Article(id=1322931467151618328, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322931411006665649, articleNumber=null, orderNo=null, doi=10.12102/j.issn.1009-6493.2026.13.006, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1763395200000, receivedDateStr=2025-11-18, revisedDate=1778947200000, revisedDateStr=2026-05-17, acceptedDate=null, acceptedDateStr=null, onlineDate=1793341040646, onlineDateStr=2026-10-30, pubDate=1783612800000, pubDateStr=2026-07-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793341040646, onlineIssueDateStr=2026-10-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793341040646, creator=13701087609, updateTime=1793341040646, updator=13701087609, issue=Issue{id=1322931411006665649, tenantId=1146029695717560320, journalId=1220038315760373764, year='2026', volume='40', issue='13', pageStart='2193', pageEnd='2384', issueExtLink='null', onlineDate='null', pubDate='1783612800000', pubDateStr='2026-07-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793341027261, creator='13701087609', updateTime=1793343114456, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322940165425082661, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322931411006665649, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322940165425082662, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322931411006665649, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2233, endPage=2241, ext={EN=ArticleExt(id=1322931468850311449, articleId=1322931467151618328, tenantId=1146029695717560320, journalId=1220038315760373764, language=EN, title=Joint trajectory analysis of pain and depressive symptoms in older adults, columnId=1220689484526572183, journalTitle=Chinese Nursing Research, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=
Objective

To identify joint trajectories of pain and depressive symptoms in older adults,to explore the dynamic relationship between them,and to identify common influencing factors,so as to provide a basis for developing intervention strategies.

Methods

Based on data from the China Health and Retirement Longitudinal Study(CHARLS) from 2011 to 2020,a total of 2 772 older adults were included.A group-based trajectory modeling(GBTM) dual-trajectory approach was used to analyze the joint developmental trajectories of pain and depression.Logistic regression was used to identify common influencing factors.

Results

Two types of pain trajectories were identified: the few sites-stable group and the multiple sites-increasing group.Three types of depression trajectories were identified:the low level-stable group,the medium level-increasing group,and the high level-increasing group.Dual-trajectory analysis showed that compared with the few sites-stable group,older adults in the multiple sites-increasing group had a higher probability of experiencing the medium level-increasing depression(53.3%) and the high level-increasing depression(89.8%).Compared with the low level-stable group,older adults in the medium level-increasing depression group and the high level-increasing depression group had a higher probability of experiencing the multiple sites-increasing pain(59.8% and 29.5%,respectively).Age,gender,educational level,place of residence,nighttime sleep duration,self-rated health,number of chronic diseases,and activities of daily living were common influencing factors for both pain and depression trajectories(all P<0.05).

Conclusions

Pain and depression trajectories in older adults show a high degree of correlation.Attention should be given to the physical and mental health of older adults aged 60 years,females,those living in rural areas,those with poor self-rated health,low education level,a high number of chronic diseases,poor self-care ability,and insufficient sleep duration.Interventions should be developed based on the joint trajectories and common influencing factors of pain and depression.

, authors=Zitong ZHOU, Yu JIA, Qin LIU, Shixiu WANG, Yunqiong WANG, Qian WANG, Xiaozhao GU, Yue'e DAI, Xuemei LUO, authorsList=Zitong ZHOU, Yu JIA, Qin LIU, Shixiu WANG, Yunqiong WANG, Qian WANG, Xiaozhao GU, Yue'e DAI, Xuemei LUO, authorCompany=null, correspAuthors=Xuemei LUO, 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=1322931469785641249, articleId=1322931467151618328, tenantId=1146029695717560320, journalId=1220038315760373764, language=CN, title=老年人疼痛和抑郁症状的联合轨迹分析, columnId=1220689484681761433, journalTitle=护理研究, columnName=科研论著, runingTitle=null, highlight=null, articleAbstract=
目的

识别老年人疼痛和抑郁症状的联合轨迹,探讨二者之间的动态关联及共同影响因素,为制定干预策略提供依据。

方法

基于中国健康与养老追踪调查(CHARLS) 2011—2020年数据,共纳入2 772名老年人。采用基于组基轨迹(GBTM)双轨迹模型分析疼痛与抑郁的联合发展轨迹,采用Logistic回归分析识别其共同影响因素。

结果

疼痛轨迹识别出少部位-稳定组和多部位-增长组2类,抑郁轨迹识别出低水平-稳定组、中水平-增长组和高水平-增长组3类。双轨迹分析显示,相较于少部位-稳定组,多部位-增长组的老年人有更大概率经历抑郁中水平-增长(53.3%)和抑郁高水平-增长(89.8%);相较于低水平-稳定组,中水平-增长组和高水平-增长组老年人有更大概率经历多部位-增长疼痛(59.8%和29.5%)。年龄、性别、文化程度、居住地、夜间睡眠时间、自评健康、慢性病数量以及日常生活能力是疼痛轨迹和抑郁轨迹的共同影响因素(均P<0.05)。

结论

老年人疼痛轨迹和抑郁轨迹有高度相关性。应重点关注60岁年龄组、女性、居住在农村、自评健康差、教育程度低、慢性病数量多、自理能力差、睡眠时间不足的老年人身心健康状况,并基于疼痛和抑郁的联合轨迹及共同影响因素制定干预措施。

, authors=周紫彤, 贾钰, 刘芹, 汪世秀, 王云琼, 王千, 辜小钊, 代月娥, 罗学梅*, *, authorsList=周紫彤, 贾钰, 刘芹, 汪世秀, 王云琼, 王千, 辜小钊, 代月娥, 罗学梅, authorCompany=null, correspAuthors=罗学梅, authorNote=

