回归分析生物学衰老指数（biological aging index，BAI）、生物学衰老类型（biological aging type，BAT）与MoCA评分、轻度认知障碍（mild cognitive impairment，MCI）风险的相关性。并按中年组（45~64岁）和老年组（65岁及以上）进行亚组分析，探究生物学衰老与认知功能的相关性在不同年龄组中是否存在差异。

结果

本研究共纳入407人，平均MoCA得分为23.30±4.30，MCI检出率为41.5%。BAI与MoCA评分呈负相关，调整协变量后的回归系数为-0.135（95%CI：-0.229~-0.042）。与滞后衰老相比，提前衰老的研究对象认知功能评分更低（β=-0.882，95%CI：-1.566~-0.198），MCI风险更高（OR=1.736，95%CI：1.072~2.833）。亚组分析发现中年组仍存在上述关联，而老年组不成立。

结论

中老年人生物学衰老与认知功能存在负向关联，且提前衰老的研究对象认知功能更差，中年组中这种效应更为显著，提示应在中年甚至更早时期识别提前衰老个体并采取干预措施预防或延缓痴呆发生。

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张洋，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=03Z0Ea95rmotm+qT0ZFdtw==, magXml=h6tgGM0Ciz35QljifWOd4w==, pdfUrl=null, pdf=qRCMlld6z6U97cG9/nN1Gg==, pdfFileSize=948262, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=P76Zsj6jChLjyREguCKghQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=wBGqHUAvf4+c+IYswKUGcw==, mapNumber=null, authorCompany=null, fund=null, authors=

魏孟伶（2000—），女，硕士在读，研究方向：劳动卫生与环境卫生

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魏孟伶（2000—），女，硕士在读，研究方向：劳动卫生与环境卫生

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Proceedings of the National Academy of Sciences of the United States of America, 2015, 112(30): E4104-E4110., articleTitle=Quantification of biological aging in young adults, refAbstract=null), Reference(id=1241023869692211409, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, doi=null, pmid=null, pmcid=null, year=2023, volume=36, issue=2, pageStart=40, pageEnd=46, url=null, language=null, rfNumber=[30], rfOrder=31, authorNames=蔡少华, 谭萍芬, 王军永, journalName=医学与社会, refType=null, unstructuredReference=蔡少华，谭萍芬，王军永，等．基于健康生态学理论的我国老年人认知功能影响因素分析[J].医学与社会，2023, 36(2): 40-46., articleTitle=基于健康生态学理论的我国老年人认知功能影响因素分析, refAbstract=null), Reference(id=1241023869767708887, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, doi=null, pmid=null, pmcid=null, year=2023, volume=36, issue=2, pageStart=40, pageEnd=46, url=null, language=null, rfNumber=[30], rfOrder=32, authorNames=Cai SH, Tan PF, Wang JY, journalName=Medicine and Society, refType=null, unstructuredReference=Cai SH, Tan PF, Wang JY, et al. 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Series a, Biological Sciences and Medical Sciences, 2021, 76(10): 1854-1863., articleTitle=Epigenetic age acceleration and cognitive decline: a twin study, refAbstract=null), Reference(id=1241023870031950057, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, doi=null, pmid=null, pmcid=null, year=2020, volume=94, issue=6, pageStart=e613, pageEnd=e625, url=null, language=null, rfNumber=[33], rfOrder=35, authorNames=Beydoun MA, Shaked D, Tajuddin SM, journalName=Neurology, refType=null, unstructuredReference=Beydoun MA, Shaked D, Tajuddin SM, et al. Accelerated epigenetic age and cognitive decline among urban-dwelling adults[J]. Neurology, 2020, 94(6): e613-e625., articleTitle=Accelerated epigenetic age and cognitive decline among urban-dwelling adults, refAbstract=null), Reference(id=1241023870203916532, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, doi=null, pmid=null, pmcid=null, year=2022, volume=16, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[34], rfOrder=36, authorNames=Liang WS, Goetz LH, Schork NJ, journalName=Frontiers in Neuroscience, refType=null, unstructuredReference=Liang WS, Goetz LH, Schork NJ. Assessing brain and biological aging trajectories associated with Alzheimer’s disease[J]. Frontiers in Neuroscience, 2022, 16: 1036102., articleTitle=Assessing brain and biological aging trajectories associated with Alzheimer’s disease, refAbstract=null)], funds=[Fund(id=1241023864264782768, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, awardId=2023NSFSC1736, language=CN, fundingSource=四川省自然科学基金青年基金项目(2023NSFSC1736), fundOrder=null, country=null), Fund(id=1241023864365446073, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, awardId=2022YFS0422, language=CN, fundingSource=四川省科技计划资助(2022YFS0422), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241023855104422253, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, xref=1．, ext=[AuthorCompanyExt(id=1241023855137976690, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, companyId=1241023855104422253, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China), AuthorCompanyExt(id=1241023855167336820, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, companyId=1241023855104422253, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1．四川大学华西公共卫生学院/四川大学华西第四医院劳动卫生与环境卫生学系，四川　成都　610041)]), AuthorCompany(id=1241023855263805815, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, xref=2．, ext=[AuthorCompanyExt(id=1241023855322526075, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, companyId=1241023855263805815, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2．四川大学华西公共卫生学院/华西第四医院健康管理中心)]), AuthorCompany(id=1241023855439966595, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, xref=3．, ext=[AuthorCompanyExt(id=1241023855452549509, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, companyId=1241023855439966595, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3．四川大学华西公共卫生学院/华西第四医院骨质疏松科)]), AuthorCompany(id=1241023855674847624, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, xref=4．, ext=[AuthorCompanyExt(id=1241023855679041929, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, companyId=1241023855674847624, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4．四川大学华西医院/四川大学华西临床医学院)])], figs=[ArticleFig(id=1241023861488153367, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=EN, label=Fig.1, caption=Scatter plot and smooth curve of BAI and MoCA scores, figureFileSmall=9ySeEBgDMdF2jdNOYe1XEw==, figureFileBig=P76Zsj6jChLjyREguCKghQ==, tableContent=null), ArticleFig(id=1241023863023268651, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=CN, label=图1, caption=BAI与MoCA评分的散点图及平滑曲线, figureFileSmall=9ySeEBgDMdF2jdNOYe1XEw==, figureFileBig=P76Zsj6jChLjyREguCKghQ==, tableContent=null), ArticleFig(id=1241023863304287047, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=EN, label=Fig.2, caption=Relationship between BAI and MoCA score, figureFileSmall=SYuS059Kjl3M9SvraQZugA==, figureFileBig=qtL/stA9oqhgYsEW+XA56A==, tableContent=null), ArticleFig(id=1241023863451087702, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=CN, label=图2, caption=BAI与MoCA评分的关系

