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Article(id=1324078291652575796, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078175000605624, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202509049, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1756828800000, receivedDateStr=2025-09-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614464915, onlineDateStr=2026-11-02, pubDate=1769270400000, pubDateStr=2026-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614464915, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614464915, creator=13701087609, updateTime=1793614464915, updator=13701087609, issue=Issue{id=1324078175000605624, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='2', pageStart='193', pageEnd='384', issueExtLink='null', onlineDate='null', pubDate='1769270400000', pubDateStr='2026-01-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614437103, creator='13701087609', updateTime=1793614526046, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078548130082942, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078175000605624, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078548130082943, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078175000605624, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=225, endPage=231, ext={EN=ArticleExt(id=1324078291933594165, articleId=1324078291652575796, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=The impact of urban-rural health insurance integration on depression among rural middle-aged and elderly individuals——An Empirical Study Based on CHARLS Data, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To examine the impact of the integrated urban-rural health insurance policy on depression levels among rural middle-aged and elderly populations.

Methods

A multi-period difference-in-differences model was constructed using five waves of the China Health and Retirement Longitudinal Study (CHARLS) data from 2011-2020 to evaluate policy effects.

Results

The integration policy reduced depression scores among rural middle-aged and elderly individuals by 0.426 points (β=-0.426, P<0.05), with significant effects observed among rural males (β=-0.416, P<0.01) and middle-aged cohorts (β=-0.570, P<0.1). Improved chronic disease conditions partially mediated this effect.

Conclusion

The integration of health insurance significantly reduces depression levels among rural middle-aged and elderly individuals. Future efforts should focus on deepening institutional reforms, optimizing chronic disease coverage, and strengthening targeted interventions to enhance the physical and mental health security of this demographic.

, authors=Tai-nan LI, Jing ZHAO, Ke-man QU, Ying CHEN, Ya-ru LI, authorsList=Tai-nan LI, Jing ZHAO, Ke-man QU, Ying CHEN, Ya-ru LI, authorCompany=null, correspAuthors=Jing 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=1324078295821714000, articleId=1324078291652575796, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=城乡医保整合对农村中老年人抑郁的影响——基于CHARLS数据的实证研究, columnId=1228016567632462653, journalTitle=现代预防医学, columnName=流行病与统计方法, runingTitle=null, highlight=null, articleAbstract=
目的

探讨城乡居民医保整合政策对农村中老年群体抑郁水平的影响。

方法

基于中国健康与养老追踪调查（CHARLS）2011—2020年五轮追踪数据，构建多期双重差分模型评估政策效应。

结果

医保整合政策使农村中老年人抑郁评分降低0.426分（β=-0.426，P<0.05），且对农村男性（β=-0.416，P<0.01）和中年群体（β=-0.570，P<0.1）作用显著。慢性病状况的改善在其中发挥了部分中介作用。

结论

医保整合对农村中老年人抑郁水平有显著降低作用，未来应深化制度改革、优化慢病保障、加强精准施策，提升农村中老年身心健康保障水平。

, authors=李台南, 赵静, 屈可曼, 陈颖, 李雅茹, authorsList=李台南, 赵静, 屈可曼, 陈颖, 李雅茹, authorCompany=null, correspAuthors=赵静, authorNote=

李台南（2001—），女，硕士在读，研究方向：卫生政策与管理

, correspAuthorsNote=
赵静，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=gaO34Vl5KJHiVZexlnXlqg==, magXml=/2cpzSNxx5AVNGCbHhEIEA==, pdfUrl=null, pdf=OG5Gkoh1c1Y0XM/ZmnppPA==, pdfFileSize=910450, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=9L4irIufjQ8a6al9gIGcfw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=FCjC+y82kx1r++EhnqdnEw==, mapNumber=null, fund=null)}, authors=[Author(id=1324078296190812757, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1324078296287281751, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, authorId=1324078296190812757, language=EN, stringName=Tai-nan LI, firstName=Tai-nan, middleName=null, lastName=LI, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=School of Management, Beijing University of Chinese Medicine, Beijing 102401, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1324078296366973528, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, authorId=1324078296190812757, language=CN, stringName=李台南, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=北京中医药大学管理学院，北京 102401, bio={"content":"

李台南（2001—），女，硕士在读，研究方向：卫生政策与管理

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李台南（2001—），女，硕士在读，研究方向：卫生政策与管理

