Article(id=1240395012438029249, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240395006914130733, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202501175, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1736438400000, receivedDateStr=2025-01-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773662816390, onlineDateStr=2026-03-16, pubDate=1753372800000, pubDateStr=2025-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773662816390, onlineIssueDateStr=2026-03-16, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773662816390, creator=13701087609, updateTime=1773662816390, updator=13701087609, issue=Issue{id=1240395006914130733, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='14', pageStart='2497', pageEnd='2688', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1773662815073, creator=13701087609, updateTime=1773662858015, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240395187109810535, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240395006914130733, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240395187109810536, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240395006914130733, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2613, endPage=2618, ext={EN=ArticleExt(id=1240395014036059128, articleId=1240395012438029249, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Relationship between mobile phone and internet usage and subjective and objective cognitive functions in middle-aged and elderly people, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the relationship between smartphones usage, internet usage and subjective, objective cognitive functions.

Methods

Multi-stage cluster random sampling method was used to select 45-70 year old permanent residents from 7 sample villages in Pingyin County, Shandong Province who meet the standards. The subjective cognitive decline-questionnaire 9 (SCD-Q9) and the montreal cognitive assessment basic scale (MoCA-B) were used to evaluate the subjective and objective cognitive functions, respectively. The logistic regression model was used to calculate the odds ratio (OR) and 95% confidence interval (95% CI) of the relationship between smartphones usage, internet usage and subjective, objective cognitive function. Furthermore, the non-linear relationship between smartphones usage, internet usage and cognitive function scores was explored.

Results

This study included 1 654 participants. Compared with those who did not use mobile phones, those who used mobile phones had a 42% lower risk of experiencing abnormal objective cognitive scores (OR=0.58, 95% CI: 0.46-0.73), and the risk of abnormal objective cognitive scores was relatively low when using a mobile phone for less than or equal to 2 hours per day or more than 2 hours per day (0.65, 0.51-0.82; 0.69, 0.55-0.88). Compared to those who did not use the internet, internet users had a 41% lower risk of experiencing abnormal objective cognitive scores (0.59, 0.47-0.74), and people who spent less than 1 hour online or more than 2 hours online had a lower risk of experiencing abnormal objective cognitive scores compared to those who spent less than or equal to 1 hour online (0.65, 0.52-0.83; 0.66, 0.52-0.83). Nonlinear correlation showed that as the duration of mobile phone use and internet usage gradually increased, the objective cognitive score showed a trend of first increasing and then decreasing.

Conclusion

People who use mobile phones and the internet have a lower risk of experiencing objective cognitive score abnormalities. As the duration of mobile phone use and internet usage increases, the objective cognitive score shows a non-linear trend of first increasing and then decreasing. Overuse of mobile phones and the internet (such as>5.5 h/d) may have adverse effects on cognitive function.

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目的

探讨手机及网络使用情况与主、客观认知功能的关系。

方法

采用多阶段整群随机抽样方法选取符合标准的山东省平阴县7个样本村的45~70岁常住居民,分别采用主观认知下降自测量表(SCD-Q9)和蒙特利尔认知评估基础量表(MoCA-B)评估研究对象的主、客观认知功能。采用logistic回归模型计算手机及网络使用情况与主、客观认知功能的比值比(OR)和95%置信区间(95% CI),进一步拟合手机使用时长及上网时长与主、客观认知功能得分的非线性关系。

结果

本研究共纳入1 654名参与者。与不使用手机者相比,使用手机者发生客观认知得分异常的风险低42%(OR=0.58,95% CI:0.46~0.73),使用手机>1~2 h/d或>2 h/d出现客观认知得分异常的风险较低(0.65,0.51~0.82;0.69,0.55~0.88)。相较于不上网者,上网者出现客观认知得分异常的风险低41%(0.59,0.47~0.74),且上网>1~2 h/d或>2 h/d的人群比上网时长≤1 h/d的人群发生客观认知得分异常的风险更低(0.65,0.52~0.83;0.66,0.52~0.83)。而非线性关联显示,当手机使用时长、上网时长逐渐增多时,客观认知得分呈先上升后下降的趋势。

结论

使用手机及网络的人群发生客观认知得分异常的风险较低。随着手机使用时长及上网时长增加,客观认知得分呈先上升后下降的非线性趋势,过度使用手机和网络(如>5.5 h/d)可能对认知功能产生不利影响。

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朱东山,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=sg+7qY+ZXS/j4tkWgzw24g==, magXml=NepWQWLgQP+oEBaCdc+0ag==, pdfUrl=null, pdf=8FiqSYR+bnrxEfT5fNPXTA==, pdfFileSize=767003, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=QRPv1Tk7GI33C08eeRHGkw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=macNPc7efnc81r7cDeAYIQ==, mapNumber=null, authorCompany=null, fund=null, authors=

