Article(id=1324078255841607926, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078175000605624, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202509092, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1756915200000, receivedDateStr=2025-09-04, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614456377, onlineDateStr=2026-11-02, pubDate=1769270400000, pubDateStr=2026-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614456377, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614456377, creator=13701087609, updateTime=1793614456377, 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=193, endPage=199, ext={EN=ArticleExt(id=1324078256076488951, articleId=1324078255841607926, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between Body Roundness Index and mortality risk in patients with cardiovascular disease, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate association between Body Roundness Index (BRI) and all-cause and cardiovascular disease (CVD)-specific mortality among patients with CVD.

Methods

A total of 188 428 CVD patients from UK Biobank were included. Cox proportional hazards regression and restricted cubic spline (RCS) analyses were used to examine the association and dose-response relationship between BRI and risks of deaths. Subgroup and sensitivity analyses were also conducted.

Results

Over a median follow-up of 12.75 years, 21 548 deaths occurred, including 5 367 CVD-related deaths. In multivariable Cox models, higher BRI was positively associated with risks of all-cause, CVD, and ischemic heart disease (IHD) mortality (P for trend <0.001). Compared with the lowest quintile (Q1), participants in the highest quintile (Q5) had 32% higher risk of all-cause mortality (HR=1.32, 95% CI: 1.26-1.38), 71% higher risk of CVD mortality (HR=1.71, 95% CI: 1.55-1.89), and 104% higher risk of IHD mortality (HR=2.04, 95% CI: 1.76-2.37); no significant association was observed for stroke mortality. RCS analyses indicated a J-shaped association of BRI with all-cause and CVD mortality. With BRI=4.45 as the threshold, relatively flat mortality risk below the threshold and a steep increase above it. BRI was positively associated with IHD mortality without clear evidence of nonlinearity, and showed no association with stroke mortality.

Conclusion

Among patients with CVD, BRI exhibits a J-shaped association with all-cause and CVD mortality, a positive association with IHD mortality, and no association with stroke mortality.

, authors=Jing-ting LIANG1, 2, Yan-xin SUN1, 2, Hui-xian LI2, Ming-xing NI1, 2, Hui-ying LIANG1, 2, authorsList=Jing-ting LIANG, Yan-xin SUN, Hui-xian LI, Ming-xing NI, Hui-ying LIANG, authorCompany=null, correspAuthors=Hui-ying LIANG, 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=1324078257183785216, articleId=1324078255841607926, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=身体圆度指数与心血管疾病患者死亡风险的关联研究, 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

探讨心血管疾病(Cardiovascular Disease,CVD)患者的身体圆度指数(Body Roundness Index,BRI)与全因及CVD特异性死亡的关联。

方法

纳入UK Biobank的188 428名CVD患者,采用Cox比例风险回归模型和限制性立方样条(Restricted cubic spline,RCS)分析BRI与死亡风险的关联和剂量反应关系,并进行亚组分析和敏感性分析。

结果

在中位随访12.75年期间,共21 548人死亡,其中5 367人死于CVD。多变量Cox比例风险回归模型显示,BRI与全因、CVD及缺血性心脏病(Ischemic Heart Disease,IHD)死亡风险呈正相关(P趋势<0.001):与Q1相比,Q5 全因、CVD和IHD死亡的HR(95% CI)分别为1.32(1.26~1.38)、1.71(1.55~1.89)和2.04(1.76~2.37),未发现与卒中死亡风险有关。RCS分析表明,BRI与全因及CVD死亡风险呈“J 型”关联,以BRI=4.45为阈值,低水平时风险平缓,超过阈值后风险陡升;BRI与IHD死亡风险呈正相关,未见非线性;BRI与卒中死亡风险不相关。