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articleId=1324078291652575796, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=佚名, journalName=null, refType=null, unstructuredReference=佚名．民政部、全国老龄办发布《2024年度国家老龄事业发展公报》—中华人民共和国民政部[EB/OL]．[2025-12-10]．https://www.mca.gov.cn/n152/n166/c1662004999980006135/content.html., articleTitle=民政部、全国老龄办发布《2024年度国家老龄事业发展公报》—中华人民共和国民政部, refAbstract=null), Reference(id=1324078304529089162, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[1], rfOrder=1, authorNames=Anonym, journalName=null, refType=null, unstructuredReference=Anonym.Ministry of Civil Affairs of the People’s Republic of China, National Office on Aging. 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(In Chinese), articleTitle=Moving towards a high-quality medical insurance system with universal and unified coverage, refAbstract=null), Reference(id=1324078308534649511, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, doi=null, pmid=null, pmcid=null, year=2024, volume=56, issue=2, pageStart=157, pageEnd=170, url=null, language=null, rfNumber=[17], rfOrder=30, authorNames=周婷, 高月霞, 左学金, journalName=华东师范大学学报：哲学社会科学版, refType=null, unstructuredReference=周婷，高月霞，左学金．共同富裕背景下基本医疗保险的受益公平性研究——基于CHARLS数据的实证分析[J]．华东师范大学学报：哲学社会科学版，2024，56（2）：157-170., articleTitle=共同富裕背景下基本医疗保险的受益公平性研究——基于CHARLS数据的实证分析, refAbstract=null), Reference(id=1324078308622729896, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, doi=null, pmid=null, pmcid=null, year=2024, volume=56, issue=2, pageStart=157, pageEnd=170, url=null, language=null, rfNumber=[17], rfOrder=31, authorNames=Zhou T, Gao YX, Zuo XJ, journalName=Journal of East China Normal University (Philosophy and Social Sciences), refType=null, unstructuredReference=Zhou T, Gao YX, Zuo XJ. A study on the benefit equity of basic medical insurance in the context of common prosperity: An empirical analysis based on CHARLS data[J]. Journal of East China Normal University (Philosophy and Social Sciences), 2024, 56(2): 157-170. (In Chinese), articleTitle=A study on the benefit equity of basic medical insurance in the context of common prosperity: An empirical analysis based on CHARLS data, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1324078296069177937, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, xref=null, ext=[AuthorCompanyExt(id=1324078296077566546, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, companyId=1324078296069177937, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Management, Beijing University of Chinese Medicine, Beijing 102401, China), AuthorCompanyExt(id=1324078296085955155, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, companyId=1324078296069177937, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=北京中医药大学管理学院，北京 102401)])], figs=[ArticleFig(id=1324078300196373109, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Fig.1, caption=Sample screening flowchart, figureFileSmall=OXNf42WK9xwCt5tNiCiZLg==, figureFileBig=9L4irIufjQ8a6al9gIGcfw==, tableContent=null), ArticleFig(id=1324078300288647798, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=图1, caption=样本筛选流程图, figureFileSmall=OXNf42WK9xwCt5tNiCiZLg==, figureFileBig=9L4irIufjQ8a6al9gIGcfw==, tableContent=null), ArticleFig(id=1324078300565471863, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Fig.2, caption=Parallel trend test, figureFileSmall=GupiqzJ5tDEFOJz66mSukQ==, figureFileBig=cL9illbmZKlSjhPWIqwNmQ==, tableContent=null), ArticleFig(id=1324078300657746552, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=图2, caption=平行趋势检验, figureFileSmall=GupiqzJ5tDEFOJz66mSukQ==, figureFileBig=cL9illbmZKlSjhPWIqwNmQ==, tableContent=null), ArticleFig(id=1324078300737438329, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Fig.3, caption=Estimated coefficients after random sampling, figureFileSmall=CroqEuPxH+CURzPktQXB+A==, figureFileBig=wZrv4oVBV9uf09jswgR/Mg==, tableContent=null), ArticleFig(id=1324078300817130106, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=图3, caption=随机抽样后的估计系数, figureFileSmall=CroqEuPxH+CURzPktQXB+A==, figureFileBig=wZrv4oVBV9uf09jswgR/Mg==, tableContent=null), ArticleFig(id=1324078300892627579, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Table 1, caption=

