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Article(id=1241023934057992782, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202407423, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1721664000000, receivedDateStr=2024-07-23, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812762988, onlineDateStr=2026-03-18, pubDate=1739116800000, pubDateStr=2025-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812762988, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812762988, creator=13701087609, updateTime=1773812762988, updator=13701087609, issue=Issue{id=1241023927812682133, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='3', pageStart='385', pageEnd='576', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812761500, creator=13701087609, updateTime=1773812858867, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024336258200259, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024336258200260, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=513, endPage=519, ext={EN=ArticleExt(id=1241023935203037793, articleId=1241023934057992782, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=A study on the correlation between depression symptoms and physical functional impairment in the elderly based on a dual trajectory model, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the bidirectional relationship between depression symptoms and physical functional impairment trajectories in Chinese elderly individuals.

Methods

Utilizing data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, and 2018, we employed group-based trajectory modeling to identify distinct trajectory groups for depression symptoms and physical functional impairment among the elderly. A dual trajectory model was then used to assess the degree of association between these trajectory groups.

Results

The group-based trajectory model categorized depression symptoms into four groups: consistently low depression symptoms, decreasing depression symptoms, increasing depression symptoms, and consistently high depression symptoms. Physical functional impairment was classified into four groups: no physical functional impairment, worsening physical functional impairment, improving physical functional impairment, and high physical functional impairment. Dual trajectory analysis revealed that 44.86% of individuals in the decreasing depression symptoms group followed the improving physical functional impairment trajectory; conversely, 37.58% of individuals in the increasing depression symptoms group followed the worsening physical functional impairment trajectory. Among those in the worsening physical functional impairment group, 47.8% followed the increasing depression symptoms trajectory, while 41.9% of individuals in the improving physical functional impairment group followed the decreasing depression symptoms trajectory.

Conclusion

In most cases, there is a positive correlation between the trajectories of depression symptoms and physical functional impairment. A decrease in depression symptoms is typically associated with an improvement in physical functional impairment, while an increase in depression symptoms corresponds with a worsening of physical functional impairment, and vice versa.

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目的

探索中国老年人抑郁症状和身体功能障碍发展轨迹间的双向关系。

方法

使用2011、2013、2015和2018年中国健康与养老追踪调查(CHARLS)的4轮数据，利用组基轨迹模型识别老年人抑郁症状和身体功能障碍不同轨迹组，并利用双轨迹模型评估抑郁症状和身体功能障碍轨迹组关联程度。

结果

组基轨迹模型将抑郁症状分为持续低抑郁症状组、抑郁症状下降组、抑郁症状上升组、持续高抑郁症状组。身体功能障碍分为无身体功能障碍组、身体功能障碍加重组、身体功能障碍缓解组和高身体功能障碍组。双轨迹分析表明抑郁症状下降组中，44.86%的人遵循身体功能障碍缓解轨迹；抑郁症状上升组中，37.58%的人遵循身体功能障碍加重轨迹。身体功能障碍加重组中，47.8%的人遵循抑郁症状上升轨迹；身体功能障碍缓解组中，41.9%的人遵循抑郁症状下降。

结论

在大多数情况下，抑郁症状和身体功能障碍轨迹是正相关的，抑郁症状下降通常伴随身体功能障碍缓解，抑郁症状上升伴随身体功能障碍加重。反之亦然。

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徐德民，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=ySz5v/q/iruUKMIZjxKmVQ==, magXml=E/gVGOl356J3HDCn8PL/rg==, pdfUrl=null, pdf=XYCIZXEYOoIXh9431yn0hg==, pdfFileSize=807528, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=YkyWbINjWtoOKEJy8hAmPA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=IS4YYZOlHItyQnqhpS7/hQ==, mapNumber=null, authorCompany=null, fund=null, authors=

张洁（1997—），女，硕士在读，研究方向：流行病与卫生统计学

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张洁（1997—），女，硕士在读，研究方向：流行病与卫生统计学