张小宇(2001—),女,硕士在读,研究方向:慢性病流行病学

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Journal of the American Geriatrics Society, 2016, 64(12): e285-e290., articleTitle=Validation of the Chinese version of Montreal cognitive assessment basic for screening mild cognitive impairment, refAbstract=null), Reference(id=1240413554084467216, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, doi=null, pmid=null, pmcid=null, year=2022, volume=43, issue=4, pageStart=619, pageEnd=631, url=null, language=null, rfNumber=[20], rfOrder=25, authorNames=中国营养学会肥胖防控分会, 中国营养学会临床营养分会, 中华预防医学会行为健康分会, journalName=西安交通大学学报:医学版, refType=null, unstructuredReference=中国营养学会肥胖防控分会,中国营养学会临床营养分会,中华预防医学会行为健康分会,等.中国居民肥胖防治专家共识[J].西安交通大学学报:医学版2022,43(4):619-631., articleTitle=中国居民肥胖防治专家共识, refAbstract=null), Reference(id=1240413554155770387, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, doi=null, pmid=null, pmcid=null, year=2022, volume=43, issue=4, pageStart=619, pageEnd=631, url=null, language=null, rfNumber=[20], rfOrder=26, authorNames=Chinese Nutrition Society Obesity Prevention and Control Branch, Chinese Nutrition Society Clinical Nutrition Branch, Chinese Preventive Medicine Association Behavioral Health Branch, journalName=Journal of Xi’an Jiaotong University: Medical Sciences, refType=null, unstructuredReference=Chinese Nutrition Society Obesity Prevention and Control Branch, Chinese Nutrition Society Clinical Nutrition Branch, Chinese Preventive Medicine Association Behavioral Health Branch, et al. Expert consensus on obesity prevention and treatment in China[J]. Journal of Xi’an Jiaotong University: Medical Sciences, 2022, 43(4): 619-631. (In Chinese), articleTitle=Expert consensus on obesity prevention and treatment in China, refAbstract=null), Reference(id=1240413554239656470, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, doi=null, pmid=null, pmcid=null, year=2012, volume=7, issue=8, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[21], rfOrder=27, authorNames=Almeida OP, Yeap BB, Alfonso H, journalName=PLOS One, refType=null, unstructuredReference=Almeida OP, Yeap BB, Alfonso H, et al. Older men who use computers have lower risk of dementia[J]. PLOS One, 2012, 7(8): e44239., articleTitle=Older men who use computers have lower risk of dementia, refAbstract=null), Reference(id=1240413554357096986, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, doi=null, pmid=null, pmcid=null, year=2009, volume=47, issue=10, pageStart=2015, pageEnd=2028, url=null, language=null, rfNumber=[22], rfOrder=28, authorNames=Stern Y, journalName=Neuropsychologia, refType=null, unstructuredReference=Stern Y. Cognitive reserve[J]. Neuropsychologia, 2009, 47(10): 2015-2028., articleTitle=Cognitive reserve, refAbstract=null), Reference(id=1240413554432594461, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, doi=null, pmid=null, pmcid=null, year=2007, volume=11, issue=5, pageStart=477, pageEnd=484, url=null, language=null, rfNumber=[23], rfOrder=29, authorNames=Shapira N, Barak A, Gal I, journalName=Aging & Mental Health, refType=null, unstructuredReference=Shapira N, Barak A, Gal I. Promoting older adults’ well-being through Internet training and use[J]. 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Trends in Cognitive Sciences, 2016, 20(3): 214-226., articleTitle=The locus coeruleus: essential for maintaining cognitive function and the aging brain, refAbstract=null), Reference(id=1240413554596172323, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, doi=null, pmid=null, pmcid=null, year=2015, volume=10, issue=4, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[25], rfOrder=31, authorNames=Kim GH, Jeon S, Im K, journalName=PLOS One, refType=null, unstructuredReference=Kim GH, Jeon S, Im K, et al. Structural brain changes after traditional and robot-assisted multi-domain cognitive training in community-dwelling healthy elderly[J]. PLOS One, 2015, 10(4): e0123251., articleTitle=Structural brain changes after traditional and robot-assisted multi-domain cognitive training in community-dwelling healthy elderly, refAbstract=null), Reference(id=1240413554701029925, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, doi=null, pmid=null, pmcid=null, year=2020, volume=22, issue=2, pageStart=179, pageEnd=187, url=null, language=null, rfNumber=[26], rfOrder=32, authorNames=Small GW, Lee J, Kaufman A, journalName=Dialogues in Clinical Neuroscience, refType=null, unstructuredReference=Small GW, Lee J, Kaufman A, et al. Brain health Consequences of digital technology use[J]. Dialogues in Clinical Neuroscience, 2020, 22(2): 179-187., articleTitle=Brain health Consequences of digital technology use, refAbstract=null), Reference(id=1240413554818470441, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, doi=null, pmid=null, pmcid=null, year=2019, volume=24, issue=1, pageStart=100, pageEnd=109, url=null, language=null, rfNumber=[27], rfOrder=33, authorNames=Zhou F, Montag C, Sariyska R, journalName=Addiction Biology, refType=null, unstructuredReference=Zhou F, Montag C, Sariyska R, et al. Orbitofrontal gray matter deficits as marker of Internet gaming disorder: converging evidence from a cross-sectional and prospective longitudinal design[J]. Addiction Biology, 2019, 24(1): 100-109., articleTitle=Orbitofrontal gray matter deficits as marker of Internet gaming disorder: converging evidence from a cross-sectional and prospective longitudinal design, refAbstract=null)], funds=[Fund(id=1240413549357486464, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, awardId=82273702, language=CN, fundingSource=国家自然科学基金资助项目(82273702), fundOrder=null, country=null), Fund(id=1240413549483315593, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, awardId=2022HWYQ-030, language=CN, fundingSource=山东省优秀青年学者资助项目(2022HWYQ-030), fundOrder=null, country=null), Fund(id=1240413549588173195, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, awardId=tsqnz20221103, language=CN, fundingSource=泰山学者项目专项基金(tsqnz20221103), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1240413540834661368, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, xref=1., ext=[AuthorCompanyExt(id=1240413540843049977, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, companyId=1240413540834661368, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China), AuthorCompanyExt(id=1240413540847244282, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, companyId=1240413540834661368, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.山东大学齐鲁医学院公共卫生学院流行病学系,山东 济南 250012)]), AuthorCompany(id=1240413540977266694, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, xref=2., ext=[AuthorCompanyExt(id=1240413540985655305, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, companyId=1240413540977266694, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.山东大学临床流行病学和循证医学中心)])], figs=[ArticleFig(id=1240413546652160315, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, language=EN, label=Fig.1, caption=The relationship between mobile phone usage duration, internet usage duration, and subjective and objective cognitive scores, figureFileSmall=1vvP7njblMUSdOyUJv/OKA==, figureFileBig=RdUrKdP2k/TU9oPmkuzKJQ==, tableContent=null), ArticleFig(id=1240413546769600839, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, language=CN, label=图1, caption=手机使用时长、上网时长与主、客观认知得分的关系, figureFileSmall=1vvP7njblMUSdOyUJv/OKA==, figureFileBig=RdUrKdP2k/TU9oPmkuzKJQ==, tableContent=null), ArticleFig(id=1240413547004481873, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, language=EN, label=Table 1, caption=

