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Article(id=1324078066233913515, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078037817504735, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202507410, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1753286400000, receivedDateStr=2025-07-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614411171, onlineDateStr=2026-11-02, pubDate=1770652800000, pubDateStr=2026-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614411171, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614411171, creator=13701087609, updateTime=1793614411171, updator=13701087609, issue=Issue{id=1324078037817504735, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='3', pageStart='385', pageEnd='576', issueExtLink='null', onlineDate='null', pubDate='1770652800000', pubDateStr='2026-02-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614404396, creator='13701087609', updateTime=1793614474144, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078330420527919, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078037817504735, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078330420527920, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078037817504735, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=498, endPage=501, ext={EN=ArticleExt(id=1324078066477183148, articleId=1324078066233913515, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Correlation between social relationships and the risk of death among Chinese older adults, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

This study aims to explore the association between social relationships and the risk of death among older adults in China.

Methods

The research subjects were 5 642 older people aged 65 and above who participated in the China Longitudinal Healthy Longevity Survey from 2011 to 2018. Social relationships were defined using the social relations model and its subdimensions: social activities, social networks, and social support. The Cox proportional hazards regression model was used to estimate the association between social relationships and the risk of death among older adults.

Results

Compared with a medium-level social relationship, a high-level social relationships (HR: 0.73, 95% CI: 0.64-0.84) was inversely associated with the risk of death among older adults in China. Compared with moderate levels of social activities and social support, high-level social activities (HR: 0.64, 95% CI: 0.40-0.96) and high-level social support (HR: 0.91, 95% CI: 0.74-0.98) were inversely associated with the risk of death among older adults in China, but the relationship between social networks and the risk of death among older adults in China was not significant.

Conclusion

A high level of social relationships is significantly inversely associated with the risk of death among older adults in China. Policy interventions should create and promote social activity platforms suitable for the elderly, and support and consolidate family-based social support systems.

, authors=Pan KE1, Zu-xun LU1, Xiao-xu YIN1, Zhi-guang ZHAO2, authorsList=Pan KE, Zu-xun LU, Xiao-xu YIN, Zhi-guang ZHAO, authorCompany=null, correspAuthors=Zhi-guang ZHAO, 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=1324078069107011763, articleId=1324078066233913515, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=社会关系与中国老年人死亡风险的关联性研究, columnId=1228016572640461823, journalTitle=现代预防医学, columnName=健康与社会行为, runingTitle=null, highlight=null, articleAbstract=
目的

本研究旨在探讨社会关系与中国老年人死亡风险的关联。

方法

研究对象来自5 642名2011—2018年中国老年健康影响因素跟踪调查数据的65岁及以上老年人。社会关系运用社会关系模型及其子维度社会活动、社会网络和社会支持定义。采用Cox比例风险回归模型计算社会关系与老年人死亡风险之间的关系。

结果

与中等水平的社会关系相比，高水平社会关系（HR=0.73, 95% CI: 0.64～0.84）与中国老年人的死亡风险呈负相关。与中等水平的社会活动和社会支持相比，高水平社会活动（HR=0.64, 95% CI: 0.40～0.96）和高水平社会支持（HR=0.91, 95% CI: 0.74～0.98）与中国老年人的死亡风险呈负相关，但社会网络与中国老年人的死亡风险关系不显著。

结论

高水平的社会关系与中国老年人的死亡风险呈负相关。政策干预应创造和推广适合老年人的社会活动平台，支持和巩固以家庭为基础的社会支持系统。

, authors=柯攀1, 卢祖洵1, 殷晓旭1, 赵志广2, authorsList=柯攀, 卢祖洵, 殷晓旭, 赵志广, authorCompany=null, correspAuthors=赵志广, authorNote=

