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Article(id=1311350411202752709, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350363295417204, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202604318, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1776614400000, receivedDateStr=2026-04-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579901743, onlineDateStr=2026-09-28, pubDate=1787587200000, pubDateStr=2026-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579901743, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579901743, creator=13701087609, updateTime=1790579901743, updator=13701087609, issue=Issue{id=1311350363295417204, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='16', pageStart='2881', pageEnd='3072', issueExtLink='null', onlineDate='null', pubDate='1787587200000', pubDateStr='2026-08-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1790579890321, creator='13701087609', updateTime=1790584112451, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311368072267653663, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350363295417204, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311368072267653664, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350363295417204, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2881, endPage=2886, ext={EN=ArticleExt(id=1311350411446022342, articleId=1311350411202752709, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Joint association of intrinsic capacity and long-term PM2.5 exposure with cardiovascular risk in older Chinese adults, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To examine the joint association of intrinsic capacity (IC) and long-term fine particulate matter (PM2.5) exposure with incident cardiovascular disease (CVD) among older Chinese adults.

Methods

This prospective cohort study used data from the China Health and Retirement Longitudinal Study (CHARLS). We included 3 241 participants aged ≥60 years who were free of CVD at baseline in 2011 and followed them through 2020. IC was assessed across five domains: locomotion, vitality, sensory function, cognition, and psychological well-being, and categorized by the number of deficits (0, 1, 2, or ≥3). Long-term PM2.5 exposure was estimated using satellite-based data linked to participants’ residential locations. Cox proportional hazards models were used to estimate the association between IC-PM2.5 joint exposure groups and incident CVD, with hazard ratios (HRs) and 95% confidence intervals (CIs) reported. In addition, group-based trajectory modelling (GBTM) was applied to identify IC trajectories, and the association between PM2.5 exposure and CVD risk was further evaluated across different trajectory groups.

Results

During a mean follow-up of 7.9±2.2 years, 697 participants (21.5%) developed incident CVD, with an incidence density of 27.3 per 1 000 person-years (95%CI: 25.3-29.4). Compared with the “high IC + low PM2.5 exposure” group, the adjustedHRs for incident CVD were 1.53 (95%CI: 1.20-1.96) for the “low IC + high PM2.5 exposure” group. Three IC trajectories were further identified: “low-level with transient improvement”, “moderate-level with persistent decline”, and “high-level with stable improvement”. In the “low-level with transient improvement” trajectory group, each 10 μg/m3 increase in PM2.5 exposure was associated with an increased risk of incident CVD (HR=1.20, 95%CI: 1.02-1.42), whereas no statistically significant associations were observed in the other trajectory groups.

Conclusion

Older adults with both lower IC levels and higher long-term PM2.5 exposure had the highest risk of incident CVD. PM2.5-related CVD risk also differed across IC trajectory groups.

, authors=Xiao-chen YANG1, Xiao-yue ZHANG1, Xiao-xiao LING2, Xin-ran LIU1, 3, Chun CHANG1, 3, authorsList=Xiao-chen YANG, Xiao-yue ZHANG, Xiao-xiao LING, Xin-ran LIU, Chun CHANG, authorCompany=null, correspAuthors=Chun CHANG, 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=1311350415699046603, articleId=1311350411202752709, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=内在能力与PM2.5长期暴露对中国老年人心血管疾病发病风险的联合影响分析, 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

探讨内在能力（intrinsic capacity，IC）与长期PM2.5暴露对我国老年人心血管疾病（cardiovascular disease，CVD）发病风险的联合影响，并进一步分析不同IC变化轨迹人群中的环境暴露相关风险特征。

方法

数据来源于中国健康与养老追踪调查（China Health and Retirement Longitudinal Study，CHARLS）。纳入2011年基线时无心血管疾病、年龄≥60岁的3 241名研究对象，并随访至2020年。IC从运动、活力、感觉、认知及心理5个维度进行评估，并按功能缺损数量分为0项、1项、2项及≥3项缺损。长期PM2.5暴露水平基于卫星遥感数据估算，并与研究对象居住地信息匹配。采用Cox比例风险回归模型分析IC与长期PM2.5暴露对CVD发病风险的联合影响，结果以风险比（hazard ratio，HR）和95%置信区间（confidence interval，CI）表示。此外，采用基于群组的轨迹模型（group-based trajectory modelling，GBTM）识别IC变化轨迹，分析不同轨迹组中PM2.5暴露与CVD发病风险的关联。

结果

平均随访为（7.9±2.2）年，共697名研究对象（21.5%）发生CVD事件，发病密度为27.3/1 000人年（95%CI：25.3～29.4）。与“高IC+低PM2.5暴露”组相比，“低IC+高PM2.5暴露”组CVD发病风险升高（HR=1.53，95%CI：1.20～1.96）。识别出3种IC变化轨迹，分别为“低水平—短暂改善型”、“中等水平—持续下降型”及“高水平—稳定改善型”。在“低水平—短暂改善型”轨迹组中，PM2.5暴露每增加10μg/m3，CVD发病风险升高（HR=1.20，95%CI：1.02～1.42），而其余轨迹组中未观察到统计学显著关联。