Descriptive statistics of regression model variables

, figureFileSmall=null, figureFileBig=null, tableContent=
变量类别变量名称统计值
被解释变量抑郁水平9.081±6.479
控制变量性别[n(%)]
女性23 115(52.62)
男性20 812(47.38)
教育水平[n(%)]
小学以下22 594(51.44)
小学10 652(24.25)
中学8 101(18.44)
高中及以上2 577(5.87)
年龄60.858±9.322
婚姻状况[n(%)]
无配偶5 725(13.03)
有配偶38 202(86.97)
是否有养老保险[n(%)]
否18 345(46.77)
是20 883(53.23)
自评健康2.959±0.992
是否残疾[n(%)]
否32 423(93.05)
是2 422(6.95)
是否吸烟[n(%)]
否30 498(72.51)
是11 565(27.49)
是否饮酒[n(%)]
否29 076(66.22)
是14 831(33.78)
子女对父母的经济支持7.798±1.370
家庭规模()3.258±1.715
健在子女数2.778±1.357
中介变量慢性病数量1.821±1.685
), ArticleFig(id=1324078301010068092, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=表1, caption=

回归模型变量描述性统计分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量类别变量名称统计值
被解释变量抑郁水平9.081±6.479
控制变量性别[n(%)]
女性23 115(52.62)
男性20 812(47.38)
教育水平[n(%)]
小学以下22 594(51.44)
小学10 652(24.25)
中学8 101(18.44)
高中及以上2 577(5.87)
年龄60.858±9.322
婚姻状况[n(%)]
无配偶5 725(13.03)
有配偶38 202(86.97)
是否有养老保险[n(%)]
否18 345(46.77)
是20 883(53.23)
自评健康2.959±0.992
是否残疾[n(%)]
否32 423(93.05)
是2 422(6.95)
是否吸烟[n(%)]
否30 498(72.51)
是11 565(27.49)
是否饮酒[n(%)]
否29 076(66.22)
是14 831(33.78)
子女对父母的经济支持7.798±1.370
家庭规模()3.258±1.715
健在子女数2.778±1.357
中介变量慢性病数量1.821±1.685
), ArticleFig(id=1324078301093954173, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Table 2, caption=

Baseline regression results on the impact of medical insurance integration on the mental health of rural middle-aged and elderly individuals

, figureFileSmall=null, figureFileBig=null, tableContent=
变量回归系数稳健标准误
城乡居民医保整合-0.426b0.193
年龄0.1840.347
婚姻-1.253c0.354
是否有养老保险-0.1390.110
自评健康-0.868c0.088
是否残疾0.737b0.309
是否吸烟-0.1760.235
是否饮酒-0.0720.129
子女对父母的经济支持-0.0430.037
家庭规模-0.0520.033
健在子女数0.0140.168
个体固定效应控制
年份固定效应控制
变量回归系数稳健标准误
观测值15 716
调整后R20.496
), ArticleFig(id=1324078301169451646, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=表2, caption=

医保整合对农村中老年人抑郁影响的基准回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量回归系数稳健标准误
城乡居民医保整合-0.426b0.193
年龄0.1840.347
婚姻-1.253c0.354
是否有养老保险-0.1390.110
自评健康-0.868c0.088
是否残疾0.737b0.309
是否吸烟-0.1760.235
是否饮酒-0.0720.129
子女对父母的经济支持-0.0430.037
家庭规模-0.0520.033
健在子女数0.0140.168
个体固定效应控制
年份固定效应控制
变量回归系数稳健标准误
观测值15 716
调整后R20.496
), ArticleFig(id=1324078301244949119, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Table 3, caption=

Balance test results

, figureFileSmall=null, figureFileBig=null, tableContent=
变量样本均值标准化偏差(%)偏差减少幅度(%)t检验
处理组控制组t值P值
年龄未匹配62.93561.83912.293.38.39<0.001
匹配62.93562.8620.80.520.604
婚姻状况未匹配0.8670.868-0.5-104.7-0.330.739
匹配0.8670.8631.00.620.533
是否有养老保险未匹配0.5770.47021.597.814.75<0.001
匹配0.5770.579-0.5-0.300.767
自评健康未匹配2.9942.9445.179.23.54<0.001
匹配2.9943.005-1.1-0.670.506
是否残疾未匹配0.0990.05914.890.010.37<0.001
匹配0.0990.103-1.5-0.840.402
是否吸烟未匹配0.2810.2731.7-74.41.200.231
匹配0.2810.2673.01.930.054
是否饮酒未匹配0.3370.339-0.3-721.2-0.220.829
匹配0.3370.3252.61.640.100
子女对父母的经济支持未匹配7.8147.68010.088.26.86<0.001
匹配7.8147.7981.20.760.448
家庭规模未匹配2.7743.311-34.497.9-23.28<0.001
匹配2.7752.786-0.7-0.500.615
健在子女数未匹配2.9413.175-17.498.6-11.88<0.001
匹配2.9412.9380.20.160.873
), ArticleFig(id=1324078301404332672, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=表3, caption=