结论

在CVD患者中,BRI与全因及CVD死亡风险呈“J 型”关联,与IHD死亡风险呈正相关,但与卒中死亡风险无关。

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梁靖婷(2000—),女,硕士在读,研究方向:公共卫生

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梁会营,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=c+U/9CBZ0WGTNxNlCa6v1A==, magXml=0LLjzwBKGAGf76f0aIoIhw==, pdfUrl=null, pdf=iX1qDTt3NPUuaYMGXvPT9w==, pdfFileSize=1103835, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=pMMJEYONuMtBckA6Hcn11g==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=ADQN7Oq3G9eGtIjQl6EUUg==, mapNumber=null, fund=null)}, authors=[Author(id=1324078257586438407, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, 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=1324078257670324490, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, authorId=1324078257586438407, language=EN, stringName=Jing-ting LIANG, firstName=Jing-ting, middleName=null, lastName=LIANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=School of Public Health, China Medical University, Shenyang, Liaoning 110122, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1324078257762599179, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, authorId=1324078257586438407, language=CN, stringName=梁靖婷, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1.中国医科大学公共卫生学院,辽宁 沈阳 110122
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Front Public Health, 2023, 11: 1107158., articleTitle=Association of body roundness index and its trajectories with all-cause and cardiovascular mortality among a Chinese middle-aged and older population: A retrospective cohort study, refAbstract=null)], funds=[Fund(id=1324078260912521527, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, awardId=2022YFC3601600, language=CN, fundingSource=国家重点研发计划项目(2022YFC3601600), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324078257414471937, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, xref=1., ext=[AuthorCompanyExt(id=1324078257427054850, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, companyId=1324078257414471937, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, China Medical University, Shenyang, Liaoning 110122, China), AuthorCompanyExt(id=1324078257435443459, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, companyId=1324078257414471937, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中国医科大学公共卫生学院,辽宁 沈阳 110122)]), AuthorCompany(id=1324078257510940932, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, xref=2., ext=[AuthorCompanyExt(id=1324078257519329541, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, companyId=1324078257510940932, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.南方医科大学附属广东省人民医院(广东省医学科学院)医学大数据中心)])], figs=[ArticleFig(id=1324078259696173355, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=EN, label=Fig.1, caption=Dose response relationship between BRI and the risks of all-cause and cardiovascular specific mortality among cardiovascular patients, figureFileSmall=iIVnlXQO8x8nt1PfzwBUeQ==, figureFileBig=pMMJEYONuMtBckA6Hcn11g==, tableContent=null), ArticleFig(id=1324078259788448044, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=CN, label=图1, caption=心血管患者中BRI与全因死亡和心血管特异性死亡风险的剂量反应关系, figureFileSmall=iIVnlXQO8x8nt1PfzwBUeQ==, figureFileBig=pMMJEYONuMtBckA6Hcn11g==, tableContent=null), ArticleFig(id=1324078259977191725, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=EN, label=Fig.2, caption=Fully adjusted associations between BRI and mortality risk among cardiovascular patients stratified by risk factors, figureFileSmall=L1B7LPrDAAo4nc3NrLRyYg==, figureFileBig=cmrygRTwo39j9qd+/ER2FQ==, tableContent=null), ArticleFig(id=1324078260061077806, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=CN, label=图2, caption=心血管患者中BRI与死亡风险的完全调整关联按危险因素分层, figureFileSmall=L1B7LPrDAAo4nc3NrLRyYg==, figureFileBig=cmrygRTwo39j9qd+/ER2FQ==, tableContent=null), ArticleFig(id=1324078260144963887, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=EN, label=Table 1, caption=

Baseline characteristics of study participants stratified by BRI Quintiles[M(P25, P75),n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群Q1(-0.559, 3.25)Q2(3.25, 4.07)Q3(4.07, 4.85)
n188 42837 68637 68637 686
年龄(岁)a61(54, 65)59(52, 64)60(54, 65)61(55, 65)
性别=男95 359(50.61)10 227(27.14)19 574(51.94)22 731(60.32)
种族=白人173 408(92.03)35 336(93.76)34 879(92.55)34 518(91.59)
学历=大学51 553(27.36)13 364(35.46)11 618(30.83)10 098(26.80)
就业情况=是86 614(45.97)19 263(51.11)18 019(47.81)17 259(45.80)
汤森剥夺指数a-2.01(-3.57, 0.83)-2.38(-3.78, 0.05)-2.32(-3.72, 0.19)-2.13(-3.63, 0.58)
吸烟状况
目前19 108(10.14)3 932(10.43)3 808(10.10)3 814(10.12)
先前74 324(39.44)11 735(31.14)13 961(37.05)15 550(41.26)
从不94 996(50.42)22 019(58.43)19 917(52.85)18 322(48.62)
饮酒状况
目前170 719(90.60)34 617(91.86)34 809(92.37)34 543(91.66)
先前8 428(4.47)1 414(3.75)1 342(3.56)1 537(4.08)
从不9 281(4.93)1 655(4.39)1 535(4.07)1 606(4.26)
饮食=健康29 842(15.84)8 471(22.48)6 683(17.73)5 522(14.65)
高血压史=是126 569(67.17)18 878(50.09)23 597(62.61)26 090(69.23)
糖尿病史=是19 307(10.25)967(2.57)1 929(5.12)3 042(8.07)
变量Q4(4.85, 5.92)Q5(5.92, 23.6)Z或χ2P
n37 68537 685
年龄(岁)a61(56, 65)61(55, 65)1 963.563<0.001
性别=男22 837(60.60)19 990(53.04)11 347.788<0.001
种族=白人34 383(91.24)34 292(91.00)265.380<0.001
学历=大学8 911(23.65)7 562(20.07)2 749.012<0.001
就业情况=是16 611(44.08)15 462(41.03)878.200<0.001
汤森剥夺指数a-1.86(-3.47, 1.02)-1.10(-3.11, 2.11)3 248.177<0.001
吸烟状况1 964.086<0.001
目前3 801(10.09)3 753(9.96)
先前16 339(43.36)16 739(44.42)
从不17 545(46.56)17 193(45.62)
饮酒状况974.017<0.001
目前34 117(90.53)32 633(86.59)
先前1 705(4.52)2 430(6.45)
从不1 863(4.94)2 622(6.96)
饮食=健康4 832(12.82)4 334(11.50)2 176.858<0.001
高血压史=是27 970(74.22)30 034(79.70)8 942.556<0.001
糖尿病史=是4 677(12.41)8 692(23.06)10 613.711<0.001
), ArticleFig(id=1324078260237238576, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=CN, label=表1, caption=