周紫彤,护师,硕士研究生

, correspAuthorsNote=
罗学梅,E-mail:
LUO Xuemei, E-mail:
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year=2022, volume=8, issue=17, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=21, rfOrder=20, authorNames=Yamauchi N, Sato K, Sato K, journalName=Science Advances, refType=null, unstructuredReference=Yamauchi N,Sato K,Sato K,et al.Chronic pain-induced neuronal plasticity in the bed nucleus of the stria terminalis causes maladaptive anxiety[J].Science Advances,2022,8(17):eabj5586., articleTitle=Chronic pain-induced neuronal plasticity in the bed nucleus of the stria terminalis causes maladaptive anxiety, refAbstract=null), Reference(id=1322931482381136267, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, doi=null, pmid=null, pmcid=null, year=2021, volume=21, issue=null, pageStart=534, pageEnd=null, url=null, language=null, rfNumber=22, rfOrder=21, authorNames=Li X H, Zhu W, Li J P, journalName=BMC Geriatrics, refType=null, unstructuredReference=Li X H,Zhu W,Li J P,et al.Prevalence and characteristics of chronic pain in the 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authorNames=Zhou Z T, Jia Y, Yan H, journalName=Archives of Psychiatric Nursing, refType=null, unstructuredReference=Zhou Z T,Jia Y,Yan H.Analysis of the prevalence and influencing factors of depression in middle-aged women:a nationwide study from CHARLS[J].Archives of Psychiatric Nursing,2025,55:151859., articleTitle=Analysis of the prevalence and influencing factors of depression in middle-aged women:a nationwide study from CHARLS, refAbstract=null), Reference(id=1322931482616017294, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, doi=null, pmid=null, pmcid=null, year=2020, volume=274, issue=null, pageStart=85, pageEnd=92, url=null, language=null, rfNumber=25, rfOrder=24, authorNames=Liu D X, Xi J, Hall B J, journalName=Journal of Affective disorders, refType=null, unstructuredReference=Liu D X,Xi J,Hall B J,et al.Attitudes toward aging,social support and depression among older adults:difference by urban and rural areas in China[J].Journal of Affective disorders,2020,274:85-92., articleTitle=Attitudes toward aging,social support and depression among older adults:difference by urban and rural areas in China, refAbstract=null), Reference(id=1322931482691514767, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, doi=null, pmid=null, pmcid=null, year=2020, volume=45, issue=null, pageStart=74, pageEnd=89, url=null, language=null, rfNumber=26, rfOrder=25, authorNames=Riemann D, Krone L B, Wulff K, journalName=Neuropsychopharmacology, refType=null, unstructuredReference=Riemann D,Krone L B,Wulff K,et al.Sleep,insomnia,and depression[J].Neuropsychopharmacology,2020,45:74-89., articleTitle=Sleep,insomnia,and depression, refAbstract=null), Reference(id=1322931482775400848, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, doi=null, pmid=null, pmcid=null, year=2008, volume=73, issue=2, pageStart=204, pageEnd=226, url=null, language=null, rfNumber=27, rfOrder=26, authorNames=Yang Y, journalName=American Sociological Review, refType=null, unstructuredReference=Yang Y.Social inequalities in happiness in the United States,1972 to 2004:an age-period-cohort analysis[J].American Sociological Review,2008,73(2):204-226., articleTitle=Social inequalities in happiness in the United States,1972 to 2004:an age-period-cohort analysis, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1322931470007939362, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, xref=1, ext=[AuthorCompanyExt(id=1322931470012133667, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, companyId=1322931470007939362, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Sichuan Academy of Medical Sciences/Sichuan Provincial People's Hospital(Affiliated Hospital of University of Electronic Science and Technology of China), Sichuan Provincial Center for Mental Disorders, Sichuan 611135 China), AuthorCompanyExt(id=1322931470020522276, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, companyId=1322931470007939362, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1四川省医学科学院·四川省人民医院(电子科技大学附属医院),四川省精神医学中心,四川 611135)])], figs=[ArticleFig(id=1322931475208876384, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Figure 1, caption=Flowchart for screening research subjects, figureFileSmall=PoED7YThTb8eIm0I8lYk8A==, figureFileBig=/NcBgn9ggbwFkm/+LAyDpw==, tableContent=null), ArticleFig(id=1322931475263402337, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=图1, caption=研究对象筛选流程图, figureFileSmall=PoED7YThTb8eIm0I8lYk8A==, figureFileBig=/NcBgn9ggbwFkm/+LAyDpw==, tableContent=null), ArticleFig(id=1322931475477311842, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Figure 2, caption=Trajectory of pain sites in the older adults, figureFileSmall=Bo0Ghz8VlHOL0U5wTygwMQ==, figureFileBig=Q148sUSyQ0NNshFev/ITTw==, tableContent=null), ArticleFig(id=1322931475536032099, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=图2, caption=老年人疼痛部位纵向轨迹, figureFileSmall=Bo0Ghz8VlHOL0U5wTygwMQ==, figureFileBig=Q148sUSyQ0NNshFev/ITTw==, tableContent=null), ArticleFig(id=1322931475653472612, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Figure 3, caption=Longitudinal trajectory of depressive symptoms in older adults, figureFileSmall=CSs9AqWCV0vfu7AMNpMgLg==, figureFileBig=sPxOiZr/1NJ84JJPFMUL9A==, tableContent=null), ArticleFig(id=1322931476009988453, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=图3, caption=老年人抑郁症状纵向轨迹, figureFileSmall=CSs9AqWCV0vfu7AMNpMgLg==, figureFileBig=sPxOiZr/1NJ84JJPFMUL9A==, tableContent=null), ArticleFig(id=1322931477683515750, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Table 1, caption=

Baseline characteristics of the study population in 2011(n=2 772)

