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Article(id=1322168419584168645, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322167989802217791, articleNumber=null, orderNo=null, doi=10.12102/j.issn.1009-6493.2026.04.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1745251200000, receivedDateStr=2025-04-22, revisedDate=1769875200000, revisedDateStr=2026-02-01, acceptedDate=null, acceptedDateStr=null, onlineDate=1793159115929, onlineDateStr=2026-10-28, pubDate=1771948800000, pubDateStr=2026-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793159115929, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793159115929, creator=13701087609, updateTime=1793159115929, updator=13701087609, issue=Issue{id=1322167989802217791, tenantId=1146029695717560320, journalId=1220038315760373764, year='2026', volume='40', issue='4', pageStart='529', pageEnd='704', issueExtLink='null', onlineDate='null', pubDate='1771948800000', pubDateStr='2026-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793159013461, creator='13701087609', updateTime=1793159013461, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=542, endPage=548, ext={EN=ArticleExt(id=1322168421450633926, articleId=1322168419584168645, tenantId=1146029695717560320, journalId=1220038315760373764, language=EN, title=Dynamic trajectory of estimated pulse wave velocity in middle-aged and elderly people and its relationship with cardiovascular diseases, columnId=1220689484526572183, journalTitle=Chinese Nursing Research, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the dynamic trajectory of estimated pulse wave velocity in middle-aged and elderly people and its relationship with cardiovascular diseases.

Methods

Based on the population cohort data from the China health and retirement longitudinal study(CHARLS),general information and laboratory indicators of the population were collected. The group-based trajectory model (GBTM) was used to construct the heterogeneous trajectories of the estimated pulse wave velocity dynamics in the community among the elderly. Logistic regression analysis was applied to explore the relationship between the estimated pulse wave velocity dynamic trajectory and cardiovascular diseases.

Results

A total of 5 933 participants were included in the analysis, among whom 1 112 cases (18.7%) developed cardiovascular diseases.The GBTM analysis revealed four estimated trajectories of pulse wave velocity changes:the low-level stable group(30.0%),the medium-level ascending group(39.6%),the ascending and stable group(23.0%),and the high-level ascending group(7.4%).Logistic regression analysis showed that, after adjusting for confounding factors, compared with the low-level stable group,the risk of cardiovascular diseases significantly increased in the medium-level ascending group, the ascending and stable group,and the high-level ascending group.

Conclusions

The estimated pulse wave velocity trajectories of the elderly in the community showed population heterogeneity.The higher estimated pulse wave velocity trajectories was correlated with the occurrence of cardiovascular diseases.It is suggested that medical staff should pay attention to the changes in the estimated pulse wave velocity of the elderly and formulate corresponding intervention strategies based on different trajectories.

, authors=Mingliang HUANG, Qiuping MA, authorsList=Mingliang HUANG, Qiuping MA, authorCompany=null, correspAuthors=Qiuping MA, authorNote=null, correspAuthorsNote=
MA Qiuping， E-mail：
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目的

探讨社区中老年人估计脉搏波速度动态变化轨迹及其与心血管疾病的关系。

方法

基于中国健康与养老追踪调查（CHARLS）的队列数据，收集人群一般资料及实验室指标。采用群组轨迹模型（GBTM）构建社区中老年人估计脉搏波速度动态变化的异质性轨迹，应用Logistic回归分析探讨估计脉搏波速度动态变化轨迹与心血管疾病的关系。

结果

共5 933名参与者纳入分析，其中发生心血管疾病1 112例（18.7%）。群组轨迹模型分析显示，存在4种估计脉搏波速度变化轨迹：低水平稳定组（30.0%）、中水平上升组（39.6%）、上升后平稳组（23.0%）和高水平上升组（7.4%）。Logistic回归分析显示，校正混杂因素后，相对于低水平稳定组，中水平上升组、上升后平稳组和高水平上升组心血管疾病的发生风险明显增加。

