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Article(id=1240929924849136577, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240929920461886112, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202403172, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1710432000000, receivedDateStr=2024-03-15, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773790349446, onlineDateStr=2026-03-18, pubDate=1717948800000, pubDateStr=2024-06-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773790349446, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773790349446, creator=13701087609, updateTime=1773790349446, updator=13701087609, issue=Issue{id=1240929920461886112, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='11', pageStart='1921', pageEnd='2112', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1773790348400, creator=13701087609, updateTime=1773827281389, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241084828704109275, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240929920461886112, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241084828704109276, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240929920461886112, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2061, endPage=2065, ext={EN=ArticleExt(id=1240929925708967945, articleId=1240929924849136577, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study on the relationship between nocturnal sleep time and depression in the middle-aged and elderly in Chinese community, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=

Objective To explore the correlation between sleep and depression in middle-aged and elderly people in Chinese community, so as to provide references for improving sleep quality, mental health and quality of life of middle-aged and elderly people. Methods The data of this study were collected from the China Health and Retirement Longitudinal Study (CHARLS) in 2013 and 2018. After screening the data, 6 312 participants were included in the study, and they were divided into groups according to their nocturnal sleep duration. The multivariate linear regression model and multivariate logistic regression model were constructed, and the covariates were adjusted to analyze the relationship between nocturnal sleep duration and depression. Results There were 76.81% of the patients having too short or too long sleep at night (7 to < 8 hours was the normal sleep time).The scores and detection rates of depression in 2018 were significantly different among different night sleep length groups (F=30.127, χ2=67.928, P<0.001). There was a negative correlation between night sleep time and depression score (β=-0.278, P<0.001). After further consideration of covariates, short sleep duration (≤ 5 h) was a risk factor for depression (OR=1.621, 95%CI:1.371-1.918), and the risk of depression was higher in women than in men (OR=1.673, 95%CI: 1.363-2.054 in women; OR=1.501, 95%CI: 1.120-2.012 in men). Conclusion The nocturnal sleep of the middle-aged and elderly is related to depression and is affected by demographic, socio-economic factors, health behavior factors and other covariables, and middle-aged and elderly women have a higher risk than men and older age. Attention should be paid to sleep health and mental health of the middle-aged and elderly, so as to improve their quality of life.

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目的 探讨中国社区中老年人睡眠情况与抑郁的相关性，为提升中老年人睡眠质量、心理健康及生活质量提供参考。方法 本研究数据来自中国健康与养老追踪调查（China Health and Retirement Longitudinal Study，CHARLS）2013和2018年资料，经过筛选数据，最终纳入研究对象6 312例。将研究对象按其夜间睡眠时长进行分组，构建多因素线性回归模型及多元logistic回归模型，调整协变量，分析夜间睡眠时长与抑郁的关系。结果 夜间睡眠时长过短或过长（7～<8 h为正常睡眠时长）的占76.81%；2018年的抑郁得分及检出率在不同夜间睡眠时长分组中差异具有统计学意义（F=30.127，χ2=67.928，均有P<0.001）。夜间睡眠时间与抑郁得分呈负相关（β=-0.278，P<0.001），进一步考虑协变量后，短时睡眠时长（≤5 h）是检出抑郁的风险因素（OR=1.621，95%CI：1.371～1.918），且女性相较男性风险更高（女性OR=1.673，95%CI：1.363～2.054；男性OR=1.501，95%CI：1.120～2.012）。结论 中老年人的夜间睡眠与抑郁相关，并受到人口学、社会经济因素、健康行为因素等协变量影响，且中老年女性较男性、高龄较低龄有更高风险。应重视中老年人睡眠健康与心理健康，提高中老年人生活质量。

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杨春霞，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=8f8OLSwGSOt0X2bacAeDLg==, magXml=/FE7h2PAfLy/uWO1GM0Rqg==, pdfUrl=null, pdf=lhzawvt9ikv4+30CGt41yA==, pdfFileSize=518532, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=a1lAgEykPVoXBRybmTho1A==, mapNumber=null, authorCompany=null, fund=null, authors=

汪玥杉（1999—），女，硕士在读，研究方向：慢性非传染性流行病学

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4.四川大学华西第四医院陈志潜慢性病研究中心，四川 成都 610041, bio={"content":"

