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Article(id=1240977222186627136, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240977214964036360, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202411468, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732464000000, receivedDateStr=2024-11-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773801626011, onlineDateStr=2026-03-18, pubDate=1748102400000, pubDateStr=2025-05-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773801626011, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773801626011, creator=13701087609, updateTime=1773801626011, updator=13701087609, issue=Issue{id=1240977214964036360, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='10', pageStart='1729', pageEnd='1920', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773801624289, creator=13701087609, updateTime=1773825591019, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241077738770068227, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240977214964036360, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241077738770068228, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240977214964036360, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1748, endPage=1753, ext={EN=ArticleExt(id=1240977222597668967, articleId=1240977222186627136, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between body roundness index and risk of cardiometabolic multimorbidity among residents aged 35-75 years, Zhejiang, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the association between Body Roundness Index (BRI) and to cardiometabolic comorbidities among individuals aged 35-75 years in Zhejiang Province.

Methods

Residents aged 35-75 years recruited in the 2022 China National Nutrition and Health Survey (Zhejiang region) were selected as the study population. Statistical analyses were performed using R 4.3.3 and SPSS 30.0. The χ2 test and logistic regression were used to evaluate the impact of BRI on cardiometabolic diseases.

Results

The overall prevalence rates of hypertension, diabetes, dyslipidemia, coronary heart disease, stroke, and cardiometabolic comorbidities in Zhejiang residents aged 35-75 years were 41.43%, 15.46%, 40.07%, 1.20%, 0.78%, and 27.99%, respectively. Logistic regression analysis showed that after adjusting for confounders, individuals in the fourth quartile (Q4) of BRI had a higher risk of hypertension (OR=4.10, 95%CI: 3.11-5.38）, diabetes (OR=3.18, 95%CI: 2.20-4.61), dyslipidemia (OR=3.84, 95%CI: 2.95-5.00), coronary heart disease (OR=3.40, 95%CI: 0.74-15.71), stroke (OR=1.10，95%CI: 0.34-3.56) and cardiometabolic comorbidities (OR=5.20, 95%CI: 3.76-7.13) compared with the first quartile (Q1). Female participants (OR=1.43, 95%CI: 1.28-1.60) had a lower risk compared to males (OR=1.70，95%CI: 1.48-1.96). Significant interaction effects of age and smoking on the risk of cardiometabolic comorbidities were observed, with the risk significantly higher in middle-aged adults (35-54 years). In a population with normal BMI, ROC curve analysis indicated that BRI was superior to BMI in predicting the risk of CMM, however, both AUC values were below 0.7, suggesting that the predictive ability remains weak.

Conclusion

Higher BRI levels were positively associated with cardiometabolic comorbidities. To identify high-risk populations for cardiometabolic comorbidities early, targeted management and intervention strategies should be implemented to reduce the burden of cardiometabolic diseases. However, caution is warranted when promoting the use of BRI in public health and clinical practice, as further research is needed to validate its effectiveness.

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目的

分析浙江省35~75岁身体圆度指数（body roundness index，BRI）与心血管代谢性疾病共病（cardiometabolic morbidity，CMM）患病的关联。

方法

以2022年中国居民营养与健康状况监测（浙江区）调查所招募的35~75岁居民作为研究对象。采用R 4.3.3和SPSS 30.0进行统计学分析，使用χ2检验和logistic回归，评估BRI对心血管代谢性疾病（cardiometabolic disease，CMD）的影响。

结果

浙江省35~75岁居民高血压、糖尿病、血脂异常、冠心病、脑卒中和CMM的总体患病率分别为41.43%、15.46%、40.07%、1.20%、0.78%和 27.99%。Logistic回归分析结果显示，调整混杂因素后，BRI第四分位数（Q4）与第一分位数（Q1）相比，患高血压（OR=4.10，95% CI：3.11~5.38）、糖尿病（OR=3.18，95% CI：2.20~4.61）、血脂异常（OR=3.84，95% CI：2.95~5.00）、冠心病（OR=3.40，95% CI：0.74~15.71）、脑卒中（OR=1.10，95% CI：0.34~3.56）以及CMM（OR=5.20，95% CI：3.76~7.13）的风险增加。女性（OR=1.43，95% CI：1.28~1.60）的患病风险低于男性（OR=1.70，95% CI：1.48~1.96）。年龄和吸烟对CMM风险存在交互作用，中青年（35~54岁）人群的患病风险升高。在BMI正常人群中，ROC曲线分析表明BRI在预测CMM发病风险方面优于BMI，但AUC值均低于0.7，表明预测能力仍较弱。

结论

BRI水平与CMM呈正相关。为早期识别CMM潜在的高危人群，采取针对性的管理和干预措施，有效降低CMD负担，但在公共卫生和临床实践中推广使用时应谨慎，需进一步研究以验证其有效性。

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章荣华，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=XcSyF7gsr5BnG8RaTEvIVA==, magXml=LZ+O/poVijo3MECssNanfg==, pdfUrl=null, pdf=Y0MpaMtvyK1yK82G85KFoQ==, pdfFileSize=709686, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=df3f3+7Vl5gQxePvVPinoQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=pxLlcZp+icC0IZyi5bB9tA==, mapNumber=null, authorCompany=null, fund=null, authors=

