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Article(id=1241067200635785635, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241067197318091153, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202410150, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1728662400000, receivedDateStr=2024-10-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773823078545, onlineDateStr=2026-03-18, pubDate=1741536000000, pubDateStr=2025-03-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773823078545, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773823078545, creator=13701087609, updateTime=1773823078545, updator=13701087609, issue=Issue{id=1241067197318091153, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='5', pageStart='769', pageEnd='960', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773823077754, creator=13701087609, updateTime=1773823268053, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241067995544482681, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241067197318091153, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241067995544482682, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241067197318091153, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=831, endPage=835, ext={EN=ArticleExt(id=1241067208676266810, articleId=1241067200635785635, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study on the association between cardiorespiratory fitness and stroke and its subtypes, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the impact of different levels of cardiorespiratory fitness on the occurrence of stroke.

Methods

This study was based on the Kailun cohort study, which included a total of 37 547 participants, followed up until December 31, 2019.Cardiorespiratory fitness (Estimated cardiorespiratory fitness, eCRF) was estimated using a non-exercise algorithm, and the average eCRF values from measurements taken in 2006, 2008, and 2010 were calculated, standardized, and grouped according to gender-specific tertiles. Cox regression models were employed to explore the relationship between varying levels of eCRF and the incidence of stroke and its subtypes.

Results

During a median follow-up of 9.05 (8.67, 9.33) years, a total of 2 100 cases of stroke (5.59%) were observed, including 1 899 (5.06%) ischemic strokes and 226 (0.60%) hemorrhagic strokes. After adjusting for confounding factors, compared to the low average eCRF group, the high eCRF group exhibited a 28% reduction in stroke risk (HR=0.72, 95%CI: 0.62-0.82), a 23% reduction in ischemic stroke risk (HR=0.77, 95%CI: 0.67-0.89), and a 40% reduction in hemorrhagic stroke risk (HR=0.60, 95%CI: 0.39-0.91).

Conclusion

Higher levels of cardiorespiratory fitness can reduce the risk of stroke and its subtypes.

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目的

探讨不同水平的心肺适能对脑卒中发生的影响。

方法

本研究基于开滦队列研究，共纳入了37 547名研究对象，随访至2019年12月31日。采用非运动算法估计心肺适能（estimated cardiorespiratory fitness, eCRF），计算2006、2008和2010年三次测量的eCRF平均值，将其标准化并按性别特异性三分位数分组。采用Cox回归模型探讨eCRF不同水平与脑卒中及其亚型的关系。

结果

中位随访9.05 (8.67，9.33)年期间，共观察到2 100例（5.59%）脑卒中，其中包括1 899（5.06%）例缺血性卒中和226例（0.60%）出血性卒中。调整混杂因素后，与平均eCRF低水平组相比，高水平组脑卒中发生风险降低28%（HR=0.72，95%CI：0.62～0.82），缺血性卒中发生风险降低23%（HR=0.77，95%CI：0.67～0.89），出血性卒中发生风险降低40%（HR=0.60，95%CI：0.39～0.91）。

结论

较高的心肺适能水平可以降低脑卒中及其亚型的发生风险。

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罗艳侠，E-mail:
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罗会（1999—），男，硕士在读，研究方向：疾病预测模型与统计决策

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注：A为脑卒中；B为缺血性卒中；C为出血性卒中。

, figureFileSmall=xylgk0Gbme0uuWvPesuLzA==, figureFileBig=1PqSDiVv83TBAMzSeWp6rA==, tableContent=null), ArticleFig(id=1241067224337797424, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241067200635785635, language=EN, label=Figure 2, caption=Stratified analysis of the relationship between mean eCRF and stroke and its subtypes, figureFileSmall=BHFpxtI86n4djwJSwcCnMA==, figureFileBig=mUEB0iAROu+cy3vqb5qtzw==, tableContent=null), ArticleFig(id=1241067224442655030, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241067200635785635, language=CN, label=图2, caption=平均eCRF和脑卒中及其亚型关系的分层分析

