Article(id=1320431967829610682, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320431836577247574, articleNumber=null, orderNo=null, doi=10.11847/zgggws1148944, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1758211200000, receivedDateStr=2025-09-19, revisedDate=1760630400000, revisedDateStr=2025-10-17, acceptedDate=1772812800000, acceptedDateStr=2026-03-07, onlineDate=1792745113569, onlineDateStr=2026-10-23, pubDate=1783612800000, pubDateStr=2026-07-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792745113569, onlineIssueDateStr=2026-10-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792745113569, creator=13701087609, updateTime=1792745113569, updator=13701087609, issue=Issue{id=1320431836577247574, tenantId=1146029695717560320, journalId=1319373219989389464, year='2026', volume='42', issue='7', pageStart='769', pageEnd='896', issueExtLink='null', onlineDate='null', pubDate='1783612800000', pubDateStr='2026-07-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792745082277, creator='13701087609', updateTime=1792748015122, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320444137892069377, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320431836577247574, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320444137892069378, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320431836577247574, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=826, endPage=834, ext={EN=ArticleExt(id=1320431971503820987, articleId=1320431967829610682, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Predictive performance of insulin resistance surrogate indices for hyperuricemia among Chinese older adults aged over 80 years: based on the China nutrition and health surveillance, 2015–2017, columnId=1320431862472880698, journalTitle=Chinese Journal of Public Health, columnName=Special Report—Promoting Active and Healthy Ageing, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the associations between insulin resistance surrogate indices and hyperuricemia among Chinese older adults aged over 80 years and evaluate the predictive performance of different indices for hyperuricemia, thus providing a scientific basis for the prevention and control of hyperuricemia in this population.

Methods

On the basis of the data from the China Nutrition and Health Surveillance (2015–2017), multistage stratified cluster random sampling was employed to select 2 667 participants aged over 80 years from 31 provinces (autonomous regions, municipalities) in China. A questionnaire survey, physical measurements, and laboratory tests were conducted. The triglyceride-glucose (TyG) index was combined with body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) to derive the TyG-BMI, TyG-WC, and TyG-WHtR indices, which, together with the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR), were used as insulin resistance surrogate indices. The participants were categorized by ascending quartiles. Hyperuricemia was defined as a serum uric acid concentration ≥ 420 μmol/L in men and ≥ 360 μmol/L in women. Multivariable unconditional logistic regression was adopted to explore the associations between insulin resistance surrogate indices and hyperuricemia. Receiver operating characteristic (ROC) curves were established to compare the predictive performance of different indices for hyperuricemia.

Results

Among the 2 667 Chinese older adults, 23.24% had hyperuricemia, and the prevalence of hyperuricemia was statistically different among different groups of body mass index (BMI) (χ2 = 38.167), marital status (χ2 = 4.012), sleep duration (χ2 = 6.452), hypertension (χ2 = 12.320), diabetes (χ2 = 4.922), and dyslipidemia (χ2 = 38.541) (all P < 0.05). The results of multivariable unconditional logistic regression showed that after adjusting for age, sex, BMI, place of residence, educational background, marital status, annual household income per capita, current smoking, current drinking, physical activity level, sleep duration, and the prevalence of hypertension, diabetes, and dyslipidemia, each insulin resistance surrogate index was positively associated with the risk of hyperuricemia. Compared with the lowest group, the highest group of TyG (OR = 1.79, 95%CI: 1.30–2.45), TyG-BMI (OR = 2.41, 95%CI: 1.41–4.13), TyG-WC (OR = 1.84, 95%CI: 1.27–2.67), TyG-WHtR (OR = 1.99, 95%CI: 1.39–2.86), TG/HDL-C (OR = 1.81, 95%CI: 1.31–2.50), and MET-IR (OR = 2.20, 95%CI: 1.32–3.69) had a significantly higher risk of hyperuricemia. ROC analysis suggested that the TyG-WC index had the best predictive performance for the prevalence of hyperuricemia in this population.

Conclusions

TyG, TyG-BMI, TyG-WC, TyG-WHtR, TG/HDL-C, and METS-IR are independent risk factors for hyperuricemia in the Chinese older adults aged over 80 years. The TyG-WC index could be used as an elite predictor of hyperuricemia risk, providing a new target for the prevention and treatment of hyperuricemia in this population.