注：95%CI代表95%置信区间。模型1仅调整年龄和性别；模型2进一步调整受教育年限、收入、婚姻状况和生活方式等其他协变量。

, figureFileSmall=SYuS059Kjl3M9SvraQZugA==, figureFileBig=qtL/stA9oqhgYsEW+XA56A==, tableContent=null), ArticleFig(id=1241023863581111140, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=EN, label=Fig.3, caption=Relationship between BAI and MCI risk, figureFileSmall=Wl/AuWC4YmTztV1T4K1LFA==, figureFileBig=N/+VTwSWeUYqYMo6Do8Ylg==, tableContent=null), ArticleFig(id=1241023863669191533, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=CN, label=图3, caption=BAI与MCI风险的关系

注：95%CI代表95%置信区间。模型1仅调整年龄和性别；模型2进一步调整受教育年限、收入、婚姻状况和生活方式等其他协变量。

, figureFileSmall=Wl/AuWC4YmTztV1T4K1LFA==, figureFileBig=N/+VTwSWeUYqYMo6Do8Ylg==, tableContent=null), ArticleFig(id=1241023863778243451, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=EN, label=Table 1, caption=

Basic characteristics of research objects

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总体中年组
（<65岁）		老年组
（≥65岁）		t/χ2值P值
人数407272(66.8)135(33.2)
CA60.38±10.6853.95±5.2373.33±6.0931.64<0.001
性别52.36<0.001
男160(39.3)141(51.8)19(14.1)
女247(60.4)131(48.2)116(85.9)
文化程度87.00<0.001
小学及以下48(11.8)9(3.3)39(28.9)
初中86(21.1)46(16.9)40(29.6)
高中(中专)85(20.9)56(20.6)29(21.5)
本科(大专)及以上188(46.2)161(59.2)27(20.0)
婚姻状况45.30<0.001
已婚361(88.7)262(96.3)99(73.3)
离婚/分居/丧偶46(11.3)10(3.7)36(26.7)
月平均收入(元)20.35<0.001
≤2 00052(12.8)30(11.0)22(16.3)
2 001~6 000160(39.3)93(34.2)67(49.6)
6 001~9 999123(30.2)87(32.0)36(26.7)
≥10 00072(17.7)62(22.8)10(7.4)
吸烟情况25.85<0.001
不吸烟299(73.5)178(65.4)121(89.6)
吸烟108(26.5)94(34.6)14(10.4)
饮酒情况29.01<0.001
从不喝酒298(73.2)176(64.7)122(90.4)
喝酒(≥1次/周)109(26.8)96(35.3)13(9.6)
夜间睡眠时长（h）18.84<0.001
<7106(26.0)55(20.2)51(37.8)
7~8252(61.9)188(69.1)64(47.4)
≥949(12.0)29(10.7)20(14.8)
自评睡眠质量4.620.202
很好114(28.0)74(27.2)40(29.6)
较好198(48.6)135(49.6)63(46.7)
较差74(18.2)53(19.5)21(15.6)
很差21(5.2)10(3.7)11(8.1)
午睡情况（min）7.080.069
不午睡135(33.2)79(29.0)56(41.5)
≤30145(35.6)106(39.0)39(28.9)
31~6099(24.3)67(24.6)32(23.7)
>6028(6.9)20(7.4)8(5.9)
BA60.34±11.2753.93±6.0673.26±7.6725.59<0.001
BAI0.00±3.620.01±3.29-0.03±4.210.100.921
BAT0.210.648
提前201(49.4)137(50.4)64(47.4)
滞后206(50.6)135(49.6)71(52.6)