研究对象的基本特征(按BRI分位数进行分组)[M(P25, P75),n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群Q1(-0.559, 3.25)Q2(3.25, 4.07)Q3(4.07, 4.85)
n188 42837 68637 68637 686
年龄(岁)a61(54, 65)59(52, 64)60(54, 65)61(55, 65)
性别=男95 359(50.61)10 227(27.14)19 574(51.94)22 731(60.32)
种族=白人173 408(92.03)35 336(93.76)34 879(92.55)34 518(91.59)
学历=大学51 553(27.36)13 364(35.46)11 618(30.83)10 098(26.80)
就业情况=是86 614(45.97)19 263(51.11)18 019(47.81)17 259(45.80)
汤森剥夺指数a-2.01(-3.57, 0.83)-2.38(-3.78, 0.05)-2.32(-3.72, 0.19)-2.13(-3.63, 0.58)
吸烟状况
目前19 108(10.14)3 932(10.43)3 808(10.10)3 814(10.12)
先前74 324(39.44)11 735(31.14)13 961(37.05)15 550(41.26)
从不94 996(50.42)22 019(58.43)19 917(52.85)18 322(48.62)
饮酒状况
目前170 719(90.60)34 617(91.86)34 809(92.37)34 543(91.66)
先前8 428(4.47)1 414(3.75)1 342(3.56)1 537(4.08)
从不9 281(4.93)1 655(4.39)1 535(4.07)1 606(4.26)
饮食=健康29 842(15.84)8 471(22.48)6 683(17.73)5 522(14.65)
高血压史=是126 569(67.17)18 878(50.09)23 597(62.61)26 090(69.23)
糖尿病史=是19 307(10.25)967(2.57)1 929(5.12)3 042(8.07)
变量Q4(4.85, 5.92)Q5(5.92, 23.6)Z或χ2P
n37 68537 685
年龄(岁)a61(56, 65)61(55, 65)1 963.563<0.001
性别=男22 837(60.60)19 990(53.04)11 347.788<0.001
种族=白人34 383(91.24)34 292(91.00)265.380<0.001
学历=大学8 911(23.65)7 562(20.07)2 749.012<0.001
就业情况=是16 611(44.08)15 462(41.03)878.200<0.001
汤森剥夺指数a-1.86(-3.47, 1.02)-1.10(-3.11, 2.11)3 248.177<0.001
吸烟状况1 964.086<0.001
目前3 801(10.09)3 753(9.96)
先前16 339(43.36)16 739(44.42)
从不17 545(46.56)17 193(45.62)
饮酒状况974.017<0.001
目前34 117(90.53)32 633(86.59)
先前1 705(4.52)2 430(6.45)
从不1 863(4.94)2 622(6.96)
饮食=健康4 832(12.82)4 334(11.50)2 176.858<0.001
高血压史=是27 970(74.22)30 034(79.70)8 942.556<0.001
糖尿病史=是4 677(12.41)8 692(23.06)10 613.711<0.001
), ArticleFig(id=1324078260337901873, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=EN, label=Table 2, caption=

Multivariable Cox regression analysis of BRI and mortality outcomes in cardiovascular patients [HR(95% CI)]

, figureFileSmall=null, figureFileBig=null, tableContent=
结局模型五分位数
Q1Q2Q3
全因死亡死亡数21 5482 9483 6214 094
人年数2 300 069.08465 638.32463 088.83461 256.49
模型11.001.24(1.18~1.30)1.41(1.34~1.47)
模型21.000.98(0.93~1.02)1.03(0.98~1.08)
模型31.000.96(0.91~1.01)0.96(0.92~1.01)
CVD死亡死亡数5 367584803988
人年数2 377 860.99477 726.41476 824.71476 103.52
模型11.001.38(1.24~1.53)1.70(1.53~1.88)
模型21.001.05(0.95~1.17)1.19(1.08~1.32)
模型31.001.03(0.93~1.15)1.11(1.00~1.23)
IHD死亡死亡数2 854232395541
人年数2 390 026.17479 436.47478 754.2478 187.97
模型11.001.71(1.46~2.02)2.36(2.02~2.75)
模型21.001.17(0.99~1.37)1.44(1.23~1.68)
模型31.001.14(0.96~1.34)1.30(1.11~1.52)
卒中死亡死亡数967168190174
人年数2 400 853.89479 875.54480 094.3480 303.15
模型11.001.14(0.93~1.40)1.05(0.85~1.30)
模型21.001.01(0.82~1.25)0.89(0.72~1.11)
模型31.000.98(0.79~1.20)0.82(0.66~1.02)
结局模型五分位数
Q4Q5P趋势
全因死亡死亡数21 5484 7136 172
人年数2 300 069.08458 189.17451 896.27
模型11.63(1.56~1.71)2.18(2.09~2.28)<0.001
模型21.18(1.13~1.24)1.68(1.61~1.76)<0.001
模型31.04(0.99~1.09)1.32(1.26~1.38)<0.001
CVD死亡死亡数53671 2101 782
人年数2 377 860.99475 115.86472 090.49
模型12.09(1.89~2.30)3.10(2.82~3.40)<0.001
模型21.45(1.32~1.61)2.33(2.12~2.56)<0.001
模型31.25(1.13~1.38)1.71(1.55~1.89)<0.001
IHD死亡死亡数2 8546691 017
人年数2 390 026.17477 741.41475 906.12
模型12.94(2.53~3.42)4.56(3.95~5.25)<0.001
模型21.78(1.53~2.07)3.05(2.64~3.52)<0.001
模型31.45(1.25~1.70)2.04(1.76~2.37)<0.001
卒中死亡死亡数967203232
人年数2 400 853.89480 323.42480 257.48
模型11.24(1.01~1.52)1.44(1.18~1.76)<0.001
模型21.05(0.85~1.29)1.27(1.04~1.56)0.006
模型30.91(0.74~1.13)0.99(0.80~1.22)0.978
), ArticleFig(id=1324078260425982258, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=CN, label=表2, caption=