周梦怡（1998—），女，硕士在读，研究方向：营养与食品卫生

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周梦怡（1998—），女，硕士在读，研究方向：营养与食品卫生

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周梦怡（1998—），女，硕士在读，研究方向：营养与食品卫生

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注：BRI，身体圆度指数；BMI，身体质量指数。

, figureFileSmall=xYANnLAhoT4Qsl/4xlB7fw==, figureFileBig=J7pVEoo45NLKnSCNCgd25Q==, tableContent=null), ArticleFig(id=1240996913059787377, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=EN, label=Table 1, caption=

Basic characteristics of different BRI groups

, figureFileSmall=null, figureFileBig=null, tableContent=
变量调查人数BRI四分位分组χ2/F值P
Q1Q2Q3Q4
性别23.23<0.001
男979(40.35)236(41.26)275(44.93)269(42.83)199(32.41)
女1 447(59.65)336(58.74)337(55.07)359(57.17)415(67.59)
年龄（岁）87.94<0.001
35~44532(21.93)206(36.01)157(25.65)102(16.24)67(10.91)
45~54549(22.63)144(25.17)159(25.98)142(22.61)104(16.94)
55~64686(28.28)108(18.88)168(27.45)200(31.85)210(34.20)
65~75659(27.16)114(19.93)128(20.92)184(29.30)233(37.95)
民族0.620.891
汉族2 405(99.13)566(98.95)608(99.35)622(99.04)609(99.19)
其他民族21(0.87)6(1.05)4(0.65)6(0.96)5(0.81)
居住地4.640.200
城市1 000(41.22)235(41.08)261(42.65)272(43.31)232(37.79)
农村1 426(58.78)337(58.92)351(57.35)356(56.69)382(62.21)
婚姻状况10.780.013
非在婚191(7.87)40(6.99)44(7.19)40(6.37)67(10.91)
在婚2 235(92.13)532(93.01)568(92.81)588(93.63)547(89.09)
教育程度102.84<0.001
文盲445(18.34)69(12.06)91(14.87)114(18.15)171(27.85)
初中及以下1 536(63.31)361(63.11)374(61.11)419(66.72)382(62.21)
高中及中专291(12.00)88(15.38)92(15.03)65(10.35)46(7.49)
大专及以上154(6.35)54(9.44)55(8.99)30(4.78)15(2.44)
饮酒18.81<0.001
是653(26.92)143(25.00)205(33.50)161(25.64)144(23.45)
否1 773(73.08)429(75.00)407(66.50)467(74.36)470(76.55)
吸烟11.990.007
是428(17.64)119(20.80)121(19.77)101(16.08)87(14.17)
否1 998(82.36)453(79.20)491(80.23)527(83.92)527(85.83)
睡眠时长（小时）17.7300.007
<6247(10.18)53(9.27)55(8.99)54(8.60)85(13.84)
6~81 901(78.36)448(78.32)494(80.72)488(77.71)471(76.71)
>8278(11.46)71(12.41)63(10.29)86(13.69)58(9.45)
身体活动（分钟）2.620.454
充足974(40.15)234(40.91)258(42.16)250(39.81)232(37.79)
不足1 452(59.85)338(59.09)354(57.84)378(60.19)382(62.21)
腰围(cm)83.16±9.2872.18±4.7679.93±4.3985.87±4.5693.81±5.902 043.90<0.001
BMI(kg/m2)24.14±3.3920.92±2.3723.00±2.1024.81±2.1527.60±2.75864.36<0.001
BRI3.84±1.172.45±0.383.32±0.224.08±0.265.41±0.754 555.39<0.001
), ArticleFig(id=1240996913160450683, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=CN, label=表1, caption=