平衡性检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量样本均值标准化偏差(%)偏差减少幅度(%)t检验
处理组控制组t值P值
年龄未匹配62.93561.83912.293.38.39<0.001
匹配62.93562.8620.80.520.604
婚姻状况未匹配0.8670.868-0.5-104.7-0.330.739
匹配0.8670.8631.00.620.533
是否有养老保险未匹配0.5770.47021.597.814.75<0.001
匹配0.5770.579-0.5-0.300.767
自评健康未匹配2.9942.9445.179.23.54<0.001
匹配2.9943.005-1.1-0.670.506
是否残疾未匹配0.0990.05914.890.010.37<0.001
匹配0.0990.103-1.5-0.840.402
是否吸烟未匹配0.2810.2731.7-74.41.200.231
匹配0.2810.2673.01.930.054
是否饮酒未匹配0.3370.339-0.3-721.2-0.220.829
匹配0.3370.3252.61.640.100
子女对父母的经济支持未匹配7.8147.68010.088.26.86<0.001
匹配7.8147.7981.20.760.448
家庭规模未匹配2.7743.311-34.497.9-23.28<0.001
匹配2.7752.786-0.7-0.500.615
健在子女数未匹配2.9413.175-17.498.6-11.88<0.001
匹配2.9412.9380.20.160.873
), ArticleFig(id=1324078301488218753, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Table 4, caption=

PSM-DID regression results

, figureFileSmall=null, figureFileBig=null, tableContent=
变量回归系数稳健标准误
城乡居民医保整合-0.525c0.168
年龄0.1220.525
婚姻状况-1.414b0.606
是否有养老保险-0.2220.173
自评健康-0.862c0.106
是否残疾0.6270.368
是否吸烟-0.4730.377
是否饮酒-0.0210.179
子女对父母的经济支持-0.130b0.051
家庭规模-0.0380.043
健在子女数-0.0370.213
个体固定效应控制
年份固定效应控制
观测值14 142
调整后R20.496
), ArticleFig(id=1324078301572104834, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=表4, caption=

PSM-DID回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量回归系数稳健标准误
城乡居民医保整合-0.525c0.168
年龄0.1220.525
婚姻状况-1.414b0.606
是否有养老保险-0.2220.173
自评健康-0.862c0.106
是否残疾0.6270.368
是否吸烟-0.4730.377
是否饮酒-0.0210.179
子女对父母的经济支持-0.130b0.051
家庭规模-0.0380.043
健在子女数-0.0370.213
个体固定效应控制
年份固定效应控制
观测值14 142
调整后R20.496
), ArticleFig(id=1324078301823763075, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Table 5, caption=

Regression results for fictitious processing time

, figureFileSmall=null, figureFileBig=null, tableContent=
变量提前2年
(1)		提前3年
(2)
城乡居民医保整合0.058(0.184)0.315(0.221)
控制变量控制
个体固定效应控制
年份固定效应控制
观测值15 716
调整后R20.496
), ArticleFig(id=1324078301916037764, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=表5, caption=

虚构处理时间的回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量提前2年
(1)		提前3年
(2)
城乡居民医保整合0.058(0.184)0.315(0.221)
控制变量控制
个体固定效应控制
年份固定效应控制
观测值15 716
调整后R20.496
), ArticleFig(id=1324078302234804869, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Table 6, caption=

Results of heterogeneity analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
变量性别年龄收入水平
男女中年老年低收入高收入
城乡居民医保整合-0.416c(0.135)-0.447(0.343)-0.570a(0.294)-0.222(0.277)-0.231(0.423)-0.419(0.313)
控制变量控制控制控制控制控制控制
个体固定效应控制控制控制控制控制控制
年份固定效应控制控制控制控制控制控制
观测值6 9848 7324 7059 4083 4718 378
调整后R20.4740.4820.5080.4980.4990.501
), ArticleFig(id=1324078302331273862, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=表6, caption=