Baseline characteristics of the research population[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
特征总人群
(n=2 150)
是否使用手机是否上网

(n=647)

(n=1 503)

(n=676)

(n=1 474)
基线年龄(岁)
<601 589380(58.73)1 209(80.44)390(57.69)1 199(81.34)
≥60561267(41.27)294(19.56)286(42.31)275(18.66)
性别
1 411450(69.55)961(63.94)469(69.38)942(63.91)
739197(30.45)542(36.06)207(30.62)532(36.09)
教育水平
没上过学275162(25.04)113(7.52)177(26.18)98(6.65)
小学636208(32.15)428(28.48)216(31.95)420(28.49)
初中871224(34.62)647(43.05)225(33.28)646(43.83)
高中及以上36853(8.19)315(20.96)58(8.58)310(21.03)
月收入(元)
<1 0001 405514(79.44)891(59.28)545(80.62)860(58.34)
1 000~<5 000584119(18.39)465(30.94)116(17.16)468(31.75)
≥5 00016114(2.16)147(9.78)15(2.22)146(9.91)
婚姻状况
未婚、丧偶及离异16685(13.14)81(5.39)87(12.87)79(5.36)
已婚1 984562(86.86)1 422(94.61)589(87.13)1 395(94.64)
子女数量
≤1757192(29.68)565(37.59)202(29.88)555(37.65)
21 198384(59.35)814(54.16)398(58.88)800(54.27)
≥319571(10.97)124(8.25)76(11.24)119(8.07)
BMI(kg/m2
<18.5308(1.24)22(1.46)13(1.92)17(1.15)
18.5~<24.0700226(34.93)474(31.54)236(34.91)464(31.48)
24.0~<28.0941291(44.98)650(43.25)299(44.23)642(43.55)
≥28479122(18.86)357(23.75)128(18.93)351(23.81)
久坐时长(小时)
≤2634221(34.16)413(27.48)226(33.43)408(27.68)
>2~4699219(33.85)480(31.94)231(34.17)468(31.75)
4~<6553147(22.72)406(27.01)157(23.22)396(26.87)
≥626460(9.27)204(13.57)62(9.17)202(13.7)
吸烟状况
从不吸烟1 677513(79.29)1 164(77.45)536(79.29)1 141(77.41)
已戒烟18355(8.5)128(8.52)56(8.28)127(8.62)
吸烟29079(12.21)211(14.04)84(12.43)206(13.98)
饮酒频率
从不1 433449(69.4)984(65.47)467(69.08)966(65.54)
偶尔18548(7.42)137(9.12)49(7.25)136(9.23)
经常15337(5.72)116(7.72)37(5.47)116(7.87)
每天24362(9.58)181(12.04)66(9.76)177(12.01)
戒酒13651(7.88)85(5.66)57(8.43)79(5.36)
睡眠时长(小时)
<6534163(25.19)371(24.68)164(24.26)370(25.1)
6~<81 295373(57.65)922(61.34)387(57.25)908(61.6)
≥8321111(17.16)210(13.97)125(18.49)196(13.3)
独居
1 989595(91.96)1 394(92.75)619(91.57)1 370(92.94)
16152(8.04)109(7.25)57(8.43)104(7.06)
高血压
1 484415(64.14)1 069(71.12)433(64.05)1 051(71.3)
666232(35.86)434(28.88)243(35.95)423(28.7)
二型糖尿病
1 888562(86.86)1 326(88.22)585(86.54)1 303(88.4)
26285(13.14)177(11.78)91(13.46)171(11.6)
抑郁状况
1 900563(87.02)1 337(88.96)587(86.83)1 313(89.08)
25084(12.98)166(11.04)89(13.17)161(10.92)
), ArticleFig(id=1240413548531208544, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, language=CN, label=表1, caption=