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Impaired activity of daily living status of the older adults and its influencing factors: a Cross-Sectional study[J].International Journal of Environmental Research and Public Health,2022, 19(23): 15607., articleTitle=Impaired activity of daily living status of the older adults and its influencing factors: a Cross-Sectional study, refAbstract=null), Reference(id=1241023947576234375, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, doi=null, pmid=null, pmcid=null, year=2022, volume=99, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[15], rfOrder=17, authorNames=Huang XT, Zhang MQ, Fang JY, journalName=Archives of Gerontology and Geriatrics, refType=null, unstructuredReference=Huang XT, Zhang MQ, Fang JY. Growth patterns of activity of daily living disability and associated factors among the Chinese elderly: A twelve-year longitudinal study[J]. 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BMC Geriatrics,2024, 24(1): 659., articleTitle=Bidirectional, longitudinal associations between depressive symptoms and IADL/ADL disability in older adults in China: a National cohort study, refAbstract=null)], funds=[Fund(id=1241023945667825944, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, awardId=3502Z20234018, language=CN, fundingSource=厦门市医疗卫生重点项目(3502Z20234018), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241023937669288738, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, xref=1., ext=[AuthorCompanyExt(id=1241023937673483043, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, companyId=1241023937669288738, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Xiamen University, Xiamen, Fujian 361000, China), AuthorCompanyExt(id=1241023937686065956, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, companyId=1241023937669288738, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.厦门大学公共卫生学院，福建 厦门 361000)]), AuthorCompany(id=1241023937778340655, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, xref=2., ext=[AuthorCompanyExt(id=1241023937786729264, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, companyId=1241023937778340655, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.复旦大学附属中山医院厦门医院医务部，福建 厦门 361000)]), AuthorCompany(id=1241023937937724222, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, xref=3., ext=[AuthorCompanyExt(id=1241023937954501441, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, companyId=1241023937937724222, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.复旦大学附属中山医院心脏外科，上海 200000)])], figs=[ArticleFig(id=1241023942144610385, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Figure 1, caption=Flowchart of research subjects selection, figureFileSmall=JeZHUbtGBDA4+vhVUp39ow==, figureFileBig=YkyWbINjWtoOKEJy8hAmPA==, tableContent=null), ArticleFig(id=1241023942228496476, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=图1, caption=研究人群纳入排除标准, figureFileSmall=JeZHUbtGBDA4+vhVUp39ow==, figureFileBig=YkyWbINjWtoOKEJy8hAmPA==, tableContent=null), ArticleFig(id=1241023943486787701, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Figure 2, caption=Depressive symptoms trajectory, figureFileSmall=eMExXPBJcsu2g/GcSoOERA==, figureFileBig=WsR+mKkKVj6ed45UBBHWyw==, tableContent=null), ArticleFig(id=1241023943591645310, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=图2, caption=抑郁症状轨迹

注：周期1、2、3、4分别为2011—2012年、2013—2014年、2015—2017年、2018—2019年。

, figureFileSmall=eMExXPBJcsu2g/GcSoOERA==, figureFileBig=WsR+mKkKVj6ed45UBBHWyw==, tableContent=null), ArticleFig(id=1241023943688114314, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Figure 3, caption=Physical function disability trajectory, figureFileSmall=3oKw6KUM7cl+5mg8vVEKaQ==, figureFileBig=g7D6mX9OqlM6a98PJYa9vQ==, tableContent=null), ArticleFig(id=1241023943801360533, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=图3, caption=身体功能障碍轨迹

注：周期1、2、3、4分别为2011—2012年、2013—2014年、2015—2017年、2018—2019年。

, figureFileSmall=3oKw6KUM7cl+5mg8vVEKaQ==, figureFileBig=g7D6mX9OqlM6a98PJYa9vQ==, tableContent=null), ArticleFig(id=1241023943893635230, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Figure 4, caption=Dual trajectory model of depressive symptoms and physical function disability, figureFileSmall=zgeSxKc/7AFOrj1rny3RDA==, figureFileBig=63KY28HzFkz/6Zmjm2gdGg==, tableContent=null), ArticleFig(id=1241023944006881449, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=图4, caption=抑郁症状与身体障碍轨的双重轨迹模型

注：图A以抑郁轨迹为基础各身体功能障碍轨迹发生的条件概率;图B以身体功能障碍轨迹为基础各抑郁轨迹发生的条件概率;图C抑郁轨迹和身体功能轨迹的联合概率。

, figureFileSmall=zgeSxKc/7AFOrj1rny3RDA==, figureFileBig=63KY28HzFkz/6Zmjm2gdGg==, tableContent=null), ArticleFig(id=1241023944124321975, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Table 1, caption=

Basic characteristics of participants [（），n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总体男性女性P值
样本量5 0102 5092 501
年龄（岁）66.87±5.766.90±5.666.84±5.70.701
教育<0.001
文盲1 770(34.1)427(16.4)1 343(52.0)
小学2 442(47.1)1 484(57.0)958(37.1)
初中637(12.3)438(16.8)199(7.7)
高中及以上336(6.5)253(9.7)83(3,2)
居住地(农村)3 301(63.7)1 679(64.5)1 622(62.8)0.205
同居情况(独居)975(18.8)307(11.8)668(25.9)<0.001
饮酒2 089(40.5)1 664(64.2)425(16.5)<0.001
吸烟2 174(42.1)1 897(73.0)277(10.8)<0.001
高血压2 530(48.9)1 180(45.4)1350(52.5)<0.001
糖尿病712(13.8)338(13.0)374(14.5)0.128
心血管疾病906(17.7)431(16.7)475(18.6)0.083
认知障碍1 393(36.2)464(18.5%)522(20.8%)0.078
抑郁1 365(27.1)509(20.1)856(34.0)<0.001
身体功能障碍1 108(21.6)461(17.9)647(25.3)<0.001
), ArticleFig(id=1241023944212402364, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=表1, caption=

