Article(id=1241023854827590199, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202410246, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1729094400000, receivedDateStr=2024-10-17, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812744098, onlineDateStr=2026-03-18, pubDate=1737734400000, pubDateStr=2025-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812744098, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812744098, creator=13701087609, updateTime=1773812744098, updator=13701087609, issue=Issue{id=1241023847537897695, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='2', pageStart='193', pageEnd='384', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812742361, creator=13701087609, updateTime=1773812823817, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024189247845056, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024189247845057, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=198, endPage=202, ext={EN=ArticleExt(id=1241023855607730792, articleId=1241023854827590199, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between cardiometabolic index and risk of kidney stones in a health screening population, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To assess the association between the cardiometabolic index (CMI) and the risk of kidney stone prevalence, and to analyze its role across different population subgroups.

Methods

This cross-sectional study included health examination data from 76 624 adults. The association between CMI and the risk of kidney stones was evaluated using multivariable logistic regression models. Stratified analyses were conducted to explore the effect of different population characteristics. A piecewise linear regression model was used to assess the nonlinear relationship between CMI and kidney stone risk.

Results

CMI levels were positively associated with the prevalence of kidney stones, with the prevalence increasing from 4.33% in the lowest tertile to 9.94% in the highest tertile (P<0.001). Even after adjusting for potential confounders, CMI remained significantly associated with an increased risk of kidney stones (OR = 1.15, 95% CI = 1.10-1.20, P<0.001). Stratified analyses showed that the effect of CMI on kidney stone risk was more pronounced in individuals aged ≥60 years (OR = 1.19, 95% CI = 1.08-1.32, P<0.001) and in males (OR = 1.16, 95% CI = 1.10-1.21, P<0.001), while no significant association was found in females (OR = 1.11, 95% CI = 0.96-1.28, P = 0.157). A nonlinear relationship was observed between CMI and kidney stone risk. Risk significantly increased when CMI was <0.73 (OR = 1.15, 95% CI = 1.10-1.20, P<0.001), while the risk plateaued for CMI ≥0.73 (OR = 1.09, 95% CI = 1.03-1.15, P = 0.002).

Conclusion

Elevated CMI is significantly associated with a higher risk of kidney stones, demonstrating a nonlinear threshold effect. As a comprehensive marker reflecting metabolic burden, CMI may be useful for screening and targeting interventions in high-risk populations for kidney stones.

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目的

评估心脏代谢指数(cardiometabolic index,CMI)与肾结石患病风险之间的关联,并分析其在不同人群特征中的作用。

方法

采用横断面研究设计,纳入76 624名成年人的健康体检数据。通过多因素logistic回归模型评估CMI与肾结石风险的关联,并进行分层分析以探讨不同人群特征的影响。利用分段线性回归模型分析CMI与肾结石风险的非线性关系。

结果

CMI水平与肾结石患病率呈正相关,患病率从最低三分位组的4.33%上升至最高组的9.94%(P<0.001)。即使在调整混杂因素后,CMI仍与肾结石风险显著相关(OR=1.15, 95% CI=1.10~1.20, P<0.001)。分层分析显示,CMI对肾结石风险的影响在≥60岁人群(OR=1.19, 95% CI=1.08~1.32, P<0.001)和男性(OR=1.16, 95% CI=1.10~1.21, P<0.001)中更为显著,而在女性中未发现显著性(OR=1.11, 95% CI=0.96~1.28, P=0.157)。CMI与肾结石风险呈现非线性关系,CMI <0.73时风险显著增加(OR=1.15, 95% CI=1.10~1.20, P<0.001),而CMI ≥0.73时风险增加趋势减缓(OR=1.09, 95% CI=1.03~1.15, P=0.002)。

结论

CMI升高与肾结石风险显著相关,且呈现非线性阈值效应。作为反映代谢负担的综合指标,CMI可用于肾结石高风险人群的筛查与干预。

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姚曳和李一帆为共同通信作者;姚曳,E-mail:
李一帆,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=Ig4A3Lik8hAPKOVfrpKyIA==, magXml=0XuGzB2GPzYB58K8QETD0w==, pdfUrl=null, pdf=FWyw+5vhxXblNrW3tpuDjA==, pdfFileSize=611660, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=BjhHN9zIVcgc9niwJqcO/A==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=ldaXjdPh07fUDWHTePGTCg==, mapNumber=null, authorCompany=null, fund=null, authors=