结论

较低IC水平和较高长期PM2.5暴露共同存在时，老年人CVD发病风险最高；不同IC变化轨迹人群中PM2.5暴露相关的CVD发病风险亦存在差异。

, authors=杨晓晨1, 张晓悦1, 凌晓潇2, 刘欣然1, 3, 常春1, 3, authorsList=杨晓晨, 张晓悦, 凌晓潇, 刘欣然, 常春, authorCompany=null, correspAuthors=常春, authorNote=

杨晓晨（1996—），男，博士在读，研究方向：老年健康促进

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常春，E-mail：
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杨晓晨（1996—），男，博士在读，研究方向：老年健康促进

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J Nutr Health Aging, 2023, 27(3): 174-181., articleTitle=Trajectories of intrinsic capacity: determinants and associations with disability, refAbstract=null), Reference(id=1311350426985918753, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, doi=null, pmid=null, pmcid=null, year=2024, volume=11, issue=11, pageStart=350, pageEnd=null, url=null, language=null, rfNumber=[26], rfOrder=25, authorNames=Sabanayagam C, He F, Chee ML, journalName=J Cardiovasc Dev Dis, refType=null, unstructuredReference=Sabanayagam C, He F, Chee ML, et al. Validity and reliability of self-reported prevalent and incident cardiovascular disease among Asian adults［J］. J Cardiovasc Dev Dis, 2024, 11(11): 350., articleTitle=Validity and reliability of self-reported prevalent and incident cardiovascular disease among Asian adults, refAbstract=null)], funds=[Fund(id=1311350422950998279, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, awardId=2023ZD0508506, language=CN, fundingSource=国家卫生健康委医药卫生科技发展研究中心国家科技重大专项(2023ZD0508506), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1311350415971676364, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, xref=1., ext=[AuthorCompanyExt(id=1311350415980064973, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, companyId=1311350415971676364, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Social Medicine and Health Education, Deans of School of Public Health, Peking University, Beijing 100191, China), AuthorCompanyExt(id=1311350415988453582, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, companyId=1311350415971676364, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.北京大学公共卫生学院社会医学与健康教育系，北京 100191)]), AuthorCompany(id=1311350416072339663, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, xref=2., ext=[AuthorCompanyExt(id=1311350416076533968, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, companyId=1311350416072339663, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.牛津大学纳菲尔德初级保健与行为科学系)]), AuthorCompany(id=1311350416152031441, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, xref=3., ext=[AuthorCompanyExt(id=1311350416156225746, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, companyId=1311350416152031441, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.北京大学医学部老年健康研究中心)])], figs=[ArticleFig(id=1311350419918516472, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=EN, label=Fig.1, caption=Flow chart of participant selection, figureFileSmall=XVX9hj36+I6+/KNm4r1wdA==, figureFileBig=2OrG6DOjZqmAKRCjeiE4yw==, tableContent=null), ArticleFig(id=1311350419985625337, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=CN, label=图1, caption=研究对象纳入与排除流程图, figureFileSmall=XVX9hj36+I6+/KNm4r1wdA==, figureFileBig=2OrG6DOjZqmAKRCjeiE4yw==, tableContent=null), ArticleFig(id=1311350420195340538, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=EN, label=Fig.2, caption=Identified longitudinal trajectories of intrinsic capacity among participants, figureFileSmall=h/D2w9+WzQr1r7GlR+EhqQ==, figureFileBig=ygUkQc1Ywflfm7kngiONSQ==, tableContent=null), ArticleFig(id=1311350420270838011, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=CN, label=图2, caption=研究对象内在能力纵向变化轨迹识别结果, figureFileSmall=h/D2w9+WzQr1r7GlR+EhqQ==, figureFileBig=ygUkQc1Ywflfm7kngiONSQ==, tableContent=null), ArticleFig(id=1311350420346335484, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=EN, label=Table 1, caption=

Baseline characteristics of participants according to intrinsic capacity deficit groups