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类人数构成比(%)变量分类人数构成比(%)
年龄60~70岁2 23680.66饮酒否1 87367.57
>70~80岁51618.61是89932.43
>80岁200.72吸烟否1 88668.04
性别女1 35848.99是88631.96
男1 41451.01文化程度文盲1 38449.93
婚姻状况其他42415.30小学78728.39
已婚2 34884.70中学40014.43
居住地城市94233.98高中及以上2017.25
农村1 83066.02慢性病数量无72226.05
自评健康很差1043.751种84530.48
较差67024.172种59821.57
一般1 42251.303种及以上60721.90
较好42615.37IADL无障碍2 15277.63
很好1505.41有障碍62022.37
夜晚睡眠时间<7 h1 52254.91ADL无障碍2 25381.28
7~9 h1 14741.38有障碍51918.72
>9 h1033.72
), ArticleFig(id=1322931477759013223, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=表1, caption=

2011年研究对象基本特征(n=2 772)

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类人数构成比(%)变量分类人数构成比(%)
年龄60~70岁2 23680.66饮酒否1 87367.57
>70~80岁51618.61是89932.43
>80岁200.72吸烟否1 88668.04
性别女1 35848.99是88631.96
男1 41451.01文化程度文盲1 38449.93
婚姻状况其他42415.30小学78728.39
已婚2 34884.70中学40014.43
居住地城市94233.98高中及以上2017.25
农村1 83066.02慢性病数量无72226.05
自评健康很差1043.751种84530.48
较差67024.172种59821.57
一般1 42251.303种及以上60721.90
较好42615.37IADL无障碍2 15277.63
很好1505.41有障碍62022.37
夜晚睡眠时间<7 h1 52254.91ADL无障碍2 25381.28
7~9 h1 14741.38有障碍51918.72
>9 h1033.72
), ArticleFig(id=1322931477834510696, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Table 2, caption=

Parameters for fitting pain site trajectories

, figureFileSmall=null, figureFileBig=null, tableContent=
轨迹数AICBICLLEntropyAvePP
2-28 727.0-28 741.8-28 722.00.9370.895/0.838
3-26 916.3-26 940.0-26 908.30.8940.895/0.838/0.861
4-26 279.4-26 312.0-26 268.40.8670.957/0.894/0.866/0.960
5-25 864.6-25 906.0-25 850.60.8560.873/0.946/0.898/0.926/0.845
), ArticleFig(id=1322931477922591081, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=表2, caption=

疼痛部位轨迹拟合参数

, figureFileSmall=null, figureFileBig=null, tableContent=
轨迹数AICBICLLEntropyAvePP
2-28 727.0-28 741.8-28 722.00.9370.895/0.838
3-26 916.3-26 940.0-26 908.30.8940.895/0.838/0.861
4-26 279.4-26 312.0-26 268.40.8670.957/0.894/0.866/0.960
5-25 864.6-25 906.0-25 850.60.8560.873/0.946/0.898/0.926/0.845
), ArticleFig(id=1322931478069391722, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Table 3, caption=

Logistic regression analysis of influencing factors of pain trajectories

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类回归系数标准误Z值POR值[95%CI]
年龄60~70岁
>70~80岁-0.360.13-2.870.0040.70[0.54,0.89]
>80岁-0.610.62-0.990.3240.54[0.16,1.83]
性别女
男-0.910.11-8.18<0.0010.40[0.32,0.50]
居住地城市
农村0.470.114.29<0.0011.59[1.29,1.97]
自评健康很好
较好0.350.341.020.3071.42[0.73,2.77]
一般1.020.313.250.0012.78[1.50,5.16]
较差1.650.325.14<0.0015.22[2.78,9.81]
很差1.990.405.01<0.0017.32[3.36,15.97]
文化程度高中及以上
初中0.370.261.440.1511.45[0.87,2.41]
小学0.700.242.890.0042.01[1.25,3.23]
文盲1.000.244.21<0.0012.73[1.71,4.36]
夜间睡眠时间7~9 h
<7 h0.360.103.60<0.0011.43[1.18,1.74]
>9 h-0.090.27-0.350.7280.91[0.54,1.54]
饮酒否
是0.170.121.490.1361.19[0.95,1.50]
慢性病数量无
1种0.810.145.60<0.0012.25[1.69,2.98]
2种1.320.158.79<0.0013.76[2.80,5.05]
3种及以上1.970.1512.71<0.0017.17[5.29,9.71]
IADL无障碍
有障碍0.380.123.220.0011.46[1.16,1.84]
ADL无障碍
有障碍0.740.126.00<0.0012.10[1.65,2.68]
), ArticleFig(id=1322931478149083499, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=表3, caption=

疼痛轨迹影响因素的Logistics回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类回归系数标准误Z值POR值[95%CI]
年龄60~70岁
>70~80岁-0.360.13-2.870.0040.70[0.54,0.89]
>80岁-0.610.62-0.990.3240.54[0.16,1.83]
性别女
男-0.910.11-8.18<0.0010.40[0.32,0.50]
居住地城市
农村0.470.114.29<0.0011.59[1.29,1.97]
自评健康很好
较好0.350.341.020.3071.42[0.73,2.77]
一般1.020.313.250.0012.78[1.50,5.16]
较差1.650.325.14<0.0015.22[2.78,9.81]
很差1.990.405.01<0.0017.32[3.36,15.97]
文化程度高中及以上
初中0.370.261.440.1511.45[0.87,2.41]
小学0.700.242.890.0042.01[1.25,3.23]
文盲1.000.244.21<0.0012.73[1.71,4.36]
夜间睡眠时间7~9 h
<7 h0.360.103.60<0.0011.43[1.18,1.74]
>9 h-0.090.27-0.350.7280.91[0.54,1.54]
饮酒否
是0.170.121.490.1361.19[0.95,1.50]
慢性病数量无
1种0.810.145.60<0.0012.25[1.69,2.98]
2种1.320.158.79<0.0013.76[2.80,5.05]
3种及以上1.970.1512.71<0.0017.17[5.29,9.71]
IADL无障碍
有障碍0.380.123.220.0011.46[1.16,1.84]
ADL无障碍
有障碍0.740.126.00<0.0012.10[1.65,2.68]
), ArticleFig(id=1322931478241358188, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Table 4, caption=