郑生旗(1997—),男,硕士,研究方向:泌尿系结石的发生发展机制

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郑生旗(1997—),男,硕士,研究方向:泌尿系结石的发生发展机制

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Association between cardiometabolic index andhyperuricemia in ethnic minorities, Guizhou[J]. Modern Preventive Medicine, 2024, 51(16): 2887-2891,2917. (In Chinese), articleTitle=Association between cardiometabolic index andhyperuricemia in ethnic minorities, Guizhou, refAbstract=null), Reference(id=1241023867603439867, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=1, pageStart=1525, pageEnd=null, url=null, language=null, rfNumber=[23], rfOrder=23, authorNames=Deng HY, Zhang XH, Cheng N, journalName=BMC Public Health, refType=null, unstructuredReference=Deng HY, Zhang XH, Cheng N, et al. Asymptomatic hyperuricemia associated with increased risk of nephrolithiasis: a cross-sectional study[J]. BMC Public Health, 2023, 23(1): 1525., articleTitle=Asymptomatic hyperuricemia associated with increased risk of nephrolithiasis: a cross-sectional study, refAbstract=null)], funds=[Fund(id=1241023863644016690, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, awardId=82002675, language=CN, fundingSource=国家自然科学基金(82002675), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241023856496923299, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, xref=1., ext=[AuthorCompanyExt(id=1241023856505311908, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, companyId=1241023856496923299, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Urology, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu 225001, China), AuthorCompanyExt(id=1241023856513700517, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, companyId=1241023856496923299, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.扬州大学附属医院泌尿外科,江苏 扬州 225001)]), AuthorCompany(id=1241023856601780904, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, xref=2., ext=[AuthorCompanyExt(id=1241023856610169513, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, companyId=1241023856601780904, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.苏北人民医院疝儿外科)])], figs=[ArticleFig(id=1241023861009994673, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=EN, label=Fig.1, caption=Smooth curve fitting of cardiometabolic index and kidney stone risk, figureFileSmall=z9rqPIshVxyWEgqT53zEjw==, figureFileBig=BjhHN9zIVcgc9niwJqcO/A==, tableContent=null), ArticleFig(id=1241023861106463672, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=CN, label=图1, caption=心脏代谢指数与肾结石患病风险的平滑曲线拟合

注:图中中间的实线是拟合线,阴影部分是95%可信区间。

, figureFileSmall=z9rqPIshVxyWEgqT53zEjw==, figureFileBig=BjhHN9zIVcgc9niwJqcO/A==, tableContent=null), ArticleFig(id=1241023861349733336, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=EN, label=Table 1, caption=

Baseline characteristics of the study population by CMI tertiles

, figureFileSmall=null, figureFileBig=null, tableContent=
变量CMI三等分P
T1T2T3
人数25 54125 54125 542
年龄(岁)44.26±14.6249.53±14.8449.42±13.61<0.001
性别<0.001
9 242(36.18)15 843(62.03)20 272(79.37)
16 299(63.82)9 698(37.97)5 270(20.63)
肾结石<0.001
1 105(4.33)1 775(6.95)2 540(9.94)
24 436(95.67)23 766(93.05)23 002(90.06)
糖尿病<0.001
890(3.48)2131(8.34)3 572(13.98)
24 651(96.52)23 410(91.66)21 970(86.02)
高血压<0.001
4 832(18.92)9 534(37.33)12 858(50.34)
20 709(81.08)16 007(62.67)12 684(49.66)
腰围(cm)77.02±7.5484.64±7.9590.04±8.41<0.001
身高(cm)166.59±7.76168.60±8.36170.58±8.00<0.001
BMI(kg/m221.97±2.6924.48±3.0026.40±3.30<0.001
FBG(mmol/L)5.18±0.865.51±1.205.88±1.66<0.001
TC(mmol/L)4.64±0.864.88±0.925.03±0.93<0.001
TG(mmol/L)0.81±0.221.40±0.312.72±1.04<0.001
HDL-C(mmol/L)1.57±0.271.28±0.211.05±0.18<0.001
LDL-C(mmol/L)2.56±0.692.92±0.742.86±0.77<0.001
Cr(μmol/L)61.34±16.1067.77±21.7571.91±23.02<0.001
SU(μmol/L)296.19±74.31345.71±82.27391.37±88.64<0.001
), ArticleFig(id=1241023861442008033, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=CN, label=表1, caption=