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总体
（n=3 241）		内在能力缺损项数P值
0（n=1 003）1（n=1 055）2（n=760）≥3（n=423）
年龄（岁）［M（P25，P75）］65.0(62.0, 70.0)64.0(62.0, 69.0)65.0(62.0, 70.0)66.0(62.0, 71.0)67.0(63.0, 73.0)<0.001
性别［n（%）］<0.001
男性1 836(56.6)653(65.1)641(60.8)381(50.1)161(38.1)
女性1 405(43.4)350(34.9)414(39.2)379(49.9)262(61.9)
居住地［n（%）］<0.001
农村2 062(63.6)556(55.4)680(64.5)517(68.0)309(73.0)
城市1 179(36.4)447(44.6)375(35.5)243(32.0)114(27.0)
婚姻状况［n（%）］<0.001
已婚2 681(82.7)134(13.4)166(15.7)151(19.9)109(25.8)
单身或其他560(17.3)869(86.6)889(84.3)609(80.1)314(74.2)
文化程度［n（%）］<0.001
未接受过正式教育918(28.3)163(16.3)256(24.3)276(36.3)223(52.7)
小学1 656(51.1)519(51.7)579(54.9)381(50.1)177(41.8)
初中及以上667(20.6)321(32.0)220(20.9)103(13.6)23(5.4)
吸烟状况［n（%）］<0.001
从不吸烟1 722(53.1)498(49.7)532(50.4)419(55.1)273(64.5)
曾经吸烟369(11.4)131(13.1)125(11.8)80(10.5)33(7.8)
当前吸烟1 150(35.5)374(37.3)398(37.7)261(34.3)117(27.7)
饮酒状况［n（%）］<0.001
从不饮酒2 108(65.0)608(60.6)653(61.9)516(67.9)331(78.3)
曾经饮酒237(7.3)90(9.0)80(7.6)49(6.4)18(4.3)
当前饮酒896(27.6)305(30.4)322(30.5)195(25.7)74(17.5)
地区［n（%）］0.016
北方1 288(39.7)399(39.8)456(43.2)275(36.2)158(37.4)
南方1 953(60.3)604(60.2)599(56.8)485(63.8)265(62.6)
合并症数量［n（%）］<0.001
0种1 002(30.9)376(37.5)348(33.0)183(24.1)95(22.5)
1种1 081(33.4)338(33.7)356(33.7)249(32.8)138(32.6)
≥2种1 158(35.7)289(28.8)351(33.3)328(43.2)190(44.9)
PM2.5（μg/m2）
［M（P25，P75）暴露］		48.1(36.7, 60.8)47.6(35.9, 60.7)48.9(36.9, 61.3)49.1(37.2, 60.8)47.1(39.0, 60.8)0.607
), ArticleFig(id=1311350420434415869, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=CN, label=表1, caption=

不同内在能力缺损组研究对象基线特征比较

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总体
（n=3 241）		内在能力缺损项数P值
0（n=1 003）1（n=1 055）2（n=760）≥3（n=423）
年龄（岁）［M（P25，P75）］65.0(62.0, 70.0)64.0(62.0, 69.0)65.0(62.0, 70.0)66.0(62.0, 71.0)67.0(63.0, 73.0)<0.001
性别［n（%）］<0.001
男性1 836(56.6)653(65.1)641(60.8)381(50.1)161(38.1)
女性1 405(43.4)350(34.9)414(39.2)379(49.9)262(61.9)
居住地［n（%）］<0.001
农村2 062(63.6)556(55.4)680(64.5)517(68.0)309(73.0)
城市1 179(36.4)447(44.6)375(35.5)243(32.0)114(27.0)
婚姻状况［n（%）］<0.001
已婚2 681(82.7)134(13.4)166(15.7)151(19.9)109(25.8)
单身或其他560(17.3)869(86.6)889(84.3)609(80.1)314(74.2)
文化程度［n（%）］<0.001
未接受过正式教育918(28.3)163(16.3)256(24.3)276(36.3)223(52.7)
小学1 656(51.1)519(51.7)579(54.9)381(50.1)177(41.8)
初中及以上667(20.6)321(32.0)220(20.9)103(13.6)23(5.4)
吸烟状况［n（%）］<0.001
从不吸烟1 722(53.1)498(49.7)532(50.4)419(55.1)273(64.5)
曾经吸烟369(11.4)131(13.1)125(11.8)80(10.5)33(7.8)
当前吸烟1 150(35.5)374(37.3)398(37.7)261(34.3)117(27.7)
饮酒状况［n（%）］<0.001
从不饮酒2 108(65.0)608(60.6)653(61.9)516(67.9)331(78.3)
曾经饮酒237(7.3)90(9.0)80(7.6)49(6.4)18(4.3)
当前饮酒896(27.6)305(30.4)322(30.5)195(25.7)74(17.5)
地区［n（%）］0.016
北方1 288(39.7)399(39.8)456(43.2)275(36.2)158(37.4)
南方1 953(60.3)604(60.2)599(56.8)485(63.8)265(62.6)
合并症数量［n（%）］<0.001
0种1 002(30.9)376(37.5)348(33.0)183(24.1)95(22.5)
1种1 081(33.4)338(33.7)356(33.7)249(32.8)138(32.6)
≥2种1 158(35.7)289(28.8)351(33.3)328(43.2)190(44.9)
PM2.5（μg/m2）
［M（P25，P75）暴露］		48.1(36.7, 60.8)47.6(35.9, 60.7)48.9(36.9, 61.3)49.1(37.2, 60.8)47.1(39.0, 60.8)0.607
), ArticleFig(id=1311350420514107646, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=EN, label=Table 2, caption=

Follow-up characteristics and incidence of cardiovascular disease according to intrinsic capacity deficit groups

, figureFileSmall=null, figureFileBig=null, tableContent=
IC缺损项数组n平均随访时间（年）总随访人年CVD发病例数n（%）发病密度
（/1 000人年，95%CI）
0项缺损1 0038.1±2.08 104179（17.8）22.1（19.0～25.6）
1项缺损1 0557.8±2.28 249232（22.0）28.1（24.6～32.0）
2项缺损7607.9±2.25 981185（24.3）30.9（26.6～35.7）
≥3项缺损4237.5±2.53 193101（23.9）31.6（25.8～38.4）
总体3 2417.9±2.225 527697（21.5）27.3（25.3～29.4）
), ArticleFig(id=1311350420589605119, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=CN, label=表2, caption=