Depression trajectory fitting parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
轨迹数AICBICLLEntropyAvePP
2-28 727.0-28 741.8-28 722.00.9370.895/0.838
3-26 916.3-26 940.0-26 908.30.8940.895/0.838/0.861
4-26 279.4-26 312.0-26 268.40.8670.957/0.894/0.866/0.960
5-25 864.6-25 906.0-25 850.60.8560.873/0.946/0.898/0.926/0.845
), ArticleFig(id=1322931478316855661, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=表4, caption=

抑郁轨迹拟合参数

, figureFileSmall=null, figureFileBig=null, tableContent=
轨迹数AICBICLLEntropyAvePP
2-28 727.0-28 741.8-28 722.00.9370.895/0.838
3-26 916.3-26 940.0-26 908.30.8940.895/0.838/0.861
4-26 279.4-26 312.0-26 268.40.8670.957/0.894/0.866/0.960
5-25 864.6-25 906.0-25 850.60.8560.873/0.946/0.898/0.926/0.845
), ArticleFig(id=1322931478404936046, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Table 5, caption=

Logistics regression analysis of influencing factors of depression trajectories

, figureFileSmall=null, figureFileBig=null, tableContent=
轨迹变量分类回归系数标准误Z值POR值[95%CI]
中水平-增长组性别女
男-0.470.12-3.90<0.0010.63[0.50,0.79]
居住地城市
农村0.540.115.12<0.0011.71[1.39,2.10]
自评健康很好
较好0.350.211.640.1001.42[0.94,2.14]
一般0.880.204.49<0.0012.42[1.64,3.55]
较差1.480.236.43<0.0014.39[2.79,6.88]
很差1.990.523.79<0.0017.30[2.61,20.37]
文化程度高中及以上
初中0.400.201.990.0461.49[1.01,2.22]
小学0.590.193.100.0021.80[1.24,2.62]
文盲0.770.194.06<0.0012.16[1.49,3.14]
夜间睡眠时间7~9 h
<7 h0.430.104.36<0.0011.54[1.27,1.87]
>9 h0.100.250.400.6891.11[0.67,1.82]
婚姻状况其他
已婚-0.410.15-2.780.0050.66[0.50,0.89]
慢性病数量无
1种0.230.121.910.0561.26[0.99,1.60]
2种0.360.142.560.0111.44[1.09,1.90]
3种及以上0.820.165.14<0.0012.28[1.66,3.12]
吸烟否
是0.210.121.750.0801.23[0.98,1.55]
ADL无障碍
有障碍0.720.174.15<0.0012.05[1.46,2.89]
高水平-增长组年龄60~70岁
>70~80岁-0.430.18-2.350.0190.65[0.45,0.93]
>80岁-1.070.88-1.210.2250.34[0.06,1.93]
性别女
男-0.910.15-6.10<0.0010.40[0.30,0.54]
居住地城市
农村0.870.155.60<0.0012.38[1.76,3.22]
自评健康很好
较好0.260.410.620.5321.29[0.58,2.88]
一般1.340.373.57<0.0013.81[1.83,7.92]
较差2.570.396.53<0.00113.06[6.04,28.24]
很差3.360.645.22<0.00128.92[8.17,102.39]
文化程度高中及以上
初中0.220.340.630.5291.24[0.63,2.42]
小学0.850.312.740.0062.35[1.28,4.33]
文盲1.190.313.88<0.0013.30[1.80,6.03]
夜间睡眠时间7~9 h
<7 h0.770.145.33<0.0012.16[1.63,2.87]
>9 h-0.240.39-0.610.5410.79[0.37,1.69]
婚姻状况其他
已婚-0.650.20-3.180.0010.52[0.35,0.78]
慢性病数量无
1种0.620.193.32<0.0011.86[1.29,2.68]
2种0.660.213.160.0021.93[1.28,2.89]
3种及以上1.470.226.65<0.0014.36[2.82,6.72]
IADL无障碍
有障碍0.650.183.59<0.0011.91[1.34,2.71]
ADL无障碍
有障碍1.230.206.04<0.0013.42[2.29,5.10]
), ArticleFig(id=1322931478493016431, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=表5, caption=