BRI与心血管患者死亡结局的多变量Cox回归分析[HR (95% CI)]

, figureFileSmall=null, figureFileBig=null, tableContent=
结局模型五分位数
Q1Q2Q3
全因死亡死亡数21 5482 9483 6214 094
人年数2 300 069.08465 638.32463 088.83461 256.49
模型11.001.24(1.18~1.30)1.41(1.34~1.47)
模型21.000.98(0.93~1.02)1.03(0.98~1.08)
模型31.000.96(0.91~1.01)0.96(0.92~1.01)
CVD死亡死亡数5 367584803988
人年数2 377 860.99477 726.41476 824.71476 103.52
模型11.001.38(1.24~1.53)1.70(1.53~1.88)
模型21.001.05(0.95~1.17)1.19(1.08~1.32)
模型31.001.03(0.93~1.15)1.11(1.00~1.23)
IHD死亡死亡数2 854232395541
人年数2 390 026.17479 436.47478 754.2478 187.97
模型11.001.71(1.46~2.02)2.36(2.02~2.75)
模型21.001.17(0.99~1.37)1.44(1.23~1.68)
模型31.001.14(0.96~1.34)1.30(1.11~1.52)
卒中死亡死亡数967168190174
人年数2 400 853.89479 875.54480 094.3480 303.15
模型11.001.14(0.93~1.40)1.05(0.85~1.30)
模型21.001.01(0.82~1.25)0.89(0.72~1.11)
模型31.000.98(0.79~1.20)0.82(0.66~1.02)
结局模型五分位数
Q4Q5P趋势
全因死亡死亡数21 5484 7136 172
人年数2 300 069.08458 189.17451 896.27
模型11.63(1.56~1.71)2.18(2.09~2.28)<0.001
模型21.18(1.13~1.24)1.68(1.61~1.76)<0.001
模型31.04(0.99~1.09)1.32(1.26~1.38)<0.001
CVD死亡死亡数53671 2101 782
人年数2 377 860.99475 115.86472 090.49
模型12.09(1.89~2.30)3.10(2.82~3.40)<0.001
模型21.45(1.32~1.61)2.33(2.12~2.56)<0.001
模型31.25(1.13~1.38)1.71(1.55~1.89)<0.001
IHD死亡死亡数2 8546691 017
人年数2 390 026.17477 741.41475 906.12
模型12.94(2.53~3.42)4.56(3.95~5.25)<0.001
模型21.78(1.53~2.07)3.05(2.64~3.52)<0.001
模型31.45(1.25~1.70)2.04(1.76~2.37)<0.001
卒中死亡死亡数967203232
人年数2 400 853.89480 323.42480 257.48
模型11.24(1.01~1.52)1.44(1.18~1.76)<0.001
模型21.05(0.85~1.29)1.27(1.04~1.56)0.006
模型30.91(0.74~1.13)0.99(0.80~1.22)0.978
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Two-segment Cox regression analysis of BRI and all-cause and CVD mortality in cardiovascular patients

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全因死亡率CVD死亡率
完全调整后HR (95%CI)P完全调整后HR (95%CI)P
BRI<4.450.97(0.95~1.00)0.0371.05(1.00~1.11)0.074
BRI≥4.451.18(1.17~1.21)<0.0011.26(1.22~1.30)<0.001
对数似然比检验-<0.001-<0.001
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心血管患者中BRI与全因死亡和CVD死亡率之间的两段Cox回归分析

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全因死亡率CVD死亡率
完全调整后HR (95%CI)P完全调整后HR (95%CI)P
BRI<4.450.97(0.95~1.00)0.0371.05(1.00~1.11)0.074
BRI≥4.451.18(1.17~1.21)<0.0011.26(1.22~1.30)<0.001
对数似然比检验-<0.001-<0.001
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Sensitivity analyses results[HR(95% CI)]