研究对象人群基线特征[n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
特征总人群
(n=2 150)
是否使用手机是否上网

(n=647)

(n=1 503)

(n=676)

(n=1 474)
基线年龄(岁)
<601 589380(58.73)1 209(80.44)390(57.69)1 199(81.34)
≥60561267(41.27)294(19.56)286(42.31)275(18.66)
性别
1 411450(69.55)961(63.94)469(69.38)942(63.91)
739197(30.45)542(36.06)207(30.62)532(36.09)
教育水平
没上过学275162(25.04)113(7.52)177(26.18)98(6.65)
小学636208(32.15)428(28.48)216(31.95)420(28.49)
初中871224(34.62)647(43.05)225(33.28)646(43.83)
高中及以上36853(8.19)315(20.96)58(8.58)310(21.03)
月收入(元)
<1 0001 405514(79.44)891(59.28)545(80.62)860(58.34)
1 000~<5 000584119(18.39)465(30.94)116(17.16)468(31.75)
≥5 00016114(2.16)147(9.78)15(2.22)146(9.91)
婚姻状况
未婚、丧偶及离异16685(13.14)81(5.39)87(12.87)79(5.36)
已婚1 984562(86.86)1 422(94.61)589(87.13)1 395(94.64)
子女数量
≤1757192(29.68)565(37.59)202(29.88)555(37.65)
21 198384(59.35)814(54.16)398(58.88)800(54.27)
≥319571(10.97)124(8.25)76(11.24)119(8.07)
BMI(kg/m2
<18.5308(1.24)22(1.46)13(1.92)17(1.15)
18.5~<24.0700226(34.93)474(31.54)236(34.91)464(31.48)
24.0~<28.0941291(44.98)650(43.25)299(44.23)642(43.55)
≥28479122(18.86)357(23.75)128(18.93)351(23.81)
久坐时长(小时)
≤2634221(34.16)413(27.48)226(33.43)408(27.68)
>2~4699219(33.85)480(31.94)231(34.17)468(31.75)
4~<6553147(22.72)406(27.01)157(23.22)396(26.87)
≥626460(9.27)204(13.57)62(9.17)202(13.7)
吸烟状况
从不吸烟1 677513(79.29)1 164(77.45)536(79.29)1 141(77.41)
已戒烟18355(8.5)128(8.52)56(8.28)127(8.62)
吸烟29079(12.21)211(14.04)84(12.43)206(13.98)
饮酒频率
从不1 433449(69.4)984(65.47)467(69.08)966(65.54)
偶尔18548(7.42)137(9.12)49(7.25)136(9.23)
经常15337(5.72)116(7.72)37(5.47)116(7.87)
每天24362(9.58)181(12.04)66(9.76)177(12.01)
戒酒13651(7.88)85(5.66)57(8.43)79(5.36)
睡眠时长(小时)
<6534163(25.19)371(24.68)164(24.26)370(25.1)
6~<81 295373(57.65)922(61.34)387(57.25)908(61.6)
≥8321111(17.16)210(13.97)125(18.49)196(13.3)
独居
1 989595(91.96)1 394(92.75)619(91.57)1 370(92.94)
16152(8.04)109(7.25)57(8.43)104(7.06)
高血压
1 484415(64.14)1 069(71.12)433(64.05)1 051(71.3)
666232(35.86)434(28.88)243(35.95)423(28.7)
二型糖尿病
1 888562(86.86)1 326(88.22)585(86.54)1 303(88.4)
26285(13.14)177(11.78)91(13.46)171(11.6)
抑郁状况
1 900563(87.02)1 337(88.96)587(86.83)1 313(89.08)
25084(12.98)166(11.04)89(13.17)161(10.92)
), ArticleFig(id=1240413548678009188, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, language=EN, label=Table 2, caption=