抑郁轨迹影响因素的Logistics回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
轨迹变量分类回归系数标准误Z值POR值[95%CI]
中水平-增长组性别女
男-0.470.12-3.90<0.0010.63[0.50,0.79]
居住地城市
农村0.540.115.12<0.0011.71[1.39,2.10]
自评健康很好
较好0.350.211.640.1001.42[0.94,2.14]
一般0.880.204.49<0.0012.42[1.64,3.55]
较差1.480.236.43<0.0014.39[2.79,6.88]
很差1.990.523.79<0.0017.30[2.61,20.37]
文化程度高中及以上
初中0.400.201.990.0461.49[1.01,2.22]
小学0.590.193.100.0021.80[1.24,2.62]
文盲0.770.194.06<0.0012.16[1.49,3.14]
夜间睡眠时间7~9 h
<7 h0.430.104.36<0.0011.54[1.27,1.87]
>9 h0.100.250.400.6891.11[0.67,1.82]
婚姻状况其他
已婚-0.410.15-2.780.0050.66[0.50,0.89]
慢性病数量无
1种0.230.121.910.0561.26[0.99,1.60]
2种0.360.142.560.0111.44[1.09,1.90]
3种及以上0.820.165.14<0.0012.28[1.66,3.12]
吸烟否
是0.210.121.750.0801.23[0.98,1.55]
ADL无障碍
有障碍0.720.174.15<0.0012.05[1.46,2.89]
高水平-增长组年龄60~70岁
>70~80岁-0.430.18-2.350.0190.65[0.45,0.93]
>80岁-1.070.88-1.210.2250.34[0.06,1.93]
性别女
男-0.910.15-6.10<0.0010.40[0.30,0.54]
居住地城市
农村0.870.155.60<0.0012.38[1.76,3.22]
自评健康很好
较好0.260.410.620.5321.29[0.58,2.88]
一般1.340.373.57<0.0013.81[1.83,7.92]
较差2.570.396.53<0.00113.06[6.04,28.24]
很差3.360.645.22<0.00128.92[8.17,102.39]
文化程度高中及以上
初中0.220.340.630.5291.24[0.63,2.42]
小学0.850.312.740.0062.35[1.28,4.33]
文盲1.190.313.88<0.0013.30[1.80,6.03]
夜间睡眠时间7~9 h
<7 h0.770.145.33<0.0012.16[1.63,2.87]
>9 h-0.240.39-0.610.5410.79[0.37,1.69]
婚姻状况其他
已婚-0.650.20-3.180.0010.52[0.35,0.78]
慢性病数量无
1种0.620.193.32<0.0011.86[1.29,2.68]
2种0.660.213.160.0021.93[1.28,2.89]
3种及以上1.470.226.65<0.0014.36[2.82,6.72]
IADL无障碍
有障碍0.650.183.59<0.0011.91[1.34,2.71]
ADL无障碍
有障碍1.230.206.04<0.0013.42[2.29,5.10]
), ArticleFig(id=1322931478597874032, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Table 6, caption=

Probability of depression trajectory group in the pain trajectory group condition

, figureFileSmall=null, figureFileBig=null, tableContent=
抑郁轨迹组疼痛轨迹组
少部位-稳定组多部位-增长组
低水平-稳定组70.410.7
中水平-增长组27.959.8
高水平-增长组1.829.5
), ArticleFig(id=1322931478694343025, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=表6, caption=

疼痛轨迹组条件下抑郁轨迹组概率

, figureFileSmall=null, figureFileBig=null, tableContent=
抑郁轨迹组疼痛轨迹组
少部位-稳定组多部位-增长组
低水平-稳定组70.410.7
中水平-增长组27.959.8
高水平-增长组1.829.5
), ArticleFig(id=1322931478753063282, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Table 7, caption=

Probability of pain trajectory group in depression trajectory group condition

, figureFileSmall=null, figureFileBig=null, tableContent=
疼痛轨迹组抑郁轨迹组
低水平-稳定组中水平-增长组高水平-增长组
少部位-稳定组92.546.710.2
多部位-增长组7.553.389.8
), ArticleFig(id=1322931478832755059, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=表7, caption=

抑郁轨迹组条件下疼痛轨迹组概率

, figureFileSmall=null, figureFileBig=null, tableContent=
疼痛轨迹组抑郁轨迹组
低水平-稳定组中水平-增长组高水平-增长组
少部位-稳定组92.546.710.2
多部位-增长组7.553.389.8
), ArticleFig(id=1322931478916641140, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=EN, label=Table 8, caption=

Joint probability of pain trajectory group and depression trajectory group

, figureFileSmall=null, figureFileBig=null, tableContent=
双轨迹概率
抑郁低水平-稳定组+疼痛少部位-稳定组45.9
抑郁中水平-增长组+疼痛少部位-稳定组18.2
抑郁高水平-增长组+疼痛少部位-稳定组1.2
抑郁低水平-稳定组+疼痛多部位-增长组3.7
抑郁中水平-增长组+疼痛多部位-增长组20.8
抑郁高水平-增长组+疼痛多部位-增长组10.2
), ArticleFig(id=1322931478983750005, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931467151618328, language=CN, label=表8, caption=

疼痛轨迹组和抑郁轨迹组联合概率

, figureFileSmall=null, figureFileBig=null, tableContent=
双轨迹概率
抑郁低水平-稳定组+疼痛少部位-稳定组45.9
抑郁中水平-增长组+疼痛少部位-稳定组18.2
抑郁高水平-增长组+疼痛少部位-稳定组1.2
抑郁低水平-稳定组+疼痛多部位-增长组3.7
抑郁中水平-增长组+疼痛多部位-增长组20.8
抑郁高水平-增长组+疼痛多部位-增长组10.2
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老年人疼痛和抑郁症状的联合轨迹分析
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周紫彤 , 贾钰 , 刘芹 , 汪世秀 , 王云琼 , 王千 , 辜小钊 , 代月娥 , 罗学梅 *, *
护理研究 | 科研论著 2026,40(13): 2233-2241
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护理研究 |科研论著 2026 , 40 (13) : 2233 -2241
老年人疼痛和抑郁症状的联合轨迹分析
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周紫彤, 贾钰, 刘芹, 汪世秀, 王云琼, 王千, 辜小钊, 代月娥, 罗学梅*, *
作者信息
  • 1四川省医学科学院·四川省人民医院(电子科技大学附属医院),四川省精神医学中心,四川 611135
通讯作者:
罗学梅,E-mail:
LUO Xuemei, E-mail:
作者简介:

周紫彤,护师,硕士研究生

Joint trajectory analysis of pain and depressive symptoms in older adults
Zitong ZHOU, Yu JIA, Qin LIU, Shixiu WANG, Yunqiong WANG, Qian WANG, Xiaozhao GU, Yue'e DAI, Xuemei LUO
Affiliations
  • 1Sichuan Academy of Medical Sciences/Sichuan Provincial People's Hospital(Affiliated Hospital of University of Electronic Science and Technology of China), Sichuan Provincial Center for Mental Disorders, Sichuan 611135 China
出版时间: 2026-07-10 doi: 10.12102/j.issn.1009-6493.2026.13.006
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目的