, authors=Yuxiang YANG1, 2, Shuya CAI1, 3, Jiasi HAO2, Yanmei WANG2, Jing NAN1, Ruilian WANG1, Liyun ZHAO1, Dongmei YU1, 3, authorsList=Yuxiang YANG, Shuya CAI, Jiasi HAO, Yanmei WANG, Jing NAN, Ruilian WANG, Liyun ZHAO, Dongmei YU, authorCompany=null, correspAuthors=Dongmei YU, authorNote=null, correspAuthorsNote=
YU Dongmei, E-mail:
, copyrightStatement=Copyright © 2026 Chinese Journal of Public Health. All rights reserved., 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=1320431983335952589, articleId=1320431967829610682, tenantId=1146029695717560320, journalId=1319373219989389464, language=CN, title=中国≥80岁高龄老人胰岛素抵抗替代指数与高尿酸血症患病关系及其预测效能:基于2015—2017年中国居民营养与健康状况监测, columnId=1320431862640652860, journalTitle=中国公共卫生, columnName=专题报道——健康老龄化与积极老龄化, runingTitle=null, highlight=null, articleAbstract=
目的

探索中国≥80岁高龄老人胰岛素抵抗替代指数与高尿酸血症的关系,并评价不同指标对高尿酸血症的预测效能,为该人群高尿酸血症防治提供科学依据。

方法

基于中国居民营养与健康状况监测(2015—2017年)数据,采用多阶段分层整群随机抽样,对我国31个省(自治区、直辖市)抽取的2 667名80岁以上高龄老人进行问卷调查、体格测量和实验室检测。使用甘油三酯葡萄糖(TyG)指数并结合体质指数(BMI)、腰围(WC)、腰高比(WHtR)衍生的TyG-BMI、TyG-WC、TyG-WHtR指数、甘油三酯/高密度脂蛋白胆固醇比值(TG/HDL-C)以及胰岛素抵抗代谢评分(MET-IR)作为胰岛素抵抗的评估指标,并分别按升序将人群按四分位法分组,将男性血尿酸浓度≥420 μmol/L及女性血尿酸浓度≥360 μmol/L者定义为患有高尿酸血症,使用多因素非条件logistic回归分析二者关系,并结合受试者工作特征曲线比较不同指标对高尿酸血症患病的预测效能。

结果

中国2 667名高龄老人中,患高尿酸血症者占23.24%,且高尿酸血症患病率与体质指数(χ2=38.167)、婚姻状况(χ2=4.012)、睡眠时间分组(χ2=6.452)及高血压(χ2=12.320)、糖尿病(χ2=4.922)、血脂异常患病情况(χ2=38.541)组间差异均有统计学意义(均P<0.05)。多因素非条件logistic回归结果显示,在调整年龄、性别、BMI、居住地、文化程度、婚姻状况、家庭人均年收入、目前吸烟、目前饮酒、身体活动水平、睡眠时间以及高血压、糖尿病和血脂异常的患病情况后,各胰岛素抵抗指数最高组与最低组相比,TyG(OR=1.79,95%CI=1.30~2.45)、TyG-BMI(OR=2.41,95%CI=1.41~4.13)、TyG-WC(OR=1.84,95%CI=1.27~2.67)、TyG-WHtR(OR=1.99,95%CI=1.39~2.86)、TG/HDL-C(OR=1.81,95%CI=1.31~2.50)、MET-IR(OR=2.20,95%CI=1.32~3.69),更高的胰岛素抵抗指数均与高尿酸血症的患病风险存在正向关联。ROC分析提示,TyG-WC指数对高龄老人高尿酸血症患病情况的预测效能最优。

结论

TyG、TyG-BMI、TyG-WC、TyG-WHtR、TG/HDL-C以及METS-IR为中国80岁以上高龄老人患有高尿酸血症的独立风险因素,且TyG-WC指数可作为中国高龄老人高尿酸血症患病风险的较优预测因子,为该人群高尿酸血症的防治工作提供新靶点。

, authors=杨宇祥1, 2, 蔡姝雅1, 3, 郝佳锶2, 汪艳梅2, 南晶1, 王瑞莲1, 赵丽云1, 于冬梅1, 3, *, *, authorsList=杨宇祥, 蔡姝雅, 郝佳锶, 汪艳梅, 南晶, 王瑞莲, 赵丽云, 于冬梅, authorCompany=null, correspAuthors=于冬梅, authorNote=