异质性分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量性别年龄收入水平
男女中年老年低收入高收入
城乡居民医保整合-0.416c(0.135)-0.447(0.343)-0.570a(0.294)-0.222(0.277)-0.231(0.423)-0.419(0.313)
控制变量控制控制控制控制控制控制
个体固定效应控制控制控制控制控制控制
年份固定效应控制控制控制控制控制控制
观测值6 9848 7324 7059 4083 4718 378
调整后R20.4740.4820.5080.4980.4990.501
), ArticleFig(id=1324078304038355591, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=EN, label=Table 7, caption=

Results of mechanism analysis

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变量慢性病数量
(1)		抑郁水平
(2)
城乡居民医保整合-0.151c(0.046)-0.314a(0.181)
慢性病数量0.181c(0.055)
控制变量控制控制
个体固定效应控制控制
年份固定效应控制控制
观测值4 56122 747
调整后R20.7720.505
), ArticleFig(id=1324078304197739144, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078291652575796, language=CN, label=表7, caption=

机制分析结果

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变量慢性病数量
(1)		抑郁水平
(2)
城乡居民医保整合-0.151c(0.046)-0.314a(0.181)
慢性病数量0.181c(0.055)
控制变量控制控制
个体固定效应控制控制
年份固定效应控制控制
观测值4 56122 747
调整后R20.7720.505
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城乡医保整合对农村中老年人抑郁的影响——基于CHARLS数据的实证研究
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李台南 , 赵静 , 屈可曼 , 陈颖 , 李雅茹
现代预防医学 | 流行病与统计方法 2026,53(2): 225-231
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现代预防医学 |流行病与统计方法 2026 , 53 (2) : 225 -231
城乡医保整合对农村中老年人抑郁的影响——基于CHARLS数据的实证研究
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李台南, 赵静 , 屈可曼, 陈颖, 李雅茹
作者信息
  • 北京中医药大学管理学院，北京 102401
通讯作者:
赵静，E-mail:
作者简介:

李台南（2001—），女，硕士在读，研究方向：卫生政策与管理

The impact of urban-rural health insurance integration on depression among rural middle-aged and elderly individuals——An Empirical Study Based on CHARLS Data
Tai-nan LI, Jing ZHAO , Ke-man QU, Ying CHEN, Ya-ru LI
Affiliations
  • School of Management, Beijing University of Chinese Medicine, Beijing 102401, China
出版时间: 2026-01-25 doi: 10.20043/j.cnki.MPM.202509049
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摘要
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目的

探讨城乡居民医保整合政策对农村中老年群体抑郁水平的影响。

方法

基于中国健康与养老追踪调查（CHARLS）2011—2020年五轮追踪数据，构建多期双重差分模型评估政策效应。

结果

医保整合政策使农村中老年人抑郁评分降低0.426分（β=-0.426，P<0.05），且对农村男性（β=-0.416，P<0.01）和中年群体（β=-0.570，P<0.1）作用显著。慢性病状况的改善在其中发挥了部分中介作用。

结论

医保整合对农村中老年人抑郁水平有显著降低作用，未来应深化制度改革、优化慢病保障、加强精准施策，提升农村中老年身心健康保障水平。

城乡居民医保整合  /  农村中老年人  /  抑郁  /  双重差分
Objective

To examine the impact of the integrated urban-rural health insurance policy on depression levels among rural middle-aged and elderly populations.

Methods

A multi-period difference-in-differences model was constructed using five waves of the China Health and Retirement Longitudinal Study (CHARLS) data from 2011-2020 to evaluate policy effects.

Results

The integration policy reduced depression scores among rural middle-aged and elderly individuals by 0.426 points (β=-0.426, P<0.05), with significant effects observed among rural males (β=-0.416, P<0.01) and middle-aged cohorts (β=-0.570, P<0.1). Improved chronic disease conditions partially mediated this effect.

Conclusion

The integration of health insurance significantly reduces depression levels among rural middle-aged and elderly individuals. Future efforts should focus on deepening institutional reforms, optimizing chronic disease coverage, and strengthening targeted interventions to enhance the physical and mental health security of this demographic.