汪玥杉（1999—），女，硕士在读，研究方向：慢性非传染性流行病学

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汪玥杉（1999—），女，硕士在读，研究方向：慢性非传染性流行病学

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Baseline data of all participants ［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
项目合计夜间睡眠时长
7～<8 h 		夜间睡眠时长≤5 h 夜间睡眠时长
>5～<7 h 		夜间睡眠时长≥8 h
性别
男性2 594（41.10）592（22.82）584（22.51）707（27.26）711（27.41）
女性3 718（58.90）872（23.45）951（25.58）876（23.56）1 019（27.41）
年龄（岁）
<654 952（78.45）1 213（24.50）1 118（22.58）1 257（25.38）1 364（27.54）
≥651 360（21.55）251（18.46）417（30.66）326（23.97）366（26.91）
文化程度
小学未毕业2 527（40.03）524（20.74）716（28.33）521（20.62）766（30.31）
小学毕业3 785（59.97）940（24.83）819（21.64）1 062（28.06）964（25.47）
婚姻状态
非婚姻中504（7.98）89（17.66）186（36.90）117（23.21）112（22.22）
婚姻中5 808（92.02）1 375（23.67）1 349（23.23）1 466（25.24）1 618（27.86）
居住地
乡村4 473（70.87）1 021（22.83）1 107（24.75）1 029（23.00）1 316（29.42）
城镇1 839（29.13）443（24.09）428（23.27）554（30.13）414（22.51）
慢性病
无慢性病3 726（59.03）915（24.56）860（23.08）895（24.02）1 056（28.34）
有慢性病2 586（40.97）549（21.23）675（26.10）688（26.60）674（26.06）
吸烟
从未吸烟4 464（70.72）1 059（23.72）1 088（24.37）1 065（23.86）1 252（28.05）
吸烟1 848（29.28）405（21.92）447（24.19）518（28.03）478（25.87）
饮酒
从未饮酒1 588（25.16）352（22.17）365（22.98）438（27.58）433（27.27）
饮酒4 724（74.84）1 112（23.54）1 170（24.77）1 145（24.24）1 297（27.46）
健康自评
良好1 905（30.18）512（26.88）361（18.95）488（25.62）544（28.56）
一般3 439（54.48）758（22.04）854（24.83）904（26.29）923（26.84）
较差968（15.34）194（20.04）320（33.06）191（19.73）263（27.17）
2018年抑郁得分（分）
<104 598（72.85）1 130（24.58）998（21.71）1 196（26.01）1 274（27.71）
≥101 714（27.15）334（19.49）537（31.33）387（22.58）456（26.60）
), ArticleFig(id=1240929933258715748, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240929924849136577, language=CN, label=表1, caption=

研究对象基本情况［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
项目合计夜间睡眠时长
7～<8 h 		夜间睡眠时长≤5 h 夜间睡眠时长
>5～<7 h 		夜间睡眠时长≥8 h
性别
男性2 594（41.10）592（22.82）584（22.51）707（27.26）711（27.41）
女性3 718（58.90）872（23.45）951（25.58）876（23.56）1 019（27.41）
年龄（岁）
<654 952（78.45）1 213（24.50）1 118（22.58）1 257（25.38）1 364（27.54）
≥651 360（21.55）251（18.46）417（30.66）326（23.97）366（26.91）
文化程度
小学未毕业2 527（40.03）524（20.74）716（28.33）521（20.62）766（30.31）
小学毕业3 785（59.97）940（24.83）819（21.64）1 062（28.06）964（25.47）
婚姻状态
非婚姻中504（7.98）89（17.66）186（36.90）117（23.21）112（22.22）
婚姻中5 808（92.02）1 375（23.67）1 349（23.23）1 466（25.24）1 618（27.86）
居住地
乡村4 473（70.87）1 021（22.83）1 107（24.75）1 029（23.00）1 316（29.42）
城镇1 839（29.13）443（24.09）428（23.27）554（30.13）414（22.51）
慢性病
无慢性病3 726（59.03）915（24.56）860（23.08）895（24.02）1 056（28.34）
有慢性病2 586（40.97）549（21.23）675（26.10）688（26.60）674（26.06）
吸烟
从未吸烟4 464（70.72）1 059（23.72）1 088（24.37）1 065（23.86）1 252（28.05）
吸烟1 848（29.28）405（21.92）447（24.19）518（28.03）478（25.87）
饮酒
从未饮酒1 588（25.16）352（22.17）365（22.98）438（27.58）433（27.27）
饮酒4 724（74.84）1 112（23.54）1 170（24.77）1 145（24.24）1 297（27.46）
健康自评
良好1 905（30.18）512（26.88）361（18.95）488（25.62）544（28.56）
一般3 439（54.48）758（22.04）854（24.83）904（26.29）923（26.84）
较差968（15.34）194（20.04）320（33.06）191（19.73）263（27.17）
2018年抑郁得分（分）
<104 598（72.85）1 130（24.58）998（21.71）1 196（26.01）1 274（27.71）
≥101 714（27.15）334（19.49）537（31.33）387（22.58）456（26.60）
), ArticleFig(id=1240929933350990441, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240929924849136577, language=EN, label=Table 2, caption=