识别老年人疼痛和抑郁症状的联合轨迹,探讨二者之间的动态关联及共同影响因素,为制定干预策略提供依据。

方法

基于中国健康与养老追踪调查(CHARLS) 2011—2020年数据,共纳入2 772名老年人。采用基于组基轨迹(GBTM)双轨迹模型分析疼痛与抑郁的联合发展轨迹,采用Logistic回归分析识别其共同影响因素。

结果

疼痛轨迹识别出少部位-稳定组和多部位-增长组2类,抑郁轨迹识别出低水平-稳定组、中水平-增长组和高水平-增长组3类。双轨迹分析显示,相较于少部位-稳定组,多部位-增长组的老年人有更大概率经历抑郁中水平-增长(53.3%)和抑郁高水平-增长(89.8%);相较于低水平-稳定组,中水平-增长组和高水平-增长组老年人有更大概率经历多部位-增长疼痛(59.8%和29.5%)。年龄、性别、文化程度、居住地、夜间睡眠时间、自评健康、慢性病数量以及日常生活能力是疼痛轨迹和抑郁轨迹的共同影响因素(均P<0.05)。

结论

老年人疼痛轨迹和抑郁轨迹有高度相关性。应重点关注60岁年龄组、女性、居住在农村、自评健康差、教育程度低、慢性病数量多、自理能力差、睡眠时间不足的老年人身心健康状况,并基于疼痛和抑郁的联合轨迹及共同影响因素制定干预措施。

老年人  /  疼痛  /  抑郁  /  影响因素  /  睡眠  /  联合轨迹  /  纵向研究
Objective

To identify joint trajectories of pain and depressive symptoms in older adults,to explore the dynamic relationship between them,and to identify common influencing factors,so as to provide a basis for developing intervention strategies.

Methods

Based on data from the China Health and Retirement Longitudinal Study(CHARLS) from 2011 to 2020,a total of 2 772 older adults were included.A group-based trajectory modeling(GBTM) dual-trajectory approach was used to analyze the joint developmental trajectories of pain and depression.Logistic regression was used to identify common influencing factors.

Results

Two types of pain trajectories were identified: the few sites-stable group and the multiple sites-increasing group.Three types of depression trajectories were identified:the low level-stable group,the medium level-increasing group,and the high level-increasing group.Dual-trajectory analysis showed that compared with the few sites-stable group,older adults in the multiple sites-increasing group had a higher probability of experiencing the medium level-increasing depression(53.3%) and the high level-increasing depression(89.8%).Compared with the low level-stable group,older adults in the medium level-increasing depression group and the high level-increasing depression group had a higher probability of experiencing the multiple sites-increasing pain(59.8% and 29.5%,respectively).Age,gender,educational level,place of residence,nighttime sleep duration,self-rated health,number of chronic diseases,and activities of daily living were common influencing factors for both pain and depression trajectories(all P<0.05).

Conclusions

Pain and depression trajectories in older adults show a high degree of correlation.Attention should be given to the physical and mental health of older adults aged 60 years,females,those living in rural areas,those with poor self-rated health,low education level,a high number of chronic diseases,poor self-care ability,and insufficient sleep duration.Interventions should be developed based on the joint trajectories and common influencing factors of pain and depression.