The odds ratio (OR) and 95% confidence interval (CI) of mobile phone usage to subjective and objective cognition

, figureFileSmall=null, figureFileBig=null, tableContent=
主观认知a客观认知a
是否使用智能手机
不使用1.001.00
使用0.97(0.79~1.20)0.58(0.46~0.73)
使用时长
≤1 h1.001.00
>1~2 h0.93(0.74~1.18)0.65(0.51~0.82)
>2 h1.03(0.83~1.29)0.69(0.55~0.88)
), ArticleFig(id=1240413548808032621, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, language=CN, label=表2, caption=

手机使用情况与主、客观认知的比值比(OR)和95%置信区间(CI

, figureFileSmall=null, figureFileBig=null, tableContent=
主观认知a客观认知a
是否使用智能手机
不使用1.001.00
使用0.97(0.79~1.20)0.58(0.46~0.73)
使用时长
≤1 h1.001.00
>1~2 h0.93(0.74~1.18)0.65(0.51~0.82)
>2 h1.03(0.83~1.29)0.69(0.55~0.88)
), ArticleFig(id=1240413548938056050, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, language=EN, label=Table 3, caption=

The ratio of internet usage to subjective and objective cognition (OR) and 95% confidence interval (CI)

, figureFileSmall=null, figureFileBig=null, tableContent=
主观认知a客观认知a
是否上网
不使用1.001.00
使用1.01(0.82~1.24)0.59(0.47~0.74)
上网时长
≤1 h1.001.00
>1~2 h0.86(0.68~1.08)0.65(0.52~0.83)
>2 h0.81(0.65~1.02)0.66(0.52~0.83)
), ArticleFig(id=1240413549068079476, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395012438029249, language=CN, label=表3, caption=

网络使用情况与主、客观认知的比值比(OR)和95%置信区间(CI

, figureFileSmall=null, figureFileBig=null, tableContent=
主观认知a客观认知a
是否上网
不使用1.001.00
使用1.01(0.82~1.24)0.59(0.47~0.74)
上网时长
≤1 h1.001.00
>1~2 h0.86(0.68~1.08)0.65(0.52~0.83)
>2 h0.81(0.65~1.02)0.66(0.52~0.83)
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手机及网络使用情况与中老年人主、客观认知功能的关系
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张小宇 1 , 王琪 1 , 付春迎 1 , 王仲璇 1 , 张露艺 1 , 李响 1 , 朱东山 1, 2
现代预防医学 | 健康与社会行为 2025,52(14): 2613-2618
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现代预防医学 | 健康与社会行为 2025, 52(14): 2613-2618
手机及网络使用情况与中老年人主、客观认知功能的关系
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张小宇1, 王琪1, 付春迎1, 王仲璇1, 张露艺1, 李响1, 朱东山1, 2
作者信息
  • 1.山东大学齐鲁医学院公共卫生学院流行病学系,山东 济南 250012
  • 2.山东大学临床流行病学和循证医学中心
  • 张小宇(2001—),女,硕士在读,研究方向:慢性病流行病学

通讯作者:

朱东山,E-mail:
Relationship between mobile phone and internet usage and subjective and objective cognitive functions in middle-aged and elderly people
Xiao-yu ZHANG1, Qi WANG1, Chun-ying FU1, Zhong-xuan WANG1, Lu-yi ZHANG1, Xiang LI1, Dong-shan ZHU1, 2
Affiliations
  • Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China
出版时间: 2025-07-25 doi: 10.20043/j.cnki.MPM.202501175
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目的

