Article(id=1241035551734813190, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202408306, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1724256000000, receivedDateStr=2024-08-22, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773815532859, onlineDateStr=2026-03-18, pubDate=1735056000000, pubDateStr=2024-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773815532859, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773815532859, creator=13701087609, updateTime=1773815532859, updator=13701087609, issue=Issue{id=1241035543589483182, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='24', pageStart='4417', pageEnd='4608', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773815530917, creator=13701087609, updateTime=1773815686426, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241036195896029478, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241036195896029479, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4591, endPage=4596, ext={EN=ArticleExt(id=1241035552326210088, articleId=1241035551734813190, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association of triglyceride glucose-Body Mass Index (TyG-BMI) and risk of developing type 2 diabetes mellitus, columnId=null, journalTitle=Modern Preventive Medicine, columnName=null, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the association between Triglyceride Glucose-Body Mass Index (TyG-BMI) and the risk of developing type 2 diabetes mellitus (T2DM).

Methods

The data were obtained from the natural population cohort of Shanghai suburbs established from April 2016 to September 2017 (Songjiang subcohort). 29,351 nondiabetic subjects with normal blood glucose levels aged 20-74 years at baseline were included in the analysis. The association and dose-response relationship between baseline TyG-BMI level and the risk of developing T2DM were assessed by Cox proportional risk regression model and restricted cubic spline model. Covariates such as gender and age were stratified according to their covariates and their interaction with TyG-BMI was analyzed.

Results

A total of 584 men and 777 women were initially diagnosed with T2DM after a median follow-up time of 6.98 years. After correcting for confounders, the Cox regression model showed a 58% increase in the risk of T2DM incidence for every 1 SD increase in TyG-BMI (HR=1.58, 95% CI: 1.50-1.66). After grouping TyG-BMI by quartiles and then including it as a categorical variable in the Cox regression model analysis, the risk of T2DM incidence increased progressively in the Q2, Q3, and Q4 groups with HR (95% CI) of 1.42 (1.15-1.75), 2.02(1.66-2.46), and 3.47(2.88-4.19), respectively (Ptrend<0.001), using the Q1 group as the control. Restricted cubic spline plots showed a nonlinear association between TyG-BMI and the risk of T2DM incidence (Pnonlinear =0.048). In addition, subgroup analyses showed that the association between TyG-BMI and the risk of developing T2DM was significantly higher in young and middle-aged (less than 60 years old) residents than in older residents (Pinteraction < 0.05).

Conclusion

Under normal blood glucose levels, baseline TyG-BMI was positively associated with the risk of developing T2DM, and this association was more significant in the young and middle-aged groups.

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目的

探索甘油三酯葡萄糖-体重指数(TyG-BMI)与2型糖尿病(T2DM)发病风险的关联。

方法

数据来源于2016年4月至2017年9月建立的上海郊区自然人群队列(松江子队列)。选取基线中20~74周岁、血糖水平正常的非糖尿病人群作为研究对象(29 351名)。通过Cox比例风险回归模型和限制性立方样条模型评估基线TyG-BMI水平与T2DM发病风险之间的关联及剂量-反应关系。根据性别、年龄等协变量进行分层并分析其与TyG-BMI的交互作用。

结果

经历中位随访时间6.98年,共有584名男性和777名女性被初次诊断为T2DM。校正混杂因素后,Cox回归模型显示,TyG-BMI每增加1个SD,T2DM发病风险增加58%(HR=1.58,95% CI:1.50~1.66)。将TyG-BMI按四分位数进行分组后作为分类变量纳入Cox回归模型分析,以Q1组为对照,Q2、Q3、Q4组的T2DM发病风险逐渐增加,HR(95% CI)分别为1.42(1.15~1.75)、2.02(1.66~2.46)和3.47(2.88~4.19)(P趋势<0.001)。限制性立方样条图显示,TyG-BMI与T2DM发病风险存在非线性关联(P非线性=0.048)。此外,亚组分析结果显示,青中年(60岁以下)居民TyG-BMI与T2DM发病风险的关联显著高于老年居民(P交互<0.05)。

结论

在血糖水平正常的情况下,基线TyG-BMI与T2DM的发病风险呈正相关,且这种关联在青中年群体中更为显著。

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奚超,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=JQ69FZpgJ6nrSz19jXEkJw==, magXml=opwqVtrIcFf12cOeDec+PQ==, pdfUrl=null, pdf=QfzJz5v1+RarNtHauOWvxQ==, pdfFileSize=685264, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=8PTdFOhkcg1PVh4HI0Kyvw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=CoAr+GVboSVHAHh/cXga8Q==, mapNumber=null, authorCompany=null, fund=null, authors=