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结局模型五分位数
Q1Q2Q3Q4Q5P趋势
全因死亡模型11.001.23(1.17~1.29)1.39(1.33~1.46)1.63(1.55~1.71)2.16(2.07~2.26)<0.001
模型21.000.97(0.93~1.02)1.02(0.97~1.07)1.18(1.12~1.24)1.67(1.60~1.75)<0.001
模型31.000.96(0.91~1.00)0.96(0.91~1.01)1.04(0.99~1.09)1.31(1.25~1.38)<0.001
CVD死亡模型11.001.36(1.22~1.52)1.67(1.50~1.86)2.12(1.91~2.35)3.16(2.87~3.48)<0.001
模型21.001.04(0.93~1.16)1.17(1.05~1.30)1.47(1.33~1.64)2.37(2.15~2.62)<0.001
模型31.001.01(0.90~1.12)1.07(0.95~1.19)1.24(1.12~1.38)1.71(1.54~1.90)<0.001
IHD死亡模型11.001.70(1.43~2.02)2.38(2.02~2.80)3.05(2.61~3.57)4.71(4.05~5.48)<0.001
模型21.001.17(0.99~1.37)1.44(1.23~1.68)1.78(1.53~2.07)3.05(2.64~3.52)<0.001
模型31.001.16(0.97~1.38)1.46(1.23~1.72)1.86(1.58~2.18)3.17(2.72~3.69)<0.001
模型11.001.13(0.92~1.40)1.01(0.82~1.26)1.22(0.99~1.50)1.44(1.18~1.77)<0.001
卒中死亡模型21.001.01(0.81~1.25)0.86(0.69~1.08)1.03(0.83~1.28)1.27(1.04~1.56)0.006
模型31.000.97(0.78~1.20)0.79(0.63~0.99)0.89(0.72~1.11)0.98(0.79~1.22)0.978
), ArticleFig(id=1324078260799275318, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078255841607926, language=CN, label=表4, caption=

敏感性分析结果[HR(95% CI)]

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结局模型五分位数
Q1Q2Q3Q4Q5P趋势
全因死亡模型11.001.23(1.17~1.29)1.39(1.33~1.46)1.63(1.55~1.71)2.16(2.07~2.26)<0.001
模型21.000.97(0.93~1.02)1.02(0.97~1.07)1.18(1.12~1.24)1.67(1.60~1.75)<0.001
模型31.000.96(0.91~1.00)0.96(0.91~1.01)1.04(0.99~1.09)1.31(1.25~1.38)<0.001
CVD死亡模型11.001.36(1.22~1.52)1.67(1.50~1.86)2.12(1.91~2.35)3.16(2.87~3.48)<0.001
模型21.001.04(0.93~1.16)1.17(1.05~1.30)1.47(1.33~1.64)2.37(2.15~2.62)<0.001
模型31.001.01(0.90~1.12)1.07(0.95~1.19)1.24(1.12~1.38)1.71(1.54~1.90)<0.001
IHD死亡模型11.001.70(1.43~2.02)2.38(2.02~2.80)3.05(2.61~3.57)4.71(4.05~5.48)<0.001
模型21.001.17(0.99~1.37)1.44(1.23~1.68)1.78(1.53~2.07)3.05(2.64~3.52)<0.001
模型31.001.16(0.97~1.38)1.46(1.23~1.72)1.86(1.58~2.18)3.17(2.72~3.69)<0.001
模型11.001.13(0.92~1.40)1.01(0.82~1.26)1.22(0.99~1.50)1.44(1.18~1.77)<0.001
卒中死亡模型21.001.01(0.81~1.25)0.86(0.69~1.08)1.03(0.83~1.28)1.27(1.04~1.56)0.006
模型31.000.97(0.78~1.20)0.79(0.63~0.99)0.89(0.72~1.11)0.98(0.79~1.22)0.978
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身体圆度指数与心血管疾病患者死亡风险的关联研究
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梁靖婷 1, 2 , 孙琰欣 1, 2 , 李惠先 2 , 倪明星 1, 2 , 梁会营 1, 2
现代预防医学 | 流行病与统计方法 2026,53(2): 193-199
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现代预防医学 |流行病与统计方法 2026 , 53 (2) : 193 -199
身体圆度指数与心血管疾病患者死亡风险的关联研究
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梁靖婷(2000—),女,硕士在读,研究方向:公共卫生

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梁靖婷1, 2, 孙琰欣1, 2, 李惠先2, 倪明星1, 2, 梁会营1, 2
作者信息
  • 1.中国医科大学公共卫生学院,辽宁 沈阳 110122
  • 2.南方医科大学附属广东省人民医院(广东省医学科学院)医学大数据中心
通讯作者:
梁会营,E-mail:
作者简介:

梁靖婷(2000—),女,硕士在读,研究方向:公共卫生

Association between Body Roundness Index and mortality risk in patients with cardiovascular disease
Jing-ting LIANG1, 2, Yan-xin SUN1, 2, Hui-xian LI2, Ming-xing NI1, 2, Hui-ying LIANG1, 2
Affiliations
  • School of Public Health, China Medical University, Shenyang, Liaoning 110122, China
出版时间: 2026-01-25 doi: 10.20043/j.cnki.MPM.202509092
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目的