柯攀（1992—），男，博士，无职称，研究方向：健康的社会决定因素

, correspAuthorsNote=
赵志广，E-mail:
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(In Chinese), articleTitle=The impact of widowhood on the mental health of older adults in China: analysis based on the perspective of mental frailty index, refAbstract=null)], funds=[Fund(id=1324078073833992413, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, awardId=18ZDA085, language=CN, fundingSource=国家社会科学基金重大项目(18ZDA085), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324078069379641524, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, xref=1., ext=[AuthorCompanyExt(id=1324078069392224437, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, companyId=1324078069379641524, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430040, China), AuthorCompanyExt(id=1324078069404807350, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, companyId=1324078069379641524, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.华中科技大学同济医学院公共卫生学院社会医学与卫生事业管理系，湖北 武汉 430040)]), AuthorCompany(id=1324078069522247863, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, xref=2., ext=[AuthorCompanyExt(id=1324078069530636472, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, companyId=1324078069522247863, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.深圳市慢性病防治中心心脑血管疾病与糖尿病防控科，广东 深圳 518020)])], figs=[ArticleFig(id=1324078071497765077, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, language=EN, label=Table 1, caption=

Baseline characteristics of the participants ［n（%），（）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量社会关系
低水平中水平高水平χ2/F值P值
参与者1 902(33.7)2 837 (50.3)903(16.0)
死亡数1 256(66.0)1 531(54.0)238(31.3)197.611<0.001
男性747(39.3)1 327(46.8)561(62.1)128.469<0.001
年龄（岁）87.58±10.6884.21±10.8977.81±9.26261.883<0.001
受教育年限 （年）1.80±3.232.16±3.403.69±3.8697.6510.216
居住在农村957(50.3)1 656(58.4)536(59.4)35.440<0.001
家庭年收入（元）51.482<0.001
<10 000803(42.2)1 209(42.6)311(34.4)
10 001~29 999533(28.0)771(27.2)274(30.3)
≥30 000370(19.5)634(22.3)260(28.8)
缺失值196(10.3)223(7.9)58(6.4)
BMI（kg/m2）22.90±44.9021.46±5.0823.11±17.262.1720.114
收缩压（mm Hg）137.80±23.77137.19±21.50136.20±19.541.6070.201
舒张压（mm Hg）80.40±15.0780.74±13.7480.92±11.760.5180.596
吸烟313(16.5)531(18.7)250(27.7)65.508<0.001
饮酒280(14.7)539(19.0)537(59.5)50.129<0.001
运动613(32.2)939(33.1)400(44.3)78.548<0.001
合并高血压523(27.5)843(29.7)271(30.0)2.0550.358
合并糖尿病71(3.7)117(4.1)41(4.5)0.8100.667
合并心血管疾病237(12.5)341(12.0)89(9.9)5.1900.075
合并中风128(6.7)195(6.8)58(6.4)0.2550.880
合并癌症18(9.4)20(7.0)12(1.3)3.0680.216
社会活动评分0.12±0.350.34±0.591.15±0.91961.442<0.001
社会网络评分1.01±0.701.60±0.722.47±0.821 243.216<0.001
社会支持评分4.26±1.045.49±0.735.79±0.501 621.046<0.001
), ArticleFig(id=1324078073146126550, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, language=CN, label=表1, caption=

研究对象的基线特征 ［n（%），（）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量社会关系
低水平中水平高水平χ2/F值P值
参与者1 902(33.7)2 837 (50.3)903(16.0)
死亡数1 256(66.0)1 531(54.0)238(31.3)197.611<0.001
男性747(39.3)1 327(46.8)561(62.1)128.469<0.001
年龄（岁）87.58±10.6884.21±10.8977.81±9.26261.883<0.001
受教育年限 （年）1.80±3.232.16±3.403.69±3.8697.6510.216
居住在农村957(50.3)1 656(58.4)536(59.4)35.440<0.001
家庭年收入（元）51.482<0.001
<10 000803(42.2)1 209(42.6)311(34.4)
10 001~29 999533(28.0)771(27.2)274(30.3)
≥30 000370(19.5)634(22.3)260(28.8)
缺失值196(10.3)223(7.9)58(6.4)
BMI（kg/m2）22.90±44.9021.46±5.0823.11±17.262.1720.114
收缩压（mm Hg）137.80±23.77137.19±21.50136.20±19.541.6070.201
舒张压（mm Hg）80.40±15.0780.74±13.7480.92±11.760.5180.596
吸烟313(16.5)531(18.7)250(27.7)65.508<0.001
饮酒280(14.7)539(19.0)537(59.5)50.129<0.001
运动613(32.2)939(33.1)400(44.3)78.548<0.001
合并高血压523(27.5)843(29.7)271(30.0)2.0550.358
合并糖尿病71(3.7)117(4.1)41(4.5)0.8100.667
合并心血管疾病237(12.5)341(12.0)89(9.9)5.1900.075
合并中风128(6.7)195(6.8)58(6.4)0.2550.880
合并癌症18(9.4)20(7.0)12(1.3)3.0680.216
社会活动评分0.12±0.350.34±0.591.15±0.91961.442<0.001
社会网络评分1.01±0.701.60±0.722.47±0.821 243.216<0.001
社会支持评分4.26±1.045.49±0.735.79±0.501 621.046<0.001
), ArticleFig(id=1324078073230012631, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, language=EN, label=Table 2, caption=