Multivariate linear regression of nocturnal sleep duration and depression scores

, figureFileSmall=null, figureFileBig=null, tableContent=
项目回归模型亚组分析βP值
抑郁得分（2018）全样本-0.278<0.001
男性-0.252<0.001
女性-0.295<0.001
年龄<65岁-0.281<0.001
年龄≥65岁-0.2820.001
), ArticleFig(id=1240929933460042350, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240929924849136577, language=CN, label=表2, caption=

夜间睡眠时长与抑郁得分的多元线性回归

, figureFileSmall=null, figureFileBig=null, tableContent=
项目回归模型亚组分析βP值
抑郁得分（2018）全样本-0.278<0.001
男性-0.252<0.001
女性-0.295<0.001
年龄<65岁-0.281<0.001
年龄≥65岁-0.2820.001
), ArticleFig(id=1240929933585871477, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240929924849136577, language=EN, label=Table 3, caption=

Multivariate Logistic regression analysis of nocturnal sleep duration and depression

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回归模型≤5 h >5～<7 h 7～<8 h ≥8 h
模型1
OR（95%CI）1.820（1.550～2.138）1.095（0.926～1.294）1.0001.211（1.030～1.424）
P值<0.0010.289—0.021
模型2
OR（95%CI）1.834（1.558～2.159）1.126（0.951～1.332）1.0001.224（1.039～1.441）
P值<0.0010.169—0.015
模型3
OR（95%CI）1.785（1.514～2.105）1.165（0.982～1.381）1.0001.169（0.991～1.378）
P值<0.0010.079—0.064
模型4
OR（95%CI）1.621（1.371～1.918）1.119（0.941～1.330）1.0001.141（0.965～1.349）
P值<0.0010.204—0.123
), ArticleFig(id=1240929933711700603, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240929924849136577, language=CN, label=表3, caption=

夜间睡眠时长与抑郁的多元logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
回归模型≤5 h >5～<7 h 7～<8 h ≥8 h
模型1
OR（95%CI）1.820（1.550～2.138）1.095（0.926～1.294）1.0001.211（1.030～1.424）
P值<0.0010.289—0.021
模型2
OR（95%CI）1.834（1.558～2.159）1.126（0.951～1.332）1.0001.224（1.039～1.441）
P值<0.0010.169—0.015
模型3
OR（95%CI）1.785（1.514～2.105）1.165（0.982～1.381）1.0001.169（0.991～1.378）
P值<0.0010.079—0.064
模型4
OR（95%CI）1.621（1.371～1.918）1.119（0.941～1.330）1.0001.141（0.965～1.349）
P值<0.0010.204—0.123
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中国社区中老年人夜间睡眠时长与抑郁的相关性研究
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汪玥杉 1, 4 , 龙文成 1, 4 , 彭介入 1, 3 , 沈晓丽 1, 4 , 张璐 1, 4 , 张绮文 1, 4 , 董尧 1, 4 , 黄祖波 2 , 余葱葱 2 , 王超 2 , 周浩 2 , 杨春霞 1, 4
现代预防医学 | 健康与社会行为 2024,51(11): 2061-2065
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现代预防医学 | 健康与社会行为 2024, 51(11): 2061-2065
中国社区中老年人夜间睡眠时长与抑郁的相关性研究
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汪玥杉1, 4, 龙文成1, 4, 彭介入1, 3, 沈晓丽1, 4, 张璐1, 4, 张绮文1, 4, 董尧1, 4, 黄祖波2, 余葱葱2, 王超2, 周浩2, 杨春霞1, 4
作者信息
  • 1.四川大学华西公共卫生学院/华西第四医院流行病与卫生统计学系，四川 成都 610041
  • 2.四川省中西医结合医院亚健康研究中心
  • 3.成都市妇女儿童中心医院
  • 4.四川大学华西第四医院陈志潜慢性病研究中心，四川 成都 610041