杨宇祥(1996—),博士,研究方向:营养与健康流行病学

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于冬梅,E-mail:
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Ecotoxicology and Environmental Safety, 2025, 292: 117943., articleTitle=null, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1320431985009479886, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, xref=1, ext=[AuthorCompanyExt(id=1320431985030451407, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, companyId=1320431985009479886, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China), AuthorCompanyExt(id=1320431985064005840, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, companyId=1320431985009479886, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1中国疾病预防控制中心营养与健康所,北京 100050)]), AuthorCompany(id=1320431987047911634, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, xref=2, ext=[AuthorCompanyExt(id=1320431987068883155, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, companyId=1320431987047911634, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2University Medical Center Groningen, University of Groningen, Groningen 9713GZ, the Netherlands), AuthorCompanyExt(id=1320431987102437588, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, companyId=1320431987047911634, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2格罗宁根大学医学中心,荷兰 格罗宁根 9713GZ)]), AuthorCompany(id=1320431987475730645, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, xref=3, ext=[AuthorCompanyExt(id=1320431987488313558, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, companyId=1320431987475730645, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3NHC Key Laboratory of Public Nutrition and Health, Beijing 100050, China), AuthorCompanyExt(id=1320431987505090775, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, companyId=1320431987475730645, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3国家卫生健康委公共营养与健康重点实验室,北京 100050)])], figs=[ArticleFig(id=1320432008002654493, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=EN, label=Fig.1, caption=ROC curves of different insulin resistance surrogate indices for predicting hyperuricemia among Chinese older adults aged over 80 years, figureFileSmall=9M+nk9hu3ee/D5NFshgMIg==, figureFileBig=MFZva9VuRt/GJuloKYTUPA==, tableContent=null), ArticleFig(id=1320432008984121631, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=CN, label=图1, caption=中国80岁以上高龄老人不同胰岛素抵抗指标预测高尿酸血症的ROC曲线, figureFileSmall=9M+nk9hu3ee/D5NFshgMIg==, figureFileBig=MFZva9VuRt/GJuloKYTUPA==, tableContent=null), ArticleFig(id=1320432012662526243, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=EN, label=Tab.1, caption=

Basic information and prevalence of hyperuricemia in different characteristic groups of Chinese older adults aged over 80 years

, figureFileSmall=null, figureFileBig=null, tableContent=
基本特征总体高尿酸血症χ2值/t值P值
人数/均数a(构成比/%)/标准差b未患高尿酸血症患高尿酸血症
例数/均数(构成比/%)/标准差人数/均数(构成比/%)/标准差
总体2 667100.002 07476.7662023.24
性别0.9360.333
 男1 26747.5198377.5828422.42
 女1 40052.491 06476.0033624.00
BMI38.167<0.001
 消瘦2549.5221383.864116.14
 正常1 51456.771 19979.1931520.81
 超重69526.0650572.6619027.34
 肥胖2047.6513063.737436.27
居住地0.8380.360
 城市1 07240.1981375.8425924.16
 农村1 59559.811 23477.3736122.63
正规教育0.5910.442
 未接受1 43453.771 10977.3432522.66
 接受1 23346.2393876.0729523.93
家庭人均年收入/元0.3020.960
 <10 00092634.7271076.6721623.33
 10 000~<25 00067925.4652677.4715322.53
 ≥25 00052419.6540176.5312323.47
 未报告53820.1741076.2112823.79
婚姻状况4.0120.045
 已婚1 62961.081 22975.4540024.55
 离异及其他1 03838.9281878.8122021.19
吸烟0.0890.765
 是51019.1239477.2511622.75
 否2 15780.881 65376.6350423.37
饮酒1.7110.191
 是54020.2540374.6313725.37
 否2 12779.751 64477.2948322.71
身体活动水平1.8830.390
 低1 25947.2196576.6529423.35
 中74828.0556475.4018424.60
 高66024.7551878.4814221.52
睡眠时间/(h/d)6.4520.040
 <71 23946.4694776.4329223.57
 7~<974928.0859779.7115220.29
 ≥967925.4650374.0817625.92
高血压12.320<0.001
 是1 93572.551 45174.9948425.01
 否73227.4559681.4213618.58
糖尿病4.9220.027
 是37514.0627172.2710427.73
 否2 29285.941 77677.4951622.51
血脂异常38.541<0.001
 是91934.4664169.7527830.25
 否1 74865.541 40680.4334219.57
年龄/岁83.443.0283.433.0183.473.080.2600.796
TyG8.550.608.510.588.710.647.450<0.001
TyG-BMI195.5237.18192.2136.03206.4638.818.480<0.001
TyG-WC698.36117.83687.54114.34734.08122.148.740<0.001
TyG-WHtR4.540.754.470.734.760.798.380<0.001
TG/HDL-C2.742.812.522.293.504.007.680<0.001
METS-IR33.947.1733.206.8536.157.748.880<0.001
蔬菜摄入量/(g/d)278.63261.77273.76247.58294.72303.631.7500.081
水果摄入量/(g/d)58.95108.2656.5398.0666.93136.412.1000.036
畜肉类摄入量/(g/d)44.7368.3043.2065.8749.5775.612.0100.044
血清尿酸/(μmol/L)332.3992.47294.9159.49456.1371.7756.220<0.001
), ArticleFig(id=1320432013086150948, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=CN, label=表1, caption=