The association between social relationships and the risk of death among older adults in China ［HR（95% CI）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量模型1模型2
社会关系
中水平参照组参照组
低水平1.38(1.28~1.49)1.11(1.02~1.20)
高水平0.49(0.43~0.56)0.73(0.64~0.84)
P值<0.001<0.001
社会活动
中水平参照组参照组
低水平1.96(1.64~2.34)1.35(1.12~1.63)
高水平0.62(0.40~0.98)0.64(0.40~0.96)
P值<0.001<0.001
社会网络
中水平参照组参照组
低水平1.26(1.17~1.36)1.08(0.92~1.17)
高水平0.54(0.47~0.62)0.86(0.74~1.01)
P值<0.0010.882
社会支持
中水平参照组参照组
低水平1.51(1.13~2.01)1.49 (1.10~2.06)
高水平0.80(0.66~0.97)0.91(0.74~0.98)
P值<0.001<0.001
), ArticleFig(id=1324078073343258840, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, language=CN, label=表2, caption=

社会关系与中国老年人死亡风险的关联［HR（95% CI）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量模型1模型2
社会关系
中水平参照组参照组
低水平1.38(1.28~1.49)1.11(1.02~1.20)
高水平0.49(0.43~0.56)0.73(0.64~0.84)
P值<0.001<0.001
社会活动
中水平参照组参照组
低水平1.96(1.64~2.34)1.35(1.12~1.63)
高水平0.62(0.40~0.98)0.64(0.40~0.96)
P值<0.001<0.001
社会网络
中水平参照组参照组
低水平1.26(1.17~1.36)1.08(0.92~1.17)
高水平0.54(0.47~0.62)0.86(0.74~1.01)
P值<0.0010.882
社会支持
中水平参照组参照组
低水平1.51(1.13~2.01)1.49 (1.10~2.06)
高水平0.80(0.66~0.97)0.91(0.74~0.98)
P值<0.001<0.001
), ArticleFig(id=1324078073422950617, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, language=EN, label=Table 3, caption=

Subgroup analysis of the association between social relationships and the risk of death among older adults in China［HR（95% CI）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量中水平低水平高水平P值（交互效应）
性别0.430
男性参考组1.05(0.92~1.20)0.80(0.67~0.95)
女性参考组1.14(1.02~1.27)0.69(0.54~0.88)
年龄（岁）0.289
65~79参考组1.27(1.03~1.55)0.88(0.70~1.10)
≥80参考组1.17(1.09~1.27)0.71(0.60~0.83)
受教育年限（年）0.095
0参考组1.21(1.11~1.31)0.76(0.64~0.91)
1~6参考组1.18(1.04~1.35)0.70(0.50~1.10)
>6参考组1.04(0.80~1.36)0.68(0.56~0.83)
家庭年收入（元）0.492
<10 000参考组1.14(1.03~1.30)0.84(0.66~1.05)
10 001~29 999参考组1.06(0.90~1.25)0.83(0.64~1.08)
≥30 000参考组1.11(0.93~1.33)0.67(0.51~0.89)
), ArticleFig(id=1324078073511031002, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, language=CN, label=表3, caption=