探讨心血管疾病(Cardiovascular Disease,CVD)患者的身体圆度指数(Body Roundness Index,BRI)与全因及CVD特异性死亡的关联。

方法

纳入UK Biobank的188 428名CVD患者,采用Cox比例风险回归模型和限制性立方样条(Restricted cubic spline,RCS)分析BRI与死亡风险的关联和剂量反应关系,并进行亚组分析和敏感性分析。

结果

在中位随访12.75年期间,共21 548人死亡,其中5 367人死于CVD。多变量Cox比例风险回归模型显示,BRI与全因、CVD及缺血性心脏病(Ischemic Heart Disease,IHD)死亡风险呈正相关(P趋势<0.001):与Q1相比,Q5 全因、CVD和IHD死亡的HR(95% CI)分别为1.32(1.26~1.38)、1.71(1.55~1.89)和2.04(1.76~2.37),未发现与卒中死亡风险有关。RCS分析表明,BRI与全因及CVD死亡风险呈“J 型”关联,以BRI=4.45为阈值,低水平时风险平缓,超过阈值后风险陡升;BRI与IHD死亡风险呈正相关,未见非线性;BRI与卒中死亡风险不相关。

结论

在CVD患者中,BRI与全因及CVD死亡风险呈“J 型”关联,与IHD死亡风险呈正相关,但与卒中死亡风险无关。

内脏脂肪  /  身体圆度指数  /  心血管疾病死亡率  /  全因死亡率
Objective

To investigate association between Body Roundness Index (BRI) and all-cause and cardiovascular disease (CVD)-specific mortality among patients with CVD.

Methods

A total of 188 428 CVD patients from UK Biobank were included. Cox proportional hazards regression and restricted cubic spline (RCS) analyses were used to examine the association and dose-response relationship between BRI and risks of deaths. Subgroup and sensitivity analyses were also conducted.

Results

Over a median follow-up of 12.75 years, 21 548 deaths occurred, including 5 367 CVD-related deaths. In multivariable Cox models, higher BRI was positively associated with risks of all-cause, CVD, and ischemic heart disease (IHD) mortality (P for trend <0.001). Compared with the lowest quintile (Q1), participants in the highest quintile (Q5) had 32% higher risk of all-cause mortality (HR=1.32, 95% CI: 1.26-1.38), 71% higher risk of CVD mortality (HR=1.71, 95% CI: 1.55-1.89), and 104% higher risk of IHD mortality (HR=2.04, 95% CI: 1.76-2.37); no significant association was observed for stroke mortality. RCS analyses indicated a J-shaped association of BRI with all-cause and CVD mortality. With BRI=4.45 as the threshold, relatively flat mortality risk below the threshold and a steep increase above it. BRI was positively associated with IHD mortality without clear evidence of nonlinearity, and showed no association with stroke mortality.

Conclusion

Among patients with CVD, BRI exhibits a J-shaped association with all-cause and CVD mortality, a positive association with IHD mortality, and no association with stroke mortality.