不同心脏代谢指数受试者的一般临床资料比较

, figureFileSmall=null, figureFileBig=null, tableContent=
变量CMI三等分P
T1T2T3
人数25 54125 54125 542
年龄(岁)44.26±14.6249.53±14.8449.42±13.61<0.001
性别<0.001
9 242(36.18)15 843(62.03)20 272(79.37)
16 299(63.82)9 698(37.97)5 270(20.63)
肾结石<0.001
1 105(4.33)1 775(6.95)2 540(9.94)
24 436(95.67)23 766(93.05)23 002(90.06)
糖尿病<0.001
890(3.48)2131(8.34)3 572(13.98)
24 651(96.52)23 410(91.66)21 970(86.02)
高血压<0.001
4 832(18.92)9 534(37.33)12 858(50.34)
20 709(81.08)16 007(62.67)12 684(49.66)
腰围(cm)77.02±7.5484.64±7.9590.04±8.41<0.001
身高(cm)166.59±7.76168.60±8.36170.58±8.00<0.001
BMI(kg/m221.97±2.6924.48±3.0026.40±3.30<0.001
FBG(mmol/L)5.18±0.865.51±1.205.88±1.66<0.001
TC(mmol/L)4.64±0.864.88±0.925.03±0.93<0.001
TG(mmol/L)0.81±0.221.40±0.312.72±1.04<0.001
HDL-C(mmol/L)1.57±0.271.28±0.211.05±0.18<0.001
LDL-C(mmol/L)2.56±0.692.92±0.742.86±0.77<0.001
Cr(μmol/L)61.34±16.1067.77±21.7571.91±23.02<0.001
SU(μmol/L)296.19±74.31345.71±82.27391.37±88.64<0.001
), ArticleFig(id=1241023861593002996, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=EN, label=Table 2, caption=

Association between CMI and risk of nephrolithiasis

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指标模型1模型2模型3
OR值(95% CI)POR值(95% CI)POR值(95% CI)P
CMI(连续变量)1.52(1.47~1.58)<0.0011.26(1.21~1.31)<0.0011.15(1.10~1.20)<0.001
CMI三分位
T11.001.001.00
T21.66(1.54~1.79)<0.0011.26(1.16~1.36)<0.0011.12(1.03~1.21)0.008
T32.47(2.29~2.65)<0.0011.58(1.46~1.71)<0.0011.29(1.18~1.41)<0.001
P趋势<0.001<0.001<0.001
), ArticleFig(id=1241023863102952444, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=CN, label=表2, caption=

心脏代谢指数与肾结石风险的关联分析

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指标模型1模型2模型3
OR值(95% CI)POR值(95% CI)POR值(95% CI)P
CMI(连续变量)1.52(1.47~1.58)<0.0011.26(1.21~1.31)<0.0011.15(1.10~1.20)<0.001
CMI三分位
T11.001.001.00
T21.66(1.54~1.79)<0.0011.26(1.16~1.36)<0.0011.12(1.03~1.21)0.008
T32.47(2.29~2.65)<0.0011.58(1.46~1.71)<0.0011.29(1.18~1.41)<0.001
P趋势<0.001<0.001<0.001
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Stratified analysis of the association between CMI and kidney stone

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变量OR值(95% CI)PP交互作用
年龄(岁)0.455
<401.16(1.06~1.26)0.001
40~<601.08(1.02~1.15)0.01
≥601.19(1.08~1.32)<0.001
高血压0.841
1.12(1.06~1.19)<0.001
1.15(1.08~1.23)<0.001
性别0.123
1.16(1.10~1.21)<0.001
1.11(0.96~1.28)0.157
糖尿病0.149
1.22(1.10~1.35)<0.001
1.13(1.07~1.18)<0.001
BMI分类0.106
正常1.22(1.11~1.35)<0.001
超重1.19(1.12~1.26)<0.001
肥胖1.07(0.99~1.16)0.084
), ArticleFig(id=1241023863329443856, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=CN, label=表3, caption=