Urban-Rural Health Insurance Integration  /  Rural middle-aged and elderly individuals  /  Depression  /  Difference-in-differences
李台南, 赵静, 屈可曼, 陈颖, 李雅茹. 城乡医保整合对农村中老年人抑郁的影响——基于CHARLS数据的实证研究. 现代预防医学, 2026 , 53 (2) : 225 -231 . DOI: 10.20043/j.cnki.MPM.202509049
Tai-nan LI, Jing ZHAO, Ke-man QU, Ying CHEN, Ya-ru LI. The impact of urban-rural health insurance integration on depression among rural middle-aged and elderly individuals——An Empirical Study Based on CHARLS Data[J]. Modern Preventive Medicine, 2026 , 53 (2) : 225 -231 . DOI: 10.20043/j.cnki.MPM.202509049
正文
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2024年末我国60岁及以上老年人口达3.1亿，占总人口的22.0%，已进入中度老龄化社会[1]。推进健康老龄化，改善老年群体身心健康，成为应对挑战的关键，也对医疗保障制度提出了更高要求。为促进健康公平，我国逐步整合原有的新型农村合作医疗与城镇居民医保制度，并于2020年底基本完成。农村中老年群体因健康脆弱性较高而处于制度性弱势地位，城乡医保整合政策可为该群体带来更为显著的健康促进效应[2]。心理健康是多维健康的重要维度，研究显示，中国老年人的抑郁率相较于美国存在显著的城乡差异，农村人口的抑郁风险更高[3]。《“健康中国2030”规划纲要》提出“推动开展老年人心理健康与关怀服务”，但目前针对该群体的心理干预仍不足。学界对城乡医保整合影响的研究主要聚焦于居民的医疗服务利用、医疗负担、健康公平等方面，证实了其对健康促进的直接效应[4–6]，部分研究关注了医疗保险对精神健康的影响[7]，但聚焦于城乡医保整合政策对农村中老年人抑郁水平的深入探讨仍不足。此外，以往研究多采用较短周期的面板数据[8]，难以捕捉政策实施后的长期效应。本研究利用CHARLS五期面板数据和多期双重差分模型，探讨医保整合对农村中老年人抑郁的影响及其作用机制，为政策优化提供实证依据。
1　理论分析与假设提出
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根据Grossman (1972)的健康生产函数模型，个体健康资本的提升受到收入、年龄、医疗服务利用等因素的影响[9]。城乡医保整合通过提升保障待遇，降低了农村中老年人的疾病负担与未来健康风险焦虑[10]。基于此，本文提出假设1。
H1：城乡医保整合能够显著降低农村中老年人的抑郁水平。
健康资本会随着年龄增长而折旧，有效的慢性病管理是一种减缓健康资本折旧率的投资行为。有研究指出参加新农合的农村老年人慢性病医疗负担降低程度小于城镇老年人[11]，因此医保整合通过将更多慢性病门诊服务纳入保障范围，提升了农村中老年人对慢性病进行系统长期管理的可行性，并通过减轻病痛、缓解经济负担等降低抑郁水平。基于此，本文进一步提出假设2。
H2a：城乡医保整合能够显著改善农村中老年人的慢性病状况。
H2b：慢性病状况的改善有助于降低农村中老年人的抑郁水平。
2　研究设计
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2.1　数据来源与样本筛选
数据来自中国健康与养老追踪调查（China Health and Retirement Longitudinal Study, CHARLS）2011、2013、2015、2018、2020年五期面板数据。图1展示了具体的样本筛选流程。
2.2　变量设定
2.2.1　被解释变量：抑郁水平
采用国际通用的简版抑郁自评量表(CES-D-10)进行衡量：受访者根据过去一周的感受对10个问题进行评分，答项“很少或者根本没有（<1天）”“不太多（1~2天）”“有时或者说有一半的时间（3~4天）”“大多数的时间（5~7天）”分别赋值为0~3分，同时对积极条目反向计分后加总，总分0~30分，分值越高表示抑郁倾向越高。
2.2.2　核心解释变量：城乡居民医保整合