社会关系与中国老年人死亡风险关联的亚组分析［HR（95% CI）］

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变量中水平低水平高水平P值（交互效应）
性别0.430
男性参考组1.05(0.92~1.20)0.80(0.67~0.95)
女性参考组1.14(1.02~1.27)0.69(0.54~0.88)
年龄（岁）0.289
65~79参考组1.27(1.03~1.55)0.88(0.70~1.10)
≥80参考组1.17(1.09~1.27)0.71(0.60~0.83)
受教育年限（年）0.095
0参考组1.21(1.11~1.31)0.76(0.64~0.91)
1~6参考组1.18(1.04~1.35)0.70(0.50~1.10)
>6参考组1.04(0.80~1.36)0.68(0.56~0.83)
家庭年收入（元）0.492
<10 000参考组1.14(1.03~1.30)0.84(0.66~1.05)
10 001~29 999参考组1.06(0.90~1.25)0.83(0.64~1.08)
≥30 000参考组1.11(0.93~1.33)0.67(0.51~0.89)
), ArticleFig(id=1324078073594917083, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, language=EN, label=Table 4, caption=

Sensitivity analysis of the association between social relationships and the risk of death among older adults in China［HR（95% CI）］

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敏感性分析方法中水平低水平高水平
排除参与者在随访
前二年内死亡事件		参考组1.09(1.03~1.22)0.78(0.66~0.92)
), ArticleFig(id=1324078073666220252, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078066233913515, language=CN, label=表4, caption=

社会关系与老年人死亡风险关联的敏感性分析［HR（95% CI）］

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敏感性分析方法中水平低水平高水平
排除参与者在随访
前二年内死亡事件		参考组1.09(1.03~1.22)0.78(0.66~0.92)
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社会关系与中国老年人死亡风险的关联性研究
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柯攀 1 , 卢祖洵 1 , 殷晓旭 1 , 赵志广 2
现代预防医学 | 健康与社会行为 2026,53(3): 498-501
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现代预防医学 |健康与社会行为 2026 , 53 (3) : 498 -501
社会关系与中国老年人死亡风险的关联性研究
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柯攀1, 卢祖洵1, 殷晓旭1, 赵志广2
作者信息
  • 1.华中科技大学同济医学院公共卫生学院社会医学与卫生事业管理系，湖北 武汉 430040
  • 2.深圳市慢性病防治中心心脑血管疾病与糖尿病防控科，广东 深圳 518020
通讯作者:
赵志广，E-mail:
作者简介:

柯攀（1992—），男，博士，无职称，研究方向：健康的社会决定因素

Correlation between social relationships and the risk of death among Chinese older adults
Pan KE1, Zu-xun LU1, Xiao-xu YIN1, Zhi-guang ZHAO2
Affiliations
  • Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430040, China
出版时间: 2026-02-10 doi: 10.20043/j.cnki.MPM.202507410
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摘要
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目的

本研究旨在探讨社会关系与中国老年人死亡风险的关联。

方法

研究对象来自5 642名2011—2018年中国老年健康影响因素跟踪调查数据的65岁及以上老年人。社会关系运用社会关系模型及其子维度社会活动、社会网络和社会支持定义。采用Cox比例风险回归模型计算社会关系与老年人死亡风险之间的关系。

结果

与中等水平的社会关系相比，高水平社会关系（HR=0.73, 95% CI: 0.64～0.84）与中国老年人的死亡风险呈负相关。与中等水平的社会活动和社会支持相比，高水平社会活动（HR=0.64, 95% CI: 0.40～0.96）和高水平社会支持（HR=0.91, 95% CI: 0.74～0.98）与中国老年人的死亡风险呈负相关，但社会网络与中国老年人的死亡风险关系不显著。

结论

高水平的社会关系与中国老年人的死亡风险呈负相关。政策干预应创造和推广适合老年人的社会活动平台，支持和巩固以家庭为基础的社会支持系统。

社会关系  /  老年人  /  死亡率  /  中国健康与寿命纵向调查
Objective

This study aims to explore the association between social relationships and the risk of death among older adults in China.