不同BRI分组的基本特征

, figureFileSmall=null, figureFileBig=null, tableContent=
变量调查人数BRI四分位分组χ2/F值P
Q1Q2Q3Q4
性别23.23<0.001
男979(40.35)236(41.26)275(44.93)269(42.83)199(32.41)
女1 447(59.65)336(58.74)337(55.07)359(57.17)415(67.59)
年龄（岁）87.94<0.001
35~44532(21.93)206(36.01)157(25.65)102(16.24)67(10.91)
45~54549(22.63)144(25.17)159(25.98)142(22.61)104(16.94)
55~64686(28.28)108(18.88)168(27.45)200(31.85)210(34.20)
65~75659(27.16)114(19.93)128(20.92)184(29.30)233(37.95)
民族0.620.891
汉族2 405(99.13)566(98.95)608(99.35)622(99.04)609(99.19)
其他民族21(0.87)6(1.05)4(0.65)6(0.96)5(0.81)
居住地4.640.200
城市1 000(41.22)235(41.08)261(42.65)272(43.31)232(37.79)
农村1 426(58.78)337(58.92)351(57.35)356(56.69)382(62.21)
婚姻状况10.780.013
非在婚191(7.87)40(6.99)44(7.19)40(6.37)67(10.91)
在婚2 235(92.13)532(93.01)568(92.81)588(93.63)547(89.09)
教育程度102.84<0.001
文盲445(18.34)69(12.06)91(14.87)114(18.15)171(27.85)
初中及以下1 536(63.31)361(63.11)374(61.11)419(66.72)382(62.21)
高中及中专291(12.00)88(15.38)92(15.03)65(10.35)46(7.49)
大专及以上154(6.35)54(9.44)55(8.99)30(4.78)15(2.44)
饮酒18.81<0.001
是653(26.92)143(25.00)205(33.50)161(25.64)144(23.45)
否1 773(73.08)429(75.00)407(66.50)467(74.36)470(76.55)
吸烟11.990.007
是428(17.64)119(20.80)121(19.77)101(16.08)87(14.17)
否1 998(82.36)453(79.20)491(80.23)527(83.92)527(85.83)
睡眠时长（小时）17.7300.007
<6247(10.18)53(9.27)55(8.99)54(8.60)85(13.84)
6~81 901(78.36)448(78.32)494(80.72)488(77.71)471(76.71)
>8278(11.46)71(12.41)63(10.29)86(13.69)58(9.45)
身体活动（分钟）2.620.454
充足974(40.15)234(40.91)258(42.16)250(39.81)232(37.79)
不足1 452(59.85)338(59.09)354(57.84)378(60.19)382(62.21)
腰围(cm)83.16±9.2872.18±4.7679.93±4.3985.87±4.5693.81±5.902 043.90<0.001
BMI(kg/m2)24.14±3.3920.92±2.3723.00±2.1024.81±2.1527.60±2.75864.36<0.001
BRI3.84±1.172.45±0.383.32±0.224.08±0.265.41±0.754 555.39<0.001
), ArticleFig(id=1240996913290474119, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=EN, label=Table 2, caption=

Disease prevalence in different BRI quartiles

, figureFileSmall=null, figureFileBig=null, tableContent=
变量调查人数BRI四分位分组χ2值PP趋势
Q1Q2Q3Q4
高血压205.17<0.001<0.001
否1 421(58.57)450(78.67)393(64.22)338(53.82)240(39.09)
是1 005(41.43)122(21.33)219(35.78)290(46.18)374(60.91)
糖尿病73.82<0.001<0.001
否2 051(84.54)528(92.31)539(88.07)522(83.12)462(75.24)
是375(15.46)44(7.69)73(11.93)106(16.88)152(24.76)
血脂异常127.12<0.001<0.001
否1 454(59.93)445(77.80)385(62.91)320(50.96)304(49.51)
是972(40.07)127(22.20)227(37.09)308(49.04)310(50.49)
冠心病8.920.030.003
否2 397(98.80)570(99.65)607(99.18)619(98.57)601(97.88)
是29(1.20)2(0.35)5(0.82)9(1.43)13(2.12)
脑卒中4.010.260.30
否2407(99.22)567(99.13)610(99.67)624(99.36)606(98.70)
是19(0.78)5(0.87)2(0.33)4(0.64)8(1.30)
代谢性共病182.36<0.001<0.001
否1 747(72.01)511(89.34)475(77.61)417(66.40)344(56.03)
是679(27.99)61(10.66)137(22.39)211(33.60)270(43.97)
), ArticleFig(id=1240996913357582994, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=CN, label=表2, caption=

不同BRI四分位分组的疾病患病情况

, figureFileSmall=null, figureFileBig=null, tableContent=
变量调查人数BRI四分位分组χ2值PP趋势
Q1Q2Q3Q4
高血压205.17<0.001<0.001
否1 421(58.57)450(78.67)393(64.22)338(53.82)240(39.09)
是1 005(41.43)122(21.33)219(35.78)290(46.18)374(60.91)
糖尿病73.82<0.001<0.001
否2 051(84.54)528(92.31)539(88.07)522(83.12)462(75.24)
是375(15.46)44(7.69)73(11.93)106(16.88)152(24.76)
血脂异常127.12<0.001<0.001
否1 454(59.93)445(77.80)385(62.91)320(50.96)304(49.51)
是972(40.07)127(22.20)227(37.09)308(49.04)310(50.49)
冠心病8.920.030.003
否2 397(98.80)570(99.65)607(99.18)619(98.57)601(97.88)
是29(1.20)2(0.35)5(0.82)9(1.43)13(2.12)
脑卒中4.010.260.30
否2407(99.22)567(99.13)610(99.67)624(99.36)606(98.70)
是19(0.78)5(0.87)2(0.33)4(0.64)8(1.30)
代谢性共病182.36<0.001<0.001
否1 747(72.01)511(89.34)475(77.61)417(66.40)344(56.03)
是679(27.99)61(10.66)137(22.39)211(33.60)270(43.97)
), ArticleFig(id=1240996913491800737, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=EN, label=Table 3, caption=

Multivariate logistic regression analysis of the relationship between BRI and CMD and CMM