不同IC缺损组研究对象随访情况及CVD发病情况

, figureFileSmall=null, figureFileBig=null, tableContent=
IC缺损项数组n平均随访时间（年）总随访人年CVD发病例数n（%）发病密度
（/1 000人年，95%CI）
0项缺损1 0038.1±2.08 104179（17.8）22.1（19.0～25.6）
1项缺损1 0557.8±2.28 249232（22.0）28.1（24.6～32.0）
2项缺损7607.9±2.25 981185（24.3）30.9（26.6～35.7）
≥3项缺损4237.5±2.53 193101（23.9）31.6（25.8～38.4）
总体3 2417.9±2.225 527697（21.5）27.3（25.3～29.4）
), ArticleFig(id=1311350420694462720, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=EN, label=Table 3, caption=

Associations of combined intrinsic capacity status and long-term PM2.5 exposure with incident cardiovascular disease

, figureFileSmall=null, figureFileBig=null, tableContent=
变量未调整调整后
HR (95%CI)P值HR (95%CI)P值
高IC+低PM2.5暴露refref
高IC+高PM2.5暴露1.19(0.89～1.60)0.2341.05(0.78～1.41)0.755
低IC+低PM2.5暴露1.29(1.01～1.64)0.0441.15(0.89～1.47)0.290
低IC+高PM2.5暴露1.89(1.49～2.39)<0.0011.53(1.20～1.96)<0.001
), ArticleFig(id=1311350420778348801, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=CN, label=表3, caption=

内在能力与长期PM2.5暴露联合与心血管疾病发病风险的关联

, figureFileSmall=null, figureFileBig=null, tableContent=
变量未调整调整后
HR (95%CI)P值HR (95%CI)P值
高IC+低PM2.5暴露refref
高IC+高PM2.5暴露1.19(0.89～1.60)0.2341.05(0.78～1.41)0.755
低IC+低PM2.5暴露1.29(1.01～1.64)0.0441.15(0.89～1.47)0.290
低IC+高PM2.5暴露1.89(1.49～2.39)<0.0011.53(1.20～1.96)<0.001
), ArticleFig(id=1311350422401544451, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=EN, label=Table 4, caption=

Model fit indices and group proportions for intrinsic capacity trajectory models

, figureFileSmall=null, figureFileBig=null, tableContent=
组别数BICAvePP组别比例(%)
15 994.97-100
25 242.670.85939.8/60.2
35 189.410.84124.6/45.4/30.0
45 020.300.83924.7/15.2/50.3/9.8
), ArticleFig(id=1311350422460264708, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=CN, label=表4, caption=

内在能力轨迹模型拟合指标及分组结果比较

, figureFileSmall=null, figureFileBig=null, tableContent=
组别数BICAvePP组别比例(%)
15 994.97-100
25 242.670.85939.8/60.2
35 189.410.84124.6/45.4/30.0
45 020.300.83924.7/15.2/50.3/9.8
), ArticleFig(id=1311350422544150789, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=EN, label=Table 5, caption=

Associations of intrinsic capacity trajectories and long-term PM2.5 exposure with incident cardiovascular disease

, figureFileSmall=null, figureFileBig=null, tableContent=
变量未调整调整后
HR (95%CI)P值HR (95%CI)P值
总体人群
内在能力轨迹
轨迹1refref
轨迹20.72(0.56～0.94)0.0160.74(0.57～0.97)0.027
轨迹30.64(0.47～0.87)0.0040.65(0.47～0.89)0.008
PM2.5a1.08(1.00～1.16)0.0471.02(0.93～1.11)0.704
轨迹1亚组
PM2.51.17(1.02～1.34)0.0301.20(1.02～1.42)0.031
轨迹2亚组
PM2.51.12(1.00～1.24)0.0431.00(0.89～1.14)0.947
轨迹3亚组
PM2.50.98(0.84～1.15)0.8410.91(0.76～1.09)0.291
), ArticleFig(id=1311350422615453958, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350411202752709, language=CN, label=表5, caption=

内在能力变化轨迹及长期PM2.5暴露与新发心血管疾病风险的关联

, figureFileSmall=null, figureFileBig=null, tableContent=
变量未调整调整后
HR (95%CI)P值HR (95%CI)P值
总体人群
内在能力轨迹
轨迹1refref
轨迹20.72(0.56～0.94)0.0160.74(0.57～0.97)0.027
轨迹30.64(0.47～0.87)0.0040.65(0.47～0.89)0.008
PM2.5a1.08(1.00～1.16)0.0471.02(0.93～1.11)0.704
轨迹1亚组
PM2.51.17(1.02～1.34)0.0301.20(1.02～1.42)0.031
轨迹2亚组
PM2.51.12(1.00～1.24)0.0431.00(0.89～1.14)0.947
轨迹3亚组
PM2.50.98(0.84～1.15)0.8410.91(0.76～1.09)0.291
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内在能力与PM2.5长期暴露对中国老年人心血管疾病发病风险的联合影响分析
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杨晓晨 1 , 张晓悦 1 , 凌晓潇 2 , 刘欣然 1, 3 , 常春 1, 3
现代预防医学 | 流行病与统计方法 2026,53(16): 2881-2886
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现代预防医学 |流行病与统计方法 2026 , 53 (16) : 2881 -2886
内在能力与PM2.5长期暴露对中国老年人心血管疾病发病风险的联合影响分析
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杨晓晨1, 张晓悦1, 凌晓潇2, 刘欣然1, 3, 常春1, 3
作者信息
  • 1.北京大学公共卫生学院社会医学与健康教育系，北京 100191
  • 2.牛津大学纳菲尔德初级保健与行为科学系
  • 3.北京大学医学部老年健康研究中心
通讯作者:
常春，E-mail：
作者简介:

杨晓晨（1996—），男，博士在读，研究方向：老年健康促进

Joint association of intrinsic capacity and long-term PM2.5 exposure with cardiovascular risk in older Chinese adults
Xiao-chen YANG1, Xiao-yue ZHANG1, Xiao-xiao LING2, Xin-ran LIU1, 3, Chun CHANG1, 3
Affiliations
  • Department of Social Medicine and Health Education, Deans of School of Public Health, Peking University, Beijing 100191, China
出版时间: 2026-08-25 doi: 10.20043/j.cnki.MPM.202604318
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摘要
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目的

探讨内在能力（intrinsic capacity，IC）与长期PM2.5暴露对我国老年人心血管疾病（cardiovascular disease，CVD）发病风险的联合影响，并进一步分析不同IC变化轨迹人群中的环境暴露相关风险特征。

方法

数据来源于中国健康与养老追踪调查（China Health and Retirement Longitudinal Study，CHARLS）。纳入2011年基线时无心血管疾病、年龄≥60岁的3 241名研究对象，并随访至2020年。IC从运动、活力、感觉、认知及心理5个维度进行评估，并按功能缺损数量分为0项、1项、2项及≥3项缺损。长期PM2.5暴露水平基于卫星遥感数据估算，并与研究对象居住地信息匹配。采用Cox比例风险回归模型分析IC与长期PM2.5暴露对CVD发病风险的联合影响，结果以风险比（hazard ratio，HR）和95%置信区间（confidence interval，CI）表示。此外，采用基于群组的轨迹模型（group-based trajectory modelling，GBTM）识别IC变化轨迹，分析不同轨迹组中PM2.5暴露与CVD发病风险的关联。

结果

平均随访为（7.9±2.2）年，共697名研究对象（21.5%）发生CVD事件，发病密度为27.3/1 000人年（95%CI：25.3～29.4）。与“高IC+低PM2.5暴露”组相比，“低IC+高PM2.5暴露”组CVD发病风险升高（HR=1.53，95%CI：1.20～1.96）。识别出3种IC变化轨迹，分别为“低水平—短暂改善型”、“中等水平—持续下降型”及“高水平—稳定改善型”。在“低水平—短暂改善型”轨迹组中，PM2.5暴露每增加10μg/m3，CVD发病风险升高（HR=1.20，95%CI：1.02～1.42），而其余轨迹组中未观察到统计学显著关联。

结论

较低IC水平和较高长期PM2.5暴露共同存在时，老年人CVD发病风险最高；不同IC变化轨迹人群中PM2.5暴露相关的CVD发病风险亦存在差异。

内在能力  /  PM2.5  /  心脑血管疾病  /  队列研究  /  老年人
Objective

To examine the joint association of intrinsic capacity (IC) and long-term fine particulate matter (PM2.5) exposure with incident cardiovascular disease (CVD) among older Chinese adults.

Methods

This prospective cohort study used data from the China Health and Retirement Longitudinal Study (CHARLS). We included 3 241 participants aged ≥60 years who were free of CVD at baseline in 2011 and followed them through 2020. IC was assessed across five domains: locomotion, vitality, sensory function, cognition, and psychological well-being, and categorized by the number of deficits (0, 1, 2, or ≥3). Long-term PM2.5 exposure was estimated using satellite-based data linked to participants’ residential locations. Cox proportional hazards models were used to estimate the association between IC-PM2.5 joint exposure groups and incident CVD, with hazard ratios (HRs) and 95% confidence intervals (CIs) reported. In addition, group-based trajectory modelling (GBTM) was applied to identify IC trajectories, and the association between PM2.5 exposure and CVD risk was further evaluated across different trajectory groups.

Results

During a mean follow-up of 7.9±2.2 years, 697 participants (21.5%) developed incident CVD, with an incidence density of 27.3 per 1 000 person-years (95%CI: 25.3-29.4). Compared with the “high IC + low PM2.5 exposure” group, the adjustedHRs for incident CVD were 1.53 (95%CI: 1.20-1.96) for the “low IC + high PM2.5 exposure” group. Three IC trajectories were further identified: “low-level with transient improvement”, “moderate-level with persistent decline”, and “high-level with stable improvement”. In the “low-level with transient improvement” trajectory group, each 10 μg/m3 increase in PM2.5 exposure was associated with an increased risk of incident CVD (HR=1.20, 95%CI: 1.02-1.42), whereas no statistically significant associations were observed in the other trajectory groups.

Conclusion

Older adults with both lower IC levels and higher long-term PM2.5 exposure had the highest risk of incident CVD. PM2.5-related CVD risk also differed across IC trajectory groups.