结论

社区中老年人的估计脉搏波速度变化轨迹存在群体异质性，较高的估计脉搏波速度轨迹与心血管疾病的发生相关。提示医务人员应重视中老年人的估计脉搏波速度变化，并根据不同轨迹制定对应干预策略。

, authors=黄明亮, 马秋平*, *, authorsList=黄明亮, 马秋平, authorCompany=null, correspAuthors=马秋平, authorNote=

黄明亮，主管护师，硕士研究生

, correspAuthorsNote=
马秋平，E-mail：
MA Qiuping， E-mail：
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pageEnd=252, url=null, language=null, rfNumber=36, rfOrder=35, authorNames=PETERSEN K S, BLANCH N, KEOGH J B, journalName=Arteriosclerosis,Thrombosis,and Vascular Biology, refType=null, unstructuredReference=PETERSEN K S,BLANCH N,KEOGH J B,et al.Effect of weight loss on pulse wave velocity:systematic review and meta-analysis[J].Arteriosclerosis,Thrombosis,and Vascular Biology,2015,35(1):243-252., articleTitle=Effect of weight loss on pulse wave velocity:systematic review and meta-analysis, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1322530319249555822, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, xref=1, ext=[AuthorCompanyExt(id=1322530319257944431, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, companyId=1322530319249555822, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Guangxi University of Chinese Medicine, Guangxi 530200 China), AuthorCompanyExt(id=1322530319266333040, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, companyId=1322530319249555822, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1广西中医药大学，广西 530200)])], figs=[ArticleFig(id=1322530322172985732, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, language=EN, label=Figure 1, caption=Trajectory of estimated pulse wave velocity changes in the elderly population, figureFileSmall=1ND6eok5EZjPmA1MQAfulg==, figureFileBig=nlJmNGW0DB6X8JFvrFw+rg==, tableContent=null), ArticleFig(id=1322530322240094597, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, language=CN, label=图1, caption=中老年人估计脉搏波速度变化轨迹, figureFileSmall=1ND6eok5EZjPmA1MQAfulg==, figureFileBig=nlJmNGW0DB6X8JFvrFw+rg==, tableContent=null), ArticleFig(id=1322530322344952198, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, language=EN, label=Table 1, caption=

Group trajectory model group iteration situation

, figureFileSmall=null, figureFileBig=null, tableContent=
类别BICAvePP类别占比（%）
231 528.650.963/0.94165.0/35.0
329 467.510.940/0.921/0.94639.0/43.5/17.5
428 582.870.930/0.904/0.901/0.92830.0/39.6/23.0/7.4
428 565.490.930/0.904/0.901/0.92830.0/39.6/23.0/7.4
428 558.360.929/0.905/0.901/0.92930.0/39.6/23.0/7.4
528 095.250.906/0.860/0.872/0.917/0.93219.7/32.9/27.9/15.2/4.3
), ArticleFig(id=1322530322407866759, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, language=CN, label=表1, caption=

群组轨迹模型分组迭代情况

, figureFileSmall=null, figureFileBig=null, tableContent=
类别BICAvePP类别占比（%）
231 528.650.963/0.94165.0/35.0
329 467.510.940/0.921/0.94639.0/43.5/17.5
428 582.870.930/0.904/0.901/0.92830.0/39.6/23.0/7.4
428 565.490.930/0.904/0.901/0.92830.0/39.6/23.0/7.4
428 558.360.929/0.905/0.901/0.92930.0/39.6/23.0/7.4
528 095.250.906/0.860/0.872/0.917/0.93219.7/32.9/27.9/15.2/4.3
), ArticleFig(id=1322530322470781320, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, language=EN, label=Table 2, caption=