注：调整年龄、性别、饮酒、高血压、糖尿病、血脂异常和父母脑卒中病史。

, figureFileSmall=BHFpxtI86n4djwJSwcCnMA==, figureFileBig=mUEB0iAROu+cy3vqb5qtzw==, tableContent=null), ArticleFig(id=1241067224543318332, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241067200635785635, language=EN, label=Table 1, caption=

Baseline characteristics of subjects ［（），n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量合计（n=37 547）平均eCRF水平F/H/χ2值P值
低（n=12 515）中（n=12 516）高（n=12 516）
年龄（岁）47.96±11.2955.17±11.7246.83±8.9641.87±8.638 936.049<0.001
男性30 122 (80.22)10 040 (80.22)10 041 (80.23)10 041 (80.23)0.0001.000
积极体力活动4 809 (12.81)1 630 (13.02)1 547 (12.36)1 632 (13.04)3.3720.185
目前吸烟13 426 (35.76)4 016 (32.09)4 858 (38.81)4 552 (36.37)126.251<0.001
目前饮酒13 613 (36.26)3 815 (30.50)4 856 (38.80)4 942 (39.49)270.904<0.001
收缩压（mm Hg）130.95±18.82140.20±19.53130.41±16.92122.23±15.256 026.488<0.001
舒张压（mm Hg）84.75±10.6687.95±11.0385.07±10.0981.18±9.722 584.658<0.001
高血压16 959 (45.17)8 122 (64.90)5 537 (44.24)3 300 (26.37)3 757.938<0.001
空腹血糖（mg/dl）5.67±1.616.02±1.895.67±1.645.33±1.131 617.230<0.001
糖尿病3 925 (10.45)2 169 (17.33)1 229 (9.82)527 (4.21)1 158.898<0.001
总胆固醇（mg/dl）192.00±46.04196.92±39.30193.81±54.10185.25±42.63683.406<0.001
甘油三酯（mg/dl）67.35±68.0373.70±72.5671.88±75.8156.43±51.861 252.731<0.001
血脂异常21 005 (55.94)8 117 (64.86)7 379 (58.96)5 509 (44.02)1 172.122<0.001
BMI （kg/m2）25.29±3.2527.63±3.3425.37±2.2622.86±2.0114 480.341<0.001
腰围（cm）88.56±10.0694.91±9.7988.95±7.9381.81±7.6811 432.980<0.001
静息心率（bpm）73.75±10.3376.12±11.2573.88±9.7571.23±9.321 250.652<0.001
2006年eCRF （METs）11.29±1.6210.04±1.3211.39±1.8212.44±1.3515 214.327<0.001
2008年eCRF （METs）11.16±1.639.85±1.3211.27±1.1512.35±1.3116 163.094<0.001
2010年eCRF （METs）10.97±1.699.56±1.3611.10±1.1712.24±1.3316 767.788<0.001
平均eCRF （METs）11.14±1.589.82±1.2311.25±1.0712.34±1.2618 325.047<0.001
父母卒中病史1 240 (3.30)360 (2.88)451 (3.60)429 (3.43)11.2720.004
), ArticleFig(id=1241067224639787329, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241067200635785635, language=CN, label=表1, caption=