older adults  /  pain  /  depression  /  influencing factors  /  sleep  /  joint trajectory  /  longitudinal study
周紫彤, 贾钰, 刘芹, 汪世秀, 王云琼, 王千, 辜小钊, 代月娥, 罗学梅. 老年人疼痛和抑郁症状的联合轨迹分析. 护理研究, 2026 , 40 (13) : 2233 -2241 . DOI: 10.12102/j.issn.1009-6493.2026.13.006
Zitong ZHOU, Yu JIA, Qin LIU, Shixiu WANG, Yunqiong WANG, Qian WANG, Xiaozhao GU, Yue'e DAI, Xuemei LUO. Joint trajectory analysis of pain and depressive symptoms in older adults[J]. Chinese Nursing Research, 2026 , 40 (13) : 2233 -2241 . DOI: 10.12102/j.issn.1009-6493.2026.13.006
人口老龄化是当今各国乃至世界面临的共同问题,也是人口发展的必然结果。根据中国国家统计局数据,截至2023 年底,中国60岁及以上老年人口已超过2.9亿人[1]。随着机体功能的衰退,老年人面临的身心问题日益凸显。据统计,我国老年人身体疼痛患病率高达39.1%[2]。疼痛是指与实际或潜在组织损伤相关的不愉快感觉,是一种情绪复合体验。2018年世界卫生组织(WHO)修订的《国际疾病分类第11版》(ICD-11)首次将慢性疼痛列为独立疾病[3]。慢性疼痛常引发身体功能减退、睡眠障碍及情绪异常(如抑郁)等并发症,其中抑郁最为高发[4]。流行病学数据显示,全球抑郁症患病率约3.8%[5],在老年群体中高达28.4%[6];而疼痛与抑郁的共病率可达30%~50%[7]。然而,既往研究主要侧重于在横断面研究中探讨疼痛和抑郁之间的关系[8-10],而没有探讨随时间变化的疼痛-抑郁联合轨迹。本研究采用群体轨迹模型(group-based trajectory modeling,GBTM)识别老年人疼痛和抑郁的联合轨迹,分析二者之间的关联模式及共同影响因素,为降低老年群体疼痛-抑郁共病率提供依据。
本研究数据来源于中国健康与养老追踪调查(https://charls.pku.edu.cn/en/)CHARLS数据库,采用2011年、2013年、2015年、2018年、2020年5期调查数据。数据已获得北京大学生物医学伦理委员会批准(审批号:IRB00001052-11015)[11]。选取2011年年龄≥60岁的老年人,同时完整参与2013年、2015年、2018年、2020年4次随访的研究对象,最终纳入有效样本量2 772人。具体筛选流程见图1。
采用流行病学研究中心抑郁量表(CESD-10)的简易版用于评估老年人的抑郁症状。该量表共包含10个项目,每个项目回答“很少”或“没有”计1分,“有些”或“一点点”计2分,“偶尔”或“中等时间”计3分,“大部分时间”计4分。第5项“我对未来充满希望”和第8项“我很快乐”采用反向计分。总分越高,抑郁症状越严重。该量表在中国老年人群中信效度较好,是筛查抑郁症状的可靠工具[12]。
通过询问受试者是否受到身体疼痛的困扰及疼痛的具体位置,包括头部、肩部、手臂、腕部、手指、胸部、腹部、背部、腰部、臀部、腿部、膝盖、脚踝、脚趾以及颈部等部位。统计时,将“是”计为有疼痛困扰,并对其报告的疼痛部位逐项计数后求和,得到疼痛部位总数(例如,若同时报告头部和颈部疼痛,则计数为2)。
一般人口学特征,包括年龄、性别、婚姻状况、居住地、文化程度;生活习惯,包括饮酒、吸烟、夜晚睡眠时间;健康状况,包括患有慢性病种数、日常生活活动能力(ADL)、工具性日常生活活动能力(IADL)。
GBTM能够识别纵向数据中人群的异质性发展轨迹,分析轨迹与影响因素或结局的关联;在单轨迹模型基础上,GBTM双轨迹模型通过条件概率或联合概率,进一步分析两个相关结果的发展轨迹之间的联系[13]。首先,通过GBTM单轨迹建模识别老年人疼痛部位和抑郁症状轨迹。假设二者单轨迹的数量范围为2~5。模型选择标准包括贝叶斯信息准则(BIC)、赤池信息准则(AIC)、对数似然值(Log-likelihood,LL)和熵(Entropy)。同时,各组参与者占比大于5%,平均后验概率(average of the posterior probability,AvePP)高于0.7的分组被认为是可接受[13]。采用疼痛部位和抑郁最优单轨迹模型参数拟合双轨迹模型,分析双轨迹的条件概率和联合概率。最后,采用频数、百分比(%)对定性资料进行统计描述,采用均数±标准差(x±s)对定量资料进行描述;运用Logistic回归模型探究疼痛部位轨迹和抑郁症状轨迹的影响因素。检验水准,双侧α=0.05。
共纳入2 772名老年人,年龄(65.45±4.75)岁,男1 414人(51.01%),女1 358人(48.99%)。研究对象2011年基本特征见表1。
根据轨迹拟合指标结合轨迹图,最终拟合出少部位-稳定组(1 826人,占65.9%)、多部位-增长组(946人,占34.1%)2种老年人疼痛部位轨迹。见表2和图2。
将GBTM轨迹模型得出的老年人疼痛部位轨迹作为因变量,以少部位-稳定组为参照,进行无序多分类 Logistic回归分析。结果显示,年龄在70~80岁分段、男性老年人更容易归属于少部位-稳定组(P<0.05);居住在农村、自评健康为一般及以下、小学及以下学历、夜间睡眠时间<7 h、患有慢性病、ADL和IADL有障碍的老年人更容易归属于多部位-增长组(P<0.05),见表3。
根据轨迹拟合指标结合轨迹图,最终拟合出低水平-稳定组(825人,占29.8%)、中水平-增长组(1 260人,占45.5%)和高水平-增长组(687人,占24.8%)3种老年人抑郁症状轨迹。见表4和图3。
将GBTM轨迹模型得出的老年人抑郁症状轨迹作为因变量,以低水平-稳定组为参照,进行无序多分类 Logistic回归分析。结果显示,居住在农村、自评健康状况在一般及以下、初中及以下学历、睡眠时间<7 h、慢性病数量2种及以上、ADL有障碍的老年人更容易归属于中水平-增长组和高水平-增长组;男性、已婚状态的老年人更容易归属于低水平-稳定组(P<0.05);年龄在70~80岁更容易归属于低水平-稳定组;IADL有障碍更容易归属于高水平-增长组(P<0.05)。具体见表5。
结果显示,抑郁低水平-稳定组属于疼痛少部位-稳定组的概率较高(占70.4%),抑郁中水平-增长组属于疼痛多部位-增长组的概率较高(占59.8%)。疼痛轨迹组条件下抑郁轨迹组概率见表6。
疼痛少部位-稳定组属于抑郁低水平-稳定组的概率较高(占92.5%),疼痛多部位-增长组属于抑郁高水平-增长组的概率较高(占89.8%)。抑郁轨迹组下疼痛轨迹组概率见表7。