, figureFileSmall=null, figureFileBig=null, tableContent=
变量BRI四分位分组
Q2Q3Q4
高血压
模型12.06(1.59~2.66)a3.16(2.45~4.08)a5.75(4.44~7.44)a
模型21.93(1.47~2.54)a2.53(1.93~3.29)a4.10(3.11 ~5.38)a
糖尿病
模型11.63(1.10~2.41)b2.44(1.68~3.53)a3.95(2.76~5.65)a
模型21.51(1.02~2.26)b2.02(1.38~2.95)a3.18(2.20~4.61)a
血脂异常
模型12.07(1.60~2.67)a3.37(2.62~4.34)a3.57(2.77~4.60a
模型22.12(1.63~2.75)a3.41(2.63~4.42)a3.84(2.95~5.00)a
冠心病
模型12.35(0.45~12.15)4.14(0.89~19.26)6.16(1.39~27.44)b
模型22.41(0.45~12.71)2.96(0.62~14.07)3.40(0.74~15.71)
脑卒中
模型1 0.37(0.07~1.92)0.73(0.19~2.72)1.50(0.49~4.60)
模型20.35(0.07~1.82)0.49(0.13~1.88)1.10(0.34~3.56)
心血管代谢性疾病共病
模型12.42(1.74~3.35)a4.24(3.10~5.80)a6.58(4.82~8.96)a
模型22.29(1.64~3.20)a3.53(2.55~4.84)a5.20(3.76~7.13)a
), ArticleFig(id=1240996915022721709, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=CN, label=表3, caption=

BRI与CMD和CMM多因素logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量BRI四分位分组
Q2Q3Q4
高血压
模型12.06(1.59~2.66)a3.16(2.45~4.08)a5.75(4.44~7.44)a
模型21.93(1.47~2.54)a2.53(1.93~3.29)a4.10(3.11 ~5.38)a
糖尿病
模型11.63(1.10~2.41)b2.44(1.68~3.53)a3.95(2.76~5.65)a
模型21.51(1.02~2.26)b2.02(1.38~2.95)a3.18(2.20~4.61)a
血脂异常
模型12.07(1.60~2.67)a3.37(2.62~4.34)a3.57(2.77~4.60a
模型22.12(1.63~2.75)a3.41(2.63~4.42)a3.84(2.95~5.00)a
冠心病
模型12.35(0.45~12.15)4.14(0.89~19.26)6.16(1.39~27.44)b
模型22.41(0.45~12.71)2.96(0.62~14.07)3.40(0.74~15.71)
脑卒中
模型1 0.37(0.07~1.92)0.73(0.19~2.72)1.50(0.49~4.60)
模型20.35(0.07~1.82)0.49(0.13~1.88)1.10(0.34~3.56)
心血管代谢性疾病共病
模型12.42(1.74~3.35)a4.24(3.10~5.80)a6.58(4.82~8.96)a
模型22.29(1.64~3.20)a3.53(2.55~4.84)a5.20(3.76~7.13)a
), ArticleFig(id=1240996915156939446, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=EN, label=Table 4, caption=

Subgroup analysis of the association between BRI and CMM

, figureFileSmall=null, figureFileBig=null, tableContent=
变量BRIP交互
OR(95%CI)P
所有调查对象1.57(1.44~1.71)<0.001
性别0.178
男1.70(1.48~1.96)<0.001
女1.43(1.28~1.60)<0.001
饮酒0.329
是1.74(1.47~2.07)<0.001
否1.51(1.37~1.66)<0.001
年龄(岁)0.014
35~441.92(1.51~2.43)<0.001
45~541.98(1.60~2.46)<0.001
55~641.34(1.16~1.55)<0.001
65~751.41(1.22~1.62)<0.001
吸烟0.048
是1.90(1.51~2.39)<0.001
否1.49(1.36~1.64)<0.001
睡眠时长(小时)0.545
<61.42(1.07~1.87)0.014
6~81.55(1.41~1.70)<0.001
>81.80(1.38~2.35)<0.001
身体活动（分钟）0.396
充足1.66(1.44~1.90)<0.001
不充足1.51(1.35~1.68)<0.001
), ArticleFig(id=1240996915291157183, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=CN, label=表4, caption=

BRI与CMM的关联关系的亚组分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量BRIP交互
OR(95%CI)P
所有调查对象1.57(1.44~1.71)<0.001
性别0.178
男1.70(1.48~1.96)<0.001
女1.43(1.28~1.60)<0.001
饮酒0.329
是1.74(1.47~2.07)<0.001
否1.51(1.37~1.66)<0.001
年龄(岁)0.014
35~441.92(1.51~2.43)<0.001
45~541.98(1.60~2.46)<0.001
55~641.34(1.16~1.55)<0.001
65~751.41(1.22~1.62)<0.001
吸烟0.048
是1.90(1.51~2.39)<0.001
否1.49(1.36~1.64)<0.001
睡眠时长(小时)0.545
<61.42(1.07~1.87)0.014
6~81.55(1.41~1.70)<0.001
>81.80(1.38~2.35)<0.001
身体活动（分钟）0.396
充足1.66(1.44~1.90)<0.001
不充足1.51(1.35~1.68)<0.001
), ArticleFig(id=1240996915437957838, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=EN, label=Table 5, caption=