研究对象基线特征［（），n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量合计（n=37 547）平均eCRF水平F/H/χ2值P值
低（n=12 515）中（n=12 516）高（n=12 516）
年龄（岁）47.96±11.2955.17±11.7246.83±8.9641.87±8.638 936.049<0.001
男性30 122 (80.22)10 040 (80.22)10 041 (80.23)10 041 (80.23)0.0001.000
积极体力活动4 809 (12.81)1 630 (13.02)1 547 (12.36)1 632 (13.04)3.3720.185
目前吸烟13 426 (35.76)4 016 (32.09)4 858 (38.81)4 552 (36.37)126.251<0.001
目前饮酒13 613 (36.26)3 815 (30.50)4 856 (38.80)4 942 (39.49)270.904<0.001
收缩压（mm Hg）130.95±18.82140.20±19.53130.41±16.92122.23±15.256 026.488<0.001
舒张压（mm Hg）84.75±10.6687.95±11.0385.07±10.0981.18±9.722 584.658<0.001
高血压16 959 (45.17)8 122 (64.90)5 537 (44.24)3 300 (26.37)3 757.938<0.001
空腹血糖（mg/dl）5.67±1.616.02±1.895.67±1.645.33±1.131 617.230<0.001
糖尿病3 925 (10.45)2 169 (17.33)1 229 (9.82)527 (4.21)1 158.898<0.001
总胆固醇（mg/dl）192.00±46.04196.92±39.30193.81±54.10185.25±42.63683.406<0.001
甘油三酯（mg/dl）67.35±68.0373.70±72.5671.88±75.8156.43±51.861 252.731<0.001
血脂异常21 005 (55.94)8 117 (64.86)7 379 (58.96)5 509 (44.02)1 172.122<0.001
BMI （kg/m2）25.29±3.2527.63±3.3425.37±2.2622.86±2.0114 480.341<0.001
腰围（cm）88.56±10.0694.91±9.7988.95±7.9381.81±7.6811 432.980<0.001
静息心率（bpm）73.75±10.3376.12±11.2573.88±9.7571.23±9.321 250.652<0.001
2006年eCRF （METs）11.29±1.6210.04±1.3211.39±1.8212.44±1.3515 214.327<0.001
2008年eCRF （METs）11.16±1.639.85±1.3211.27±1.1512.35±1.3116 163.094<0.001
2010年eCRF （METs）10.97±1.699.56±1.3611.10±1.1712.24±1.3316 767.788<0.001
平均eCRF （METs）11.14±1.589.82±1.2311.25±1.0712.34±1.2618 325.047<0.001
父母卒中病史1 240 (3.30)360 (2.88)451 (3.60)429 (3.43)11.2720.004
), ArticleFig(id=1241067224753033543, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241067200635785635, language=EN, label=Table 2, caption=

Association of mean eCRF levels with stroke and its subtypes

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结局平均eCRF水平趋势性检验P值
低中高
脑卒中 (n=2 100)
例数[n (%)]1 081 (8.64)634 (5.07)385 (3.08)
发病率[千人年，(95%CI)]10.40 (9.78～11.00)5.77 (5.34～6.24)3.44 (3.11～3.80)
模型1参照组0.53 (0.48～0.59)0.31 (0.27～0.34)<0.001
模型2参照组0.77 (0.69～0.86)0.54 (0.47～0.62)<0.001
模型3参照组0.88 (0.79～0.98)0.72 (0.62～0.82)<0.001
缺血性卒中 (n=1 899)
例数[n (%)]977 (7.81)573 (4.58)349 (2.79)
发病率[千人年，(95%CI)]9.34 (8.77～9.94)5.20 (4.79～5.65)3.11 (2.80～3.46)
模型1参照组0.58 (0.52～0.65)0.35 (0.31～0.40)<0.001
模型2参照组0.80 (0.71～0.89)0.59 (0.51～0.68)<0.001
模型3参照组0.91(0.81～1.02)0.77 (0.67～0.89)<0.001
出血性卒中 (n=226)
例数[n (%)]118 (0.94)67 (0.54)41 (0.33)
发病率[千人年，(95%CI)]1.10 (0.92～1.32)0.60 (0.47～0.77)0.36 (0.27～0.49)
模型1参照组0.59 (0.44～0.80)0.36 (0.25～0.52)<0.001
模型2参照组0.70 (0.51～0.98)0.48 (0.32～0.72)<0.001
模型3参照组0.79 (0.57～1.10)0.60 (0.39～0.91)<0.001
), ArticleFig(id=1241067224853696842, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241067200635785635, language=CN, label=表2, caption=