探讨手机及网络使用情况与主、客观认知功能的关系。

方法

采用多阶段整群随机抽样方法选取符合标准的山东省平阴县7个样本村的45~70岁常住居民,分别采用主观认知下降自测量表(SCD-Q9)和蒙特利尔认知评估基础量表(MoCA-B)评估研究对象的主、客观认知功能。采用logistic回归模型计算手机及网络使用情况与主、客观认知功能的比值比(OR)和95%置信区间(95% CI),进一步拟合手机使用时长及上网时长与主、客观认知功能得分的非线性关系。

结果

本研究共纳入1 654名参与者。与不使用手机者相比,使用手机者发生客观认知得分异常的风险低42%(OR=0.58,95% CI:0.46~0.73),使用手机>1~2 h/d或>2 h/d出现客观认知得分异常的风险较低(0.65,0.51~0.82;0.69,0.55~0.88)。相较于不上网者,上网者出现客观认知得分异常的风险低41%(0.59,0.47~0.74),且上网>1~2 h/d或>2 h/d的人群比上网时长≤1 h/d的人群发生客观认知得分异常的风险更低(0.65,0.52~0.83;0.66,0.52~0.83)。而非线性关联显示,当手机使用时长、上网时长逐渐增多时,客观认知得分呈先上升后下降的趋势。

结论

使用手机及网络的人群发生客观认知得分异常的风险较低。随着手机使用时长及上网时长增加,客观认知得分呈先上升后下降的非线性趋势,过度使用手机和网络(如>5.5 h/d)可能对认知功能产生不利影响。

主观认知功能  /  客观认知功能  /  智能手机  /  网络使用
Objective

To explore the relationship between smartphones usage, internet usage and subjective, objective cognitive functions.

Methods

Multi-stage cluster random sampling method was used to select 45-70 year old permanent residents from 7 sample villages in Pingyin County, Shandong Province who meet the standards. The subjective cognitive decline-questionnaire 9 (SCD-Q9) and the montreal cognitive assessment basic scale (MoCA-B) were used to evaluate the subjective and objective cognitive functions, respectively. The logistic regression model was used to calculate the odds ratio (OR) and 95% confidence interval (95% CI) of the relationship between smartphones usage, internet usage and subjective, objective cognitive function. Furthermore, the non-linear relationship between smartphones usage, internet usage and cognitive function scores was explored.

Results

This study included 1 654 participants. Compared with those who did not use mobile phones, those who used mobile phones had a 42% lower risk of experiencing abnormal objective cognitive scores (OR=0.58, 95% CI: 0.46-0.73), and the risk of abnormal objective cognitive scores was relatively low when using a mobile phone for less than or equal to 2 hours per day or more than 2 hours per day (0.65, 0.51-0.82; 0.69, 0.55-0.88). Compared to those who did not use the internet, internet users had a 41% lower risk of experiencing abnormal objective cognitive scores (0.59, 0.47-0.74), and people who spent less than 1 hour online or more than 2 hours online had a lower risk of experiencing abnormal objective cognitive scores compared to those who spent less than or equal to 1 hour online (0.65, 0.52-0.83; 0.66, 0.52-0.83). Nonlinear correlation showed that as the duration of mobile phone use and internet usage gradually increased, the objective cognitive score showed a trend of first increasing and then decreasing.

Conclusion

People who use mobile phones and the internet have a lower risk of experiencing objective cognitive score abnormalities. As the duration of mobile phone use and internet usage increases, the objective cognitive score shows a non-linear trend of first increasing and then decreasing. Overuse of mobile phones and the internet (such as>5.5 h/d) may have adverse effects on cognitive function.