MoCA得分23.30±4.3024.53±3.4220.81±4.818.03<0.001
MCI169(41.5)83(30.5)86(63.7)39.57<0.001
), ArticleFig(id=1241023863853740936, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=CN, label=表1, caption=

研究对象的基本特征

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总体中年组
（<65岁）		老年组
（≥65岁）		t/χ2值P值
人数407272(66.8)135(33.2)
CA60.38±10.6853.95±5.2373.33±6.0931.64<0.001
性别52.36<0.001
男160(39.3)141(51.8)19(14.1)
女247(60.4)131(48.2)116(85.9)
文化程度87.00<0.001
小学及以下48(11.8)9(3.3)39(28.9)
初中86(21.1)46(16.9)40(29.6)
高中(中专)85(20.9)56(20.6)29(21.5)
本科(大专)及以上188(46.2)161(59.2)27(20.0)
婚姻状况45.30<0.001
已婚361(88.7)262(96.3)99(73.3)
离婚/分居/丧偶46(11.3)10(3.7)36(26.7)
月平均收入(元)20.35<0.001
≤2 00052(12.8)30(11.0)22(16.3)
2 001~6 000160(39.3)93(34.2)67(49.6)
6 001~9 999123(30.2)87(32.0)36(26.7)
≥10 00072(17.7)62(22.8)10(7.4)
吸烟情况25.85<0.001
不吸烟299(73.5)178(65.4)121(89.6)
吸烟108(26.5)94(34.6)14(10.4)
饮酒情况29.01<0.001
从不喝酒298(73.2)176(64.7)122(90.4)
喝酒(≥1次/周)109(26.8)96(35.3)13(9.6)
夜间睡眠时长（h）18.84<0.001
<7106(26.0)55(20.2)51(37.8)
7~8252(61.9)188(69.1)64(47.4)
≥949(12.0)29(10.7)20(14.8)
自评睡眠质量4.620.202
很好114(28.0)74(27.2)40(29.6)
较好198(48.6)135(49.6)63(46.7)
较差74(18.2)53(19.5)21(15.6)
很差21(5.2)10(3.7)11(8.1)
午睡情况（min）7.080.069
不午睡135(33.2)79(29.0)56(41.5)
≤30145(35.6)106(39.0)39(28.9)
31~6099(24.3)67(24.6)32(23.7)
>6028(6.9)20(7.4)8(5.9)
BA60.34±11.2753.93±6.0673.26±7.6725.59<0.001
BAI0.00±3.620.01±3.29-0.03±4.210.100.921
BAT0.210.648
提前201(49.4)137(50.4)64(47.4)
滞后206(50.6)135(49.6)71(52.6)
MoCA得分23.30±4.3024.53±3.4220.81±4.818.03<0.001
MCI169(41.5)83(30.5)86(63.7)39.57<0.001
), ArticleFig(id=1241023864025707414, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=EN, label=Table 2, caption=

Relationship analysis between BAI and MoCA scores

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人群模型1模型2
β（95%CI）P值β（95%CI）P值
总体-0.164（-0.264~-0.063）0.002-0.135（-0.229~-0.042）0.005
中年组-0.151（-0.267~-0.035）0.011-0.140（-0.257~-0.024）0.019
老年组-0.198（-0.387~-0.010）0.040-0.107（-0.273~0.058）0.202
), ArticleFig(id=1241023864134759328, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023851476349181, language=CN, label=表2, caption=