Methods

The research subjects were 5 642 older people aged 65 and above who participated in the China Longitudinal Healthy Longevity Survey from 2011 to 2018. Social relationships were defined using the social relations model and its subdimensions: social activities, social networks, and social support. The Cox proportional hazards regression model was used to estimate the association between social relationships and the risk of death among older adults.

Results

Compared with a medium-level social relationship, a high-level social relationships (HR: 0.73, 95% CI: 0.64-0.84) was inversely associated with the risk of death among older adults in China. Compared with moderate levels of social activities and social support, high-level social activities (HR: 0.64, 95% CI: 0.40-0.96) and high-level social support (HR: 0.91, 95% CI: 0.74-0.98) were inversely associated with the risk of death among older adults in China, but the relationship between social networks and the risk of death among older adults in China was not significant.

Conclusion

A high level of social relationships is significantly inversely associated with the risk of death among older adults in China. Policy interventions should create and promote social activity platforms suitable for the elderly, and support and consolidate family-based social support systems.

Social relationships  /  Older adults  /  Mortality  /  China Longitudinal Healthy Longevity Survey
柯攀, 卢祖洵, 殷晓旭, 赵志广. 社会关系与中国老年人死亡风险的关联性研究. 现代预防医学, 2026 , 53 (3) : 498 -501 . DOI: 10.20043/j.cnki.MPM.202507410
Pan KE, Zu-xun LU, Xiao-xu YIN, Zhi-guang ZHAO. Correlation between social relationships and the risk of death among Chinese older adults[J]. Modern Preventive Medicine, 2026 , 53 (3) : 498 -501 . DOI: 10.20043/j.cnki.MPM.202507410
正文
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中国是全球老年人口规模最大的国家，其健康老龄化进程关系到国家发展全局与社会和谐稳定。科学识别影响老年人健康结局的关键社会因素，并制定有针对性的干预策略，具有重要的现实意义。社会关系是人们在共同物质与精神活动中形成的相互联系的总和，被广泛认为是影响老年人健康的核心社会决定因素之一[1]。依据Kelly等人[2]的理论框架，社会关系可概念化为社会活动、社会网络与社会支持三个相互关联的维度。现有证据表明，良好的社会关系与较低的死亡风险相关[3]。然而，社会关系不同维度对老年人死亡风险的影响是否存在差异，仍有待深入探讨。
中国具有深厚的家庭本位文化与集体主义传统，社会关系多嵌入于以血缘、地缘为纽带的亲属与邻里网络中[4]。在这一文化情境下，社会关系的结构、功能及其对健康的影响路径可能具有鲜明特点。因此，厘清社会关系各维度与老年人死亡风险之间的关联，不仅有助于揭示社会因素影响健康的内在机制，也能为推动精准化的老年健康干预提供实证依据。