    • 汪玥杉（1999—），女，硕士在读，研究方向：慢性非传染性流行病学

通讯作者:

杨春霞，E-mail:
Study on the relationship between nocturnal sleep time and depression in the middle-aged and elderly in Chinese community
Yue-shan WANG1, 4, Wen-cheng LONG1, 4, Jie-ru PENG1, 3, Xiao-li SHEN1, 4, Lu ZHANG1, 4, Qi-wen ZHANG1, 4, Yao DONG1, 4, Zu-bo HUANG2, Cong-cong YU2, Chao WANG2, Hao ZHOU2, Chun-xia YANG1, 4
Affiliations
  • Department of Epidemiology and Health Statistics, West China School of Public Health / West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2024-06-10 doi: 10.20043/j.cnki.MPM.202403172
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摘要
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目的 探讨中国社区中老年人睡眠情况与抑郁的相关性，为提升中老年人睡眠质量、心理健康及生活质量提供参考。方法 本研究数据来自中国健康与养老追踪调查（China Health and Retirement Longitudinal Study，CHARLS）2013和2018年资料，经过筛选数据，最终纳入研究对象6 312例。将研究对象按其夜间睡眠时长进行分组，构建多因素线性回归模型及多元logistic回归模型，调整协变量，分析夜间睡眠时长与抑郁的关系。结果 夜间睡眠时长过短或过长（7～<8 h为正常睡眠时长）的占76.81%；2018年的抑郁得分及检出率在不同夜间睡眠时长分组中差异具有统计学意义（F=30.127，χ2=67.928，均有P<0.001）。夜间睡眠时间与抑郁得分呈负相关（β=-0.278，P<0.001），进一步考虑协变量后，短时睡眠时长（≤5 h）是检出抑郁的风险因素（OR=1.621，95%CI：1.371～1.918），且女性相较男性风险更高（女性OR=1.673，95%CI：1.363～2.054；男性OR=1.501，95%CI：1.120～2.012）。结论 中老年人的夜间睡眠与抑郁相关，并受到人口学、社会经济因素、健康行为因素等协变量影响，且中老年女性较男性、高龄较低龄有更高风险。应重视中老年人睡眠健康与心理健康，提高中老年人生活质量。

睡眠时间  /  抑郁  /  CHARLS  /  老龄化

Objective To explore the correlation between sleep and depression in middle-aged and elderly people in Chinese community, so as to provide references for improving sleep quality, mental health and quality of life of middle-aged and elderly people. Methods The data of this study were collected from the China Health and Retirement Longitudinal Study (CHARLS) in 2013 and 2018. After screening the data, 6 312 participants were included in the study, and they were divided into groups according to their nocturnal sleep duration. The multivariate linear regression model and multivariate logistic regression model were constructed, and the covariates were adjusted to analyze the relationship between nocturnal sleep duration and depression. Results There were 76.81% of the patients having too short or too long sleep at night (7 to < 8 hours was the normal sleep time).The scores and detection rates of depression in 2018 were significantly different among different night sleep length groups (F=30.127, χ2=67.928, P<0.001). There was a negative correlation between night sleep time and depression score (β=-0.278, P<0.001). After further consideration of covariates, short sleep duration (≤ 5 h) was a risk factor for depression (OR=1.621, 95%CI:1.371-1.918), and the risk of depression was higher in women than in men (OR=1.673, 95%CI: 1.363-2.054 in women; OR=1.501, 95%CI: 1.120-2.012 in men). Conclusion The nocturnal sleep of the middle-aged and elderly is related to depression and is affected by demographic, socio-economic factors, health behavior factors and other covariables, and middle-aged and elderly women have a higher risk than men and older age. Attention should be paid to sleep health and mental health of the middle-aged and elderly, so as to improve their quality of life.