CMI和肾结石关联的分层分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量OR值(95% CI)PP交互作用
年龄(岁)0.455
<401.16(1.06~1.26)0.001
40~<601.08(1.02~1.15)0.01
≥601.19(1.08~1.32)<0.001
高血压0.841
1.12(1.06~1.19)<0.001
1.15(1.08~1.23)<0.001
性别0.123
1.16(1.10~1.21)<0.001
1.11(0.96~1.28)0.157
糖尿病0.149
1.22(1.10~1.35)<0.001
1.13(1.07~1.18)<0.001
BMI分类0.106
正常1.22(1.11~1.35)<0.001
超重1.19(1.12~1.26)<0.001
肥胖1.07(0.99~1.16)0.084
), ArticleFig(id=1241023863438495773, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=EN, label=Table 4, caption=

Threshold effect analysis of the association between CMI and risk of kidney stone

, figureFileSmall=null, figureFileBig=null, tableContent=
CMIULR检验PLR检验LRT
P
OR值(95% CI)POR值(95% CI)P
<0.731.15(1.10~1.20)<0.0011.62(1.34~1.95)<0.001<0.001
≥0.731.09(1.03~1.15)0.002
), ArticleFig(id=1241023863530770472, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023854827590199, language=CN, label=表4, caption=

CMI与肾结石风险的阈值效应分析

, figureFileSmall=null, figureFileBig=null, tableContent=
CMIULR检验PLR检验LRT
P
OR值(95% CI)POR值(95% CI)P
<0.731.15(1.10~1.20)<0.0011.62(1.34~1.95)<0.001<0.001
≥0.731.09(1.03~1.15)0.002
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健康体检人群心脏代谢指数与肾结石风险的相关性分析
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郑生旗 1 , 王佳龙 1 , 邓泽勋 1 , 沈新宇 1 , 姚曳 2 , 李一帆 1
现代预防医学 | 流行病与统计方法 2025,52(2): 198-202
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现代预防医学 | 流行病与统计方法 2025, 52(2): 198-202
健康体检人群心脏代谢指数与肾结石风险的相关性分析
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郑生旗1, 王佳龙1, 邓泽勋1, 沈新宇1, 姚曳2 , 李一帆1
作者信息
  • 1.扬州大学附属医院泌尿外科,江苏 扬州 225001
  • 2.苏北人民医院疝儿外科
  • 郑生旗(1997—),男,硕士,研究方向:泌尿系结石的发生发展机制

通讯作者:

姚曳和李一帆为共同通信作者;姚曳,E-mail:
李一帆,E-mail:
Association between cardiometabolic index and risk of kidney stones in a health screening population
Sheng-qi ZHENG1, Jia-long WANG1, Ze-xun DENG1, Xin-yu SHEN1, Ye YAO2 , Yi-fan LI1
Affiliations
  • Department of Urology, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu 225001, China
出版时间: 2025-01-25 doi: 10.20043/j.cnki.MPM.202410246
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目的

评估心脏代谢指数(cardiometabolic index,CMI)与肾结石患病风险之间的关联,并分析其在不同人群特征中的作用。

方法

采用横断面研究设计,纳入76 624名成年人的健康体检数据。通过多因素logistic回归模型评估CMI与肾结石风险的关联,并进行分层分析以探讨不同人群特征的影响。利用分段线性回归模型分析CMI与肾结石风险的非线性关系。

结果

CMI水平与肾结石患病率呈正相关,患病率从最低三分位组的4.33%上升至最高组的9.94%(P<0.001)。即使在调整混杂因素后,CMI仍与肾结石风险显著相关(OR=1.15, 95% CI=1.10~1.20, P<0.001)。分层分析显示,CMI对肾结石风险的影响在≥60岁人群(OR=1.19, 95% CI=1.08~1.32, P<0.001)和男性(OR=1.16, 95% CI=1.10~1.21, P<0.001)中更为显著,而在女性中未发现显著性(OR=1.11, 95% CI=0.96~1.28, P=0.157)。CMI与肾结石风险呈现非线性关系,CMI <0.73时风险显著增加(OR=1.15, 95% CI=1.10~1.20, P<0.001),而CMI ≥0.73时风险增加趋势减缓(OR=1.09, 95% CI=1.03~1.15, P=0.002)。

结论

CMI升高与肾结石风险显著相关,且呈现非线性阈值效应。作为反映代谢负担的综合指标,CMI可用于肾结石高风险人群的筛查与干预。

肾结石  /  心脏代谢指数  /  腹部肥胖  /  胰岛素抵抗
Objective

To assess the association between the cardiometabolic index (CMI) and the risk of kidney stone prevalence, and to analyze its role across different population subgroups.