Subjective cognitive function  /  Objective cognitive function  /  Smartphone  /  Internet use
张小宇, 王琪, 付春迎, 王仲璇, 张露艺, 李响, 朱东山. 手机及网络使用情况与中老年人主、客观认知功能的关系. 现代预防医学, 2025 , 52 (14) : 2613 -2618 . DOI: 10.20043/j.cnki.MPM.202501175
Xiao-yu ZHANG, Qi WANG, Chun-ying FU, Zhong-xuan WANG, Lu-yi ZHANG, Xiang LI, Dong-shan ZHU. Relationship between mobile phone and internet usage and subjective and objective cognitive functions in middle-aged and elderly people[J]. Modern Preventive Medicine, 2025 , 52 (14) : 2613 -2618 . DOI: 10.20043/j.cnki.MPM.202501175
认知功能是人脑接受、加工转换外界信息为内在心理活动,进而获取或应用知识的过程[1],包括主观认知功能和客观认知功能[2]。主观认知下降(Subjective Cognitive Decline,SCD)指个体出现主观感觉认知功能下降,但缺乏认知损害的客观证据[3],被认为与未来客观认知功能下降(如轻度认知功能障碍)和大脑结构异常改变有关联,并且可能增加痴呆症的风险[4]。若能分析主、客观认知功能的影响因素,打开痴呆早期诊治的有效时间窗,可能降低痴呆发生的风险[5]。目前的研究大多数表明,手机和网络的使用与更好的认知健康有关,然而先前的研究表明过度使用手机和网络与各种神经认知结果呈负相关,包括语言智力降低、注意力下降以及灰质和白质区域的缺陷,但是对主、客观认知功能的影响尚不清楚[6-12]。鉴于此,本研究从手机及网络的使用情况入手,利用主观和客观认知功能的评估结果,探究手机及网络使用情况与认知功能的关联,可以为今后预防认知功能下降、制定相应的干预措施提供理论依据。
本研究采用多阶段整群抽样法,在平阴县北、中、南部各选1个乡镇,筛选常住人口≥1 500人的行政村,每镇随机抽取2村(不足则补至3村),最终纳入7个样本村。基线调查覆盖45~70岁常住居民2 187人,经知情同意并排除严重疾病、视听障碍或不配合者后,有效样本2 165人(应答率98.9%)。数据总缺失率5.28%,其中“上网时长”(19.72%)和“是否使用智能手机”(17.49%)缺失率较高,经多重填补[13]后分析2 150人。样本量基于横断面研究公式:,中国中老年人SCD患病率约为46.4%,MCI患病率约为19.0%,取二者最小值π=0.19计算得最小样本量1 638人,因此本研究满足要求。基线调查内容包括体格检查、流行病学问卷及生物样本采集,研究经山东大学伦理委员会批准(LL20220319)。
采用面对面问卷调查的方式,通过询问参与者“您是否有可以上网的智能手机?”得知其是否使用手机,答案为“是”和“否”;通过询问“您平均每天使用手机多长时间?”获取手机使用时长,答案分为“≤1小时/天(h/d)、>1~2 h/d和>2 h/d”三类。根据“过去一年内,您上网的频率?(包括使用手机和电脑看抖音视频、看微信、打游戏等)”,答案为“0.从不或几乎没有”、“1.不是每月,但有时会”、“2.每月至少一次(不是每周)”、“3.每周至少一次(不是每天)和“4.几乎每天”,将选项0定义为“否”,选项1、2、3、4定义为“是”;通过询问“您平均每天上网多长时间?”获取上网时长信息,分为“≤1 h/d、>1~2 h/d和>2 h/d”三类。本研究结合文献综述、专家意见及预调查优化问卷设计,最终形成科学的正式调查问卷。经Cronbach α检验,“手机及网络使用情况”维度的信度α值为0.654,达探索性研究可接受阈值(α≥0.60)[14]
认知功能分为主观认知功能和客观认知功能。主观认知功能评估采用主观认知下降自测量表(Subjective Cognitive Decline-Questionnaire 9,SCD-Q9),包含整体记忆功能及与时间对比维度和日常活动能力维度[15],Cronbach’s α系数为0.870~0.881[16],评分<5分为主观认知得分正常,≥5分为异常[17]。客观认知功能评估基于农村受试者文化水平,选用题目相对简单的蒙特利尔认知评估基础量表(Montreal Cognitive Assessment Scale,MoCA-B),包括空间与执行功能、命名、注意力、语言、抽象思维、延迟回忆、定向力(α=0.807[18]),满分30分。按教育程度设定分界值:19/20(受教育年限≤6年)、22/23(6年<受教育年限≤12年)和24/25(受教育年限>12年)[19],低于对应分界值视为客观认知得分异常。
校正的协变量包括基线年龄、性别、教育水平、月收入、婚姻状况、子女数量、BMI[20]、久坐时长、吸烟状况、饮酒频率、睡眠时长、独居、高血压、二型糖尿病和抑郁状况。
研究设计阶段基于文献与专家意见编制初始问卷,经预调查优化后形成终版。调研前开展两次标准化培训,统一调查流程以降低指导语差异导致的信息偏倚。数据收集后实施双人核查并剔除无效问卷,确保数据质量。