张方芳(1994—),女,硕士,医师,研究方向:健康教育与健康促进。

王云辉(1977—),男,本科,主管医师,研究方向:疾病控制

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PLOS One, 2023, 18(7): e0287263., articleTitle=Lifestyle factors related to prevalent chronic disease multimorbidity: A population-based cross-sectional study, refAbstract=null)], funds=[Fund(id=1241069989906674237, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, awardId=GWVI-11.1-23, language=CN, fundingSource=上海市加强公共卫生体系建设三年行动计划(2023-2025年)重点学科建设项目(GWVI-11.1-23), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241069981354487868, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, xref=1., ext=[AuthorCompanyExt(id=1241069981362876475, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, companyId=1241069981354487868, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Songjiang Center for Disease Control and Prevention, Shanghai 201620, China), AuthorCompanyExt(id=1241069981371265084, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, companyId=1241069981354487868, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.上海市松江区疾病预防控制中心,上海 201620)]), AuthorCompany(id=1241069981442568258, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, xref=2., ext=[AuthorCompanyExt(id=1241069981446762563, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, companyId=1241069981442568258, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.上海市松江区新桥社区卫生服务中心)]), AuthorCompany(id=1241069981518065737, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, xref=3., ext=[AuthorCompanyExt(id=1241069981543231562, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, companyId=1241069981518065737, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.复旦大学公共卫生学院流行病学教研室/公共卫生安全教育部重点实验室)]), AuthorCompany(id=1241069981631311949, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, xref=4., ext=[AuthorCompanyExt(id=1241069981656477776, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, companyId=1241069981631311949, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.上海市松江区中山街道社区卫生服务中心)])], figs=[ArticleFig(id=1241069987125850534, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=EN, label=Fig.1, caption=Flowchart for screening research subjects, figureFileSmall=3s8rnWpHoXCEjHKd18dZfw==, figureFileBig=l7p+HHp7NKySeOJTXlPm5w==, tableContent=null), ArticleFig(id=1241069987222319537, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=CN, label=图1, caption=研究对象筛选流程图, figureFileSmall=3s8rnWpHoXCEjHKd18dZfw==, figureFileBig=l7p+HHp7NKySeOJTXlPm5w==, tableContent=null), ArticleFig(id=1241069987398480318, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=EN, label=Fig.2, caption=Dose-response relationship between TyG-BMI and risk of developing T2DM, figureFileSmall=SH+U9qghWLfM4s8qeeNCYw==, figureFileBig=NrOferqXObbQhyMA4pgHLA==, tableContent=null), ArticleFig(id=1241069987599806928, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=CN, label=图2, caption=TyG-BMI与T2DM发病风险之间的剂量反应关系, figureFileSmall=SH+U9qghWLfM4s8qeeNCYw==, figureFileBig=NrOferqXObbQhyMA4pgHLA==, tableContent=null), ArticleFig(id=1241069989084590558, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=EN, label=Table 1, caption=

Comparison of general baseline information for subgroups with different TyG-BMI levels