ROC Curve Analysis and DiagnosticPerformance Indicators

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变量AUC最佳界值敏感度特异度截断值95%CIP
BMI0.6400.2170.8030.41422.70.617~0.664P<0.01
BRI0.6840.2890.7750.5143.5430.662~0.707P<0.01
), ArticleFig(id=1240996915555398364, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240977222186627136, language=CN, label=表5, caption=

ROC曲线分析及诊断效能指标

, figureFileSmall=null, figureFileBig=null, tableContent=
变量AUC最佳界值敏感度特异度截断值95%CIP
BMI0.6400.2170.8030.41422.70.617~0.664P<0.01
BRI0.6840.2890.7750.5143.5430.662~0.707P<0.01
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浙江省35～75岁居民身体圆度指数与心血管代谢性疾病共病风险的关联性研究
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周梦怡 1 , 苏丹婷 2 , 何梦洁 2 , 黄李春 2 , 韩丹 2 , 章荣华 2
现代预防医学 | 流行病与统计方法 2025,52(10): 1748-1753
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现代预防医学 | 流行病与统计方法 2025, 52(10): 1748-1753
浙江省35～75岁居民身体圆度指数与心血管代谢性疾病共病风险的关联性研究
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周梦怡1, 苏丹婷2, 何梦洁2, 黄李春2, 韩丹2, 章荣华2
作者信息
  • 1.杭州医学院公共卫生学院，浙江 杭州 311399
  • 2.浙江省疾病预防控制中心

    • 周梦怡（1998—），女，硕士在读，研究方向：营养与食品卫生

通讯作者:

章荣华，E-mail:
Association between body roundness index and risk of cardiometabolic multimorbidity among residents aged 35-75 years, Zhejiang
Meng-yi ZHOU1, Dan-ting SU2, Meng-jie HE2, Li-chun HUANG2, Dan HAN2, Rong-hua ZHANG2
Affiliations
  • School of Public Health, Hangzhou Medical College, Hangzhou, Zhejiang 311399, China
出版时间: 2025-05-25 doi: 10.20043/j.cnki.MPM.202411468
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摘要
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目的

分析浙江省35~75岁身体圆度指数（body roundness index，BRI）与心血管代谢性疾病共病（cardiometabolic morbidity，CMM）患病的关联。

方法

以2022年中国居民营养与健康状况监测（浙江区）调查所招募的35~75岁居民作为研究对象。采用R 4.3.3和SPSS 30.0进行统计学分析，使用χ2检验和logistic回归，评估BRI对心血管代谢性疾病（cardiometabolic disease，CMD）的影响。

结果

浙江省35~75岁居民高血压、糖尿病、血脂异常、冠心病、脑卒中和CMM的总体患病率分别为41.43%、15.46%、40.07%、1.20%、0.78%和 27.99%。Logistic回归分析结果显示，调整混杂因素后，BRI第四分位数（Q4）与第一分位数（Q1）相比，患高血压（OR=4.10，95% CI：3.11~5.38）、糖尿病（OR=3.18，95% CI：2.20~4.61）、血脂异常（OR=3.84，95% CI：2.95~5.00）、冠心病（OR=3.40，95% CI：0.74~15.71）、脑卒中（OR=1.10，95% CI：0.34~3.56）以及CMM（OR=5.20，95% CI：3.76~7.13）的风险增加。女性（OR=1.43，95% CI：1.28~1.60）的患病风险低于男性（OR=1.70，95% CI：1.48~1.96）。年龄和吸烟对CMM风险存在交互作用，中青年（35~54岁）人群的患病风险升高。在BMI正常人群中，ROC曲线分析表明BRI在预测CMM发病风险方面优于BMI，但AUC值均低于0.7，表明预测能力仍较弱。

结论

BRI水平与CMM呈正相关。为早期识别CMM潜在的高危人群，采取针对性的管理和干预措施，有效降低CMD负担，但在公共卫生和临床实践中推广使用时应谨慎，需进一步研究以验证其有效性。

身体圆度指数  /  心血管代谢性疾病共病  /  心血管疾病
Objective

To analyze the association between Body Roundness Index (BRI) and to cardiometabolic comorbidities among individuals aged 35-75 years in Zhejiang Province.

Methods

Residents aged 35-75 years recruited in the 2022 China National Nutrition and Health Survey (Zhejiang region) were selected as the study population. Statistical analyses were performed using R 4.3.3 and SPSS 30.0. The χ2 test and logistic regression were used to evaluate the impact of BRI on cardiometabolic diseases.

Results

The overall prevalence rates of hypertension, diabetes, dyslipidemia, coronary heart disease, stroke, and cardiometabolic comorbidities in Zhejiang residents aged 35-75 years were 41.43%, 15.46%, 40.07%, 1.20%, 0.78%, and 27.99%, respectively. Logistic regression analysis showed that after adjusting for confounders, individuals in the fourth quartile (Q4) of BRI had a higher risk of hypertension (OR=4.10, 95%CI: 3.11-5.38）, diabetes (OR=3.18, 95%CI: 2.20-4.61), dyslipidemia (OR=3.84, 95%CI: 2.95-5.00), coronary heart disease (OR=3.40, 95%CI: 0.74-15.71), stroke (OR=1.10，95%CI: 0.34-3.56) and cardiometabolic comorbidities (OR=5.20, 95%CI: 3.76-7.13) compared with the first quartile (Q1). Female participants (OR=1.43, 95%CI: 1.28-1.60) had a lower risk compared to males (OR=1.70，95%CI: 1.48-1.96). Significant interaction effects of age and smoking on the risk of cardiometabolic comorbidities were observed, with the risk significantly higher in middle-aged adults (35-54 years). In a population with normal BMI, ROC curve analysis indicated that BRI was superior to BMI in predicting the risk of CMM, however, both AUC values were below 0.7, suggesting that the predictive ability remains weak.