研究人群基线特征[（），n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总体男性女性P值
样本量5 0102 5092 501
年龄（岁）66.87±5.766.90±5.666.84±5.70.701
教育<0.001
文盲1 770(34.1)427(16.4)1 343(52.0)
小学2 442(47.1)1 484(57.0)958(37.1)
初中637(12.3)438(16.8)199(7.7)
高中及以上336(6.5)253(9.7)83(3,2)
居住地(农村)3 301(63.7)1 679(64.5)1 622(62.8)0.205
同居情况(独居)975(18.8)307(11.8)668(25.9)<0.001
饮酒2 089(40.5)1 664(64.2)425(16.5)<0.001
吸烟2 174(42.1)1 897(73.0)277(10.8)<0.001
高血压2 530(48.9)1 180(45.4)1350(52.5)<0.001
糖尿病712(13.8)338(13.0)374(14.5)0.128
心血管疾病906(17.7)431(16.7)475(18.6)0.083
认知障碍1 393(36.2)464(18.5%)522(20.8%)0.078
抑郁1 365(27.1)509(20.1)856(34.0)<0.001
身体功能障碍1 108(21.6)461(17.9)647(25.3)<0.001
), ArticleFig(id=1241023944346620100, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Table 2, caption=

Fit statistics of depression symptoms trajectory

, figureFileSmall=null, figureFileBig=null, tableContent=
分组组别AICBICAvePP
271.91/28.0959 024.459 063.70.95/0.90
354.55/35.35/10.0958 590.758 649.70.90/0.83/0.87
455.37/16.2/19.04/9.3958 463.858 542.50.91/0.70/0.72/0.86
536.64/33.82/10.83/11.98/6.7358 370.958 466.90.81/0.68/0.70/0.72/0.84
616.57/44.33/9.75/9.47/12.04/7.8458 272.358 390.20.73/0.76/0.69/0.71/0.71/0.85
), ArticleFig(id=1241023944631832785, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=表2, caption=

抑郁症状轨迹模型拟合指标

, figureFileSmall=null, figureFileBig=null, tableContent=
分组组别AICBICAvePP
271.91/28.0959 024.459 063.70.95/0.90
354.55/35.35/10.0958 590.758 649.70.90/0.83/0.87
455.37/16.2/19.04/9.3958 463.858 542.50.91/0.70/0.72/0.86
536.64/33.82/10.83/11.98/6.7358 370.958 466.90.81/0.68/0.70/0.72/0.84
616.57/44.33/9.75/9.47/12.04/7.8458 272.358 390.20.73/0.76/0.69/0.71/0.71/0.85
), ArticleFig(id=1241023944732496091, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Table 3, caption=

Maximum likelihood parameter estimates for trajectories　of depressive symptoms and physical functional disability

, figureFileSmall=null, figureFileBig=null, tableContent=
组别抑郁症状身体功能障碍
1截距4.03(0.81)***-2.69(0.07)***
线性1.92(1.23)
二次项-1.05(0.54)
立方项0.16(0.07)*
2截距28.25(2.40)***0.55(0.11)***
线性-19.47(3.55)***-0.32(0.05)***
二次项7.08(1.60)***
立方项-0.86(0.27)***
3截距15.60(2.12)***-0.30(0.86)
线性-10.40(3.26)**-3.10(1.21)*
二次项4.89(1.51)**1.86(0.50)***
立方项-0.57(0.20)**-0.26(0.06)***
4截距27.88(2.10)***0.62(0.05)***
线性-15.40(3.25)***0.15(0.02)***
二次项7.17(1.44)***
立方项-0.97(0.19)***
), ArticleFig(id=1241023944858325216, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=表3, caption=

抑郁症状和身体功能轨迹估计的极大似然参数估计

, figureFileSmall=null, figureFileBig=null, tableContent=
组别抑郁症状身体功能障碍
1截距4.03(0.81)***-2.69(0.07)***
线性1.92(1.23)
二次项-1.05(0.54)
立方项0.16(0.07)*
2截距28.25(2.40)***0.55(0.11)***
线性-19.47(3.55)***-0.32(0.05)***
二次项7.08(1.60)***
立方项-0.86(0.27)***
3截距15.60(2.12)***-0.30(0.86)
线性-10.40(3.26)**-3.10(1.21)*
二次项4.89(1.51)**1.86(0.50)***
立方项-0.57(0.20)**-0.26(0.06)***
4截距27.88(2.10)***0.62(0.05)***
线性-15.40(3.25)***0.15(0.02)***
二次项7.17(1.44)***
立方项-0.97(0.19)***
), ArticleFig(id=1241023944992542954, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Table 4, caption=

Fit statistics of physical functional disability trajectory

, figureFileSmall=null, figureFileBig=null, tableContent=
分组组别AICBICAvePP
274.48/25.5218428.918464.40.95/0.98
360.25/29.6/10.1617997.418052.60.92/0.85/0.89
459.42/15.22/15.81/17741178160.91/0.75/0.77/0.89
59.18/59.78/11.68/9.78/9.5717656.917751.60.68/0.92/0.73/0.73/0.88
62.02/41.46/28.38/11.51/10/6.6217652.417766.90.77/0.79/0.76/0.78/0.73/0.87
), ArticleFig(id=1241023945097400561, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=表4, caption=