, figureFileSmall=null, figureFileBig=null, tableContent=
变量TyG-BMI水平检验统计值P
Q1(n=7 338)Q2(n=7 337)Q3(n=7 338)Q4(n=7 338)
年龄(岁)53.00(42.00,62.00)57.00(50.00,64.00)59.00(51.00,65.00)58.00(51.00,65.00)691.993a<0.001
性别(%)327.831b<0.001
2 424(33.03)2 776(37.84)3 193(43.51)3 411(46.48)
4 914(66.97)4 561(62.16)4 145(56.49)3 927(53.52)
文化程度(%)706.359b<0.001
小学及以下2 642(36.00)3 341(45.54)3 451(47.03)3 545(48.31)
初中2 668(36.36)2 720(37.07)2 727(37.16)2 592(35.32)
高中及中专1 020(13.90)842(11.48)785(10.70)812(11.07)
高职大专及以上1 008(13.74)434(5.92)375(5.11)389(5.30)
吸烟(%)110.245b<0.001
现在吸烟1 312(17.88)1 344(18.32)1 481(20.18)1 660(22.62)
过去吸烟185(2.52)246(3.35)300(4.09)302(4.12)
从不吸烟5 841(79.60)5 747(78.33)5 557(75.73)5 376(73.26)
饮酒(%)153.169b<0.001
现在饮酒702(9.57)811(11.05)971(13.23)1 114(15.18)
过去饮酒47(0.64)60(0.82)101(1.38)88(1.20)
从不饮酒6 589(89.79)6 466(88.13)6 266(85.39)6 136(83.62)
糖尿病家族史(%)20.532b<0.001
607(8.27)719(9.80)712(9.70)762(10.38)
6 731(91.73)6 618(90.20)6 626(90.30)6 576(89.62)
FPG(mmol/L)4.49(4.16,4.86)4.58(4.20,5.02)4.65(4.24,5.18)4.81(4.32,5.41)892.302a<0.001
HbA1c(mmol/L)5.40(5.20,5.70)5.50(5.30,5.80)5.60(5.30,5.90)5.70(5.40,6.00)1 492.853a<0.001
TG(mmol/L)0.91(0.73,1.16)1.18(0.93,1.51)1.48(1.14,1.93)1.98(1.47,2.75)10 455.240a<0.001
BMI(kg/m220.39±1.5223.08±1.1925.03±1.3328.05±2.4027 148.636c<0.001
SBP(mm Hg)123.71±17.60130.85±18.27135.04±18.19138.85±18.44937.430c<0.001
DBP(mm Hg)75.25±9.9378.75±9.9381.10±10.0583.62±10.32918.307c<0.001
TC(mmol/L)4.67±0.854.90±0.884.97±0.905.11±1.00302.948c<0.001
LDL-C(mmol/L)2.60±0.762.83±0.792.86±0.822.80±0.91155.474c<0.001
HDL-C(mmol/L)1.62±0.351.48±0.311.36±0.301.23±0.341 916.213c<0.001
), ArticleFig(id=1241069989189448169, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=CN, label=表1, caption=

不同TyG-BMI水平分组一般基线资料比较

, figureFileSmall=null, figureFileBig=null, tableContent=
变量TyG-BMI水平检验统计值P
Q1(n=7 338)Q2(n=7 337)Q3(n=7 338)Q4(n=7 338)
年龄(岁)53.00(42.00,62.00)57.00(50.00,64.00)59.00(51.00,65.00)58.00(51.00,65.00)691.993a<0.001
性别(%)327.831b<0.001
2 424(33.03)2 776(37.84)3 193(43.51)3 411(46.48)
4 914(66.97)4 561(62.16)4 145(56.49)3 927(53.52)
文化程度(%)706.359b<0.001
小学及以下2 642(36.00)3 341(45.54)3 451(47.03)3 545(48.31)
初中2 668(36.36)2 720(37.07)2 727(37.16)2 592(35.32)
高中及中专1 020(13.90)842(11.48)785(10.70)812(11.07)
高职大专及以上1 008(13.74)434(5.92)375(5.11)389(5.30)
吸烟(%)110.245b<0.001
现在吸烟1 312(17.88)1 344(18.32)1 481(20.18)1 660(22.62)
过去吸烟185(2.52)246(3.35)300(4.09)302(4.12)
从不吸烟5 841(79.60)5 747(78.33)5 557(75.73)5 376(73.26)
饮酒(%)153.169b<0.001
现在饮酒702(9.57)811(11.05)971(13.23)1 114(15.18)
过去饮酒47(0.64)60(0.82)101(1.38)88(1.20)
从不饮酒6 589(89.79)6 466(88.13)6 266(85.39)6 136(83.62)
糖尿病家族史(%)20.532b<0.001
607(8.27)719(9.80)712(9.70)762(10.38)
6 731(91.73)6 618(90.20)6 626(90.30)6 576(89.62)
FPG(mmol/L)4.49(4.16,4.86)4.58(4.20,5.02)4.65(4.24,5.18)4.81(4.32,5.41)892.302a<0.001
HbA1c(mmol/L)5.40(5.20,5.70)5.50(5.30,5.80)5.60(5.30,5.90)5.70(5.40,6.00)1 492.853a<0.001
TG(mmol/L)0.91(0.73,1.16)1.18(0.93,1.51)1.48(1.14,1.93)1.98(1.47,2.75)10 455.240a<0.001
BMI(kg/m220.39±1.5223.08±1.1925.03±1.3328.05±2.4027 148.636c<0.001
SBP(mm Hg)123.71±17.60130.85±18.27135.04±18.19138.85±18.44937.430c<0.001
DBP(mm Hg)75.25±9.9378.75±9.9381.10±10.0583.62±10.32918.307c<0.001
TC(mmol/L)4.67±0.854.90±0.884.97±0.905.11±1.00302.948c<0.001
LDL-C(mmol/L)2.60±0.762.83±0.792.86±0.822.80±0.91155.474c<0.001
HDL-C(mmol/L)1.62±0.351.48±0.311.36±0.301.23±0.341 916.213c<0.001
), ArticleFig(id=1241069989344637435, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=EN, label=Table 2, caption=