Visceral fat  /  Body Roundness Index  /  Cardiovascular mortality  /  All-cause mortality
梁靖婷, 孙琰欣, 李惠先, 倪明星, 梁会营. 身体圆度指数与心血管疾病患者死亡风险的关联研究. 现代预防医学, 2026 , 53 (2) : 193 -199 . DOI: 10.20043/j.cnki.MPM.202509092
Jing-ting LIANG, Yan-xin SUN, Hui-xian LI, Ming-xing NI, Hui-ying LIANG. Association between Body Roundness Index and mortality risk in patients with cardiovascular disease[J]. Modern Preventive Medicine, 2026 , 53 (2) : 193 -199 . DOI: 10.20043/j.cnki.MPM.202509092
1990—2021年,全球 ≥ 55 岁人群心血管疾病(Cardiovascular Disease,CVD)发病率和死亡率虽下降,但因人口老龄化和数量增长,总体负担仍上升[1]。肥胖是CVD的重要危险因素,机制涉及慢性炎症和胰岛素抵抗等[2-4]。相较BMI,身体圆度指数(Body Roundness Index, BRI)更能反映脂肪分布,在心代谢风险识别[5-6] 和预测[7-8]上有优势。然而既往结果并不一致:美国成年人提示BRI与全因及CVD死亡率呈“U型”关联[9-11],中老年人BRI与腹主动脉钙化无显著关联[12];中国开滦队列研究亦未见与心衰的非线性关联[13]。上述研究均基于一般人群,对CVD患者这一高危群体证据不足。
鉴于缺血性心脏病(Ischemic Heart Disease, IHD)与卒中是CVD的主要亚型并贡献最大死亡负担,而卒中分缺血性和出血性,分别代表动脉粥样硬化/血栓形成与血管破裂相关机制;因此,探讨 BRI 对 IHD、缺血性卒中和出血性卒中的亚型特异性关联,有助于理解脂肪分布相关代谢异常与不同心血管致死机制之间的潜在联系。因此,本研究利用UK Biobank(UKB)CVD患者数据,探究基线BRI与全因、CVD、IHD和缺血性/出血性卒中死亡的关联(UKB申请号:88365)。
数据来自UKB队列,纳入逾50万名37~73岁英国成年人并随访健康结局。本研究结合初级保健、住院、死亡登记及自报信息,依据ICD-10判断CVD的首次发生和诊断。纳入基线时确诊CVD者,排除BRI 数据缺失(n=1 132)、妊娠(n=60)和失访(n=404)者,最终纳入188 428人。
主要结局是全因死亡和CVD 死亡(任何心血管病导致的死亡),次要结局是 IHD 死亡和卒中死亡。研究对象的死亡状态和时间依据死亡记录确定,研究截止于2021年10月31日。随访时间为入组日期与研究截止日期或死亡日期之间的时间,以先发生者为准。死因根据ICD-10编码,CVD为I00~I99,IHD为I20~25,卒中为I60~64和I69。卒中死亡共 967 例(出血性 379 例,缺血性 109 例,未指明类型 450 例等),分型后部分事件数较少且未指明类型比例较高,为保证模型稳定性,本研究将卒中作为整体终点进行分析。
BRI由Thomas[14]等提出,计算公式如下:
其中WC为腰围(单位cm),Height为身高(单位cm)。BRI按第20、40、60、80分位数分为5组。
结合生物学合理性和文献[10-11,15-17],纳入:人口学因素(年龄、性别、种族、学历和就业情况)、社会经济地位(汤森剥夺指数)、生活方式(体力活动、吸烟、饮酒和饮食模式)及疾病史(高血压和糖尿病)[18]。饮食模式按健康饮食评分(≥ 4为健康)。体力活动因缺失比例超过20%,未纳入最终模型。
连续变量若符合正态分布用均数±标准差()表示,组间比较用方差分析描述;否则以中位数和四分位数间距[M(P25, P75)]表示,组间比较用Kruskal-Wallis秩和检验,并采用线性回归趋势检验分析趋势。分类变量以n(%)表示,组间比较采用χ2检验。所有检验均为双侧检验,以P<0.05为差异有统计学意义。多重插补法填补缺失值。
Schoenfeld 残差法检验比例风险假设,未发现明显违反。采用三个Cox比例风险回归模型计算风险比例(Hazard Ratio,HR)和 95%置信区间(Confidence Interval,CI),分析BRI与结局事件(全因、CVD、IHD和卒中死亡)的关联。模型1未调整,模型2调整年龄、性别和种族,模型3再进一步调整学历、就业情况、汤森剥夺指数、吸烟状况、饮酒状态、饮食模式、高血压和糖尿病史。为进一步评估BRI对结局事件的影响,进行以下分析:(1)按BRI五分位数分组并进行趋势性检验;(2)使用限制性立方样条(Restricted cubic spline, RCS)检验非线性关系,采用中位数作为经验拐点[19],在拐点两侧构建分段Cox模型[9]。
仅对与BRI显著相关的死亡结局进行亚组和交互作用分析,按年龄(≤ 65岁或> 65岁)、性别、吸烟状况(目前、从未或先前)和饮酒状态(目前、从未或先前)分层,检验交互作用。交互作用P值检验亚组间效应差异显著性,亚组HR/95% CI 用于描述各组风险水平,交互作用不显著时仅作趋势参考。敏感性分析排除随访两年内发生CVD死亡者,以减弱反向因果关系影响。
所有统计分析均使用R 4.4.2进行。
基线特征 本研究纳入了188 428名CVD患者,中位年龄(四分位数间距)为61(54, 65)岁,男性占50.61%,白种人占92.03%。见表1。
在模型3中,BRI与全因、CVD和IHD死亡风险均呈正相关(均P趋势<0.001):与 Q1 相 比,Q5 全因、CVD 和 IHD 死亡的HR (95% CI)分别为1.32 (1.26~1.38)、1.71 (1.55~1.89)和2.04 (1.76~2.37),未发现与卒中死亡风险有关(HR=0.99,95% CI:0.80~1.22)。见表2。