身体功能障碍轨迹模型拟合指标

, figureFileSmall=null, figureFileBig=null, tableContent=
分组组别AICBICAvePP
274.48/25.5218428.918464.40.95/0.98
360.25/29.6/10.1617997.418052.60.92/0.85/0.89
459.42/15.22/15.81/17741178160.91/0.75/0.77/0.89
59.18/59.78/11.68/9.78/9.5717656.917751.60.68/0.92/0.73/0.73/0.88
62.02/41.46/28.38/11.51/10/6.6217652.417766.90.77/0.79/0.76/0.78/0.73/0.87
), ArticleFig(id=1241023945206452472, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Table 5, caption=

Logistic regression analysis of depressive symptoms trajectory categorization

, figureFileSmall=null, figureFileBig=null, tableContent=
变量抑郁症状下降组RRR (95%CI)抑郁症状增长组RRR (95%CI)持续高抑郁症状组RRR (95%CI)
年龄0.99(0.98~1.01)0.99(0.97~1.00)0.97(0.96~1.00)
性别(女)2.30(1.80~2.93)***2.10(1.68~2.62)***4.29(3.13~5.87)***
教育
文盲RefRefRef
小学0.75(0.27~2.09)1.53(0.48~4.91)1.35(0.21~8.65)
初中3.12(0.83~11.71)1.56(0.59~4.16)1.15(0.18~7.50)
高中及以上3.42(1.05~11.10)*1.87(0.84~4.17)2.61(0.60~11.27)
居住地(农村)1.38(1.14~1.66)***1.66(1.39~1.97)***1.96(1.54~2.49)***
同居情况(独居)1.67(1.35~2.06)***1.27(1.04~1.56)*1.75(1.35~2.25)***
饮酒1.00(0.82~1.22)0.93(0.77~1.12)1.04(0.81~1.34)
吸烟1.31(1.04~1.66)*1.37(1.11~1.69)**1.45(1.09~1.95)*
高血压0.98(0.82~1.17)0.98(0.84~1.15)1.13(0.91~1.41)
糖尿病1.12(0.87~1.44)1.30(1.04~1.62)*1.23(0.91~1.65)
心血管疾病1.18(0.93~1.48)1.29(1.05~1.59)*2.10(1.64~2.69)***
认知障碍1.42(1.19~1.70)***1.17(1.00~1.38)*1.40(1.13~1.74)***
), ArticleFig(id=1241023945302921472, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=表5, caption=

抑郁症状轨迹归属的logistic回归分析

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变量抑郁症状下降组RRR (95%CI)抑郁症状增长组RRR (95%CI)持续高抑郁症状组RRR (95%CI)
年龄0.99(0.98~1.01)0.99(0.97~1.00)0.97(0.96~1.00)
性别(女)2.30(1.80~2.93)***2.10(1.68~2.62)***4.29(3.13~5.87)***
教育
文盲RefRefRef
小学0.75(0.27~2.09)1.53(0.48~4.91)1.35(0.21~8.65)
初中3.12(0.83~11.71)1.56(0.59~4.16)1.15(0.18~7.50)
高中及以上3.42(1.05~11.10)*1.87(0.84~4.17)2.61(0.60~11.27)
居住地(农村)1.38(1.14~1.66)***1.66(1.39~1.97)***1.96(1.54~2.49)***
同居情况(独居)1.67(1.35~2.06)***1.27(1.04~1.56)*1.75(1.35~2.25)***
饮酒1.00(0.82~1.22)0.93(0.77~1.12)1.04(0.81~1.34)
吸烟1.31(1.04~1.66)*1.37(1.11~1.69)**1.45(1.09~1.95)*
高血压0.98(0.82~1.17)0.98(0.84~1.15)1.13(0.91~1.41)
糖尿病1.12(0.87~1.44)1.30(1.04~1.62)*1.23(0.91~1.65)
心血管疾病1.18(0.93~1.48)1.29(1.05~1.59)*2.10(1.64~2.69)***
认知障碍1.42(1.19~1.70)***1.17(1.00~1.38)*1.40(1.13~1.74)***
), ArticleFig(id=1241023945407779080, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=EN, label=Table 6, caption=

Logistic regression analysis of physical function disability trajectory categorization

, figureFileSmall=null, figureFileBig=null, tableContent=
变量身体功能障碍加重组RRR (95%CI)身体功能障碍缓解组RRR (95%CI))高身体功能障碍组RRR (95%CI)
年龄1.05(1.04~1.07)***1.05(1.03~1.06)***1.06(1.04~1.08)***
性别（女）1.51(1.21~1.88)***1.74(1.36~2.24)***1.43(1.05~1.95)***
教育
文盲RefRefRef
小学0.75(0.27~2.09)1.53(0.48~4.91)1.35(0.21~8.65)
初中1.55(0.75~3.21)2.21(0.86~5.65)3.59(0.84~15.34)
高中及以上3.12(0.83~11.71)1.56(0.59~4.16)1.15(0.18~7.50)
居住地（农村）1.27(1.07~1.52)**1.32(1.08~1.60)**1.17(0.93~1.47)
同居情况（独居）1.17(0.96~1.44)1.36(1.09~1.69)**1.40(1.09~1.81)**
饮酒0.96(0.80~1.16)1.06(0.86~1.31)0.97(0.76~1.25)
吸烟1.27(1.03~1.57)*1.30(1.03~1.66)*1.45(1.09~1.92)*
高血压1.13(0.96~1.33)1.20(1.00~1.44)1.43(1.15~1.78)**
糖尿病1.23(0.97~1.54)1.34(1.05~1.72)*1.49(1.12~1.99)**
心血管疾病1.57(1.28~1.93)***1.64(1.32~2.05)***1.67(1.29~2.16)***
认知障碍1.72(1.45~2.03)***1.45(1.20~1.74)***2.46(1.97~3.06)***
), ArticleFig(id=1241023945533608207, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023934057992782, language=CN, label=表6, caption=