Comparison of general conditions of two groups of research subjects

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项目分类未发生心血管疾病组（n=4 821）心血管疾病组（n=1 112）统计值P
身高(cm)158.0±8.4158.0±8.5t=-0.3290.742
体重(kg)58.7±11.461.4±12.3t=-6.712<0.001
体质指数（kg/m2）23.6±3.924.6±4.4t=-7.450<0.001
收缩压(mmHg)128.4±20.1132.6±19.9t=-6.323<0.001
舒张压(mmHg)75.3±11.776.7±12.3t=-3.519<0.001
年龄（岁）62.1±8.764.3±8.4t=-7.582<0.001
认知功能评分（分）14.0（9.0,18.0）14.0（9.0,18.0）Z=-0.3450.730
ADL（分）6.0（5.9,6.0）6.0（6.0,6.0）Z=-6.201<0.001
腰围(cm)84.0±13.888.1±12.5t=-9.164<0.001
夜间睡眠时间(h)6.4±1.96.1±2.1t=3.495<0.001
握力(kg)27.8±9.325.8±9.3t=6.636<0.001
血小板计数(×109/L)204.0±76.7205.0±72.9t=-0.3010.764
三酰甘油(mg/dL)112.4（82.3,165.9）124.8（87.6,174.3）Z=-0.8100.418
肌酐(mg/dL)0.81±0.250.82±0.26t=-1.4810.139
血尿素氮(mg/dL)15.8±4.615.7±4.7t=0.2900.772
高密度脂蛋白胆固醇(mg/dL)52.1±11.950.2±12.1t=4.664<0.001
低密度脂蛋白胆固醇(mg/dL)103.0±28.3102.0±28.9t=0.8120.417
总胆固醇(mg/dL)185.0±36.4185.0±36.9t=0.1030.918
空腹血糖(mg/dL)103.0±35.0104.0±37.5t=-0.7170.474
尿酸(mg/dL)4.91±1.385.02±1.44t=-2.5010.012
胱抑素C (mg/L)0.86±0.210.92±0.25t=-8.118<0.001
C反应蛋白(mg/L)1.4（0.8,2.6）1.6（0.9,2.9）Z=-4.139<0.001
糖化血红蛋白(%)5.99±1.056.10±1.00t=-3.1330.002
性别（例）女2 525634χ2=7.8120.006
男2 296478
婚姻状况（例）已婚4 177928χ2=7.6500.006
未婚644184
健康状况（例）一般2 592490χ2=261.106<0.001
好1 102109
差1 127513
高血压（例）否3 530531χ2=271.406<0.001
是1 291581
糖尿病（例）否4 219910χ2=24.870<0.001
是602202
饮酒（例）否3 155817χ2=26.320<0.001
是1 666295
抑郁（例）否3 339674χ2=30.873<0.001
是1 482438
生活满意度（例）一般2 664641χ2=12.8880.002
好2 073436
差8435
躯体疼痛（例）否24142χ2=2.9700.086
是4 5801 070
文化程度（例）专科及以上6622χ2=2.4130.491
中学1 391322
小学2 097483
文盲1 267285
吸烟（例）否2 687628χ2=0.2000.663
是2 134484
估计脉搏波速度轨迹（例）低水平稳定组1 576200χ2=106.802<0.001
中水平上升组1 883472
上升后平稳组1 023339
高水平上升组339101
), ArticleFig(id=1322530322575638922, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, language=CN, label=表2, caption=