Methods

This cross-sectional study included health examination data from 76 624 adults. The association between CMI and the risk of kidney stones was evaluated using multivariable logistic regression models. Stratified analyses were conducted to explore the effect of different population characteristics. A piecewise linear regression model was used to assess the nonlinear relationship between CMI and kidney stone risk.

Results

CMI levels were positively associated with the prevalence of kidney stones, with the prevalence increasing from 4.33% in the lowest tertile to 9.94% in the highest tertile (P<0.001). Even after adjusting for potential confounders, CMI remained significantly associated with an increased risk of kidney stones (OR = 1.15, 95% CI = 1.10-1.20, P<0.001). Stratified analyses showed that the effect of CMI on kidney stone risk was more pronounced in individuals aged ≥60 years (OR = 1.19, 95% CI = 1.08-1.32, P<0.001) and in males (OR = 1.16, 95% CI = 1.10-1.21, P<0.001), while no significant association was found in females (OR = 1.11, 95% CI = 0.96-1.28, P = 0.157). A nonlinear relationship was observed between CMI and kidney stone risk. Risk significantly increased when CMI was <0.73 (OR = 1.15, 95% CI = 1.10-1.20, P<0.001), while the risk plateaued for CMI ≥0.73 (OR = 1.09, 95% CI = 1.03-1.15, P = 0.002).

Conclusion

Elevated CMI is significantly associated with a higher risk of kidney stones, demonstrating a nonlinear threshold effect. As a comprehensive marker reflecting metabolic burden, CMI may be useful for screening and targeting interventions in high-risk populations for kidney stones.