数据分析使用SAS 9.4和R 4.3.3。用均数±标准差()描述连续性变量,用频率和构成比描述分类变量。本研究将手机使用时长和上网时长作为自变量,并以主、客观认知得分是否异常作为因变量,构建二元logistic回归模型探索其相关关系。使用“ggplot2”包进一步拟合曲线,分析手机使用时长、上网时长与主、客观认知得分之间的非线性关系。检验水准α=0.05,结果均以P<0.05为差异具有统计学意义。
分析纳入2 150名参与者,其中65.6%为女性。主观认知得分异常率在基线年龄≥60岁、女性、独居、高血压、二型糖尿病、高血压和抑郁的人群中较高;客观得分异常率在基线年龄≥60岁、独居、高血压、二型糖尿病、高血压和抑郁的人群中较高。
整体来看,手机使用时长和上网时长与主观认知得分的拟合曲线无显著变化(图1A、C)。手机使用时长逐渐增加时,客观认知得分呈先升后降趋势,峰值出现在3~4 h/d(图1B);上网时长逐渐增加,客观认知得分先升高(4.5~5.5 h/d时得分最高)后逐渐下降(图1D)。
结果显示,手机使用与主观认知无统计学关联,但手机使用者较非使用者客观认知得分异常风险降低42%(OR=0.58,95% CI:0.46~0.73)。相比使用手机≤1 h/d者,使用手机>1~2h/d或>2h/d者风险更低(0.65,0.51~0.82;0.69,0.55~0.88)。见表2
研究未发现网络使用与主观认知的统计学关联。但相较于不上网者,上网者客观认知得分异常风险降低(OR=0.59,95% CI:0.47~0.74)。相比上网时长≤1h/d者,上网时长>1~2h/d或>2h/d的人群出现客观认知得分异常的风险更低(0.65,0.52~0.83;0.66,0.52~0.83)。见表3
本研究分别调查手机及网络使用情况,探索其与主、客观认知功能的关联,是对既往研究的补充和完善。目前国内外少有研究关注手机及网络使用情况与主观认知功能的关联,本研究未发现手机及网络使用情况与主观认知功能的显著关联,这可能是由于结局变量样本量较小所致。
有证据表明使用网络可以作为预防痴呆发展的适当干预工具[21],我们的研究也发现使用智能手机或网络者发生客观认知得分异常的风险低于不使用者(OR=0.58,95% CI:0.46~0.73;0.59,0.47~0.74),与使用手机时长≤1 h/d的人群相比,>2 h/d的人群出现客观认知异常的风险低32%(0.69,0.55~0.88),且上网时长与客观认知功能间也具有相似关联(0.66,0.52~0.83)。其中的机制可能涉及社会因素和生理因素。一方面,手机和网络的使用可以增加社交互动,参与各种类型的在线社会或政治活动可以提升自我价值感[22-23]。另一方面,使用手机和网络等具有认知挑战性的活动可能会增强中枢神经系统中的神经递质释放、增加额颞叶关联皮层的厚度,可能有助于延缓认知能力下降[24-25]
然而,虽然大多数研究表明网络的使用与更好的认知健康有关,但过度使用手机和上网成瘾可能会对认知功能造成负面影响。本研究发现使用手机或上网时长与客观认知得分近似呈倒“U”形关联,客观认知得分随手机和网络使用时长的增加先升高后降低,说明一定时间内的手机及网络使用可以促进认知健康,过度使用对认知功能可能造成负面影响。既往研究表明,过度使用网络可能会导致面对面社交互动的机会减少、与现实世界脱离,转而沉溺虚拟环境,这可能会对认知健康产生不利影响[26-27]
本研究的结果为认知功能下降及痴呆的预防关口前移提供了参考和理论依据,通过改变智能手机及网络使用情况可能改善认知功能状况,但未来仍需大样本或多中心的队列研究进一步评估手机及网络使用与认知功能的关系。本研究也存在局限性。首先,本研究是横断面研究,所以因果关系难以确定,并且其他潜在的混杂因素,如个体差异和社交互动等可能会影响认知功能,而这些因素难以完全控制。其次,本研究中的结局变量非确诊的主观认知下降和轻度认知障碍,而是以SCD-Q9和MoCA-B量表得分为判断指标的主、客观认知功能下降。最后,研究对象均来自山东省济南市农村地区,结果外推可能受限。
综上所述,使用手机和网络的人群发生客观认知得分异常的风险更低,且手机使用时长、上网时长与客观认知得分呈非线性关联,过度使用手机或网络(如>5.5 h/d)可能对客观认知功能不利。鉴于老龄化社会面临的多重挑战,手机及网络的使用可能为维持认知健康和预防痴呆提供重要的低成本策略。
  • 国家自然科学基金资助项目(82273702)
  • 山东省优秀青年学者资助项目(2022HWYQ-030)
  • 泰山学者项目专项基金(tsqnz20221103)
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doi: 10.20043/j.cnki.MPM.202501175
  • 接收时间:2025-01-10
  • 首发时间:2026-03-16
  • 出版时间:2025-07-25
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  • 收稿日期:2025-01-10
基金
国家自然科学基金资助项目(82273702)
山东省优秀青年学者资助项目(2022HWYQ-030)
泰山学者项目专项基金(tsqnz20221103)
作者信息
    1.山东大学齐鲁医学院公共卫生学院流行病学系,山东 济南 250012
    2.山东大学临床流行病学和循证医学中心

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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
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