两组研究对象的一般情况比较

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项目分类未发生心血管疾病组（n=4 821）心血管疾病组（n=1 112）统计值P
身高(cm)158.0±8.4158.0±8.5t=-0.3290.742
体重(kg)58.7±11.461.4±12.3t=-6.712<0.001
体质指数（kg/m2）23.6±3.924.6±4.4t=-7.450<0.001
收缩压(mmHg)128.4±20.1132.6±19.9t=-6.323<0.001
舒张压(mmHg)75.3±11.776.7±12.3t=-3.519<0.001
年龄（岁）62.1±8.764.3±8.4t=-7.582<0.001
认知功能评分（分）14.0（9.0,18.0）14.0（9.0,18.0）Z=-0.3450.730
ADL（分）6.0（5.9,6.0）6.0（6.0,6.0）Z=-6.201<0.001
腰围(cm)84.0±13.888.1±12.5t=-9.164<0.001
夜间睡眠时间(h)6.4±1.96.1±2.1t=3.495<0.001
握力(kg)27.8±9.325.8±9.3t=6.636<0.001
血小板计数(×109/L)204.0±76.7205.0±72.9t=-0.3010.764
三酰甘油(mg/dL)112.4（82.3,165.9）124.8（87.6,174.3）Z=-0.8100.418
肌酐(mg/dL)0.81±0.250.82±0.26t=-1.4810.139
血尿素氮(mg/dL)15.8±4.615.7±4.7t=0.2900.772
高密度脂蛋白胆固醇(mg/dL)52.1±11.950.2±12.1t=4.664<0.001
低密度脂蛋白胆固醇(mg/dL)103.0±28.3102.0±28.9t=0.8120.417
总胆固醇(mg/dL)185.0±36.4185.0±36.9t=0.1030.918
空腹血糖(mg/dL)103.0±35.0104.0±37.5t=-0.7170.474
尿酸(mg/dL)4.91±1.385.02±1.44t=-2.5010.012
胱抑素C (mg/L)0.86±0.210.92±0.25t=-8.118<0.001
C反应蛋白(mg/L)1.4（0.8,2.6）1.6（0.9,2.9）Z=-4.139<0.001
糖化血红蛋白(%)5.99±1.056.10±1.00t=-3.1330.002
性别（例）女2 525634χ2=7.8120.006
男2 296478
婚姻状况（例）已婚4 177928χ2=7.6500.006
未婚644184
健康状况（例）一般2 592490χ2=261.106<0.001
好1 102109
差1 127513
高血压（例）否3 530531χ2=271.406<0.001
是1 291581
糖尿病（例）否4 219910χ2=24.870<0.001
是602202
饮酒（例）否3 155817χ2=26.320<0.001
是1 666295
抑郁（例）否3 339674χ2=30.873<0.001
是1 482438
生活满意度（例）一般2 664641χ2=12.8880.002
好2 073436
差8435
躯体疼痛（例）否24142χ2=2.9700.086
是4 5801 070
文化程度（例）专科及以上6622χ2=2.4130.491
中学1 391322
小学2 097483
文盲1 267285
吸烟（例）否2 687628χ2=0.2000.663
是2 134484
估计脉搏波速度轨迹（例）低水平稳定组1 576200χ2=106.802<0.001
中水平上升组1 883472
上升后平稳组1 023339
高水平上升组339101
), ArticleFig(id=1322530322646942091, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, language=EN, label=Table 3, caption=

Logistic regression analysis of the association between estimated pulse wave velocity trajectories and cardiovascular diseases in middle-aged and elderly people

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类别模型1模型2
回归系数标准误OR值[95%CI]回归系数标准误OR值[95%CI]
中水平上升组0.6810.0911.975[1.653，2.361]0.5630.1091.755[1.418，2.173]
上升后平稳组0.9600.0982.611[2.156，3.163]0.6790.1461.973[1.481，2.627]
高水平上升组0.8530.1362.348[1.799，3.065]0.4910.2171.633[1.067，2.501]
), ArticleFig(id=1322530322722439564, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322168419584168645, language=CN, label=表3, caption=