Cox regression analysis of TyG-BMI and T2DM incidence

, figureFileSmall=null, figureFileBig=null, tableContent=
变量发病例数发病密度
(千人年)
HR(95% CI
未调整模型模型Ⅰ模型Ⅱ
Per SD1 3616.961.65(1.58~1.73)1.63(1.55~1.71)1.58(1.50~1.66)
Q11432.811.001.001.00
Q22404.791.69(1.38~2.08)1.49(1.21~1.83)1.42(1.15~1.75)
Q33587.242.56(2.11~3.10)2.17(1.78~2.63)2.02(1.66~2.46)
Q462012.824.51(3.76~5.41)3.90(3.25~4.67)3.47(2.88~4.19)
P趋势<0.001<0.001<0.001
), ArticleFig(id=1241069989457883658, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=CN, label=表2, caption=

TyG-BMI与T2DM发病的COX回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量发病例数发病密度
(千人年)
HR(95% CI
未调整模型模型Ⅰ模型Ⅱ
Per SD1 3616.961.65(1.58~1.73)1.63(1.55~1.71)1.58(1.50~1.66)
Q11432.811.001.001.00
Q22404.791.69(1.38~2.08)1.49(1.21~1.83)1.42(1.15~1.75)
Q33587.242.56(2.11~3.10)2.17(1.78~2.63)2.02(1.66~2.46)
Q462012.824.51(3.76~5.41)3.90(3.25~4.67)3.47(2.88~4.19)
P趋势<0.001<0.001<0.001
), ArticleFig(id=1241069989566935576, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=EN, label=Table 3, caption=

Association between TyG-BMI and T2DM in different phenotypic populations

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分组人数HR(95% CIP交互
Q1Q2Q3Q4
性别0.943
11 8041.001.51(1.08~2.11)2.18(1.60~2.98)3.69(2.73~4.99)
17 5471.001.37(1.05~1.79)1.92(1.49~2.48)3.37(2.64~4.30)
年龄(岁)0.031
20~393 4031.001.83(0.49~6.91)1.24(0.23~6.68)6.61(2.02~21.64)
40~5913 7591.002.02(1.42~2.88)2.65(1.88~3.75)4.86(3.47~6.79)
60~7412 1891.001.11(0.85~1.45)1.70(1.33~2.17)2.74(2.17~3.46)
吸烟0.546
现在吸烟5 7971.001.70(1.08~2.66)2.31(1.50~3.55)3.69(2.44~5.60)
过去吸烟1 0331.000.81(0.29~2.24)2.05(0.87~4.79)2.52(1.07~5.91)
从不吸烟22 5211.001.39(1.09~1.77)1.94(1.54~2.44)3.51(2.82~4.37)
饮酒0.172
现在饮酒3 5981.002.75(1.44~5.28)3.09(1.64~5.84)4.75(2.56~8.83)
过去饮酒2961.003.97(0.46~34.50)2.09(0.24~18.29)4.01(0.49~33.03)
从不饮酒25 4571.001.27(1.02~1.59)1.92(1.56~2.37)3.36(2.75~4.01)
糖尿病家族史0.486
2 8001.001.88(0.90~3.92)3.06(1.52~6.15)5.70(2.90~11.19)
26 5511.001.39(1.12~1.73)1.94(1.58~2.39)3.30(2.71~4.01)
), ArticleFig(id=1241069989675987489, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035551734813190, language=CN, label=表3, caption=