Sleep time  /  Depression  /  CHARLS  /  Ageing
汪玥杉, 龙文成, 彭介入, 沈晓丽, 张璐, 张绮文, 董尧, 黄祖波, 余葱葱, 王超, 周浩, 杨春霞. 中国社区中老年人夜间睡眠时长与抑郁的相关性研究. 现代预防医学, 2024 , 51 (11) : 2061 -2065 . DOI: 10.20043/j.cnki.MPM.202403172
Yue-shan WANG, Wen-cheng LONG, Jie-ru PENG, Xiao-li SHEN, Lu ZHANG, Qi-wen ZHANG, Yao DONG, Zu-bo HUANG, Cong-cong YU, Chao WANG, Hao ZHOU, Chun-xia YANG. Study on the relationship between nocturnal sleep time and depression in the middle-aged and elderly in Chinese community[J]. Modern Preventive Medicine, 2024 , 51 (11) : 2061 -2065 . DOI: 10.20043/j.cnki.MPM.202403172
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睡眠与健康的关系历来受到人们的重视。随着工作和生活压力的增大，睡眠作为一个重要的公共卫生问题，已经成为影响人们身心健康的主要原因之一。我国已迈入老龄化进程，老年性疾病、慢性病等的发病率呈上升趋势，而夜间睡眠质量是评价中老年人身体健康情况及其生活质量的关键标志[1]。有研究表明，睡眠的改善对神经存在保护作用[2]；而根据《中国睡眠研究报告2023》显示，我国中老年人的睡眠时长相对较短且睡眠质量相对较低，并随着年龄增长逐步缩短、下降。因此，中老年人睡眠问题值得关注。
抑郁症是一种常见的心理健康问题，已成为全球主要的致残性精神障碍[3]，能引起多种慢性躯体疾病发病率增高，严重影响患者生活质量。在中国，全年龄段抑郁症患病率呈上升趋势，其中中老年人的抑郁症患病率呈现高增长[4]。在影响抑郁症的因素中，睡眠与抑郁症的关系得到广泛关注，但相关性仍待证实[5-6]。基于此，本研究拟利用2013和2018年中国健康与养老追踪调查（China Health and Retirement Longitudinal Study，CHARLS）相关数据，探究中国中老年人睡眠情况与抑郁的关系，为中老年人睡眠健康和健康老龄化提供一定的依据。
1　对象与方法
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1.1　研究对象
本研究所用数据来源于CHARLS项目，该项目覆盖全国28个省（自治区、直辖市）的150个县级单位、450个社区（村）级单位开展调查研究，对象为中国社区45岁及以上的个人或其家庭，调查内容包括人口学因素、经济情况、健康情况、养老等方面。项目2011年开展基线调查，并每两年对调查对象的情况进行一次追踪[7]。CHARLS由北京大学伦理审查委员会批准，研究对象均已签署知情同意书。
本研究以第二次调查（2013年）的人口学和健康资料数据作为基线资料，以第四次调查（2018年）数据作为随访资料，按研究对象ID号进行配比。根据本研究目的，筛选数据纳入排除标准如下：（1）研究对象2013年的年龄≥45岁；（2）2013年研究对象未患有抑郁症，及大脑受损、智力缺陷及有记忆相关疾病（如老年痴呆病、帕金森症等）；（3）具有完整的人口学及健康相关资料，包括研究对象的性别、年龄、婚姻状况、受教育程度、城乡、吸烟、饮酒、夜间睡眠情况、慢性病、抑郁症状评分等。最终在18 605名研究对象中，通过剔除年龄、性别等基本信息及健康信息缺损，余8 075名；进一步剔除2018年结局数据抑郁资料未获得者，最终共纳入6 312名研究对象。
1.2　研究方法
1.2.1　睡眠时间
根据美国国家睡眠基金会（National Sleep Foundation，NSF）[8]、国际临床诊断标准[9]对不同年龄段的适宜睡眠时间进行的总结，本研究将研究对象按照其2013年夜间睡眠时长分为4组，分别为睡眠时间≤5 h（短时间睡眠组）、>5～<7 h，7～<8 h（参照组）和≥8 h（长时间睡眠组）。
1.2.2　抑郁程度测试