Conclusion

Higher BRI levels were positively associated with cardiometabolic comorbidities. To identify high-risk populations for cardiometabolic comorbidities early, targeted management and intervention strategies should be implemented to reduce the burden of cardiometabolic diseases. However, caution is warranted when promoting the use of BRI in public health and clinical practice, as further research is needed to validate its effectiveness.

Body roundness index  /  Cardiometabolic multimorbidity  /  Cardiovascular disease
周梦怡, 苏丹婷, 何梦洁, 黄李春, 韩丹, 章荣华. 浙江省35～75岁居民身体圆度指数与心血管代谢性疾病共病风险的关联性研究. 现代预防医学, 2025 , 52 (10) : 1748 -1753 . DOI: 10.20043/j.cnki.MPM.202411468
Meng-yi ZHOU, Dan-ting SU, Meng-jie HE, Li-chun HUANG, Dan HAN, Rong-hua ZHANG. Association between body roundness index and risk of cardiometabolic multimorbidity among residents aged 35-75 years, Zhejiang[J]. Modern Preventive Medicine, 2025 , 52 (10) : 1748 -1753 . DOI: 10.20043/j.cnki.MPM.202411468
正文
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心血管代谢性疾病共病（cardiometabolic multimorbidity，CMM）是指同时存在包括糖尿病、高血压、冠心病及脑卒中等在内的两种或多种心血管代谢性疾病（Cardiometabolic Disease，CMD）[1-2]。中国心血管代谢性疾病患病率处于持续上升的阶段，且疾病负担严重[3]。研究显示，中国普通人群中CMM的患病率在5年内增加一倍以上，且超过一半的糖尿病患者和约五分之一的高血压患者进一步发展为CMM[4]。其中肥胖是一个重要的危险因素，它会增加CMM的发生风险。目前评价肥胖的传统指标是BMI（body mass index，BMI），但BMI无法准确描述人体脂肪的具体分布，特别是在评价腹部脂肪时有一定的局限性。2013年，Thomas等人开发身体圆度指数（body roundness index，BRI），结合身高和腰围，用于预测身体脂肪百分比，并进一步评估个体的健康状况[5]。多项研究表明，BRI对CMM及其危险因素的预测能力优于BMI，可以作为评价CMD患病风险的一个重要指标[6-7]。本研究探讨浙江省35~75岁居民BRI与CMM之间的关系，为通过简便的方法识别高危人群提供数据支撑。
1　对象与方法
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1.1　研究对象
基于2022年中国居民营养与健康状况监测调查的浙江省部分，于2022年4月至2023年4月，在浙江省采用多阶段分层整群抽样方法抽取18岁以上居民为研究对象。研究在3 326名符合条件的18岁及以上常住居民中进行（调查前一年内在当地居住6个月及以上，排除孕妇、乳母及患有严重精神类疾病且无法正常沟通者），筛选出符合研究年龄范围（35~75岁）的人群，共2 737人。在进一步排除缺失值后，最终纳入2 426人用于分析。本研究通过中国疾病预防控制中心营养与健康所伦理审查委员会审查通过（NO.2022-008），所有调查对象均知情同意并签署知情同意书。
1.2　研究方法
本研究由经过统一培训的调查员进行入户面访，内容包括一般情况问卷和个人健康及行为问卷。一般情况问卷主要涵盖一般资料（性别、年龄、民族、教育程度等）和生活方式（吸烟、饮酒、身体活动、睡眠等）。体格检查包括身高、体重、腰围和血压的测量，并计算BMI和BRI。身高使用SZG-210型身高坐高计测量，体重使用G&GTC-200K型电子体重计；腰围测量采用统一标准，宽1 cm，最小刻度0.1 cm的腰围尺。血压测量统一使用欧姆龙HBP1320型电子血压计，要求在清晨进行，测量对象的右臂（如右侧手臂无法测量，则换用左侧手臂），测量前需安静休息5分钟，每次测量间隔约12分钟，共测量3次取平均值。实验室检测，抽取调查对象的静脉血，要求空腹8~12小时。主要检测指标包括总胆固醇（total cholesterol，TC）、甘油三酯（triglycerides，TG）、高密度脂蛋白胆固醇（high-density lipoprotein cholesterol，HDL-C）、低密度脂蛋白胆固醇（low-density lipoprotein cholesterol，LDL-C）、空腹血糖（fasting plasma glucose，FPG）和糖化血红蛋白（hemoglobin a1c，HbA1c）。