Intrinsic capacity  /  PM2.5  /  Cardiovascular disease  /  Cohort study  /  Older adults
杨晓晨, 张晓悦, 凌晓潇, 刘欣然, 常春. 内在能力与PM2.5长期暴露对中国老年人心血管疾病发病风险的联合影响分析. 现代预防医学, 2026 , 53 (16) : 2881 -2886 . DOI: 10.20043/j.cnki.MPM.202604318
Xiao-chen YANG, Xiao-yue ZHANG, Xiao-xiao LING, Xin-ran LIU, Chun CHANG. Joint association of intrinsic capacity and long-term PM2.5 exposure with cardiovascular risk in older Chinese adults[J]. Modern Preventive Medicine, 2026 , 53 (16) : 2881 -2886 . DOI: 10.20043/j.cnki.MPM.202604318
正文
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心血管疾病（cardiovascular disease，CVD）是全球居民发病和死亡的主要原因之一［1］。在我国，CVD占全部死因的40%以上，现患人数约3.3亿［2］。随着人口老龄化进程加快，我国CVD疾病负担预计将进一步加重［3］。除吸烟、不健康饮食及身体活动不足等传统危险因素外［4］，近年来研究逐渐关注衰老相关功能储备下降及环境暴露对心血管风险的影响［5-6］。PM2.5暴露已被公认为是导致不良心血管结局的重要环境危险因素［6-7］。由于年龄相关的生理功能衰退及终生累积的环境暴露，老年人可能对PM2.5所致心血管损害更为敏感［8］。
世界卫生组织将健康老龄化定义为发展和维持功能能力的过程，以促进老年阶段的良好福祉［9］。根据该框架，功能能力由个体内在能力（intrinsic capacity，IC）、所处环境及二者共同作用决定。IC反映个体整体的身心功能储备水平［10］，并影响其在老年阶段维持独立生活和健康状态的能力。研究发现，IC下降与心血管结局风险增加相关［11-12］。然而，目前关于老年人IC状态与空气污染暴露共同影响心血管健康的流行病学证据仍较有限，尤其缺乏关于IC与长期PM2.5暴露联合存在时CVD发病风险特征的研究。此外，不同IC变化轨迹人群中环境暴露相关心血管风险的差异亦有待进一步阐明。
综上，本研究基于中国健康与养老追踪调查（China Health and Retirement Longitudinal Study，CHARLS）队列数据，探讨个体内在能力与长期PM2.5暴露对我国老年人CVD发病风险的联合影响，并进一步分析不同IC变化轨迹人群中的环境暴露相关风险特征，为老年人群心血管疾病精准防控提供科学依据。
1　资料与方法
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1.1　研究对象
本研究使用中国健康与养老追踪调查（CHARLS）公开发布的去标识化数据。CHARLS是一项针对我国45岁及以上成年人群的全国代表性持续性队列研究，采用多阶段、按人口规模比例抽样方法开展调查［13］。原始调查已获北京大学生物医学伦理委员会批准（IRB00001052-11015），所有调查对象均签署知情同意书。
本研究纳入2011年基线调查时年龄≥60岁的受访者7 645人。进一步排除基线时自报已诊断心血管疾病者1 447人、缺乏心血管结局随访信息者474人，以及内在能力各维度数据缺失2 483人。最终纳入3 241名研究对象，并于2013年、2015年、2018年和2020年随访新发心血管疾病事件，纳入流程见图1。
1.2　调查工具和方法
本研究以新发心血管疾病作为主要结局指标，定义为研究对象在随访期间首次报告经医生诊断的心脏病（包括心肌梗死、心绞痛或心力衰竭）或卒中。若研究对象在2013年、2015年、2018年或2020年任一轮随访中报告上述疾病，且2011年基线调查时无相应病史，则判定为新发CVD病例。随访时间自2011年基线调查开始，至首次发生CVD事件或最后一次有效随访时间止，以先发生者为终点。
内在能力依据其5个核心维度进行评估，包括运动、活力、感觉、认知及心理［10］。各维度均构建为二分类变量（0=无缺损，1=有缺损）。具体判定标准如下：运动能力为五次坐立试验完成时间>14 s［14］；活力为体质指数（BMI）≤18.5 kg/m2［15］；感觉功能为自评听力或视力任一项较差；认知功能为延迟词语回忆及精神状态测试得分低于同年龄组均值1个标准差及以上［16］；心理状态为CESD-10量表得分≥10分［17］。将5个维度缺损情况加总形成IC缺损项数（0～5项），数值越高表示功能受损程度越重［12］，并根据IC缺损项数将研究对象分为0项、1项、2项及≥3项缺损组进行分析。
PM2.5暴露数据来源于中国高分辨率空气污染物数据集（China High Air Pollutants，CHAP）。该数据集整合卫星遥感观测、地面监测资料、再分析数据及机器学习方法，可提供覆盖中国大陆、空间分辨率1 km × 1 km的年度PM2.5浓度估计值。既往研究表明，该数据集与地面监测数据具有较高一致性（交叉验证R2=0.94；均方根误差RMSE=5.07 μg/m3）［18］。由于CHARLS仅提供城市级地理信息，本研究根据研究对象所在城市匹配对应年度平均PM2.5浓度。长期PM2.5暴露水平定义为自2011年基线至CVD发病诊断年份或最后一次随访年份（以先发生者为准）期间年度PM2.5浓度的平均值。