身体功能障碍轨迹归属的logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量身体功能障碍加重组RRR (95%CI)身体功能障碍缓解组RRR (95%CI))高身体功能障碍组RRR (95%CI)
年龄1.05(1.04~1.07)***1.05(1.03~1.06)***1.06(1.04~1.08)***
性别（女）1.51(1.21~1.88)***1.74(1.36~2.24)***1.43(1.05~1.95)***
教育
文盲RefRefRef
小学0.75(0.27~2.09)1.53(0.48~4.91)1.35(0.21~8.65)
初中1.55(0.75~3.21)2.21(0.86~5.65)3.59(0.84~15.34)
高中及以上3.12(0.83~11.71)1.56(0.59~4.16)1.15(0.18~7.50)
居住地（农村）1.27(1.07~1.52)**1.32(1.08~1.60)**1.17(0.93~1.47)
同居情况（独居）1.17(0.96~1.44)1.36(1.09~1.69)**1.40(1.09~1.81)**
饮酒0.96(0.80~1.16)1.06(0.86~1.31)0.97(0.76~1.25)
吸烟1.27(1.03~1.57)*1.30(1.03~1.66)*1.45(1.09~1.92)*
高血压1.13(0.96~1.33)1.20(1.00~1.44)1.43(1.15~1.78)**
糖尿病1.23(0.97~1.54)1.34(1.05~1.72)*1.49(1.12~1.99)**
心血管疾病1.57(1.28~1.93)***1.64(1.32~2.05)***1.67(1.29~2.16)***
认知障碍1.72(1.45~2.03)***1.45(1.20~1.74)***2.46(1.97~3.06)***
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基于双轨迹模型的老年人抑郁症状与身体功能障碍的关联性研究
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张洁 1 , 李佳男 1 , 黄妤洁 2 , 徐德民 2, 3
现代预防医学 | 健康与社会行为 2025,52(3): 513-519
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现代预防医学 | 健康与社会行为 2025, 52(3): 513-519
基于双轨迹模型的老年人抑郁症状与身体功能障碍的关联性研究
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张洁1, 李佳男1, 黄妤洁2, 徐德民2, 3
作者信息
  • 1.厦门大学公共卫生学院，福建 厦门 361000
  • 2.复旦大学附属中山医院厦门医院医务部，福建 厦门 361000
  • 3.复旦大学附属中山医院心脏外科，上海 200000

    • 张洁（1997—），女，硕士在读，研究方向：流行病与卫生统计学

通讯作者:

徐德民，E-mail:
A study on the correlation between depression symptoms and physical functional impairment in the elderly based on a dual trajectory model
Jie ZHANG1, Jia-nan LI1, Yu-jie HUANG2, De-min XU2, 3
Affiliations
  • School of Public Health, Xiamen University, Xiamen, Fujian 361000, China
出版时间: 2025-02-10 doi: 10.20043/j.cnki.MPM.202407423
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摘要
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目的

探索中国老年人抑郁症状和身体功能障碍发展轨迹间的双向关系。

方法

使用2011、2013、2015和2018年中国健康与养老追踪调查(CHARLS)的4轮数据，利用组基轨迹模型识别老年人抑郁症状和身体功能障碍不同轨迹组，并利用双轨迹模型评估抑郁症状和身体功能障碍轨迹组关联程度。

结果

组基轨迹模型将抑郁症状分为持续低抑郁症状组、抑郁症状下降组、抑郁症状上升组、持续高抑郁症状组。身体功能障碍分为无身体功能障碍组、身体功能障碍加重组、身体功能障碍缓解组和高身体功能障碍组。双轨迹分析表明抑郁症状下降组中，44.86%的人遵循身体功能障碍缓解轨迹；抑郁症状上升组中，37.58%的人遵循身体功能障碍加重轨迹。身体功能障碍加重组中，47.8%的人遵循抑郁症状上升轨迹；身体功能障碍缓解组中，41.9%的人遵循抑郁症状下降。

结论

在大多数情况下，抑郁症状和身体功能障碍轨迹是正相关的，抑郁症状下降通常伴随身体功能障碍缓解，抑郁症状上升伴随身体功能障碍加重。反之亦然。

抑郁症状  /  身体功能障碍  /  老年人  /  双轨迹模型
Objective

To explore the bidirectional relationship between depression symptoms and physical functional impairment trajectories in Chinese elderly individuals.

Methods

Utilizing data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, and 2018, we employed group-based trajectory modeling to identify distinct trajectory groups for depression symptoms and physical functional impairment among the elderly. A dual trajectory model was then used to assess the degree of association between these trajectory groups.