解释变量为某省在相应调查年度是否实施了城乡医保整合政策，本研究构建了一个随个体所在省份和时间而变化的政策虚拟变量policyit，根据参保者所在省份发布的城乡医保整合政策文件，提取省级政策生效时间并进行变量赋值。具体而言，若个体i在调查年份t时，其所在省份的整合政策已经生效，则赋值为1作为处理组，否则赋值为0作为对照组。
2.2.3　控制变量
本研究在模型中纳入以下三类控制变量：个人基本信息，包括性别（女性=0，男性=1）、教育水平（1=小学以下，2=小学，3=中学，4=高中及以上）、年龄、婚姻状况（无配偶=0，有配偶=1）、是否有养老保险（否=0，是=1）；健康行为特征，包括自评健康（很差=1，较差=2，一般=3，较好=4，很好=5）、是否残疾（否=0，是=1）、是否吸烟（否=0，是=1）、是否饮酒（否=0，是=1）；家庭特征，包括子女对父母的经济支持（现金和实物价值总额的对数）、家庭规模、健在子女数。
2.3　实证模型
由于各省城乡医保整合实施时间不一致，本研究采用多时点双重差分法(Staggered DID)。基准回归设定如下：
公式(1)中，Yit表示个体i在t年份的抑郁评分；policyit为政策虚拟变量，表示个体i在年份t是否已经历城乡居民基本医保整合；Xit为控制变量向量；μi为个体固定效应，λt为时间固定效应；εit为随机扰动项。本研究关注核心系数β1，反映城乡居民医保整合对农村中老年人抑郁水平的平均处理效应。在稳健性检验中，为减少样本选择偏差，通过倾向性得分匹配-双重差分法(PSM-DID)进行再估计。
此外，本研究引入慢性病数量作为中介变量进行分析，借鉴温忠麟的三步法[12]，进一步探索医保整合政策效应的作用机制：
公式(2)、(3)中，Mit为中介变量，即慢性病数量。CHARLS问卷中个体自报14种医生诊断慢性病（如高血压、糖尿病等），对每种疾病，若受访者回答“是”则赋值为1，“否”则为0。将14种疾病的赋值结果相加，得到取值0~14的连续变量。
2.4　统计方法
连续变量采用（均数±标准差）描述，分类变量采用频数和百分比描述。为检验倾向性得分匹配后的样本平衡性，采用了t检验。核心分析采用固定效应回归构建多时点双重差分模型，并通过中介效应分析探究其作用机制。所有统计分析采用Stata 18.0完成。检验水准α=0.1。
3　实证结果
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3.1　描述性统计分析
表1报告了全样本的变量赋值及描述性统计结果。抑郁水平的均值为9.08，标准差为6.48，表明农村中老年人心理健康水平良好但个体差异显著；女性占比52.62%，总体性别比例较为均衡；平均受教育水平较低；年龄均值为60.86岁；样本人群的慢性病负担较重，平均每人患有1.82种慢性病。
3.2　基准回归结果
表2汇报了城乡居民医保整合对农村中老年人抑郁影响的回归结果。医保整合显著降低了农村中老年人的抑郁水平（P<0.05）。此外，多数控制变量的影响方向也与预期相符。
3.3　稳健性检验
3.3.1　平行趋势检验
平行趋势假设即验证政策实施前处理组与对照组变化趋势一致，使政策实施后观察到的差异更可靠地归因于政策本身，而非其他未观测因素[13]。为避免政策预期效应干扰，以城乡居民医保整合政策实施的前一期为基准期进行平行趋势检验。图2显示，政策实施前各期处理效应系数在统计层面均不显著，处理组与控制组不存在显著差异；政策实施后两组样本表现出显著差异，医保整合显著降低抑郁水平。因此，平行趋势假设成立。
3.3.2　PSM-DID估计
为避免过多样本匹配失败所造成的信息损失，使用1:2的最近邻倾向性得分匹配，表3显示，所有匹配变量的标准化偏差绝对值均低于10%，且匹配后的组间差异t检验不拒绝处理组与控制组无差别的原假设，表明匹配有效平衡了两组样本特征。如表4，控制选择性偏差后，城乡居民医保整合政策仍表现出对农村中老年人抑郁评分的显著降低作用，验证了基准回归结果的稳健性。
3.3.3　安慰剂检验
采用虚构处理时间和随机生成政策虚拟变量的方法。一方面，将政策开展时间提前2年和3年进行回归，结果均不显著（表5），由此证明了真实政策时间结果的可靠性；另一方面，对政策虚拟变量进行随机抽样并重复估计500次，图3显示，虚假的估计系数分布在0值附近且远离真实的估计系数。双重检验共同验证了基准回归结果的稳健性。
3.4　异质性分析
本研究根据性别、年龄、收入水平进行了分样本回归。根据世界卫生组织的标准将样本分为介于45~59岁的中年组和60岁以上的老年组。根据家庭总收入的中位数分为低收入组和高收入组。如表6所示，城乡居民医保整合对农村男性和中年群体产生显著影响，但对低收入组和高收入组均未产生显著影响。
3.5　机制分析