协变量包括基线年龄（连续变量）、性别（男、女）、婚姻状况（已婚、未婚/其他）、受教育程度（文盲、小学、中学及以上）、城乡居住地、地理区域（北方、南方）、吸烟状况（从不、既往、当前）、饮酒状况（从不、既往、当前）及自报合并症数量（0种、1种、≥2种）。
1.3　统计学分析
首先，对总体研究对象及不同IC缺损项数组的基线特征进行描述。连续变量以中位数和四分位数表示，分类变量以频数和百分比表示。由于连续变量呈非正态分布，采用Kruskal-Wallis检验比较组间连续变量差异，分类变量采用卡方检验进行比较。
采用Cox比例风险回归模型评估IC与长期PM2.5暴露对CVD发病风险的联合影响，结果以风险比（hazard ratio，HR）及95%置信区间（confidence interval，CI）表示。依据IC缺损项数，将研究对象分为高内在能力（IC）组（IC缺损项数=0）和低内在能力（IC）组（IC缺损项数≥1）；依据总体研究对象长期PM2.5暴露水平的中位数，将PM2.5暴露分为低暴露组（≤中位数）和高暴露组（>中位数）。据此构建4组联合暴露类型：高IC+低PM2.5暴露、高IC+高PM2.5暴露、低IC+低PM2.5暴露以及低IC+高PM2.5暴露。由于高IC代表较好的功能储备状态，而低PM2.5暴露代表较低环境暴露水平，因此“高IC+低PM2.5暴露”组可视为内在能力受损和空气污染暴露均较低的双低风险组，并作为参照组。构建2个模型：模型1纳入IC-PM2.5联合分组变量；模型2在模型1基础上进一步调整年龄、性别、婚姻状况、受教育程度、城乡居住地、地理区域、吸烟、饮酒及慢性病数量等协变量。采用Schoenfeld残差检验比例风险假设，结果显示比例风险假设成立。
进一步采用基于群组的轨迹模型（group-based trajectory modelling，GBTM）识别2011年、2013年和2015年IC变化轨迹。在不同IC轨迹组中，进一步以PM2.5作为连续变量纳入Cox比例风险模型，按每增加10 μg/m3估计其与CVD发病风险的关联。依据贝叶斯信息准则（BIC）、平均后验概率（average posterior probability, AvePP）及各轨迹组样本量确定最佳轨迹分组。所有统计分析均在Stata 18.0及R 4.4.1软件中完成。所有检验均为双侧检验，检验水准α=0.05。
2　结果
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2.1　研究对象基线特征描述
本研究最终纳入3 241名研究对象，年龄中位数（P25，P75）为65岁（62，70）岁，其中男性1 836人，占56.6%。1 003人（30.9%）内在能力（IC）无任何缺损，2 238人（69.1%）至少存在1项缺损，423人（13.1%）存在≥3项缺损。研究对象PM2.5暴露水平的中位数（P25，P75）为48.1 μg/m3（36.7，60.8），不同IC缺损组间PM2.5暴露水平差异无统计学意义（P=0.607）。见表1。
2.2　随访期间心血管疾病发生情况
平均随访时间为（7.9 ± 2.2）年，总计随访25 527人年，共有697人发生新发心血管疾病（CVD）事件，发病密度为27.3/1 000人年（95%CI：25.3～29.4）。不同IC缺损项数组中，0项、1项、2项及≥3项缺损者分别有179例（17.8%）、232例（22.0%）、185例（24.3%）和101例（23.9%）发生CVD事件，对应发病密度分别为22.1/1 000人年（95%CI：19.0～25.6）、28.1/1 000人年（95%CI：24.6～32.0）、30.9/1 000人年（95%CI：26.6～35.7）和31.6/1 000人年（95%CI：25.8～38.4）。见表2。
2.3　内在能力与长期PM2.5暴露联合与CVD发病风险的关联
以“高IC+低PM2.5暴露”组为参照，“低IC+高PM2.5暴露”组CVD发病风险升高，调整后的HR为1.53（95%CI：1.20～1.96）。“高IC+高PM2.5暴露”组和“低IC+低PM2.5暴露”组的CVD发病风险无明显变化（P>0.05）。 见表3。
2.4　内在能力变化轨迹及长期PM2.5暴露与CVD发病风险的关联
1 392名对象完成2011年、2013年和2015年的3次IC评估，共识别出3种不同的IC变化轨迹，见表4、图2。
轨迹1为低水平—短暂改善型（n=357，25.6%），该组研究对象基线IC水平较低，早期略有改善，随后下降至接近基线水平；轨迹2为中等水平—持续下降型（n=668，48.0%），该组研究对象基线IC处于中等水平，并随时间持续下降；轨迹3为高水平—稳定改善型（n=367，26.4%），该组研究对象基线IC水平较高，随访期间呈轻度且持续改善趋势。
以轨迹1组为参照，轨迹2组（HR=0.74，95%CI：0.57～0.97）和轨迹3组（HR=0.65，95%CI：0.47～0.89）的CVD发病风险均较低。在不同IC轨迹组中，PM2.5暴露与CVD发病风险的关联存在差异。轨迹1组中，PM2.5暴露每增加10 μg/m3，CVD发病风险升高（HR=1.20，95%CI：1.02～1.42），而轨迹2组和轨迹3组中未观察到统计学显著关联（表5）。