BAI与MoCA评分的关系分析

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人群模型1模型2
β（95%CI）P值β（95%CI）P值
总体-0.164（-0.264~-0.063）0.002-0.135（-0.229~-0.042）0.005
中年组-0.151（-0.267~-0.035）0.011-0.140（-0.257~-0.024）0.019
老年组-0.198（-0.387~-0.010）0.040-0.107（-0.273~0.058）0.202
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中老年人生物学衰老与认知功能的关系研究
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魏孟伶 1 , 贺绘宇 1 , 王娟 2 , 钟娇 3 , 黄磊 4 , 张洋 4 , 兰亚佳 1
现代预防医学 | 疾病预防控制 2025,52(2): 342-348
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现代预防医学 | 疾病预防控制 2025, 52(2): 342-348
中老年人生物学衰老与认知功能的关系研究
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魏孟伶1, 贺绘宇1, 王娟2, 钟娇3, 黄磊4, 张洋4 , 兰亚佳1
作者信息
  • 1．四川大学华西公共卫生学院/四川大学华西第四医院劳动卫生与环境卫生学系，四川　成都　610041
  • 2．四川大学华西公共卫生学院/华西第四医院健康管理中心
  • 3．四川大学华西公共卫生学院/华西第四医院骨质疏松科
  • 4．四川大学华西医院/四川大学华西临床医学院

    • 魏孟伶（2000—），女，硕士在读，研究方向：劳动卫生与环境卫生

通讯作者:

张洋，E-mail：
Study on the association between biological aging and cognitive function in middle-aged and elderly Chinese
Meng-ling WEI1, Hui-yu HE1, Juan WANG2, Jiao ZHONG3, Lei HUANG4, Yang ZHANG4 , Ya-jia LAN1
Affiliations
  • Department of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2025-01-25 doi: 10.20043/j.cnki.MPM.202409204
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摘要
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目的

探讨中老年人生物学衰老和认知功能的关系。

方法

研究对象来自某三甲医院的45岁以上体检人员，通过问卷和蒙特利尔认知评估量表（Montreal cognitive assessment，MoCA）收集一般人口学特征、协变量以及认知功能状况，采用多因素线性回归、logistic回归分析生物学衰老指数（biological aging index，BAI）、生物学衰老类型（biological aging type，BAT）与MoCA评分、轻度认知障碍（mild cognitive impairment，MCI）风险的相关性。并按中年组（45~64岁）和老年组（65岁及以上）进行亚组分析，探究生物学衰老与认知功能的相关性在不同年龄组中是否存在差异。

结果

本研究共纳入407人，平均MoCA得分为23.30±4.30，MCI检出率为41.5%。BAI与MoCA评分呈负相关，调整协变量后的回归系数为-0.135（95%CI：-0.229~-0.042）。与滞后衰老相比，提前衰老的研究对象认知功能评分更低（β=-0.882，95%CI：-1.566~-0.198），MCI风险更高（OR=1.736，95%CI：1.072~2.833）。亚组分析发现中年组仍存在上述关联，而老年组不成立。

结论

中老年人生物学衰老与认知功能存在负向关联，且提前衰老的研究对象认知功能更差，中年组中这种效应更为显著，提示应在中年甚至更早时期识别提前衰老个体并采取干预措施预防或延缓痴呆发生。

中老年人  /  生物学衰老  /  生物学年龄  /  认知功能  /  轻度认知障碍（MCI）
Objective

To investigate the association between biological aging and cognitive function in middle-aged and elderly Chinese.

Methods

The subjects were health check-up personnel over 45 years old from a top three hospital. The general demographic characteristics, covariates and cognitive function status were collected by questionnaire and Montreal cognitive assessment (MoCA). Multivariate linear regression and logistic regression were used to analyze biological aging index (BAI) and biological aging type (BAT) association with MoCA score and risk of mild cognitive impairment (MCI). Subgroup analysis was conducted by the middle-aged group (45-64 years old) and the elderly group (65 years old and above) to explore whether the correlation between biological aging and cognitive function was different in different age groups.

Results

A total of 407 participants were included in this study. The average MoCA score was 23.30±4.30, and the detection rate of MCI was 41.5%. BAI was negatively correlated with MoCA score, and the regression coefficient after adjusting for covariates was -0.135 (95%CI: -0.229--0.042). Compared with those with delayed aging, subjects with premature aging had lower cognitive function scores (β=-0.882，95%CI：-1.566--0.198) and a higher risk of MCI (OR=1.736，95%CI：1.072-2.833). Subgroup analysis found that the association was still present in the middle-aged group, but not in the elderly group.