Results

The group-based trajectory model categorized depression symptoms into four groups: consistently low depression symptoms, decreasing depression symptoms, increasing depression symptoms, and consistently high depression symptoms. Physical functional impairment was classified into four groups: no physical functional impairment, worsening physical functional impairment, improving physical functional impairment, and high physical functional impairment. Dual trajectory analysis revealed that 44.86% of individuals in the decreasing depression symptoms group followed the improving physical functional impairment trajectory; conversely, 37.58% of individuals in the increasing depression symptoms group followed the worsening physical functional impairment trajectory. Among those in the worsening physical functional impairment group, 47.8% followed the increasing depression symptoms trajectory, while 41.9% of individuals in the improving physical functional impairment group followed the decreasing depression symptoms trajectory.

Conclusion

In most cases, there is a positive correlation between the trajectories of depression symptoms and physical functional impairment. A decrease in depression symptoms is typically associated with an improvement in physical functional impairment, while an increase in depression symptoms corresponds with a worsening of physical functional impairment, and vice versa.

Depression symptoms  /  Physical functional impairment  /  Elderly  /  Dual trajectory model
张洁, 李佳男, 黄妤洁, 徐德民. 基于双轨迹模型的老年人抑郁症状与身体功能障碍的关联性研究. 现代预防医学, 2025 , 52 (3) : 513 -519 . DOI: 10.20043/j.cnki.MPM.202407423
Jie ZHANG, Jia-nan LI, Yu-jie HUANG, De-min XU. A study on the correlation between depression symptoms and physical functional impairment in the elderly based on a dual trajectory model[J]. Modern Preventive Medicine, 2025 , 52 (3) : 513 -519 . DOI: 10.20043/j.cnki.MPM.202407423
正文
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人口老龄化是21世纪人类发展的主要特征，也是全球性的社会挑战之一。截至2021年年末，中国已迈入中度老龄化社会。同时我国快速老龄化的进程还在进一步加深，预计到2052年左右，我国老年人口将达到峰值5.24亿人[1]。抑郁症是一种常见的精神疾病，1990—2019年中国老年人抑郁症发病率和伤残调整生命年呈显著上升趋势[2]。抑郁症状，在一生中的过程因个体而异，但多数研究通常将抑郁症被归类为存在或不存在，这不利于识别亚临床水平[3]。随着人口老龄化的加速和预期寿命的延长，身体功能障碍对全球卫生和社会护理系统构成了重大挑战[4]。研究发现，尽管中国老年人近十年来失能率持续下降并且这种下降趋势仍将继续，然而，由于未来老年人口基数迅速增加，2030年中国老年人需要护理的失能人数将会比2020年增加1 402万[5]。以往大多数纵向研究通常使用线性混合模型，该模型允许基线水平和时间趋势因个体而异，但无法识别某些个体群体的不同发展轨迹。组基轨迹模型(group-based trajectory model, GBTM)可以有效解决这一问题。它是一种有限混合建模技术，可以识别研究人群中具有不同发展轨迹的亚组。