本研究采用简版抑郁自评量表（Center for Epidemiological Studies Short Depression Scale，CES-D10），10条目总分共30分，得分≥10分认为存在抑郁症状。该量表具有良好信效度，且对于中老年人对象具有较高适用性[10]。
1.3　统计学方法
使用STATA 17.0进行数据整理与合并，并进行数据分析。描述连续变量采用（）表示，分类变量采用率与比表示。采用方差分析及χ2检验分析不同睡眠组间抑郁得分均值及检出率的差异；构建多元线性回归模型，分析基线时研究对象夜间睡眠时长与2018年抑郁得分的关系，并进一步构建多元logistic回归模型分析调整协变量后夜间睡眠时长与检出抑郁的关系，并进行亚组分析。检验水准α=0.05。
2　结果
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2.1　研究对象基本情况
本研究纳入的6 312名研究对象，平均年龄为（57.55±8.88）岁，男性2 594例（41.10%），女性3 718例（58.90%）；夜间睡眠时长在7～<8 h（参照组）的共1 464例（23.19%），在≤5 h（短时间睡眠）的共1 535例（24.32%），在≥8 h（长时间睡眠）的共1 730例（27.41%）；2018年抑郁得分≥10分的共1 714例（27.15%）。见表1。
2.2　研究对象睡眠与抑郁关系
2.2.1　研究对象2013年夜间睡眠时长与2018年抑郁情况的关系
将研究对象按照2013年夜间睡眠时长情况进行分组后，计算得到各组研究对象的2018年抑郁得分平均值及抑郁的检出率情况。≤5 h、>5～<7 h、7～<8 h和≥8 h组2018年抑郁得分均值分别为8.00、6.59、6.22、6.61，检出率分别为34.98%、24.45%、22.81%、26.36%，发现短时睡眠组（≤5 h）研究对象抑郁得分均值及检出率在四组中均值为最高，参照组（7～<8 h）研究对象的均值最低，方差分析及χ2检验得到四组均值及检出率均存在差异（F= 30.127，χ2=67.928，均有P<0.001），提示夜间睡眠时长可能是抑郁的影响因素。
将所有协变量纳入线性回归模型，进一步分析研究对象夜间睡眠时长与抑郁的关系。结果得到，对于全体研究对象，夜间睡眠时长与抑郁得分存在负向关联（β=-0.278，P<0.001）。进一步对研究对象按照性别、年龄分组进行亚组分析，性别、年龄分组情况不同，其分层分析结果仍然与全样本相近，提示夜间睡眠时长与抑郁得分之间均可能存在负向关联，即睡眠时长越短，抑郁得分越高。见表2。
2.2.2　研究对象短时夜间睡眠时长与抑郁检出情况的关系
进一步采用多元logistic回归进行分析，因变量为研究对象2018年是否检出抑郁情况，自变量为夜间睡眠时长分组，纳入模型1，并依次进行控制人口学、社会经济因素、健康行为因素等其他协变量影响（模型2、3、4）。结果显示，四个模型中，短时间夜间睡眠时长组（≤5 h）相较参照组（7～<8 h）而言均有更高检出抑郁风险（模型1、2、3、4：OR1=1.820，95%CI：1.550～2.138；OR2=1.834，95%CI：1.558～2.159；OR3=1.785，95%CI：1.514～2.105；OR4=1.621，95%CI：1.371～1.918）；在未考虑协变量（模型1）及在调整年龄、性别影响后（模型2），与参照组相比，长时间夜间睡眠时长组（≥8 h）的研究对象，OR值分别为1.211（95%CI：1.030～1.424）和1.224（95%CI：1.039～1.441）；考虑所有协变量（模型4）后，除短时间组外，其余组OR值无统计学意义，见表3。对男性、女性及年龄<65、≥65岁进行亚组分析，结果显示不同亚组间无显著差异，OR值与不分组接近（女性OR=1.673，95%CI：1.363～2.054；男性OR=1.501，95%CI：1.120～2.012；≥65岁OR=1.647，95%CI：1.110～2.443；<65岁OR=1.604，95%CI：1.331～1.932；均有P<0.050）。结果提示，夜间睡眠时长过短是检出抑郁的危险因素。
3　讨论