Conclusion

There is a negative correlation between biological aging and cognitive function in middle-aged and elderly people, and the cognitive function of subjects with premature aging is worse. This effect is more significant in middle-aged group, suggesting that individuals with premature aging should be identified in middle age or even earlier and that intervention measures should be taken to prevent or delay the occurrence of dementia.

Middle-aged and elderly  /  Biological aging  /  Biological age  /  Cognitive function  /  Mild cognitive impairment (MCI)
魏孟伶, 贺绘宇, 王娟, 钟娇, 黄磊, 张洋, 兰亚佳. 中老年人生物学衰老与认知功能的关系研究. 现代预防医学, 2025 , 52 (2) : 342 -348 . DOI: 10.20043/j.cnki.MPM.202409204
Meng-ling WEI, Hui-yu HE, Juan WANG, Jiao ZHONG, Lei HUANG, Yang ZHANG, Ya-jia LAN. Study on the association between biological aging and cognitive function in middle-aged and elderly Chinese[J]. Modern Preventive Medicine, 2025 , 52 (2) : 342 -348 . DOI: 10.20043/j.cnki.MPM.202409204
正文
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过去20年，我国老龄人口快速增长，65岁以上人口占比由7%增长至14.2%[1]，预计2050年将达3.95亿[1]。随着老龄化的加深，痴呆已成为继心血管、脑血管和肿瘤的第四大危害老年人健康的病因，不仅会引起老年人晚年生活不便，还会给家庭和社会带来沉重负担[3]。轻度认知障碍（mild cognitive impairment，MCI）被认为是正常老化到痴呆的过渡阶段，近80%的MCI患者将转化为痴呆，远高于正常衰老人群1%~2%的发病率[4]。因此，MCI的早期识别和干预是预防痴呆的重要途径。现有的年龄与认知功能关系研究多是基于时序年龄（chronological age，CA），但受遗传和环境因素的影响，CA不能反映衰老程度以及认知功能衰退的个体差异性[5]。基于此，生物学年龄（biological age，BA）被提出并用于衡量不同个体真实生物学衰老程度。目前已开发出多种BA估计方法，因公式直观，指标间关系明确等优点，多重线性回归、主成分分析和Klemera and Doubal method（KDM）得到广泛应用。Levine[6]对以上三种方法进行比较发现，KDM结果最稳健，近年来应用此法计算BA来探究其与死亡或年龄相关疾病的研究也颇多[7-11]。此外，有研究发现，加速的生物学衰老过程可能与记忆功能的快速下降有关，而健康老年群体的BA可以预测包括痴呆在内的衰老相关疾病[12-13]。但目前我国对BA和衰老相关结局的研究较少，BA与认知功能的系统性研究仍有空缺。且大部分研究以65岁以上老年人群为对象，这一群体往往已经处于认知下降甚至认知损害状态。研究表明在生命中期采取积极的干预手段，可以降低痴呆的发病率[14-15]。因此本研究以45岁以上人群为研究对象，采用KDM估计BA，在此基础上探索生物学衰老与认知功能的关系，以达到早期识别潜在的高危个体，及早进行干预以预防和延缓认知功能下降的目的。
1　对象与方法
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1.1　研究对象