中老年人估计脉搏波速度轨迹与心血管疾病关联的Logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
类别模型1模型2
回归系数标准误OR值[95%CI]回归系数标准误OR值[95%CI]
中水平上升组0.6810.0911.975[1.653，2.361]0.5630.1091.755[1.418，2.173]
上升后平稳组0.9600.0982.611[2.156，3.163]0.6790.1461.973[1.481，2.627]
高水平上升组0.8530.1362.348[1.799，3.065]0.4910.2171.633[1.067，2.501]
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中老年人估计脉搏波速度动态变化轨迹及其与心血管疾病的关系
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黄明亮 , 马秋平 *, *
护理研究 | 科研论著 2026,40(4): 542-548
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护理研究 |科研论著 2026 , 40 (4) : 542 -548
中老年人估计脉搏波速度动态变化轨迹及其与心血管疾病的关系
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黄明亮，主管护师，硕士研究生

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黄明亮，主管护师，硕士研究生

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黄明亮, 马秋平*, *
作者信息
  • 1广西中医药大学，广西 530200
通讯作者:
马秋平，E-mail：
MA Qiuping， E-mail：
作者简介:

黄明亮，主管护师，硕士研究生

Dynamic trajectory of estimated pulse wave velocity in middle-aged and elderly people and its relationship with cardiovascular diseases
Mingliang HUANG, Qiuping MA
Affiliations
  • 1Guangxi University of Chinese Medicine, Guangxi 530200 China
    • Corresponding Author:
    MA Qiuping， E-mail：
出版时间: 2026-02-25 doi: 10.12102/j.issn.1009-6493.2026.04.003
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摘要
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目的

探讨社区中老年人估计脉搏波速度动态变化轨迹及其与心血管疾病的关系。

方法

基于中国健康与养老追踪调查（CHARLS）的队列数据，收集人群一般资料及实验室指标。采用群组轨迹模型（GBTM）构建社区中老年人估计脉搏波速度动态变化的异质性轨迹，应用Logistic回归分析探讨估计脉搏波速度动态变化轨迹与心血管疾病的关系。

结果

共5 933名参与者纳入分析，其中发生心血管疾病1 112例（18.7%）。群组轨迹模型分析显示，存在4种估计脉搏波速度变化轨迹：低水平稳定组（30.0%）、中水平上升组（39.6%）、上升后平稳组（23.0%）和高水平上升组（7.4%）。Logistic回归分析显示，校正混杂因素后，相对于低水平稳定组，中水平上升组、上升后平稳组和高水平上升组心血管疾病的发生风险明显增加。

结论

社区中老年人的估计脉搏波速度变化轨迹存在群体异质性，较高的估计脉搏波速度轨迹与心血管疾病的发生相关。提示医务人员应重视中老年人的估计脉搏波速度变化，并根据不同轨迹制定对应干预策略。

中老年人  /  估计脉搏波速度  /  心血管疾病  /  群组轨迹模型
Objective

To explore the dynamic trajectory of estimated pulse wave velocity in middle-aged and elderly people and its relationship with cardiovascular diseases.

Methods

Based on the population cohort data from the China health and retirement longitudinal study(CHARLS),general information and laboratory indicators of the population were collected. The group-based trajectory model (GBTM) was used to construct the heterogeneous trajectories of the estimated pulse wave velocity dynamics in the community among the elderly. Logistic regression analysis was applied to explore the relationship between the estimated pulse wave velocity dynamic trajectory and cardiovascular diseases.

Results

A total of 5 933 participants were included in the analysis, among whom 1 112 cases (18.7%) developed cardiovascular diseases.The GBTM analysis revealed four estimated trajectories of pulse wave velocity changes:the low-level stable group(30.0%),the medium-level ascending group(39.6%),the ascending and stable group(23.0%),and the high-level ascending group(7.4%).Logistic regression analysis showed that, after adjusting for confounding factors, compared with the low-level stable group,the risk of cardiovascular diseases significantly increased in the medium-level ascending group, the ascending and stable group,and the high-level ascending group.