不同表型人群中TyG-BMI与T2DM之间的关联

, figureFileSmall=null, figureFileBig=null, tableContent=
分组人数HR(95% CIP交互
Q1Q2Q3Q4
性别0.943
11 8041.001.51(1.08~2.11)2.18(1.60~2.98)3.69(2.73~4.99)
17 5471.001.37(1.05~1.79)1.92(1.49~2.48)3.37(2.64~4.30)
年龄(岁)0.031
20~393 4031.001.83(0.49~6.91)1.24(0.23~6.68)6.61(2.02~21.64)
40~5913 7591.002.02(1.42~2.88)2.65(1.88~3.75)4.86(3.47~6.79)
60~7412 1891.001.11(0.85~1.45)1.70(1.33~2.17)2.74(2.17~3.46)
吸烟0.546
现在吸烟5 7971.001.70(1.08~2.66)2.31(1.50~3.55)3.69(2.44~5.60)
过去吸烟1 0331.000.81(0.29~2.24)2.05(0.87~4.79)2.52(1.07~5.91)
从不吸烟22 5211.001.39(1.09~1.77)1.94(1.54~2.44)3.51(2.82~4.37)
饮酒0.172
现在饮酒3 5981.002.75(1.44~5.28)3.09(1.64~5.84)4.75(2.56~8.83)
过去饮酒2961.003.97(0.46~34.50)2.09(0.24~18.29)4.01(0.49~33.03)
从不饮酒25 4571.001.27(1.02~1.59)1.92(1.56~2.37)3.36(2.75~4.01)
糖尿病家族史0.486
2 8001.001.88(0.90~3.92)3.06(1.52~6.15)5.70(2.90~11.19)
26 5511.001.39(1.12~1.73)1.94(1.58~2.39)3.30(2.71~4.01)
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甘油三酯葡萄糖-体重指数与2型糖尿病发病风险的关联
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张方芳 1 , 王云辉 2 , 刘星 3 , 李静 4 , 阚云龙 1 , 张文翠 1 , 唐敏华 1 , 奚超 1
现代预防医学 | 临床与预防 2024,51(24): 4591-4596
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现代预防医学 | 临床与预防 2024, 51(24): 4591-4596
甘油三酯葡萄糖-体重指数与2型糖尿病发病风险的关联
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张方芳1, 王云辉2, 刘星3, 李静4, 阚云龙1, 张文翠1, 唐敏华1, 奚超1
作者信息
  • 1.上海市松江区疾病预防控制中心,上海 201620
  • 2.上海市松江区新桥社区卫生服务中心
  • 3.复旦大学公共卫生学院流行病学教研室/公共卫生安全教育部重点实验室
  • 4.上海市松江区中山街道社区卫生服务中心
  • 张方芳(1994—),女,硕士,医师,研究方向:健康教育与健康促进。

    王云辉(1977—),男,本科,主管医师,研究方向:疾病控制

通讯作者:

奚超,E-mail:
Association of triglyceride glucose-Body Mass Index (TyG-BMI) and risk of developing type 2 diabetes mellitus
Fang-fang ZHANG1, Yun-hui WANG2, Xing LIU3, Jing LI4, Yun-long KAN1, Wen-cui ZHANG1, Min-hua TANG1, Chao XI1
Affiliations
  • Songjiang Center for Disease Control and Prevention, Shanghai 201620, China
出版时间: 2024-12-25 doi: 10.20043/j.cnki.MPM.202408306
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目的

探索甘油三酯葡萄糖-体重指数(TyG-BMI)与2型糖尿病(T2DM)发病风险的关联。

方法

数据来源于2016年4月至2017年9月建立的上海郊区自然人群队列(松江子队列)。选取基线中20~74周岁、血糖水平正常的非糖尿病人群作为研究对象(29 351名)。通过Cox比例风险回归模型和限制性立方样条模型评估基线TyG-BMI水平与T2DM发病风险之间的关联及剂量-反应关系。根据性别、年龄等协变量进行分层并分析其与TyG-BMI的交互作用。

结果

经历中位随访时间6.98年,共有584名男性和777名女性被初次诊断为T2DM。校正混杂因素后,Cox回归模型显示,TyG-BMI每增加1个SD,T2DM发病风险增加58%(HR=1.58,95% CI:1.50~1.66)。将TyG-BMI按四分位数进行分组后作为分类变量纳入Cox回归模型分析,以Q1组为对照,Q2、Q3、Q4组的T2DM发病风险逐渐增加,HR(95% CI)分别为1.42(1.15~1.75)、2.02(1.66~2.46)和3.47(2.88~4.19)(P趋势<0.001)。限制性立方样条图显示,TyG-BMI与T2DM发病风险存在非线性关联(P非线性=0.048)。此外,亚组分析结果显示,青中年(60岁以下)居民TyG-BMI与T2DM发病风险的关联显著高于老年居民(P交互<0.05)。

结论

在血糖水平正常的情况下,基线TyG-BMI与T2DM的发病风险呈正相关,且这种关联在青中年群体中更为显著。

2型糖尿病  /  甘油三酯葡萄糖-体重指数  /  队列研究
Objective

To explore the association between Triglyceride Glucose-Body Mass Index (TyG-BMI) and the risk of developing type 2 diabetes mellitus (T2DM).