本研究选取的调查对象来自2023年5—8月在某三甲医院健康管理中心进行健康体检的45岁以上人员，研究人群的纳入排除标准：（1）纳入体检项目较完善，满足BA计算要求的45岁以上中老年人；（2）排除听力及语言沟通障碍，无法完成现场调查的对象；（3）排除有影响认知功能及记忆力的药物服用史、手术史和外伤史的对象；（4）排除患有如癫痫、脑梗塞、脑卒中等导致认知功能障碍的其他疾病的对象。此次研究招募、获得知情同意且完成问卷调查的对象共469人，排除未完成认知功能测试的调查对象37人、已患有影响记忆功能的疾病的调查对象4人以及体检项目不全的调查对象21人，最终纳入407人。本研究经四川大学华西第四医院医学伦理委员会审批通过（批件号：HXSY-EC-2023056），所有研究对象均获得知情同意并签署知情同意书。
1.2　方法
1.2.1　资料收集
（1）问卷调查：调查内容包括研究对象的一般人口学特征（年龄、性别、文化程度、婚姻状况和月平均收入等），其他影响因素（吸烟、饮酒、午睡情况、夜间睡眠时长和睡眠质量等）。问卷内容由调查员面对面访谈后录入平板，当日调查结束后由核查员核实问卷收集情况，所有调查员和核查员均经过统一培训。（2）体检资料：获取纳入调查对象当日的健康体检资料，参考既往研究[16-17]并结合现场实际情况，共收集44个潜在生理指标用于估计BA，包括：①一般体格检查：身高、体重、血压、脉率；②血液常规分析：白细胞计数、中性粒细胞计数、淋巴细胞计数、单核细胞计数、嗜酸性粒细胞计数、嗜碱性粒细胞计数、未成熟粒细胞计数、中性粒细胞百分比、淋巴细胞百分比、单核细胞百分比、嗜酸性粒细胞百分比、嗜碱性粒细胞百分比、未成熟粒细胞百分比、红细胞计数、血红蛋白、红细胞比积、红细胞平均体积、平均血红蛋白量、平均血红蛋白浓度、红细胞分布宽度、血小板计数、平均血小板体积、血小板分布宽度、血小板压积；③肾功能检查：尿素氮、肌酐、尿酸；④肝功能检查：总蛋白、白蛋白、球蛋白、白球比、丙氨酸氨基转移酶、天门冬氨酸氨基转移酶、总胆红素、直接胆红素、间接胆红素；⑤其他血液生化检查：葡萄糖、总胆固醇、甘油三酯、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇。（3）认知功能评估：采用蒙特利尔认知评估量表（Montreal cognitive assessment，MoCA）-北京版[18]评估调查对象的认知功能状况。MoCA分数区间为0~30分，得分越高代表认知功能越好。此外，认知水平与文化程度密切相关，若研究对象的受教育年限不超过12年，则MoCA得分加1分，最高不超过30分[19]。参考既往中国中老年人群MCI筛查研究和汉化版MoCA量表常模[18]，本研究根据受教育年限设置MCI截断值，将文盲且MoCA分数<13分；受教育年限≥6年且MoCA分数≤19分；受教育年限≥7年且MoCA分数≤24分定义为MCI。（4）协变量定义：协变量包括一般人口学特征：年龄、性别、文化程度（小学及以下、初中、高中/中专和本科/大专及以上）、婚姻状况（已婚和其他）和月平均收入（元）（≤2 000、2 001~6 000、6 001~9 999和≥10 000）；其他影响因素：吸烟（吸烟、不吸烟）、饮酒情况（从不喝酒、喝酒）、午睡时长（min）（不午睡、≤30、31~60和>60）、夜间睡眠时长（h）（<7、7~8和>8）和自评睡眠质量（很好、较好、较差和很差）。
1.2.2　生物学衰老估算
（1）生理指标筛选：考虑到衰老过程的性别差异，分性别将44个潜在指标进行皮尔森（Pearson）相关性分析，同时参考Jee和Park[20]估计东南亚女性BA时选择生理指标的方法，纳入Pearson相关系数绝对值（即|r|）>0.15且P<0.05的指标。随后进行冗余性分析并计算方差膨胀因子（variance inflation factors，VIF），确保最终纳入的指标与CA高度相关且独立。最终纳入BA估计的生物学指标男性10个，女性13个。其中，收缩压、红细胞计数、红细胞宽度、血小板压积、尿素、肌酐、白蛋白为男性和女性共有，此外，男性还包括嗜碱性粒细胞计数、丙氨酸氨基转移酶和甘油三酯；女性还包括嗜酸性粒细胞计数、单核细胞计数、血小板分布宽度、尿酸、天门冬氨酸氨基转移酶和白球比。（2）KDM：选用由Klemera和Doubal提出的KDM估计BA，BA被定义为CA加上一个均值为0，方差为的随机项[6,21]。（3）生物学衰老指标：本研究将BA和CA做一般线性回归分析后的残差值定义为生物学衰老指数（biological aging index，BAI）。若个体BAI>0，则表示个体相较于同龄人衰老程度更大即实际生理机能更“老”；若个体BAI=0，则表示个体的衰老程度与预期相符；若个体BAI<0，则表示个体相较于同龄人衰老程度更小即实际生理机能更“年轻”。根据BAI值，本研究理论上定义三种生物学衰老类型（biological aging type，BAT）：正常衰老（BAI=0）、提前衰老（BAI>0）和滞后衰老（BAI<0）。
1.3　统计分析