平均eCRF水平与脑卒中及其亚型的关联

, figureFileSmall=null, figureFileBig=null, tableContent=
结局平均eCRF水平趋势性检验P值
低中高
脑卒中 (n=2 100)
例数[n (%)]1 081 (8.64)634 (5.07)385 (3.08)
发病率[千人年，(95%CI)]10.40 (9.78～11.00)5.77 (5.34～6.24)3.44 (3.11～3.80)
模型1参照组0.53 (0.48～0.59)0.31 (0.27～0.34)<0.001
模型2参照组0.77 (0.69～0.86)0.54 (0.47～0.62)<0.001
模型3参照组0.88 (0.79～0.98)0.72 (0.62～0.82)<0.001
缺血性卒中 (n=1 899)
例数[n (%)]977 (7.81)573 (4.58)349 (2.79)
发病率[千人年，(95%CI)]9.34 (8.77～9.94)5.20 (4.79～5.65)3.11 (2.80～3.46)
模型1参照组0.58 (0.52～0.65)0.35 (0.31～0.40)<0.001
模型2参照组0.80 (0.71～0.89)0.59 (0.51～0.68)<0.001
模型3参照组0.91(0.81～1.02)0.77 (0.67～0.89)<0.001
出血性卒中 (n=226)
例数[n (%)]118 (0.94)67 (0.54)41 (0.33)
发病率[千人年，(95%CI)]1.10 (0.92～1.32)0.60 (0.47～0.77)0.36 (0.27～0.49)
模型1参照组0.59 (0.44～0.80)0.36 (0.25～0.52)<0.001
模型2参照组0.70 (0.51～0.98)0.48 (0.32～0.72)<0.001
模型3参照组0.79 (0.57～1.10)0.60 (0.39～0.91)<0.001
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心肺适能与脑卒中及其亚型的关联性研究
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罗会 1 , 田雪 1 , 陈朔华 2 , 吴寿岭 2 , 王安心 3, 4 , 罗艳侠 1
现代预防医学 | 流行病与统计方法 2025,52(5): 831-835
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现代预防医学 | 流行病与统计方法 2025, 52(5): 831-835
心肺适能与脑卒中及其亚型的关联性研究
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罗会1, 田雪1, 陈朔华2, 吴寿岭2, 王安心3, 4, 罗艳侠1
作者信息
  • 1.首都医科大学公共卫生学院，北京 100069
  • 2.开滦总医院心内科
  • 3.首都医科大学附属北京天坛医院北京市神经外科研究所流行病学研究室
  • 4.首都医科大学临床流行病学与临床试验教研室

    • 罗会（1999—），男，硕士在读，研究方向：疾病预测模型与统计决策

通讯作者:

罗艳侠，E-mail:
Study on the association between cardiorespiratory fitness and stroke and its subtypes
Hui LUO1, Xue TIAN1, Shuo-hua CHEN2, Shou-ling WU2, An-xin WANG3, 4, Yan-xia LUO1
Affiliations
  • School of Public Health, Capital Medical University, Beijing 100069, China
出版时间: 2025-03-10 doi: 10.20043/j.cnki.MPM.202410150
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摘要
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目的

探讨不同水平的心肺适能对脑卒中发生的影响。

方法

本研究基于开滦队列研究，共纳入了37 547名研究对象，随访至2019年12月31日。采用非运动算法估计心肺适能（estimated cardiorespiratory fitness, eCRF），计算2006、2008和2010年三次测量的eCRF平均值，将其标准化并按性别特异性三分位数分组。采用Cox回归模型探讨eCRF不同水平与脑卒中及其亚型的关系。

结果

中位随访9.05 (8.67，9.33)年期间，共观察到2 100例（5.59%）脑卒中，其中包括1 899（5.06%）例缺血性卒中和226例（0.60%）出血性卒中。调整混杂因素后，与平均eCRF低水平组相比，高水平组脑卒中发生风险降低28%（HR=0.72，95%CI：0.62～0.82），缺血性卒中发生风险降低23%（HR=0.77，95%CI：0.67～0.89），出血性卒中发生风险降低40%（HR=0.60，95%CI：0.39～0.91）。

结论

较高的心肺适能水平可以降低脑卒中及其亚型的发生风险。

心肺适能  /  脑卒中  /  缺血性卒中  /  出血性卒中
Objective

To investigate the impact of different levels of cardiorespiratory fitness on the occurrence of stroke.