1.3　相关指标与定义
1.3.1　CMM定义
本研究将心血管代谢性疾病共病（CMM）定义为同时患有两种或两种以上的心血管代谢性疾病（CMD），包括糖尿病、高血压、血脂异常、冠心病和脑卒中。高血压：依据《中国高血压防治指南（2018年修订版）》[8]，在未使用降压药物的情况下，收缩压（SBP）≥ 140 mmHg 和/或舒张压（DBP） ≥ 90 mmHg；既往有高血压史且目前正在使用降压药物。糖尿病：依据《中国2型糖尿病防治指南（2020年版）》[9]，FPG ≥ 7.0 mmol/L 和/或 HbA1c ≥ 6.5%；已在正规医院诊断为糖尿病。血脂异常：依据《中国血脂管理指南（2023年）》[10]，TC≥6.22 mmol/L 和/或 TG≥2.23 mmol/L；LDL-C≥4.14 mmol/L 和/或 HDL-C < 1.04 mmol/L；最近3个月内服用过调脂类药物。冠心病：为自我报告的冠心病、心绞痛或心脏病发作史，脑卒中：为自我报告的脑卒中病史。
1.3.2　身体圆度指数BRI
[5]，具体分位数为：第1分位数Q1（≤2.95），第2分位数Q2（2.95~3.69），第3分位数Q3（3.70~4.56），第4分位数Q4（≥4.57）。
1.3.3　睡眠时长
根据睡眠时长分为三类[11-12]：睡眠不足（每日睡眠时间少于6小时）、适宜睡眠（每日睡眠时间为6~8小时）和睡眠过多（每日睡眠时间超过8小时）。
1.3.4　身体活动
依据WHO《身体活动和久坐行为的指南》[11]：（1）身体活动不足：每周总活动时间少于150分钟。（2）身体活动充足：每周总活动时间达到或超过150分钟。
1.4　质量控制
所有参与调查的人员经过统一培训并考核合格，体格检查由医学专业人员负责。所有现场测量的仪器需符合国际计量认证标准。浙江省疾病预防控制中心派督导人员驻各调查点，负责数据录入、监督现场工作并提供技术支持。
1.5　统计学分析
采用EpiData 3.1建立数据库后进行双录入，统计学分析采用R 4.3.3和 SPSS 30.0。符合正态分布的计量资料采用均数±标准差，多组间比较采用方差分析；计数资料采用构成比或率表示，组间比较采用χ2检验。BRI四分位分组与不同CMD和CMM的患病情况之间的趋势分析采用Cochran-Armitage检验。此外，采用多因素logistic回归分析BRI与CMD、CMM的关系，并调整性别、年龄、吸烟、饮酒、睡眠时长和身体活动为协变量。在本研究中，所有统计检验均采用显著性水平α=0.05进行分析。P<0.05被认为具有统计学意义。
2　结果
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2.1　基本资料
本研究纳入2 426名浙江省35~75岁居民，平均年龄为55.61±11.29岁，男性占40.35%，女性占59.65%，以农村居民为主（58.78%）。研究对象的平均腰围为83.16±9.28 cm，平均BRI为3.84±1.17kg/m2。在BRI的四个分位组间，研究人群的性别、年龄、婚姻状况、受教育程度、饮酒、吸烟、睡眠时间、腰围、BMI和BRI的分布差异均具有统计学意义（P< 0.001或P<0.05），详见表1。
2.2　BRI四分位分组不同CMD和CMM的患病情况
在本研究中，高血压（41.43%）、糖尿病（15.46%）、血脂异常（40.07%）、冠心病（1.20%）、脑卒中（0.78%）和CMM（27.99%）的总体患病率分别如表2所示。进一步进行BRI分层的趋势性检验显示，除脑卒中（P趋势=0.340）外，高血压（P趋势<0.001）、糖尿病（P趋势<0.001）、血脂异常（P趋势<0.001）、冠心病（P趋势<0.001）和CMM（P趋势<0.001）的患病率均随BRI水平的升高而增加（P<0.05）。
2.3　BRI与CMM和CMD的多因素logistic回归分析
在多因素分析中，调整了性别、年龄、吸烟、饮酒、睡眠时长和身体活动后，较高的BRI分位数（Q2、Q3、Q4）与高血压、糖尿病、血脂异常、冠心病和CMM的风险呈正相关（见表3）。与Q1组相比，在Q4组中高血压（OR=4.10，95%CI:3.11~5.38）、糖尿病（OR=3.18，95%CI:2.20~4.61）、血脂异常（OR=3.84，95%CI:2.95~5.00）及CMM（OR=5.20，95%CI:3.76~7.13）的风险均升高。值得注意的是，经多变量调整后（模型2），冠心病风险虽呈现3.40倍的升高趋势（OR=3.40，95%CI:0.74~15.71），但未达到统计学显著性（P=0.11）。
2.4　BRI与CMM关联的亚组分析
分层分析表明，BRI与CMM风险之间存在正相关关系（P<0.001），且在不同亚组（性别、饮酒状况、年龄、吸烟状况、睡眠时长和身体活动）中均有意义。此外，年龄（P交互=0.014）和吸烟状况（P交互=0.048）对BRI与CMM风险的关联具有交互作用（见表4）。
2.5　BRI和BMI对CMM的预测能力ROC曲线