本研究采用R（4.1.1版本）进行统计分析，连续变量用均数±标准差（）表示，分类变量用计数及其构成比表示。通过绘制散点图并将数据局部加权回归（locally weighted regression，Lowess）后拟合平滑曲线以初步探索生物学衰老与认知功能的关系。采用多因素线性回归模型分析BAI与认知功能评分的相关性。利用一般线性回归、logistic回归模型分析BAT与认知功能评分、MCI风险的关系进一步探究衰老类型与认知功能的相关性。此外，按中年组（45~64岁）和老年组（65岁及以上）进行亚组分析，探究生物学衰老与认知功能的相关性在不同年龄组中是否存在差异。以上分析中，模型1仅调整年龄和性别，模型2进一步调整其他协变量。分析采用双侧检验，检验水准α=0.05。
2　结果
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2.1　研究对象的基本特征
本研究最终纳入研究对象407人，女性多于男性（60.4% vs. 39.3%），65岁以下有272人（66.8%）。46.2%的研究对象文化程度在本科（大专）及以上，中年组占比更高（59.2%），80.0%的65岁以上老人文化程度在高中（中专）及以下。研究总体平均BAI为0.00±3.62岁，其中，中年组为0.01±3.29岁，老年组为-0.03±4.2岁。从BAT上看，中年组中提前衰老人群占比更大（50.4% vs. 49.6%），而老年组则相反（47.4% vs. 52.6%）。研究对象平均MoCA得分为23.30±4.30，MCI检出率为41.5%。见表1。
2.2　生物学衰老与认知功能的关系
探索从散点图和平滑曲线上看，BAI主要分布在-5岁至5岁这一区间，随着BAI增大，MoCA评分逐渐下降。当BAI>0时MoCA评分下降趋势较BAI<0时更明显，见图1。
2.3　生物学衰老与认知功能评分的回归分析
采用一般线性回归构建模型分析BAI与MoCA评分的关系，结果见表2。总体上，模型1和模型2均具有统计学意义。将CA分层进行亚组分析，中年组的两个模型仍具有统计学意义；而老年组仅模型1具有统计学意义（β=-0.198，95%CI：-0.387~-0.010，P=0.040）。
进一步探索BAT与MoCA评分的关系。滞后衰老的研究对象MoCA评分高于提前衰老的研究对象（23.80±3.96 vs. 22.78±4.58，P=0.017），MCI检出率为36.4%，低于提前衰老的研究对象（46.8%），差异具有统计学意义。按CA分组后，两个年龄组的MoCA得分均是滞后衰老组高于提前衰老组，差异具有统计学意义。此外，与全人群一致，MCI检出率均是滞后衰老组低于提前衰老组，但未达到统计学检验水准。利用多因素线性回归模型分析BAT与认知功能评分的关系，结果如图2所示。模型1仅调整年龄和性别，相较于滞后衰老组，提前衰老组的MoCA评分更低（β=-1.125，95%CI：-1.854~-0.396），进一步调整其他协变量，模型仍具有统计学意义（β=-0.882，95%CI：-1.566~-0.198）。根据CA分层进行亚组分析，中年组模型1和模型2也发现上述关联，调整协变量后的效应量略小于研究总体人群（β=-0.848，95%CI：-1.610~-0.074）。老年组模型1中，提前衰老组的MoCA评分低于滞后衰老组（β=-1.767，95%CI：-3.348~-0.185），模型2不具有统计学意义（β=-0.624，95%CI：-2.053~0.806）。
2.4　生物学衰老与MCI风险的关系
采用多因素logistic回归模型分析BAT与MCI风险的关系，结果见图3。仅调整年龄和性别时，与滞后衰老相比，提前衰老的人群的MCI风险增加78.4%（OR=1.784，95%CI：1.147~2.795），进一步调整其他协变量后，提前衰老组相较于滞后衰老组的MCI风险增加73.6%（OR=1.736，95%CI：1.072~2.833）。按CA进行亚组分析，中年组的结果与总体相似，在模型1和模型2中均发现提前衰老的研究对象MCI风险增加，且调整后的OR值大于研究总体人群，分别为2.018和1.868。老年组中2个模型均不具有统计学意义。
3　讨论
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本研究共纳入407名中老年人，年龄范围为45~88岁。既往研究表明，痴呆和MCI发病风险随年龄增加而升高[22-24]，特别是65岁以后，痴呆发病风险呈指数上升[15]。故本研究在总体探讨生物学衰老与认知功能关系的基础上，以65岁为分界将研究对象分为中年组和老年组进行亚组分析。研究结果显示，随着BAI的增大，MoCA评分逐渐下降，当BAI<0时曲线变化较小而BAI>0时MoCA评分下降趋势较明显，反映出两种衰老类型在认知功能变化上的区别。多因素线性回归分析结果显示，在调整协变量后，研究对象的BAI均与MoCA评分存在负向关联，即以CA为基准，较高的生物学衰老程度与较低的认知功能水平有关。相较于滞后衰老，提前衰老的研究对象的MoCA评分更低且MCI风险更高。目前虽缺乏生物学衰老与认知功能关系的相关文献，但仍有一些类似的研究支持两者之间的关联性。从生理机制上说，神经退行性疾病发展过程中受到不同衰老过程的调控，包括细胞衰老、表观遗传学变化、脑血管功能障碍、炎症和脂质失调等[25]。DNA甲基化时钟以表观遗传变化反映个体的衰老状态，对阿尔茨海默病（Alzheimer’s disease，AD）患者大脑前额叶皮层分析后发现，Horvath和PhenoAge时钟与AD的神经病理学标志物有关，包括弥漫和神经炎性斑块、淀粉样蛋白负荷和神经原纤维缠结等[26-27]。