Conclusions

The estimated pulse wave velocity trajectories of the elderly in the community showed population heterogeneity.The higher estimated pulse wave velocity trajectories was correlated with the occurrence of cardiovascular diseases.It is suggested that medical staff should pay attention to the changes in the estimated pulse wave velocity of the elderly and formulate corresponding intervention strategies based on different trajectories.

middle-aged and elderly people  /  estimated pulse wave velocity  /  cardiovascular diseases  /  group-based trajectory model
黄明亮, 马秋平. 中老年人估计脉搏波速度动态变化轨迹及其与心血管疾病的关系. 护理研究, 2026 , 40 (4) : 542 -548 . DOI: 10.12102/j.issn.1009-6493.2026.04.003
Mingliang HUANG, Qiuping MA. Dynamic trajectory of estimated pulse wave velocity in middle-aged and elderly people and its relationship with cardiovascular diseases[J]. Chinese Nursing Research, 2026 , 40 (4) : 542 -548 . DOI: 10.12102/j.issn.1009-6493.2026.04.003
正文
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随着社会经济的发展、国民生活方式的变化以及人口老龄化和城镇化进程的加速，居民不健康的生活方式日益突出，心血管疾病(cardiovascular diseases，CVD)对居民健康的影响更加显著。《中国心血管健康与疾病报告2023概要》[1]报道，中国心血管疾病患病率处于持续上升阶段，目前心血管疾病现患病人约3.3亿例，其中脑卒中1 300万例，冠心病1 139万例，成为导致我国死亡和伤残的主要病因。因此，识别可预测心血管疾病风险的风险因素，对预防心血管疾病、降低其发病率和死亡率有重要意义。既往研究表明，年龄和血压是成人动脉硬化的主要影响因素，对心脑血管疾病的全因死亡具有独立预测价值[2-3]。而估计脉搏波速度(estimated pulse wave velocity，ePWV)基于年龄和血压计算获得，可用于评估动脉僵硬度的指标[4]。已有研究表明，估计脉搏波速度具有与颈动脉-股动脉脉搏波速度（cfPWV）相似的预测能力[5]，并与高血压[6]、脑卒中[7-8]的发生密切相关。然而，目前估计脉搏波速度与心血管疾病关系的相关研究主要基于欧美人群，在中国中老年人群中尚缺乏大样本的相关研究[9]。此外，估计脉搏波速度可随时间变化而变化，单个时间点的估计脉搏波速度可能无法揭示其变化趋势对心血管疾病发病的影响。因此，本研究收集2011—2015年中国健康与养老追踪调查(China health and retirement longitudinal study，CHARLS)中3个时间点的估计脉搏波速度数据，通过群组轨迹模型(group-based trajectory model，GBTM)将估计脉搏波速度变化趋势可视化，根据其变化特征将研究对象分为若干亚组，并进一步分析估计脉搏波速度变化轨迹与心血管疾病的关系。
1　对象与方法
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1.1　对象