抑郁与身体功能障碍的关系长期以来都是流行病学领域的研究热点，先前的研究发现日常生活活动能力(activities of daily living, ADL)与抑郁症状之间显著相关。然而，大部分探索抑郁症状和ADL残疾之间的双向关系的研究通常仅关注单一时间点或单一发展轨迹。本文旨在利用双轨迹模型(group-based dual trajectory model, GBDTM)在具有全国代表性的老年人样本中确定抑郁症状和身体功能障碍的变化模式以及这些轨迹之间的相互关系，为提高老年人的生活质量提供依据。
1　对象与方法
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1.1　资料来源
本文数据来源于北京大学中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS)全国样本数据。CHARLS全国性基线调查开始于2011年，以全国45周岁以上人群作为基准，采用PPS抽样方法，样本每两到三年追踪一次。本研究纳入基线年龄≥60岁(n=7 290)的参与者。由于构建GBTM需要每个研究对象有3次及以上的数据，所以本研究排除了抑郁症状测量及身体功能障碍测量少于3次的参与者。最终，本研究纳入了5 185名随访者。研究对象筛选流程见图1。
1.2　研究变量
抑郁症是一种常见的精神疾病，在本研究中由流行病学研究中心抑郁量表（Center for Epidemiologic Studies Depression Scale，CES-D 10）评估。总分范围0 ~ 30分，分数越高表示抑郁症状水平越高。身体功能障碍由ADL量表进行评估，总分范围0 ~ 6分，分数越高表示身体功能障碍越严重。协变量包括年龄、性别、受教育程度、吸烟、饮酒、高血压、糖尿病、心血管疾病和认知障碍。
1.3　统计分析
使用GBTM探索抑郁症状轨迹和身体功能障碍轨迹，根据贝叶斯信息准则(BIC)，赤池信息准则(AIC)以及平均后验概率(average of posterior probability, AvePP)等诊断统计数据选择最佳拟合模型。使用无序多分类logistic回归，探讨人口学与临床特征对抑郁症状轨迹、身体功能障碍轨迹类别归属的影响。GBDTM是对GBTM的扩展，通过对两个不同但相关的变量轨迹间的条件概率和联合概率进行估计，识别变量之间的纵向关系，例如心理变化和行为变化的关系、生理变化和社会变化的关系等。拟合步骤如下，首先对单变量的最佳GBTM进行分别估计：第一步通过极大似然估计确定最佳模型轨迹的数量；第二步调整最佳组数中各轨迹的多项式阶数，确定各轨迹的形状。其次，利用最终单变量模型的初始参数，对抑郁症状和身体功能障碍的双轨迹模型进行估计[6]。轨迹模型采用STATA 17 traj插件实现，其它统计分析由R 4.3.2完成，检验水准α=0.05。
2　结果
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2.1　研究人群基线特征
研究人群基线特征如表1所示，研究纳入5 010名60岁及以上的老年人，平均年龄为（66.82±5.7）岁，女性占比达49.8%，27.1%的研究对象患有抑郁，21.6%存在身体功能障碍，63.7%居住在农村，18.8%为独居老人。其中女性患抑郁、存在身体功能障碍、文盲、独居、患高血压的比例均高于男性。
2.2　抑郁症状轨迹和身体功能障碍轨迹
拟合轨迹过程的参数如表2所示，随着轨迹组数的递增，抑郁症状BIC的绝对值逐渐减少，但5、6组轨迹的拟合模型均存在AvePP <0.7。最终，确定了4组抑郁水平发展轨迹，各轨迹形状的估计参数如表3所示，根据最大似然估计参数确定各轨迹形状都遵循立方项。
老年人最佳抑郁轨迹分组和轨迹形态如图2所示，根据抑郁症状发展趋势，将各轨迹定义为持续低抑郁症状组(n=3 721)、抑郁症状下降组(n=719)、抑郁症状上升组(n=897)、持续高抑郁症状组(n=478)。
根据表3和表4的拟合参数，本研究确定了4组身体功能障碍发展轨迹，各身体功能障碍轨迹多项式阶数分别为0,1,3,1。
如图3所示，根据身体功能障碍发展趋势，将各轨迹定义为无身体功能障碍组(n=3 270)、身体功能障碍加重组(n=824)、身体功能障碍缓解组(n=640)、高身体功能障碍组(n=451)。
2.3　抑郁轨迹和身体功能障碍轨迹归属的影响因素
2.3.1　抑郁轨迹归属的影响因素
以持续低抑郁症状轨迹组作为参照组，抑郁轨迹归属影响因素的logistic回归分析的结果如表5所示。分析结果表明，年龄与抑郁轨迹归属无关。相对于持续低抑郁症状组，女性、居住在农村、独居、吸烟、基线患有认知障碍的老年人更有可能归属于抑郁症状下降组、抑郁症状增长组及持续高抑郁症状组。受教育程度为高中及以上的老年人属于抑郁症状下降组的可能性更高。患糖尿病、心血管疾病的老年人更有可能归属于抑郁症状增长组。
2.3.2　身体功能障碍轨迹归属的影响因素
如表6所示，与无身体功能障碍组相比，年龄大、女性、居住在农村、吸烟、基线患有心血管疾病和认知障碍的老年人归属于身体功能障碍加重组、身体功能障碍缓解组或高身体功能障碍组的可能性增加。独居、患糖尿病的老年人更可能归属于身体功能障碍缓解组或高身体功能障碍组。高血压患者归属于高身体功能障碍组可能性更高。
2.4　抑郁症状和身体功能障碍的双轨迹模型
使用双轨迹模型拟合抑郁症状和身体功能障碍轨迹，二者间的连接条件概率如图4所示。持续低抑郁症状组老年人中，超过4/5的参与者遵循无身体障碍轨迹；抑郁症状下降组中，44.86%的人遵循身体功能障碍缓解轨迹，只有6.56%的人遵循身体功能障碍加重轨迹；抑郁症状上升组中，超过1/3的人遵循身体功能障碍加重轨迹，13.9%的人遵循身体功能障碍缓解轨迹；遵循持续高抑郁症状组的老年人中，近2/5归属于高身体功能障碍轨迹。
如图4B所示，在无身体功能障碍组的老年人中，超过2/3的参与者遵循持续低抑郁症状轨迹；身体功能障碍加重组中，近1/2的人遵循抑郁症状上升轨迹；身体功能障碍缓解组中，41.9%的参与者遵循抑郁症状下降轨迹；高身体功能障碍组通常伴随持续高抑郁症状轨迹（40.1%）。