Methods

The data were obtained from the natural population cohort of Shanghai suburbs established from April 2016 to September 2017 (Songjiang subcohort). 29,351 nondiabetic subjects with normal blood glucose levels aged 20-74 years at baseline were included in the analysis. The association and dose-response relationship between baseline TyG-BMI level and the risk of developing T2DM were assessed by Cox proportional risk regression model and restricted cubic spline model. Covariates such as gender and age were stratified according to their covariates and their interaction with TyG-BMI was analyzed.

Results

A total of 584 men and 777 women were initially diagnosed with T2DM after a median follow-up time of 6.98 years. After correcting for confounders, the Cox regression model showed a 58% increase in the risk of T2DM incidence for every 1 SD increase in TyG-BMI (HR=1.58, 95% CI: 1.50-1.66). After grouping TyG-BMI by quartiles and then including it as a categorical variable in the Cox regression model analysis, the risk of T2DM incidence increased progressively in the Q2, Q3, and Q4 groups with HR (95% CI) of 1.42 (1.15-1.75), 2.02(1.66-2.46), and 3.47(2.88-4.19), respectively (Ptrend<0.001), using the Q1 group as the control. Restricted cubic spline plots showed a nonlinear association between TyG-BMI and the risk of T2DM incidence (Pnonlinear =0.048). In addition, subgroup analyses showed that the association between TyG-BMI and the risk of developing T2DM was significantly higher in young and middle-aged (less than 60 years old) residents than in older residents (Pinteraction < 0.05).

Conclusion

Under normal blood glucose levels, baseline TyG-BMI was positively associated with the risk of developing T2DM, and this association was more significant in the young and middle-aged groups.