基于此，本研究利用中国老年健康影响因素跟踪调查数据（Chinese Longitudinal Healthy Longevity Survey, CLHLS）这一具有全国代表性的大样本数据，重点考察社会关系及其维度（社会活动、社会网络、社会支持）与老年人死亡风险的关联。通过构建多维度社会关系指标并控制多种混杂因素，旨在为社会关系促进健康老龄化的本土化策略提供科学参考。
1　对象与方法
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1.1　资料来源
本研究数据来源于2011—2018年CLHLS 9 765例65岁及以上老年人。CLHLS涵盖65岁及以上老年人的健康评估、慢性病、认知功能、生活方式、家庭结构、代际关系、医疗需求成本等微观数据。数据排除标准：参与者基线调查年龄<65岁（n=86）；随访期间结局含有缺失值（n=2 252）；社会关系变量含有缺失值（n=87）。最终纳入分析5 642名参与者。所有参与者都签署了基线和随访调查的知情同意书，并获北京大学生物医学伦理委员会批准(IRB00001052-13074)。
1.2　社会关系的测量
根据Kelly等人[2]和Fan[5]的研究，CLHLS对社会关系、社会活动、社会网络、社会支持的测量方法如下：（1）社会活动包括打牌/麻将、参加有组织的活动、拜访他人，共3个条目。（2）社会网络包括婚姻状况、生活安排、是否有兄弟姐妹探访、是否有子女探访，共4个条目。（3）社会支持包括交谈、分享想法、寻求帮助、生病时得到照顾、过去一年中从儿子、女儿那里获得任何经济支持，共6个条目。本研究计算了参与者社会关系的维度得分，社会活动得分为0～3、社会网络得分为0～4、社会支持得分为0～6。三个维度分数之和为个体的社会关系总分（得分：0～13）。社会关系及其子域得分越高，表明其社会关系及社会活动、社会网络、社会支持越完善。采用三分位数对个体的社会关系及其子域进行分级（低、中、高）。
1.3　结局的测量
在2014和2018年的随访期间，通过对近亲属的访谈收集参与者的结局（生存/死亡）和死亡日期。从2011年访谈日期至死亡日期（以先发生者为准）或最后一次随访日期为随访时间。
1.4　协变量的测量
在基线访问时通过问卷调查或体格检查对参与者的协变量进行评估。参考既往文献[6]，本研究将纳入以下协变量：性别、年龄（岁）、婚姻状况、居住安排、受教育年限（年）、居住地、家庭年收入（元）、吸烟状况、饮酒状况、运动状况、身体质量指数（body mass index，BMI）、收缩压、舒张压、合并症（高血压、糖尿病、心脏病、中风、癌症）。
1.5　统计学分析
分类变量用计数和百分比描述，χ2检验用于比较组间差异。连续变量用（）表示，采用单因素方差分析检验组间差异性（F值）。使用风险比（hazard ratio, HR）和95%置信区间（confidence interval, CI）的Cox比例风险模型分析社会关系与死亡风险的关联。采用 Schoenfeld法评估了比例风险假设[7]，并确定符合使用Cox回归模型的条件。本研究还将从性别、年龄、收入三个特征进行社会关系与死亡风险的亚组分析。此外，为减少潜在的反向因果偏倚，本研究还排除了参与者在随访的前二年内的死亡事件。检验水准α=0.05，所有统计分析使用R 4.1.2版本。
2　结果
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2.1　研究对象的基线特征和社会关系得分
纳入5 642例老年人，分别有1 902（33.7%）、2 837（50.3%）和903人（16.0%）被划分为低水平、中等和高水平的社会关系。老年人的性别、年龄、居住地、家庭年收入、吸烟、饮酒、运动、社会参与、社会网络、社会支持与社会关系的组间比较，差异有统计学意义（P<0.05）。老年人社会关系、社会活动、社会网络和社会支持的平均得分分别为7.06、0.39、1.54和5.13分。见表1。
2.2　社会关系及其维度与中国老年人死亡风险的关联
老年人的平均随访时间为4.56年，3 070名参与者（54.4%）死亡，见表1。以中等社会关系为参照组，Cox回归模型结果显示，高水平社会关系与较低死亡风险显著相关（HR=0.73, 95% CI: 0.64～0.84）相较于中等水平社会活动，高水平的社会活动（HR=0.64,95% CI: 0.40～0.73）和高水平的社会支持（HR=0.91～ 95% CI: 0.74～0.98）显著降低了中国老年人的死亡风险。然而，没有发现社会网络和死亡率之间存在显著关联的证据。见表2。
模型2调整了性别、年龄（岁）、婚姻状况、居住安排、受教育年限（年）、居住地、家庭年收入（元）、吸烟状况、饮酒状况、运动状况、体重指数、收缩压、舒张压、合并症（高血压、糖尿病、心脏病、中风、癌症）。
2.3　亚组分析和敏感性分析