Kidney stone  /  Cardiometabolic index  /  Abdominal obesity  /  Insulin resistance
郑生旗, 王佳龙, 邓泽勋, 沈新宇, 姚曳, 李一帆. 健康体检人群心脏代谢指数与肾结石风险的相关性分析. 现代预防医学, 2025 , 52 (2) : 198 -202 . DOI: 10.20043/j.cnki.MPM.202410246
Sheng-qi ZHENG, Jia-long WANG, Ze-xun DENG, Xin-yu SHEN, Ye YAO, Yi-fan LI. Association between cardiometabolic index and risk of kidney stones in a health screening population[J]. Modern Preventive Medicine, 2025 , 52 (2) : 198 -202 . DOI: 10.20043/j.cnki.MPM.202410246
随着现代社会生活方式和饮食习惯的变化,肾结石的发病率显著上升,成为全球公共卫生领域的一大挑战[1]。除了引起剧烈疼痛外,肾结石还可能引发尿路感染和肾功能受损等并发症,严重影响患者的生活质量[2]。尽管研究人员已广泛研究肾结石的成因,但其具体的形成机制尚未完全明了。除了遗传因素和饮食习惯,代谢异常也被认为是影响肾结石形成的重要因素[3]。研究表明,高血压、糖尿病、肥胖和血脂异常等代谢综合征的组成部分与肾结石的发生密切相关[4-5],提示肾结石可能不仅是泌尿系统的局部问题,而是全身性代谢紊乱的反映。心脏代谢指数(cardiometabolic index, CMI),作为一种新兴的综合性指标,通过整合腰围、身高、甘油三酯和高密度脂蛋白胆固醇,为评估心血管和代谢疾病风险提供了新的视角[6]。值得注意的是,CMI与胰岛素抵抗密切相关[7],而胰岛素抵抗不仅是代谢综合征的核心成分之一,也是肾结石形成的重要风险因素[8]。探讨CMI与肾结石之间的关系,对于阐明肾结石的潜在机制、优化其预防和治疗策略具有重要意义。本研究基于大规模健康体检数据,采用横断面设计,分析CMI与肾结石的关联,以期为肾结石的早期识别和预防提供理论依据。
本项研究基于2022年度在扬州大学附属医院健康管理中心接受全面健康体检的成年人群。参与者的纳入标准为年满18周岁且完成了健康筛查项目(111 428人)。排除标准包括:未进行肾脏超声检查的个体(14 523人)、未进行甘油三酯或高密度脂蛋白胆固醇检测的个体(8 364人)以及协变量数据不全的个体(11 143人)。在初步筛选的基础上,进一步排除了CMI高于人群分布99%分位数的个体(774人),以减少极端值对研究结果的潜在影响。经过筛选,共有76 624名符合条件的受试者被纳入最终分析。
由经过培训的专业人员负责收集参与者的详尽资料并进行体格检查,涵盖年龄、性别、既往疾病史等人口统计学特征。体格检查项目包括身高、体质量和腰围测量,并计算体质指数(body mass index, BMI)。所有参与者在空腹12小时后采集血液样本,样本统一使用全自动生化分析仪进行检测,测定指标包括空腹血糖(fasting blood glucose, FBG)、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)、肌酐(creatinine, Cr)、血清尿酸(serum uric acid, SU)。肾结石的超声诊断由经验丰富的超声医师执行,采用美国通用电气公司的LOGIQ E9彩色多普勒超声诊断仪,使用腹部凸阵探头,频率设定在3.5至5.0 MHz。
高血压定义为收缩压≥140 mmHg和/或舒张压≥90 mmHg,或根据参与者提供的既往诊断记录以及当前使用抗高血压药物的情况来确定。糖尿病的定义基于以下条件之一:既往明确诊断的糖尿病、空腹血糖≥7.0 mmol/L或正在接受降糖治疗(包括口服药物或胰岛素治疗)。根据中国成人标准,BMI≥24 kg/m2定义为超重,BMI≥28 kg/m2定义为肥胖。肾结石的超声诊断基于对肾和泌尿系统结构异常的检测,主要依据为在肾区域发现强回声团、伴声影。CMI的计算公式为。按照三分位数法将CMI分为T1(CMI<0.377)、T2(CMI 0.377~0.774)、T3(CMI>0.774)。
数据分析使用R语言软件(版本4.2.0)进行。分类变量采用卡方检验,正态分布的连续变量采用单因素方差分析,偏态分布的连续变量采用Kruskal-Wallis H检验,以评估不同CMI指数组间的差异。构建三种不同的回归模型进行分析CMI与肾结石发生风险之间的独立关联性。此外,为了控制混杂因素,将方差膨胀因子小于5且显著关联的协变量纳入最终模型。模型1未进行协变量调整;模型2对性别、年龄、高血压和糖尿病进行了调整;模型3进一步对BMI、LDL-C、SU和Cr进行了调整。在亚组分析中,根据性别、年龄、高血压、糖尿病和BMI进行分层多元回归分析。采用分段线性回归模型结合平滑曲线拟合分析CMI与肾结石风险的非线性关系。递归算法确定折点,构建分段模型。对数似然比检验评估模型拟合度,比较非线性与传统线性模型。检验水准α=0.05,双侧检验。