Type 2 diabetes mellitus  /  Triglyceride-glucose-body mass index  /  Cohort study
张方芳, 王云辉, 刘星, 李静, 阚云龙, 张文翠, 唐敏华, 奚超. 甘油三酯葡萄糖-体重指数与2型糖尿病发病风险的关联. 现代预防医学, 2024 , 51 (24) : 4591 -4596 . DOI: 10.20043/j.cnki.MPM.202408306
Fang-fang ZHANG, Yun-hui WANG, Xing LIU, Jing LI, Yun-long KAN, Wen-cui ZHANG, Min-hua TANG, Chao XI. Association of triglyceride glucose-Body Mass Index (TyG-BMI) and risk of developing type 2 diabetes mellitus[J]. Modern Preventive Medicine, 2024 , 51 (24) : 4591 -4596 . DOI: 10.20043/j.cnki.MPM.202408306
随着生活方式转变和人口老年化加剧,近年来我国糖尿病患者人数大幅增加,其中最常见的类型为2型糖尿病(type 2 diabetes mellitus,T2DM),占比超过90%[1]。国际糖尿病联合会发布的数据显示,2021年我国已有超过1.4亿的成年人患有糖尿病,占全球患者的26.2%,预计到2045年,我国糖尿病患者总数将增至1.74亿[2]。胰岛素抵抗(insulin resistance,IR)是指胰岛素靶器官或组织对胰岛素的敏感性和反应性降低的一种状态,与T2DM的发生密切相关[3]。目前评价IR的金标准是高胰岛素-正葡萄糖钳夹(hyper-insulinemic euglycemic clamp,HEC)技术[4],然而该方法昂贵费时,不适用于广泛的人群筛查和治疗监测。既往研究已证实,甘油三酯葡萄糖指数(triglyceride glucose index,TyG)可作为IR的简单替代指标[5-6]。近年来有研究显示,TyG和体重指数(body mass index,BMI)的联合指标甘油三酯葡萄糖-体重指数(Triglyceride Glucose-Body Mass Index,TyG-BMI)比单独TyG更能准确的评估IR[7]。但目前关于TyG-BMI与T2DM发病之间关联的研究仍然较少[8-10]。本研究基于人群队列数据探索TyG-BMI与T2DM发病之间的关系,为T2DM的早期预防和管理提供新思路。
数据来源于2016年4月—2017年9月建立的上海郊区自然人群队列(松江子队列)[11]。该队列采用多阶段分层整群抽样法招募队列成员,首先根据地理位置和人口规模在上海市松江区选取4个社区(2个城镇社区、1个城乡结合社区和1个农村社区),然后在抽中的社区中随机抽取1/3的居委会(行政村)作为队列现场,对每个现场20~74周岁、拥有上海户籍或在上海居住时间≥5年的居民进行招募,共计36 404人纳入队列。本研究剔除人员信息重复、重要体检信息(空腹血糖(FPG)、糖化血红蛋白(HbA1c)、甘油三酯(TG))缺失、BMI极端值、基线糖尿病患者以及诊断时间距离基线调查<180天者后,最终纳入分析对象29 351人(详见流程图1)。所有调查对象均签署知情同意书。该研究已获复旦大学公共卫生学院医学研究伦理委员会批准(IRB#2016-04-0586)。
研究对象在进入队列时,分别对其进行问卷调查、体格检查和生化检测。
问卷调查:采用标准化问卷,由经过专业统一培训且考核合格的调查人员,在研究对象所属的社区卫生服务中心内,进行一对一调查。问卷内容包括人口学信息、生活方式、疾病史、家族史等。
体格检查:由社区医务人员依据标准方法测量研究对象的身高、体重、静息血压(包括收缩压(SBP)和舒张压(DBP))等,其中每名研究对象的身高和体重测量两次取平均值记录,血压测量三次取平均值记录。
生化检测:采集研究对象空腹静脉血2 ml,送至迪安医学检验中心,由专业人员检测FPG、HbA1c、TG、总胆固醇(TC)、高密度脂蛋白胆固醇(HDL-C)、低密度脂蛋白胆固醇(LDL-C)等生化指标。
吸烟:每天至少一支烟、连续吸烟6个月以上,根据吸烟状态分为现在吸烟、过去吸烟和从不吸烟;饮酒:每周至少3次、连续喝酒6个月以上,根据饮酒状态分为现在饮酒、过去饮酒和从不饮酒。
BMI=身高(kg)/体重(m)2;TyG=Ln[FPG(mg/dl)×TG(mg/dl)/2][6];TyG-BMI=TyG×BMI[7]。FPG,1 mg/dl=0.055 5 mmol/l;TG,1 mg/dl=0.011 29 mmol/l。
利用上海市健康管理平台的医疗信息系统和松江区疾病预防控制中心糖尿病登记报告系统收集随访数据。基于第十版国际疾病分类(ICD-10),编码E11定义为T2DM。在基线时自我报告糖尿病史、或依据FPG≥7.0 mmol/L或HbA1c≥6.5%[12])被诊断为糖尿病、糖尿病确诊时间距离基线调查<180天的参与者被排除。在后续的随访中,首次诊断T2DM记录为新发。随访截止时间为2023年12月31日。
使用SPSS 19.0软件和R 4.2.1软件进行数据处理和统计分析。采用χ2检验比较分类变量组间差异,方差分析和Kruskal-Wallis H检验比较连续变量组间差异。采用多因素Cox比例风险回归模型评估TyG-BMI水平与T2DM发病风险之间的关联;限制性立方样条(RCS)模型评估TyG-BMI水平与T2DM发病风险之间的剂量-反应关系。检验水准α=0.05。
最终纳入29 351名符合条件的观察者。其中男性11 804名和女性17 547名,中位年龄为57.00(49.00,64.00)岁,平均TyG-BMI为206.64±34.17。根据观察对象的TyG-BMI 四分位数进行分组(Q1:TyG-BMI≤182.19;Q2:182.19<TyG-BMI≤204.43;Q3:204.43<TyG-BMI≤228.46;Q4:228.46<TyG-BMI)。结果显示,相比于Q1组,Q4组男性、文化程度小学及以下、吸烟、饮酒及有糖尿病家族史的人数占比更高,年龄、BMI、SBP、DBP、FPG、HbA1c、TG、TC和LDL-C数值更高,HDL-C数值更低(P值均<0.05)。见表1