表7回归结果(1)显示，从自变量对中介变量的影响来看，城乡居民医保整合的回归系数显著为负（P<0.01），表明城乡居民医保整合政策显著降低了农村中老年人慢性病患病数量。回归结果(2)显示，在基准回归模型中加入慢性病数量这一中介变量后，中介变量对抑郁水平具有显著正向影响，即农村中老年人慢性病患病数量越多，抑郁水平越高。同时，与基准回归模型相比，城乡居民医保整合的回归系数绝对值变小且仍显著，表明慢性病数量发挥了部分中介作用。因此，城乡居民医保整合通过改善农村中老年人的慢性病状况，间接降低了其抑郁水平。
4　讨论与建议
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4.1　城乡居民医保整合有助于降低农村中老年人抑郁水平
研究发现，城乡居民医保整合显著降低了农村中老年人的抑郁水平，与李亚青[7]、黄德荣[14]等学者的研究结果一致，印证了医疗保险不仅分散健康风险，对参保人的精神健康也有显著影响。郑超等[15]指出，城乡医保整合政策通过提高医保报销比例、降低住院支出，既能减轻居民经济压力，又能增强其健康风险意识，降低抑郁水平。建议：第一，深化城乡居民基本医保制度改革。应持续扩大参保覆盖面，健全医保关系转移接续与异地就医直接结算机制；着力消除隐性分档现象，实现“城乡一档”的实质性待遇统一，构建高质量、全民统一覆盖的社会医疗保险体系[16]。第二，优化城乡居民医保制度保障水平，向健康需求更高的中老年人倾斜，并加强基本医保、大病保险、医疗救助三者有效衔接，缓解其对未来健康风险的焦虑。
4.2　城乡居民医保整合对农村中老年人抑郁的影响在性别和年龄上存在显著异质性
医保整合政策对男性的影响更显著，这可能是由于该政策直接缓解了作为家庭主要经济责任承担者的医疗支出焦虑。医保整合对45~59岁农村中年人的抑郁水平有更显著的影响：一方面，中年群体处于慢性病的高发阶段，对医疗保障的需求更迫切；另一方面，中年群体对新政策的适应性和利用能力更强，能更充分享受医保整合带来的福利，从而降低了其抑郁水平。此外，医保整合对农村中老年人抑郁的影响在收入水平上未表现出显著差异，表明随着医保整合推进，报销比例等制度层面的差距已得到实质性改善，平等、普惠、高效的基本医疗保险制度在一定程度上缩小了不同收入群体的受益差距[17]。建议：第一，基层医保部门和村委会开展针对性的宣传活动，强化政策的精准宣传与解读，着力弥合“信息鸿沟”，使农村高龄老人充分享受政策红利。第二，加大对农村地区精神卫生服务的财政投入，重视对女性、老年人和低收入群体的心理健康支持，探索医保以外的多维度心理健康干预措施，如社区支持、志愿者服务等。
4.3　城乡居民医保整合可通过影响慢性病患病数量，进而作用于农村中老年人抑郁水平
虽然医保整合在短期内可能因提升服务利用而增加慢性病的诊断率，但其更核心的长期效应在于提升了对已患慢性病的管理水平和延缓新并发症发生。相关研究表明，慢性病纳入医保报销有助于促进老年人健康管理，避免“小病大治”[11]。城乡居民医保整合通过扩大门诊慢特病保障范围及提高报销比例，减轻了农村中老年人经济负担，增强了其对自身慢性病进行长期、规范管理的能力与意愿，最终通过增强安全预期、提高生活满意度等社会心理机制降低抑郁风险[7]。建议：第一，加快门诊统筹推进，进一步扩大慢性病门诊报销的覆盖范围，同时动态提高报销比例和封顶线，降低慢病患者长期用药负担并引导其在基层医疗机构接受规范管理。第二，强化基层医疗机构在慢性病筛查、健康教育中的作用，加强村医培训，提升其对常见慢性病及心理问题的识别和初步干预能力，消除“因病致郁”风险。

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2026年第53卷第2期
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doi: 10.20043/j.cnki.MPM.202509049
  • 接收时间：2025-09-03
  • 首发时间：2026-11-02
  • 出版时间：2026-01-25
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  • 收稿日期：2025-09-03
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    北京中医药大学管理学院，北京 102401

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2种不同金属材料的力学参数
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Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
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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