本研究已获得扬州大学附属医院伦理委员会的批准(批准号:2023-YKL01-课13),并严格遵循《赫尔辛基宣言》对人类研究的伦理准则。鉴于本研究为回顾性分析且所有数据均已去标识化,伦理委员会特此免除了获取个体知情同意的要求。
基线特征分析显示,不同CMI三分位组间的人群特征存在显著差异,见表1。随着CMI三分位数的增加,肾结石的患病率显著升高,从T1组的4.33%增加到T3组的9.94%(P<0.001)。同样,糖尿病和高血压的患病率也随CMI升高而增加,分别从3.48%上升至13.98%(P<0.001)和18.92%上升至50.34%(P<0.001)。此外,随着CMI的增加,受试者的平均年龄、BMI、WC、FBG、TC、TG、LDL-C、Cr和SU等代谢指标显著升高,而HDL-C则显著降低。性别分布方面,女性比例随着CMI的增加显著降低,从T1组的63.82%下降至T3组的20.63%,而男性比例则从36.18%增加到79.37%(P<0.001)。
多因素logistic回归分析显示,CMI与肾结石风险呈显著的正相关关系,见表2。在未调整协变量的模型1中,每增加一个单位的CMI,肾结石风险增加52%(OR=1.52, 95%CI=1.47~1.58, P<0.001)。在模型2中,调整了年龄、性别、糖尿病和高血压等潜在混杂因素后,CMI与肾结石风险的关联性略有减弱,但依然显著(OR=1.26, 95%CI=1.21~1.31, P<0.001)。在模型3中,进一步控制了BMI、LDL-C、SU和Cr后,CMI与肾结石风险的正相关性仍保持稳健(OR=1.15, 95%CI=1.10~1.20, P<0.001)。此外,与CMI最低三分位数组相比,在最终模型中,中等和高CMI三分位数组的肾结石风险分别增加了12%(OR=1.12,95% CI=1.03~1.21,P=0.008)和29%(OR=1.29,95% CI=1.18~1.41,P<0.001),且风险随CMI水平的增加呈现显著的线性趋势(P趋势<0.001)。
分层分析显示,CMI与肾结石风险的正相关性在各亚组中均显著,但关联强度在不同亚组间存在差异,见表3。在年龄分层中,CMI对肾结石风险的影响在≥60岁人群中最为显著(OR=1.19, 95%CI=1.08~1.32, P<0.001),而在40岁以下人群中风险增加16%(OR=1.16, 95%CI=1.06~1.26, P=0.001),40至60岁人群中风险增加8%(OR=1.08, 95%CI=1.02~1.15, P=0.010)。性别亚组分析中,男性中CMI与肾结石风险显著相关(OR=1.16,95%CI=1.10~1.21,P<0.001),而女性组中的关联未达到统计学显著性(OR=1.11,95%CI=0.96~1.28,P=0.157)。无论是否患有高血压或糖尿病,CMI与肾结石风险的正相关性均显著,且在糖尿病患者中关联性更强(OR=1.22, 95%CI=1.10~1.35, P<0.001)。在不同BMI分类中,CMI与肾结石的关联在正常体重和超重组中显著,而在肥胖组中则较弱(OR=1.07, 95%CI=0.99~1.16, P=0.084)。值得注意的是,所有亚组间未发现CMI与肾结石风险交互作用的统计学意义。
进一步分析揭示,CMI与肾结石风险之间存在显著的非线性关系,见图1。在CMI小于0.73时,CMI与肾结石风险显著相关(OR=1.15, 95%CI=1.10~1.20, P<0.001),而当CMI达到或超过0.73时,相关性减弱(OR=1.09, 95%CI=1.03~1.15, P=0.002),见表4。对数似然比检验也支持这一阈值效应的显著性(P<0.001)。
本研究涵盖76 624名成年人的健康检查数据,结果显示CMI升高与肾结石患病率增加显著相关。即使在调整年龄、性别、糖尿病、高血压及BMI等潜在混杂因素后,CMI与肾结石风险的正相关性仍然稳健。分层分析表明,不同年龄、性别及代谢状态下,CMI对肾结石风险的影响具有一致性。而分段线性回归模型揭示了CMI与肾结石风险之间的非线性关系,提示CMI在临床应用中可能存在一个关键的风险拐点,有助于优化个体化的干预策略。
CMI是一种结合腹部肥胖与血脂代谢异常的综合指标,近年来在代谢性疾病风险预测中得到了广泛应用。已有研究表明,CMI升高与心血管事件(如高血压和动脉粥样硬化)的独立风险增加密切相关[9-10]。在糖尿病研究中,CMI被证明能够有效评估糖尿病的发生风险,并对血糖控制效果具有预测作用[11]。此外,CMI还与多种代谢性疾病(如高尿酸血症和代谢相关脂肪性肝病)显著关联[12-13]。这些研究凸显了CMI作为整合性代谢异常指标的临床应用潜力,能够全面反映个体的代谢负担。