本研究数据来自CHARLS项目的公开数据。该项目是由北京大学国家发展研究院对中国45岁及以上人群进行的一项纵向研究，使用统一的问卷，包括家庭问卷和个人问卷，涵盖基本人口特征、健康状况、经济状况和生活方式[10]。CHARLS计划协议符合《赫尔辛基宣言》，并获得北京大学生物医学伦理审查委员会的伦理批准（批准号：IRB00001052-11015）[11]。纳入标准：年龄≥45岁；完成2011年CHARLS的基线调查；2013年和2015年均完成随访。排除标准：2015年随访时心血管疾病数据缺失的个体；基线时自报患有记忆相关疾病（如痴呆、脑萎缩、帕金森病等）；关键变量（性别、年龄、文化程度、体质指数、收缩压和舒张压等）缺失的个体；接受精神科治疗或心理治疗的个体。根据上述标准，最终5 933名参与者纳入分析。本研究收集了2011年、2013年和2015年3个时间点纳入研究对象的年龄、收缩压和舒张压，并以2015年是否发生心血管疾病为随访结局进行分析。
1.2　方法
1.2.1　心血管疾病的评估
研究结局为心血管疾病事件，包括心脏病和脑卒中。参考相关研究[12-13]，心血管疾病事件通过以下问题进行评估：您是否被医生告知您已被诊断患有心脏病、心绞痛、冠心病、心力衰竭或其他心脏问题？您是否被医生告知您已被诊断患有脑卒中？报告患有心脏病或脑卒中的参与者被定义为患有心血管疾病。
1.2.2　估计脉搏波速度的计算
估计脉搏波速度的计算公式为：估计脉搏波速度=9.587-0.402×年龄+4.560×10-3×年龄2-2.621×10-5×年龄2×平均血压+3.176×10-3×平均血压×年龄-1.832×10-2×平均血压[7,14]。其中平均血压=舒张压+0.4×(收缩压-舒张压)。
1.2.3　协变量资料收集
综合CHARLS的调查问卷及既往相关文献[15-16]，本研究协变量纳入了社会人口学特征、生活方式因素、体格检查、血生化指标、健康状况和功能等数据。社会人口学特征包括年龄、性别、文化程度、婚姻状况。生活方式因素包括饮酒、吸烟。体格检查数据包括身高、体重、腰围和握力。血生化指标包括肌酐、血尿素氮、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇、总胆固醇、空腹血糖、尿酸、胱抑素C、C反应蛋白和三酰甘油。健康状况和功能包括自觉躯体健康状况、生活满意度、躯体疼痛、高血压、糖尿病、抑郁[17]、认知功能[18]和日常生活活动能力（ADL）[19]。抑郁采用流调中心抑郁量表（CES-D10）评估。认知功能评估采用CHARLS调查的认知测验模块。ADL采用改良版日常生活能力量表测量。
1.2.4　统计学方法
采用Stata15.0中的Traj包进行群组轨迹分析，以识别具有相似轨迹的潜在群体[20]。基于群组轨迹模型构建方法[21]，通过贝斯信息准则(BIC)、赤池信息准则(AIC)、平均后验概率(AvePP)和轨迹组占比选择最优模型[22]。采用RStudio进行统计分析，符合正态分布的定量资料以均数±标准差（x±s）表示，不符合正态分布的定量资料以中位数（四分位数）[M(P25,P75)]表示，定性资料用例数、百分比（%）表示。采用多元Logistic回归分析探索不同估计脉搏波速度轨迹与心血管疾病的关系。以P<0.05为差异有统计学意义。
2　结果
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2.1　中老年人估计脉搏波速度变化轨迹
采用群组轨迹模型进行模型拟合，综合BIC、AvePP和轨迹组占比等评价指标发现，随着类别数由2~5依次迭代，BIC的绝对值逐渐变小，当轨迹组设置为5时，BIC的绝对值最小，但未满足每个轨迹组的比例大于5%的条件[23]。因此，本研究最终将最佳类别数定为4类，见表1。根据估计脉搏波速度的变化趋势，分别将各轨迹命名为低水平稳定组（30.0%）、中水平上升组（39.6%）、上升后平稳组（23.0%）和高水平上升组（7.4%），见图1。
2.2　研究人群的基本情况
本研究共纳入5 933名参与者，男2 774人，女3 159人。2015年随访时发生心血管疾病事件病人1 112例，占18.7%。发生心血管疾病组与未发生心血管疾病组一般资料比较见表2。
2.3　中老年人估计脉搏波速度轨迹组与心血管疾病关联的Logistic回归分析
Logistic回归分析显示，以估计脉搏波速度低水平稳定组为参照，在未校正协变量的模型1中，中水平上升组、上升后平稳组和高水平上升组心血管疾病发生的风险分别是低水平稳定组的1.975倍、2.611倍和2.348倍；在校正了除年龄、收缩压、舒张压以外单因素分析有统计学意义（P<0.05)的协变量后，中水平上升组、上升后平稳组和高水平上升组心血管疾病发生的风险仍增加，见表3。
3　讨论