Methods

This study was based on the Kailun cohort study, which included a total of 37 547 participants, followed up until December 31, 2019.Cardiorespiratory fitness (Estimated cardiorespiratory fitness, eCRF) was estimated using a non-exercise algorithm, and the average eCRF values from measurements taken in 2006, 2008, and 2010 were calculated, standardized, and grouped according to gender-specific tertiles. Cox regression models were employed to explore the relationship between varying levels of eCRF and the incidence of stroke and its subtypes.

Results

During a median follow-up of 9.05 (8.67, 9.33) years, a total of 2 100 cases of stroke (5.59%) were observed, including 1 899 (5.06%) ischemic strokes and 226 (0.60%) hemorrhagic strokes. After adjusting for confounding factors, compared to the low average eCRF group, the high eCRF group exhibited a 28% reduction in stroke risk (HR=0.72, 95%CI: 0.62-0.82), a 23% reduction in ischemic stroke risk (HR=0.77, 95%CI: 0.67-0.89), and a 40% reduction in hemorrhagic stroke risk (HR=0.60, 95%CI: 0.39-0.91).

Conclusion

Higher levels of cardiorespiratory fitness can reduce the risk of stroke and its subtypes.

Cardiorespiratory fitness  /  Stroke  /  Ischemic stroke  /  Hemorrhagic stroke
罗会, 田雪, 陈朔华, 吴寿岭, 王安心, 罗艳侠. 心肺适能与脑卒中及其亚型的关联性研究. 现代预防医学, 2025 , 52 (5) : 831 -835 . DOI: 10.20043/j.cnki.MPM.202410150
Hui LUO, Xue TIAN, Shuo-hua CHEN, Shou-ling WU, An-xin WANG, Yan-xia LUO. Study on the association between cardiorespiratory fitness and stroke and its subtypes[J]. Modern Preventive Medicine, 2025 , 52 (5) : 831 -835 . DOI: 10.20043/j.cnki.MPM.202410150
正文
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脑卒中是一种常见的神经系统疾病，主要包括缺血性卒中(ischemic stroke, IS)和出血性卒中(intracerebral hemorrhage, ICH)[1]，其发病率呈上升趋势[2]，是我国居民成人致死、致残的首位病因[3-4]。2021—2022年，中国成年人脑卒中粗发病率为496.7/10万[5]。因此，确定可改变的危险因素对脑卒中的初级预防至关重要。心肺适能（cardiorespiratory fitness）综合反映了一个人的心脏、肺、血管运送和利用氧气的能力[6]。研究表明，较高的心肺适能水平可以降低脑卒中的发生风险[7]。2016年，美国心脏协会发表声明将其作为“第五大生命体征”，强调了心肺适能测量在医疗保健中的重要性[8]。心肺运动试验是评估心肺适能的金标准，然而，由于心肺运动试验费用昂贵等因素使心肺适能在临床实践中没有被广泛应用[9]。基于此，有研究者采用易于获取的临床指标开发了方程模型以实现非运动方式估计心肺适能（estimated cardiorespiratory fitness, eCRF）[10]。研究表明eCRF与脑卒中之间的关联存在种族异质性，在不同脑卒中亚型中的结论也不一致[11]。因此，本研究基于开滦研究（注册号：Chi-CTR-TRNC-11001489）的数据，评估eCRF与脑卒中及其亚型的关系，以期为脑卒中的防治提供依据。