与既往研究相一致,代谢综合征及其相关的代谢风险因素(如肥胖、高血压、糖尿病和血脂异常)被认为与肾结石的形成密切相关[14]。本研究的结果不仅支持这一观点,进一步强调了CMI作为综合代谢风险指标在预测肾结石风险中的作用。CMI通过整合腰围和血脂,反映个体的代谢负担和脂肪分布,更全面揭示代谢紊乱对肾结石形成的影响。分层分析结果显示,尽管CMI与肾结石风险的关联在不同人群中保持一致,但各亚组间的关联强度有所差异。年龄分层分析显示,CMI对≥60岁人群的肾结石风险影响更显著,可能与老年人代谢功能下降和肾脏易受损有关[15]。此外,性别分析显示,CMI与肾结石风险在男性中关联更强,而在女性中未达显著性,可能与男性更高的肾结石和代谢综合征患病率相关[16]。糖尿病患者中,CMI与肾结石风险的关联更为显著,提示糖尿病引发的代谢紊乱可能通过多种机制进一步增加肾结石风险[5]。BMI分层分析显示,CMI在正常体重和超重个体中与肾结石风险的关联显著,而在肥胖人群中较弱,可能由于肥胖者的肾结石风险受到其他因素(如炎症或代谢性并发症)影响较大,削弱了CMI的作用[17]
CMI与肾结石风险的关联可能涉及多种复杂的生物学机制。首先,CMI反映了腹部脂肪堆积及血脂代谢异常,这些因素与肾结石形成密切相关。高CMI通常伴随高甘油三酯和低高密度脂蛋白胆固醇水平,这种血脂异常状态可能通过增加尿液中钙、草酸和尿酸的排泄,从而提高结石形成的风险[18]。腹部肥胖与胰岛素抵抗密切相关,后者可通过促进肾小管对钙、钠和尿酸的重吸收,改变尿液成分,进而提高结石形成的可能性[8]。其次,CMI升高反映了系统性炎症的增加[19]。腹部脂肪组织分泌的炎性因子,如肿瘤坏死因子α和白细胞介素-6,不仅可损伤肾小管细胞,还可改变尿液化学成分,进一步促进结石的形成[20]。慢性低度炎症还可能加剧肾脏氧化应激,导致尿液酸碱平衡失调,并增加钙盐沉淀的可能性[21]。此外,CMI与肾结石风险的关联可能通过代谢异常导致的尿酸水平升高来解释。研究表明,CMI升高与血清尿酸水平显著相关[12,22],高尿酸水平不仅通过促进尿液中钙和草酸盐的沉积增加结石形成的风险,还可能通过降低尿液pH值,增强尿酸盐结晶的生成[23]
本研究首次系统地探讨了CMI与肾结石风险的关联,结果表明CMI可以作为识别高风险个体的有效指标。此外,分段线性回归模型提示临床上应重点关注CMI在0.73以上的高风险人群,以实施更有针对性的干预策略。尽管本研究为CMI与肾结石风险的关系提供了新的见解,仍存在一定局限性。首先,作为单中心的横断面研究,样本代表性和选择偏倚问题可能影响结果的广泛适用性,且因果关系的推断有限。尽管调整了多种混杂因素,仍可能存在未充分考虑的变量,如饮食习惯、家族史和生活方式等。此外,肾结石的形成受多种因素影响,本研究未涵盖所有潜在的致病因素。因此,未来需要进行多中心、大规模的前瞻性研究,以进一步验证CMI与肾结石风险的关联及其潜在的生物学机制。
综上所述,CMI升高与肾结石风险显著相关,并呈现非线性阈值效应。作为整合多种代谢异常的综合性指标,CMI在肾结石风险预测中展现了较高的效用,尤其在老年人和男性中。CMI在肾结石高风险人群的筛查和个体化预防策略中具有重要的应用潜力。
  • 国家自然科学基金(82002675)
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2025年第52卷第2期
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doi: 10.20043/j.cnki.MPM.202410246
  • 接收时间:2024-10-17
  • 首发时间:2026-03-18
  • 出版时间:2025-01-25
补充材料
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出版历史
  • 收稿日期:2024-10-17
基金
国家自然科学基金(82002675)
作者信息
    1.扬州大学附属医院泌尿外科,江苏 扬州 225001
    2.苏北人民医院疝儿外科

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姚曳和李一帆为共同通信作者;姚曳,E-mail:
李一帆,E-mail:
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https://castjournals.cast.org.cn/joweb/xdyfyx/CN/10.20043/j.cnki.MPM.202410246
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2种不同金属材料的力学参数

Family
属数
Number of
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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