抑郁轨迹和身体功能障碍轨迹联合概率如图4C所示，42.9%的老年人遵循持续低抑郁症状和无身体功能障碍轨迹；7.8%的老年人遵循抑郁症状下降和身体功能障碍缓解轨迹；7.2%的老年人遵循抑郁症状上升和身体功能障碍加重的轨迹；4.1%的老年人遵循持续高抑郁症状轨迹和高身体功能障碍轨迹。
3　讨论
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本研究揭示了老年人抑郁症状和身体功能障碍的动态发展轨迹，确定了与各自轨迹相关的人口学和临床特征，发现老年人抑郁症状轨迹和身体功能障碍轨迹之间的存在正向相关关系。
本研究发现中国老年人群中存在4条抑郁症状发展轨迹，与Fan等人[7]在中国中老年人中研究结果一致，并且Fan等人的研究发现中老年人的身体功能障碍与抑郁症状发展轨迹相关。与此同时，本研究进一步分析了影抑郁症状发展轨迹的因素，发现女性、居住在农村、独居是抑郁症状的危险因素，与现有研究一致[8]。其原因可能与女性的生理和心理特征有关，女性在生理上经历更年期，容易产生烦躁、焦虑等情绪；在心理上容易受外部环境影响导致情绪波动，从而引发抑郁症状[9]。独居使老年人失去重要的社会支持来源增加了患抑郁的风险，居住在农村使其享受的医疗资源配置低于城市，导致抑郁症状的发现和治疗不及时[10-11]。吸烟也是抑郁的危险因素，Kunugi[12]认为吸烟与抑郁症之间存在双向关联：吸烟会增加抑郁症的风险，而患抑郁症又会促进吸烟行为。此外，患有心血管疾病和认知障碍也是抑郁的危险因素，这可能与疾病本身带来的身体不适、功能受限以及对未来健康的担忧相关。发现不同轨迹亚组的趋势和特征，有利于及时采取相应干预措施，改善老年人的心理健康。
在Pan等人[13]的研究中，65周岁及以上的老年人存在三种ADL障碍轨迹，存在心理健康问题的老年人更有可能属于高残疾组。本研究发现老年人中存在4条身体功能障碍发展轨迹，与先前研究结果略有差异，可能是由于研究人群、研究时期和时间跨度的不同，Pan等人使用了中国纵向健康长寿调查2005—2018年5个周期的数据，而本研究使用CHARLS 2011—2018年4个周期的数据。与先前研究一致，我们发现年龄、女性、独居、慢性病是身体功能障碍的危险因素[13-14]。农村地区的医疗资源和健康服务相对不足，较难获得及时的医疗护理和康复支持，使老年人面临更高身体功能障碍风险。本研究还发现吸烟与老年人身体功能障碍相关，因此，改变不良生活方式对促进积极老龄化有重要意义。此外，认知障碍与更严重的身体功能障碍有关，认知受损会影响老年人的记忆、判断、决策和执行能力，损害他们的身体功能[15]。因此，识别老年人身体功能发展的异质性轨迹及其影响因素，对减轻公共卫生负担具有重要意义。
本研究表明抑郁症状和身体功能障碍的轨迹高度相关，多数情况下，两组轨迹存在正相关性，例如抑郁症状下降组中超过2/5的参与者遵循身体功能障碍缓解组，远高于遵循身体功能障碍加重组的参与者，抑郁症状增加组中超过1/3的参与者遵循身体功能障碍加重组。Wang等人[16]使用交叉滞后模型发现，在中国中老年人群中，ADL失能与抑郁症状之间存在显著的相互关系和纵向关系。Zhu等人[17]采用广义估计方程模型的研究结果显示，CESD-10评分在各波之间的变化与ADL残疾恶化程度相关，反之亦然。虽然上述研究充分利用了长期队列，但对统计结果的解释是，其大小同样适用于研究人群中的所有个体，忽略了变量内部的异质性，本研究使用GBDTM可以有效弥补上述不足。然而，持续高抑郁症状组中，近1/3属于身体功能障碍缓解组；高身体功能障碍组中，近1/3属于抑郁症状下降组。持续高抑郁症状组与身体功能障碍缓解组，高身体功能障碍组与抑郁症状下降组之间存在重叠的机制尚不清楚。一个可能的解释是回答误差，高身体功能障碍组和持续高抑郁症状组的人更有可能患有认知障碍从而导致偏倚。本研究结果表明，老年人抑郁症状和身体功能障碍发展轨迹存在异质性，两者间往往相互促进，采取综合干预措施，如心理治疗结合身体康复训练，能更有效地打破抑郁症状与身体功能障碍之间的恶性循环。
本研究也存在局限性，一是，抑郁症状和身体功能障碍的评估依赖于自我报告量表，可能导致信息偏倚。二是，尽管抑郁症状和身体功能障碍随时间变化相互影响，但两者之间的相关性并不具有因果性。此外，由于建模收敛限制，我们无法识别与双轨迹相关的人口学和临床特征。未来的研究应尝试将人口学和临床特征纳入双轨迹模型，进一步深入了解老年人抑郁症状和身体功能障碍的发展如何随着时间的推移而相互关联。
基金
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  • 厦门市医疗卫生重点项目(3502Z20234018)
文献
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doi: 10.20043/j.cnki.MPM.202407423
  • 接收时间：2024-07-23
  • 首发时间：2026-03-18
  • 出版时间：2025-02-10
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  • 收稿日期：2024-07-23
基金
厦门市医疗卫生重点项目(3502Z20234018)
作者信息
    1.厦门大学公共卫生学院，福建 厦门 361000
    2.复旦大学附属中山医院厦门医院医务部，福建 厦门 361000
    3.复旦大学附属中山医院心脏外科，上海 200000

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徐德民，E-mail:
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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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