进一步分析双轨迹的条件概率和联合概率,结果显示,联合概率中占比前3位的分别为同时属于抑郁低水平-稳定组和疼痛少部位-稳定组的概率为45.9%,同时属于抑郁中水平-增长组和疼痛多部位-增长组的概率为20.8%,以及同时属于抑郁中水平-增长组和疼痛少部位-稳定组的概率为18.2%。疼痛轨迹组和抑郁轨迹组的联合概率见表8。
本研究基于CHARLS 2011—2020年纵向研究数据,采用GBTM共识别出少部位-稳定组和多部位-增长组2种老年人疼痛纵向轨迹,该结果与张舒等[14]研究结果类似,其中有34.1%的老年人表现为多部位疼痛且呈持续增长趋势。值得注意的是,国外学者针对非裔老年群体划分了5种疼痛表型轨迹,分别为无慢性疼痛、持续性轻中度慢性疼痛、持续性重度高冲击慢性疼痛、慢性疼痛缓解型及慢性疼痛恶化型[15],其研究进一步显示47.5%的非裔老年人受到不同程度慢性疼痛的影响。
本研究结果显示,老年人抑郁纵向轨迹可分为低水平-稳定组、中水平-增长组以及高水平-增长组3种轨迹。既往研究已经观察到不同人群存在多种抑郁轨迹[16-18],但由于研究对象、调查数据不同,其轨迹的种数和形状也有所不同。在本研究中,有24.8%的老年人存在高水平抑郁,其严重程度随着时间增长。另外,同时属于抑郁中水平-增长组和疼痛多部位-增长组的联合概率为20.8%。可见,部分老年人受到疼痛和抑郁的困扰,其身心健康不容忽视。
本研究结果显示,在每个分组中,属于多部位-增长组疼痛轨迹的老年人有更大可能性属于中水平抑郁或高水平抑郁轨迹组。同样,在每个分组中,中水平抑郁轨迹或高水平抑郁轨迹的老年人有更大的概率属于多部位-增长组疼痛轨迹。研究发现,疼痛与抑郁引发的神经可塑性及神经生物学机制变化存在重叠,这种重叠对慢性疼痛及其诱发的抑郁症的发生与发展至关重要[19]。机体疼痛的损伤感觉通路与情绪调控共享相同脑区(如前额叶皮层、前扣带回、丘脑、海马和杏仁核),构成了二者共存的组织学基础[20]。此外,研究表明慢性疼痛会提高终纹床核(BNST)神经元特定亚群的兴奋性,这些神经元表达可卡因和苯丙胺调控转录本(CART)。CART阳性神经元兴奋性的升高导致下丘脑外侧区(LH)投射BNST神经元的抑制性输入增加,从而诱发焦虑样行为[21]。本研究结果表明,老年人疼痛与抑郁亚型轨迹随着时间的推移相互影响,针对其干预措施应考虑不同亚组特殊需求。
本研究显示,老年人疼痛和抑郁轨迹共同受到年龄、性别、文化程度、居住地、夜间睡眠时间、自评健康、慢性病数量以及ADL等多因素影响。
女性老年人更有可能归属于多部位-增长组疼痛轨迹和中或高水平抑郁轨迹组。既往研究表明,女性颈痛、腰背痛以及髋、膝关节痛等多个部位疼痛的患病率均比男性高出约1倍[22-23]。这可能是因为女性独特的生理或心理机制,她们对疼痛更敏感。此外,社会赋予男性和女性不同的角色,女性在嗓音和体力方面较弱,在家务和养育子女方面比男性付出更多,女性更容易出现情绪问题[24]。
农村、文化程度较低的老年人更容易归属于多部位-增长组疼痛轨迹和中或高水平抑郁轨迹组。由于城乡在经济发展和资源配置上的差异,城市地区在经济基础较好的情况下,能够为居民提供更优质的医疗服务,提高居民抵御疾病的能力[25]。而受教育程度越高,社会经济资源越丰富,知识面越广,健康意识越强,在面对心理压力时自我解脱的能力越强。
夜间睡眠时间<7 h、健康状况较差的老年人更容易归属于多部位-增长组疼痛轨迹和中或高水平抑郁轨迹组。通常健康状况较差的老人可能同时经历多种慢性病与身体疼痛困扰,使得他们睡眠质量下降,失眠本身已被证明会增加抑郁症和自杀的风险,几乎所有抑郁症病人都经历过某种睡眠改变[26]。
值得注意的是,本研究显示相较于60~70岁年龄段的老年人,70岁以上年龄段的老年人更有可能归属于少部位-稳定组疼痛轨迹和低水平抑郁轨迹组,这可能与选择性生存效应有关[27]。首先,活到70岁本身就意味着个体经历了健康筛选,那些在60岁时受严重疼痛或抑郁困扰的个体可能因相关健康风险而未能进入70岁组。其次,从本研究样本量来看,最终完成5次调查的老年人70岁组(n=516)样本量远小于60岁组(n=2 236),符合老年人群随年龄增长而缩减的规律。最后,70岁组人群可能已发展出更有效的疼痛管理和心理适应策略,对疼痛和情绪的感知与报告方式也可能与60岁组不同。
本研究运用GBTM探讨老年人疼痛-抑郁的联合发展轨迹,通过识别其共同影响因素,为早期精准干预共病提供理论依据。本研究也存在一定的局限性。一方面,所有数据都是通过研究对象自我报告,易受回忆偏差与主观认知影响;另一方面,受限于协变量覆盖范围,未能全面控制潜在混杂因素,可能影响结果推断的准确性。
本研究结果显示,老年人疼痛轨迹与抑郁轨迹呈现高度一致性且显著相关。护理工作应重点关注60岁及以上、女性、农村居住、自评健康较差、教育程度较低、慢性病数量较多、自理能力不足及睡眠时间短缺的老年人群,构建系统化的护理干预体系。建议从以下层面推进:在护理评估层面,可将疼痛与抑郁的联合筛查纳入老年人健康评估常规项目;在护理干预层面,基于轨迹特征实施分层管理,对高风险人群建立动态健康档案,由社区护士开展定期随访,提供整合疼痛护理与心理支持的综合干预方案。医院与社区护理团队应协同开展慢性病管理教育,通过个性化指导提升老年病人的自我管理能力。此外,应充分发挥社区护士在老年健康管理中的核心作用,完善农村地区护理服务网络,为特殊群体提供上门护理服务。本研究通过识别疼痛与抑郁的联合轨迹特征,为制定针对性护理干预方案提供了依据,后续研究可着力开发标准化疼痛-抑郁共病管理方案,并开展干预效果验证,为建立完善的老年延续性护理服务体系提供支持。

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2026年第40卷第13期
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doi: 10.12102/j.issn.1009-6493.2026.13.006
  • 接收时间:2025-11-18
  • 首发时间:2026-10-30
  • 出版时间:2026-07-10
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  • 收稿日期:2025-11-18
  • 修回日期:2026-05-17
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    1四川省医学科学院·四川省人民医院(电子科技大学附属医院),四川省精神医学中心,四川 611135

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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