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3.1　社区中老年人估计脉搏波速度变化情况
既往研究通常使用cfPWV评估动脉硬化程度，而cfPWV的测量多依赖专业人员和专业设备，限制了其在临床实践中的广泛使用。估计脉搏波速度是一种根据年龄和平均血压计算的指标，能可靠地反映动脉硬化程度[24-25]。本研究使用基于群体的轨迹建模分析方法，根据估计脉搏波速度的动态变化模式确定了4个不同的群体：低水平稳定组、中水平上升组、上升后平稳组和高水平上升组。从估计脉搏波速度的动态变化轨迹图可看出，大部分的中老年人估计脉搏波速度处于上升状态。Song等[26]探讨了估计脉搏波速度与肌少症风险的关系，发现75%参与者的估计脉搏波速度处于较高水平。Liu等[27]研究表明，根据估计脉搏波速度四分位数分组后，第一四分位数（P25）组估计脉搏波速度的均值为7.5 m/s。
3.2　社区中老年人估计脉搏波速度与心血管疾病的关系
既往研究已经证明了估计脉搏波速度对心血管事件的预测价值[9,28]。潘锦滨等[29]研究指出，估计脉搏波速度是中国中老年人群心脑血管疾病的独立危险因素，估计脉搏波速度每增加1个单位，心脑血管疾病患病率增加8%。季春鹏等[30]结果显示，在校正传统心血管危险因素后，估计脉搏波速度每增加1 m/s，心血管事件发生风险增加38%，全因死亡风险增加53%；估计脉搏波速度≥14 m/s者发生心血管事件和全因死亡的风险分别为估计脉搏波速度<14 m/s者的3.39倍和4.21倍。以上研究虽然提供了大量有价值的信息，但是单个时间点测量的估计脉搏波速度可能无法反映其动态变化情况，而以往研究表明测量的脉搏波传导速度进展与死亡率有关[31-33]。本研究估计脉搏波速度在4年随访内的变化轨迹也显示出与心血管疾病有很强的相关性，表明了估计脉搏波速度的动态变化可以更好地提示动脉僵硬度的恶化。因此，需要控制可改变的危险因素，如通过控制体重与血压、限制饮食中的钠、适当锻炼或使用药物等方式进行有效干预，以减缓估计脉搏波速度进展[34-36]。
4　小结
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基于年龄和血压计算的估计脉搏波速度与脉搏波传导速度具有良好的一致性，可作为脉搏波传导速度的潜在替代指标。鉴于目前脉搏波传导速度需要昂贵的测量设备、复杂的操作流程且尚未在临床推广的现状，使用具有全国代表性的中老年人样本研究估计脉搏波速度与心血管疾病之间的关系具有重要意义。
本研究采用群组轨迹模型拟合了我国中老年人估计脉搏波速度的变化轨迹，更好地解释了估计脉搏波速度动态变化对心血管疾病发病的影响，为估计脉搏波速度变化的临床意义提供了依据。但也存在一定的局限性，由于估计脉搏波速度是由年龄和血压计算得出，且与年龄和血压存在显著共线性，在多因素分析时本研究并未校正年龄和血压，这也是所有估计脉搏波速度相关研究所面临的共性问题；本研究是基于CHARLS数据库的二次分析，在筛选符合研究的人群时排除了变量存在缺失值的人群，可能会造成一定的选择偏倚。后续仍需考虑在大样本队列研究及不同种族中进一步分析验证。

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2026年第40卷第4期
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doi: 10.12102/j.issn.1009-6493.2026.04.003
  • 接收时间：2025-04-22
  • 首发时间：2026-10-28
  • 出版时间：2026-02-25
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  • 收稿日期：2025-04-22
  • 修回日期：2026-02-01
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    1广西中医药大学，广西 530200

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2种不同金属材料的力学参数
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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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