1　资料与方法
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1.1　研究对象
研究对象来源于开滦研究人群。2006年6月—2007年10月，共有101 510名年龄在18～98岁的参与者(包括81 110名男性和20 400名女性)进行了健康体检，此后每两年进行一次体检。纳入标准：（1）2006、2008和2010年参加开滦健康体检的职工；（2）同意参加本研究并签署知情同意书。排除标准：（1）2010年脑卒中病史和死亡者（36 772例）；（2）不符合eCRF算法应用条件者（17 348例）；（3）eCRF计算指标数据缺失者（9 843例）。最终纳入了37 547名参与者。本研究遵守赫尔辛基宣言，并已通过开滦总医院伦理委员会批准（批号：200605）。
1.2　资料收集
采用问卷调查收集参与者人口统计学数据，如年龄、性别、吸烟和饮酒状况、体力活动水平、疾病史以及父母脑卒中病史。通过IPAQ简表记录体力活动，并将其分类为不积极(每周活动<80 min)或积极(每周活动≥80 min)[12]。体重指数(body mass index, BMI) = 体重(kg)/身高的二次方(m2)。在脐部水平测量腰围（waist circumference, WC）。受试者仰卧休息5 min后，采用10-s 12导联心电图评估静息心率（resting heart rate, RHR）。使用自动分析仪(Hitachi 747, Hitachi)测量实验室指标，如空腹血糖、总胆固醇、甘油三酯、高密度脂蛋白胆固醇和低密度脂蛋白胆固醇。当参与者静坐时，通过水银血压计测量3次血压，采用3次读数的平均值进行分析。
1.3　eCRF计算及分组
eCRF根据Jackson AS等人[10]开发的性别特异性公式计算：男性eCRF (METs) =21.287 0 +(0.165 4×年龄)-(0.002 3×年龄2)-(0.231 8×BMI)-(0.033 7×WC) -(0.039 0×RHR) +(0.635 1×体力活动)-(0.426 3×目前吸烟)；女性eCRF (METs) =14.787 3 +(0.115 9×年龄)-(0.001 7×年龄2) -(0.153 4×BMI)-(0.008 8×WC) -(0.364×RHR) +(0.598 7×体力活动)-(0.299 4×目前吸烟)。
年龄、BMI、WC和RHR作为连续变量。体力活动和目前吸烟都是二分类变量，不积极体力活动和目前不吸烟的值为0，积极体力活动和目前吸烟的值为1。为了排除单次测量偶然因素的影响，本研究计算2006、2008和2010年eCRF的平均值，将其标准化并按性别特异性三分位数分为3组［mean（SD）, 0（1）］，以最低三分位数组作为参照组评估eCRF水平与脑卒中及其亚型的关系。
1.4　随访及终点事件确定
主要结局是首次发生脑卒中，包括IS、 ICH以及蛛网膜下腔出血。医生每年查阅住院病历（二级及三级医院），核实脑卒中发生情况。由于蛛网膜下腔出血组样本量有限(n=45)，脑卒中亚型分析没有包括该亚型。所有参与者自2006年开始，每两年随访一次，直到2019年12月31日，或直到发生脑卒中，以先到者为准。
1.5　统计分析方法
使用SAS 9.4软件进行数据分析，正态或近似正态分布的计量资料用（）表示，组间比较采用方差分析；偏态分布的计量资料采用［M（P25，P75）］表示，组间比较采用秩检验（Wilcoxon）；计数资料用频数和百分比来表示，组间比较采用χ2检验。采用Kaplan-Meier法绘制生存曲线，计算各组人群中脑卒中及其亚型的累积发病率，并用Log-rank法进行检验。采用Cox比例风险回归模型评估平均eCRF水平与脑卒中及其亚型发生风险的关系，计算风险比(hazard ratios, HR)和相应的95%置信区间(confidence intervals, CI)。模型1未调整，模型2调整年龄和性别，模型3在模型2的基础上进一步调整饮酒、高血压、糖尿病、血脂异常和父母脑卒中病史。此外，按性别和年龄(<60岁vs≥60岁)进行了分层分析。双侧检验水准α=0.05。
2　结果
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2.1　调查对象基线特征
本研究包括37 547例研究对象，其中男性30 122例(占80.22%)，平均年龄为（47.96±11.29)岁。调查对象的基线特征见表1，结果显示三组研究对象年龄、吸烟、饮酒、收缩压、舒张压、高血压、空腹血糖、糖尿病、总胆固醇、甘油三酯、血脂异常、BMI、腰围、静息心率和父母脑卒中病史差异具有统计学意义，性别和体力活动差异无统计学意义。
2.2　不同eCRF水平的脑卒中发病率