表3显示，社会关系与中国老年人死亡的风险关联在性别、年龄、收入的亚组分析结果仍然显著，但未观察到上述特征的交互效应（P交互>0.05）。表4显示，排除随访前二年内死亡的1 245例参与者，关联性结果仍然显著。
3　讨论
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3.1　本研究主要发现
本研究基于CLHLS数据系统考察了社会关系及其各维度与中国老年人死亡风险的关联。结果表明，在整体层面，高水平的社会关系与死亡风险降低显著相关。更为重要的是，在社会关系的子维度上，本研究揭示了显著的差异性：社会活动与社会支持是独立的保护性因素，而社会网络则未显示出与死亡风险的显著关联。这一发现提示，对于中国老年人而言，社会关系的“质量”（即功能的实现）可能比单纯的“存在”（即结构的完备）对健康结局的影响更为关键。
3.2　中国老年人社会关系子维度作用的差异性
打牌、麻将、参加社区活动等是中国老年人最常见的社会活动方式[6，8]。这些活动不仅是休闲娱乐，更是他们获取社会信息、维持认知功能、获得归属感和价值感的重要平台。老年人积极参与这些活动，可满足其心理和社会需求，通过减轻压力、改善情绪等心理生理机制对健康产生积极影响[9-10]。本研究测量的是感知到的和实际获得的社会支持（如生病时有人照料、可以倾诉烦恼）。在中国家庭本位的文化下，家庭成员是提供这种支持的最主要来源。稳定、可靠的社会支持是应对生活压力事件（如疾病、衰老）的缓冲器[11-12]。这表明，对于中国老年人，社会关系的“深度”（即关系的质量和支持的可得性）比单纯的“广度”（即网络的大小和联系频率）更为关键。这一发现深化了学术界对社会关系影响健康的内在路径的理解，强调了从“量”到“质”的研究视角转变的必要性。社会网络指标（如是否有配偶同住、子女探望频率）更多地反映了社会关系的“结构”或“广度”。一个可能的解释是，在中国文化背景下，老年人拥有子女和配偶通常是一种“标准配置”，其存在本身可能并不直接提供健康增益，而缺失（如丧偶、无子女）才会带来显著的负面风险[13]。此外，即使存在社会网络结构，如果缺乏高质量的支持和互动，其对健康的保护作用也会大打折扣。
3.3　政策启示
本研究结果对制定促进健康老龄化的公共政策具有明确启示。首先，干预措施不应止步于泛泛地鼓励社会交往，而应着力于创造和推广适合老年人、且易于参与的社会活动平台（如社区老年活动中心、兴趣小组），以激发社会关系的功能性活力。其次，政策应继续支持和巩固以家庭为基础的社会支持系统，例如通过探亲假、家庭护理补贴等方式，强化家庭成员作为核心支持来源的作用。同时，也应关注为缺乏家庭支持的老年人构建社区支持网络，弥补其功能性支持的不足。
3.4　本研究的局限性
本研究存在以下局限性：一是CLHLS数据未报告疾病别死因。二是尽管在Cox回归模型调整了多个协变量，但仍难以排除混杂因素的影响。三是社会关系的测量可能存在主观报告偏差。四是未计算社会关系的动态变化，即社会关系与死亡风险的长期关联。五是由于观察性研究的限制，难以确定社会关系与死亡结局的时序关系，无法进行因果推断。
本研究揭示了社会关系与老年人的死亡风险呈负相关，社会活动和社会支持都能预测较低的死亡率，但社会网络没有显著影响。政策干预应创造和推广适合老年人的社会活动平台，支持和巩固以家庭为基础的社会支持系统。
基金
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  • 国家社会科学基金重大项目(18ZDA085)
文献
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参考文献 引证文献
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2026年第53卷第3期
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doi: 10.20043/j.cnki.MPM.202507410
  • 接收时间：2025-07-24
  • 首发时间：2026-11-02
  • 出版时间：2026-02-10
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  • 收稿日期：2025-07-24
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国家社会科学基金重大项目(18ZDA085)
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    1.华中科技大学同济医学院公共卫生学院社会医学与卫生事业管理系，湖北 武汉 430040
    2.深圳市慢性病防治中心心脑血管疾病与糖尿病防控科，广东 深圳 518020

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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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