3　讨论
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本研究基于CHARLS队列数据，系统评估了内在能力与长期PM2.5暴露对心血管疾病发病风险的联合影响。结果显示，同时具有较低IC水平和较高PM2.5暴露的老年人CVD发病风险最高。进一步分析发现，不同IC变化轨迹人群中PM2.5暴露相关风险存在差异，在“低水平—短暂改善型”轨迹组中，PM2.5暴露与CVD发病风险升高相关，而在其余轨迹组中未观察到统计学显著关联。上述结果表明，个体功能状态与环境暴露可能共同影响老年人心血管健康。
既往研究多关注IC或PM2.5暴露与CVD风险之间的独立关联。已有研究表明，较低IC与失能、住院、死亡及CVD风险增加相关［11,14,19］，长期PM2.5暴露亦可增加心血管疾病发病及死亡风险［20］。本研究进一步发现，与“高IC+低PM2.5暴露”组相比，“低IC+高PM2.5暴露”组CVD发病风险最高，而单独存在较低IC或较高PM2.5暴露时风险增加均未达到统计学显著性。该结果提示，在老年人群中，个体功能储备不足与较高环境暴露共同存在时，可能进一步增加CVD发病风险。
本研究结果的潜在机制可能与老年人功能储备下降状态下环境暴露易感性增加有关［8,21］。PM2.5可通过诱导氧化应激、系统性炎症反应、自主神经功能失调及血管内皮损伤等途径促进动脉粥样硬化形成和心血管事件发生［21-22］。既往研究表明，老年人由于年龄相关的生理功能衰退及慢性基础疾病累积，对PM2.5所致心血管损伤更为敏感［8］。与此同时，IC反映个体整体功能储备水平，较低IC通常意味着机体在运动、认知、感觉及心理等多个维度功能受损，维持机体稳态和应对应激的能力下降［19］。已有研究发现，PM2.5暴露本身也可能与衰弱和功能下降相关［23］。当较低IC水平与较高PM2.5暴露共同存在时，机体对炎症反应及血管损伤的代偿能力可能进一步减弱［8］，从而增加老年人CVD发病风险。相关研究亦显示，IC较低老年人对居住环境质量更为敏感，支持性环境有助于缓冲功能下降带来的不良影响［24］。因此，在老龄人群慢病防控中，应同时关注个体功能状态与环境暴露因素，尤其应加强对功能受损老年人的重点保护。
本研究进一步识别出3种不同的IC变化轨迹，其模式与既往基于CHARLS及其他队列研究的结果总体一致［14,15,25］。与“低水平—短暂改善型”相比，“中等水平—持续下降型”和“高水平—稳定改善型”人群的CVD发病风险均较低，提示IC的长期变化趋势与心血管健康密切相关。既往研究亦发现，IC持续恶化轨迹与CVD风险升高显著相关［11］。本研究进一步发现，在“低水平—短暂改善型”轨迹组中，PM2.5暴露与CVD发病风险升高相关，提示长期功能状态较差或波动较大的老年人可能更易受到空气污染暴露的不利影响。上述发现表明，在老年人群健康管理中，应重视IC的动态变化过程，尤其是在高污染环境地区，持续监测IC变化对于识别心血管高危人群具有重要意义。
本研究亦存在一定局限性。首先，PM2.5暴露水平基于城市级年均浓度，可能存在暴露错分。其次，CVD结局基于自报医生诊断，可能受到回忆偏倚和报告偏倚影响，但既往研究表明类似调查中自报CVD具有较好有效性［26］。第三，由于内在能力等关键变量缺失，较高比例的研究对象被排除，可能引入选择偏倚。此外，轨迹分析仅纳入完成多轮IC评估的研究对象，样本量相对有限，相关结果在外推时仍需谨慎解释。
综上，本研究表明，较低IC与较高PM2.5暴露共同存在时，老年人CVD发病风险最高；不同IC变化轨迹人群中PM2.5暴露相关风险亦存在差异。上述结果提示，在制定老年人CVD防控策略时，应将内在能力评估与环境健康管理相结合，以促进健康老龄化。
基金
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  • 国家卫生健康委医药卫生科技发展研究中心国家科技重大专项(2023ZD0508506)
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2026年第53卷第16期
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doi: 10.20043/j.cnki.MPM.202604318
  • 接收时间：2026-04-20
  • 首发时间：2026-09-28
  • 出版时间：2026-08-25
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  • 收稿日期：2026-04-20
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国家卫生健康委医药卫生科技发展研究中心国家科技重大专项(2023ZD0508506)
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    1.北京大学公共卫生学院社会医学与健康教育系，北京 100191
    2.牛津大学纳菲尔德初级保健与行为科学系
    3.北京大学医学部老年健康研究中心

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