图1显示,BRI与全因及CVD死亡风险呈“J型”关联:以低BRI时风险平缓,超过阈值后陡增(均P<0.05);BRI与IHD死亡风险呈正相关,未见非线性关系(P for overall<0.001, P for nonlinear>0.05),与卒中死亡无关(P for overall>0.05)。以中位数BRI=4.45为拐点构建分段Cox模型(表3),模型3显示,BRI<4.45时,全因死亡HR=0.97(95% CI: 0.95~1.00, P=0.037),CVD死亡HR=1.05(95% CI: 1.00~1.11,P=0.074),死亡风险变化平缓;BRI ≥ 4.45 时,每增加一个单位,全因及CVD死亡风险分别增加18%和26%,HR (95% CI)分别为1.18 (1.17~1.21)和1.26 (1.22~1.30)。
基于危险因素的分层分析见图2。对于全因死亡,年龄、饮酒状态和吸烟状况的交互作用显著(P交互<0.001、P交互=0.009和P交互<0.001):在≤65岁、目前饮酒者及既往或从未吸烟者中,较高BRI与全因死亡风险增加的相关性更高。对于CVD死亡,性别和吸烟状况的交互作用显著(P交互=0.008和0.009):在男性及既往或从未吸烟者中,较高BRI与死亡风险增加的关联更强;IHD死亡结果一致(P交互=0.015和<0.001)。
排除随访两年内发生CVD死亡的参与者后,结果无显著变化。见表4。
本研究发现CVD患者BRI与全因及CVD死亡风险呈“J型”关联,低BRI时风险平缓,超过中位数4.45后陡增;与IHD死亡风险呈正相关,无显著非线性。BRI与卒中死亡无关,可能有以下原因:首先,模型调整了高血压、糖尿病、饮食、吸烟和饮酒等可能位于“BRI → 代谢/血压通路 → 卒中死亡”的因果路径上的因素,部分中介效应可能被扣除,使总效应向零偏倚,更易出现“无关联”;其次,竞争风险影响,患者更易死于 IHD 或心衰,卒中死亡风险可能被低估;另外,卒中死亡事件数相对较少,效能不足;最后,BRI 与社会经济、生活方式和合并症高度相关,在事件有限时加入过多协变量可能导致方差膨胀或过拟合,使估计不稳。
亚组和交互作用分析仅针对全因、CVD和 IHD 死亡开展,卒中死亡因事件数少且未见显著关联未分析。对于全因死亡,≤65岁人群中高BRI与全因死亡风险关联更强,提示肥胖相关代谢负担在中青年阶段影响更直接;老年人中该关联减弱,可能与“肥胖悖论”有关,即年龄增长,体重下降,常反映慢性疾病或衰弱,而适度脂肪储备可能具有保护作用。目前饮酒者中BRI与全因死亡风险的正相关更明显,或因饮酒伴随高热量摄入及血压升高,放大了高BRI的心代谢风险。对于CVD 和IHD 死亡,高BRI与死亡风险增加的关联在男性中更强,提示男性对肥胖相关CVD风险更易感。吸烟状况在三种死亡结局中交互作用均显著,目前吸烟者死亡风险低于先前吸烟者和从未吸烟者,可能受选择性生存偏倚及反向因果影响:目前吸烟者多为病情较轻、存活时间较长者;而先前吸烟者多因确诊或健康状况恶化后戒烟,从未吸烟者中常包含年龄较大的女性或合并代谢疾病者,整体风险并不一定最低。
内脏脂肪通过胰岛素抵抗、慢性炎症、高血压及脂质代谢异常等途径加速动脉粥样硬化,并分泌促炎因子(如TNF-α、IL-6)和抗炎因子(如脂联素),因子失衡进一步损伤血管[20-21]。脂肪组织异常扩张导致脂毒性,使游离脂肪酸在肝脏、心脏和血管内皮积聚,加剧代谢紊乱和 CVD 发展[22]。BRI作为新型指标,可有效评估心脏代谢风险,优于传统指标,但受国家和性别差异影响[5-7,23-24]。
一项在美国成年人中的研究仅观察全因死亡,最低 BRI 范围为 4.50~5.50[10],另一项研究同时观察全因和 CVD 死亡,阈值分别为 4.99 和 3.60[11];中国中老年人群中,全因和 CVD 死亡的阈值分别为3.60 和3.42[25],本研究在CVD患者中发现BRI与全因及CVD死亡风险呈“J型”关联,<4.45时风险平缓,≥4.45时显著升高,提示可用于高危人群基于阈值的经验性风险分层与个体化管理。阈值差异可能反映高危 CVD 患者死亡风险提前出现,同时受到人群基线风险、死亡构成和种族异质性影响,提示阈值和风险分层应根据具体人群特征进行判断。
本研究存在以下优势:聚焦CVD患者死亡风险,增补高危人群BRI与死亡结局关联的研究证据;细分死因发现各结局与BRI关联存在差异,提示将BRI控制在4.45附近可综合降低多类死亡风险;大样本前瞻性设计及长期随访增强了结果稳健性,多重协变量调整减少了混杂偏倚。本研究也存在局限:研究对象为UKB欧洲人群,结果外推时需谨慎;仅使用基线BRI,未纳入动态变化轨迹,未来可进一步分析时间依赖性效应;尽管广泛调整协变量,但未测量残余混杂效应(如遗传背景、药物使用)仍可能影响结果。
  • 国家重点研发计划项目(2022YFC3601600)
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2026年第53卷第2期
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doi: 10.20043/j.cnki.MPM.202509092
  • 接收时间:2025-09-04
  • 首发时间:2026-11-02
  • 出版时间:2026-01-25
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  • 收稿日期:2025-09-04
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国家重点研发计划项目(2022YFC3601600)
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    1.中国医科大学公共卫生学院,辽宁 沈阳 110122
    2.南方医科大学附属广东省人民医院(广东省医学科学院)医学大数据中心

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2种不同金属材料的力学参数
科
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属数
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genus
种数
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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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