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本文基于CHARLS的2013和2018年数据对我国中老年人睡眠时长与抑郁关系进行分析，发现抑郁得分及检出情况在不同夜间睡眠时长中的差异具有统计学意义；调整各因素影响后发现睡眠时长过短是检出抑郁的风险因素，且女性较男性、高龄较低龄风险更高。此外，本研究在分析中发现在考虑了部分协变量的模型中，长时睡眠对检出抑郁也存在风险。过往研究认为长时睡眠对检出抑郁的关联仍存在一定争议，有研究表示长时睡眠与平均睡眠对抑郁情绪的影响并无差异[11]，但也有meta分析认为睡眠时间短和长均与成人抑郁症发病风险增加显著相关[12]。睡眠与抑郁之间的关系仍需更多关注，以探寻更有益于中老年人健康的夜间睡眠时长。
在治疗睡眠问题上，中医提出以中药汤剂如酸枣仁汤、针灸等方法调整阴阳失调、气血失和引发的失眠，但中医治疗目前仍存在一定不确定性；西医则认为失眠与γ-氨基丁酸等多种脑内神经递质有关，临床治疗采用受体激动剂、镇静类药物调节，但易产生耐药性及不良反应。失眠的认知行为疗法（cognitive behavioral therapy for insomnia，CBT-I）作为多国指南文件[13-14]中均推荐的治疗失眠首选手段，通过多模式干预行为认知变量，包括行为（如睡眠限制、刺激控制）和认知疗法策略的组合，配合心理治疗；如果治疗失败或不可用，再进行药物治疗，其安全性和临床有效性具有坚实证据基础，能够带来较为持久收益，且副作用相对较小，能够提高患者的情绪、社会功能。作为失眠的一种有效治疗方法，同时作为新时代科技发展背景下，数字化、网络化治疗失眠的有效方法，未来应考虑结合CBT-I与中西医治疗方法，对失眠进行干预治疗。
本研究发现睡眠时长过短人群中，女性较男性有更高的检出抑郁风险，这种性别差异可能由多种原因导致[15-17]，如性激素、负面情绪处理敏感性以及基因水平等，涉及下丘脑-垂体-性腺轴、下丘脑-垂体-肾上腺轴，以及激素对杏仁核和大脑之间的关联影响、女性具有更多与抑郁相关的特异性基因位点等。此外，当妇女有慢性病或社会经济压力时，可能为其带来生理、心健康的损害，增加抑郁风险，同时可能影响睡眠，形成恶性循环。总而言之，应从多方面考虑女性睡眠与抑郁之间关系，未来可开展关于遗传因素、环境因素、社会支持等方面的影响研究。
本研究通过分析得出，应重视中国社区中老年人睡眠与心理健康的影响，并关注抑郁与睡眠之间的关系，改善中老年人睡眠情况，结果与以往研究相一致。但本研究中也存在一定局限性，如研究未考虑协变量如社会经济因素、健康行为因素等可能在时间段内发生变化，以及其他生活事件发生的影响。同时，研究对象虽然在2018年抑郁得分未达到检出抑郁的标准（≥10分），但相较2013年得分有所上升的情况也应得到重视，这表明研究对象的心理状态在两年间可能发生变化，这可能是由于生活事件、环境因素、心理压力等等的变化导致的。未来或可对未判定检出抑郁、但得分在前后时间段相比有所上升的对象进行更全面的分析，以便得出更可靠的结论，对中老年人存在的心理问题及其影响因素进行及时而准确的干预。
综上所述，随着时代进步与老龄化进程展开，应重视中老年人睡眠健康与心理健康，积极开展针对相关人群的健康教育，组织宣传科普活动，普及睡眠与心理健康的重要性，并重点关注中老年女性人群，为中老年人睡眠、心理健康及健康老龄化，提升中老年人综合生活质量提供一定干预和参考依据。
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2024年第51卷第11期
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doi: 10.20043/j.cnki.MPM.202403172
  • 接收时间：2024-03-15
  • 首发时间：2026-03-18
  • 出版时间：2024-06-10
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  • 收稿日期：2024-03-15
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    1.四川大学华西公共卫生学院/华西第四医院流行病与卫生统计学系，四川 成都 610041
    2.四川省中西医结合医院亚健康研究中心
    3.成都市妇女儿童中心医院
    4.四川大学华西第四医院陈志潜慢性病研究中心，四川 成都 610041

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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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