随访至2023年末,共随访195 481.90人年,新发T2DM病例共1 361例(男性584例,女性777例),总发病密度为6.96例每千人年。将TyG-BMI以连续变量为自变量,是否新发T2DM为因变量,建立Cox回归模型。在校正性别、年龄、文化程度、吸烟、饮酒、SBP、DBP、TC、LDL-C和糖尿病家族史后,结果显示,TyG-BMI每升高1个SD,T2DM发病风险增加58%(HR=1.58,95% CI:1.50~1.66)。
将TyG-BMI以分类变量为自变量,是否新发T2DM为因变量,建立Cox回归模型。校正了上述相关因素后,与Q1组相比,Q2、Q3和Q4组T2DM发病风险逐渐增加,HR分别为1.42(95% CI:1.15~1.75)、2.02(95% CI:1.66~2.46)和3.47(95% CI:2.88~4.19)(P趋势<0.001)。见表2
以TyG-BMI连续变量的P5P25P75P95四个百分位数为节点绘制限制性立方样条曲线,在校正性别、年龄、文化程度、吸烟、饮酒、SBP、DBP、TC、LDL-C和糖尿病家族史后,结果显示,TyG-BMI与T2DM发病风险之间存在非线性关系(χ2=287.583,P整体<0.001;χ2=6.081,P非线性=0.048),T2DM发病风险随着TyG-BMI水平的增加而增加。见图2
结果显示,青年和中年人群Q4组TyG-BMI与T2DM发病风险的关联显著高于老年人群(20~39岁:HRQ4 vs. Q1=6.61;40~59岁:HRQ4 vs. Q1=4.86;60~74岁:HRQ4 vs. Q1=2.74),年龄与TyG-BMI对T2DM发病风险存在交互作用(P交互<0.05)。性别、吸烟、饮酒和有无糖尿病家族史的亚组分析中未见显著交互作用(P交互>0.05)。见表3
本研究基于上海郊区自然人群队列探索成人TyG-BMI与T2DM发病之间的关联,结果显示在血糖正常的健康成人中,较高的TyG-BMI水平与新发T2DM呈正相关。在校正混杂因素后,TyG-BMI每增加1个SD,T2DM发病风险增加58%。TyG-BMI最高四分位组T2DM发病风险是最低四分位组的3.47倍。表明TyG-BMI对T2DM新发风险具有一定的提示作用。TyG-BMI是一种涉及FPG、TG和BMI的新型指数,与T2DM发病关系的潜在机制目前尚不清楚,可能与IR有关。IR和胰岛β细胞功能缺陷已被证实是T2DM的关键致病因素[13]。研究显示在FPG水平正常的成人中,随着FPG升高,胰岛素敏感性下降[14]。TG水平与正常糖耐量患者的IR呈正相关,与血脂异常患者的β细胞功能呈负相关[15]。既往研究表明TG累积可诱导细胞应激,从而导致脂毒性促进肝脏、肌肉及脂肪中IR的发生[16]。高BMI是公认的糖尿病危险因素之一[1,17]。肥胖引起的全身慢性炎症,可诱发IR最终导致T2DM[18]
国内一随访3年的大型成人体检队列研究发现,在女性和50岁以下人群中TyG-BMI与糖尿病前期的发病风险关联更高[19]。日本一项随访13年的成人队列研究结果显示,基线TyG-BMI与T2DM发病风险成正相关,且这种风险在女性和年轻人中相对更高[9]。Jiang等人通过横断面研究发现,早发性T2DM患者(18~39岁)相比于晚发型T2DM患者(≥40岁),TyG-BMI水平更高[20]。本次研究结果显示,青年人和中年人高水平TyG-BMI与T2DM发病风险的关联显著高于老年人,但未发现性别与TyG-BMI的交互作用。不同年龄层TyG-BMI与T2DM发病风险关联不同这一现象可能与随着社会快速发展,人口老年化的加剧,青年人和中年人的社会压力日益增加,生活娱乐方式也发生转变,更易养成不健康的生活方式,进而影响机体代谢有关[21-23]
本研究数据来源于队列人群,具有较大的样本量及较长的随访时间,暴露与结局符合因果关系的时间逻辑顺序,研究结果较为可靠。同时,本研究也存在一定的局限性。研究中T2DM新发数据来源于医疗系统和糖尿病管理系统,可能会存在部分遗漏,导致糖尿病发病率低于实际情况;研究所分析的队列人群均为上海市郊区常住居民,研究结果的外推可能具有一定局限性;本次研究只分析了基线数据,无法评估TyG-BMI水平动态变化对T2DM发病的影响。
综上所述,TyG-BMI水平升高与T2DM发病风险的增加有关,在青、中年人群中这种关联更加明显。在后续研究中,将进一步探索TyG-BMI动态变化对T2DM发病风险的影响。
  • 上海市加强公共卫生体系建设三年行动计划(2023-2025年)重点学科建设项目(GWVI-11.1-23)
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2024年第51卷第24期
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doi: 10.20043/j.cnki.MPM.202408306
  • 接收时间:2024-08-22
  • 首发时间:2026-03-18
  • 出版时间:2024-12-25
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  • 收稿日期:2024-08-22
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上海市加强公共卫生体系建设三年行动计划(2023-2025年)重点学科建设项目(GWVI-11.1-23)
作者信息
    1.上海市松江区疾病预防控制中心,上海 201620
    2.上海市松江区新桥社区卫生服务中心
    3.复旦大学公共卫生学院流行病学教研室/公共卫生安全教育部重点实验室
    4.上海市松江区中山街道社区卫生服务中心

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2种不同金属材料的力学参数

Family
属数
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genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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