表5和图1结果显示BRI对CMM发病风险具有一定的预测能力，且优于BMI。BRI的AUC为0.684，95%CI:0.662~0.707，而BMI的AUC值为0.640，95%CI:0.617~0.664，两者之间的AUC差异具有统计学意义（P< 0.01）。
3　讨论
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研究结果显示，BRI与CMD、CMM之间存在密切联系。随着BRI水平的升高，CMM风险也随之增加。在调整混杂因素后，BRI在Q4组的高血压、糖尿病、血脂异常、冠心病、脑卒中和CMM患病风险分别为Q1组的4.10倍、3.18倍、3.84倍、3.40倍、1.10倍和5.20倍。此外，BRI水平对CMM的影响在中青年和吸烟者中更为明显。
多项研究已证明，BRI是一种简单有效的心血管代谢性危险因素或疾病风险评估指标[13-14]，最近的一项基于中国人群的队列研究中进一步证实，BRI在预测CMM风险方面具有较强的识别能力[7]。本研究结果也进一步支持BRI作为CMD风险评估工具，通过比较BRI和BMI的预测能力，显示BRI在识别高危人群方面优于BMI。此外，BRI与高血压、糖尿病、血脂异常、高尿酸血症和代谢综合征的风险增加密切相关[15-19]，在代谢性疾病风险评估中表现出重要价值。一项基于中国北方社区的前瞻性队列研究发现，较高的BRI轨迹与心血管事件风险密切联系，在55岁以下人群中更为显著[20]。另外一项研究指出，中年阶段，尤其是在 50岁时，临床、社会经济和行为因素对CMM的发生与进展有重要影响[21]。与既往研究一致，本研究结果显示，在男性、吸烟者以及中青年（35~54岁）中，CMM的风险高于其他组别，并且在不同年龄段和吸烟状态中存在交互作用。本研究进一步细化了年龄分段，揭示了35~54岁组的特定风险特征，即风险随年龄增长至54岁后逐渐下降。这一发现可能与年龄相关的代谢改变以及健康行为模式的变化有关。
此外，吸烟与CMM之间的交互作用进一步强调了吸烟对疾病风险的影响。有研究指出，越早开始吸烟，CMM的发生几率越高[22]。当吸烟与肥胖、血脂异常、高血压等共同存在时，疾病风险大幅增加[23]。尼古丁可能影响脂肪细胞功能，诱发炎症，进而加重胰岛素抵抗，导致腹部脂肪堆积并增加动脉粥样硬化风险[24-25]。尽管性别因素与CMM风险之间未发现显著的交互作用，但男性患病风险仍明显高于女性，可能与中年男性工作压力较大、应酬较多以及健康意识较薄弱等因素有关。此外，超过半数的参试者运动不足。同时，浙江省居民普遍存在畜禽肉类和食用油摄入量过高的现象，因此高热量的饮食和较低的身体活动水平也可能导致CMM风险的进一步增加。因此，应重点关注这一高风险人群，结合其生活方式特点，制定针对性的早期干预措施，以提供有效的预防策略。
本研究进一步提供了浙江省人群BRI与CMM关联的最新数据。通过分析BRI与CMM的关系，证实了BRI在疾病风险早期识别中的重要价值。但本研究仍有局限性：本研究为横断面研究，无法推断BRI水平与CMD、CMM之间的因果关联；基于自我报告的脑卒中和冠心病诊断信息，对这些疾病的实际患病率估计不足，可能导致信息偏差。尽管BRI优于BMI，但AUC值均低于0.7（BRI:0.684; BMI: 0.640），提示预测效能有限，可在更多中国人群样本中进行验证，以构建更可靠的相关模型。BRI作为国外学者提出的基于身体脂肪分布的新指标，未来的研究需要进一步探索其在多种人群及不同疾病状态下的适用性。
综上所述，本研究为BRI浙江省成年人BRI对于CMD的关联增添了新证据。结果表明，浙江省35 ~75岁居民的BRI水平与CMD的患病风险呈正相关。控制BRI水平可能有助于降低CMD的发生风险。因此，建议BRI水平较高的人，在预防CMD发生的同时，减少抽烟喝酒、保持健康饮食、增加体力活动等，在日常生活中，积极进行体重管理，避免脂肪在腹部堆积过多。然而，在公共卫生和临床实践中推广这些建议时应保持谨慎，需进一步研究以验证其有效性和可行性，以确保干预措施的科学性和适用性。
基金
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  • 浙江省医药卫生科技计划(2025KY760)
文献
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2025年第52卷第10期
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doi: 10.20043/j.cnki.MPM.202411468
  • 接收时间：2024-11-25
  • 首发时间：2026-03-18
  • 出版时间：2025-05-25
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  • 收稿日期：2024-11-25
基金
浙江省医药卫生科技计划(2025KY760)
作者信息
    1.杭州医学院公共卫生学院，浙江 杭州 311399
    2.浙江省疾病预防控制中心

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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