在中位随访9.05 (8.67，9.33) 年期间，共观察到2 100例（5.59%）脑卒中，其中包括1 899例（5.06%）IS和226例（0.60%）ICH。平均eCRF低、中、高水平组脑卒中累积发病率分别为8.64%、5.07%、3.08%；IS累积发病率分别为7.81%、4.58%、2.79%；ICH累积发病率分别为0.94%、0.54%、0.33%，见表2。各组之间累积发病率差异均有统计学意义(P<0. 001)，见图1。
2.3　平均eCRF水平和新发脑卒中之间关系分析
调整了其他可能的混杂因素后的模型3显示，与平均eCRF低水平组相比，平均eCRF高水平组脑卒中发生风险降低28% (HR=0.72，95%CI：0.62~0.82)，IS发生风险降低23%（HR=0.77，95%CI：0.67～0.89），ICH发生风险降低40%（HR=0.60，95%CI：0.39～0.91），见表2。分层分析结果显示，性别、年龄和平均eCRF对脑卒中的影响没有显著的交互作用(交互作用P >0.05)，见图2。
3　讨论
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基于开滦前瞻性队列研究发现，与eCRF低水平组的参与者相比，高水平组脑卒中及其亚型发生风险显著降低。
以往研究主要通过运动测试评估心肺适能，发现心肺适能与脑卒中发病风险呈负相关[7]。心肺运动测试评估心肺适能需要专业设备和训练有素的人员进行面对面的评估，成本较高、耗费时间且不易获得，限制其在临床应用上的广泛评估[9]。相比之下，eCRF使用简便、易于获取的临床数据，能够在临床实践和大型流行病学研究中广泛应用，具有较高的成本效益。目前，国内关于eCRF与脑卒中亚型之间关联的研究较为匮乏。本研究采用eCRF方法，而非直接测量，结果表明eCRF水平与脑卒中亚型的发生风险呈负相关，与Liu Y等人[13]的研究结果一致。然而，也有研究报道eCRF与脑卒中[14]和ICH[11]的关联无统计学意义，可能与观察到的结局事件较少且基于单次eCRF评估有关。
目前，eCRF和脑卒中发病之间确切的生物学机制尚不明确。然而，已有研究表明，eCRF水平与高血压、糖尿病、慢性肾病等[9]常见脑卒中危险因素密切相关，这提示eCRF与脑卒中之间可能存在类似的关联。此外，eCRF是心肺适能的预测指标，而较高水平的心肺适能有助于改善心脏结构和功能、调节血压、减轻炎症反应、优化代谢健康和血管内皮功能、改善自主神经系统的平衡，从而降低脑卒中发病风险[15]。因此，我们有理由推测eCRF与脑卒中的发生存在一定的相关性。
本研究有以下几个优势。首先，由于收集的数据来自大型社区样本，因此减少了选择偏倚。其次，eCRF算法是基于美国人群开发的，本研究为探索其在中国人群中的适用性提供了重要契机，有助于验证其在中国人群中的预测效果并推动本土化应用。最后，我们使用2006、2008和2010年三次测量的平均eCRF水平来分析eCRF与脑卒中及其亚型之间的关系，在一定程度上排除了单次测量偶然因素的影响。然而，这项研究仍存在一定局限性。第一，由于该研究的参与者仅限于中国唐山社区，这可能对研究人群的代表性有一定的影响。第二，由于研究的参与者主要是煤矿工人，女性的数量相对较少，结果的推广性受限。第三，尽管本研究调整了很多因素，但仍然存在潜在的残留混淆因素，包括饮食模式、教育水平、心理因素和社会经济地位等。
综上，本研究发现较高的eCRF水平可以降低脑卒中的发生风险，提示在中国人群中，eCRF可以作为一个有用的工具，在临床实践和大型流行病学研究中预测脑卒中的发生风险。
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doi: 10.20043/j.cnki.MPM.202410150
  • 接收时间：2024-10-12
  • 首发时间：2026-03-18
  • 出版时间：2025-03-10
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  • 收稿日期：2024-10-12
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    1.首都医科大学公共卫生学院，北京 100069
    2.开滦总医院心内科
    3.首都医科大学附属北京天坛医院北京市神经外科研究所流行病学研究室
    4.首都医科大学临床流行病学与临床试验教研室

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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
Number of
species		 占总种数比例
Percentage of total
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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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