Belsky等人[28-29]认为研究生物学衰老的最大价值在于估计那些尚未患有与衰老密切相关疾病的个体，即中年人甚至更年轻的群体。同时，既往研究发现在中年期积极干预风险因素如戒烟、限酒以及加强对高血压、听力障碍、抑郁症、糖尿病和肥胖的管理可以预防或推迟痴呆的发病[15,22]。本研究在亚组分析后发现上述负向关联在中年组的两个模型中仍然存在，但老年组在调整其他协变量后结果不具有统计学意义。高龄被认为是MCI的独立危险因素，随着年龄的增长，老年人身体、心理和社会适应能力的衰退加速了认知功能的衰退[30]。此时，无论生物学衰老程度是否较高，MCI发生率均显著增加。但中年与老年组之间呈现的差异强调了在中年期采取干预措施的重要意义。现有关于加速的表观遗传时钟与中年人痴呆风险的关系研究所得结果不尽相同，一些研究并没有在中年人群中观察到表观遗传年龄或年龄加速与认知功能之间的关系[28,31-32]，但也有研究发现表观遗传年龄加速与中年男性视觉记忆力和注意力的下降有关[33]。研究结果的差异可能与研究人群的异质性、衰老过程以及与表观遗传时钟测量相关的因素有关[34]。
本研究具有一定优势，首先，本研究定义BAI和BAT作为生物学衰老指标，并揭示了BAI与认知功能存在负向关联以及提前和滞后两种BAT的研究对象认知功能存在差异；其次，本研究选择45岁以上中老年人群作为研究对象，发现生物学衰老与认知功能的相关性在两个年龄组中存在差异，从衰老的角度强调了通过估计BA早期识别高危个体的重要性。本研究也具有一定局限性，第一，本研究仅针对一家三甲医院的45岁以上体检人员展开调查，结果外推性可能受限。第二，本研究纳入的临床指标虽易于获取、成本低廉且适用于更普遍化的临床或社区诊疗背景，但不同的生物学衰老指标可能反映了衰老过程的不同方面[28]，当前BA估计可能受到标志物可获得性的影响，今后有必要在同一人群中对比不同生物学衰老指标的区别以及与认知功能乃至痴呆风险的相关性，增强研究结果的可信度。第三，本研究仅测量了横断面上的生物学衰老程度，无法获得研究对象差异化的衰老速度等重要信息。第四，尽管在分析中调整了潜在的影响因素，但仍有其他未被测量的混杂因素可能影响研究结果稳健性和效应量。
综上所述，中老年人群生物学衰老与认知功能存在负向关联，在中年人群中尤为明显。这提醒我们应从中年甚至更早阶段进行干预，对这部分人进行健康教育并提倡健康生活方式，从而降低认知障碍的发生率，提高老年人的生活质量。
基金
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  • 四川省自然科学基金青年基金项目(2023NSFSC1736)
  • 四川省科技计划资助(2022YFS0422)
文献
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doi: 10.20043/j.cnki.MPM.202409204
  • 接收时间：2024-09-10
  • 首发时间：2026-03-18
  • 出版时间：2025-01-25
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  • 收稿日期：2024-09-10
基金
四川省自然科学基金青年基金项目(2023NSFSC1736)
四川省科技计划资助(2022YFS0422)
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    1．四川大学华西公共卫生学院/四川大学华西第四医院劳动卫生与环境卫生学系，四川　成都　610041
    2．四川大学华西公共卫生学院/华西第四医院健康管理中心
    3．四川大学华西公共卫生学院/华西第四医院骨质疏松科
    4．四川大学华西医院/四川大学华西临床医学院

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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
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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