中国80岁及以上高龄老人不同特征分组的基本情况及高尿酸血症患病率

, figureFileSmall=null, figureFileBig=null, tableContent=
基本特征总体高尿酸血症χ2值/t值P值
人数/均数a(构成比/%)/标准差b未患高尿酸血症患高尿酸血症
例数/均数(构成比/%)/标准差人数/均数(构成比/%)/标准差
总体2 667100.002 07476.7662023.24
性别0.9360.333
 男1 26747.5198377.5828422.42
 女1 40052.491 06476.0033624.00
BMI38.167<0.001
 消瘦2549.5221383.864116.14
 正常1 51456.771 19979.1931520.81
 超重69526.0650572.6619027.34
 肥胖2047.6513063.737436.27
居住地0.8380.360
 城市1 07240.1981375.8425924.16
 农村1 59559.811 23477.3736122.63
正规教育0.5910.442
 未接受1 43453.771 10977.3432522.66
 接受1 23346.2393876.0729523.93
家庭人均年收入/元0.3020.960
 <10 00092634.7271076.6721623.33
 10 000~<25 00067925.4652677.4715322.53
 ≥25 00052419.6540176.5312323.47
 未报告53820.1741076.2112823.79
婚姻状况4.0120.045
 已婚1 62961.081 22975.4540024.55
 离异及其他1 03838.9281878.8122021.19
吸烟0.0890.765
 是51019.1239477.2511622.75
 否2 15780.881 65376.6350423.37
饮酒1.7110.191
 是54020.2540374.6313725.37
 否2 12779.751 64477.2948322.71
身体活动水平1.8830.390
 低1 25947.2196576.6529423.35
 中74828.0556475.4018424.60
 高66024.7551878.4814221.52
睡眠时间/(h/d)6.4520.040
 <71 23946.4694776.4329223.57
 7~<974928.0859779.7115220.29
 ≥967925.4650374.0817625.92
高血压12.320<0.001
 是1 93572.551 45174.9948425.01
 否73227.4559681.4213618.58
糖尿病4.9220.027
 是37514.0627172.2710427.73
 否2 29285.941 77677.4951622.51
血脂异常38.541<0.001
 是91934.4664169.7527830.25
 否1 74865.541 40680.4334219.57
年龄/岁83.443.0283.433.0183.473.080.2600.796
TyG8.550.608.510.588.710.647.450<0.001
TyG-BMI195.5237.18192.2136.03206.4638.818.480<0.001
TyG-WC698.36117.83687.54114.34734.08122.148.740<0.001
TyG-WHtR4.540.754.470.734.760.798.380<0.001
TG/HDL-C2.742.812.522.293.504.007.680<0.001
METS-IR33.947.1733.206.8536.157.748.880<0.001
蔬菜摄入量/(g/d)278.63261.77273.76247.58294.72303.631.7500.081
水果摄入量/(g/d)58.95108.2656.5398.0666.93136.412.1000.036
畜肉类摄入量/(g/d)44.7368.3043.2065.8749.5775.612.0100.044
血清尿酸/(μmol/L)332.3992.47294.9159.49456.1371.7756.220<0.001
), ArticleFig(id=1320432013451055398, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=EN, label=Tab.2, caption=

Associations between different insulin resistance surrogate indices and the risk of hyperuricemia among Chinese older adults aged over 80 years

, figureFileSmall=null, figureFileBig=null, tableContent=
胰岛素抵抗指标样本量模型1a模型2b模型3c
人数患病率/%OR(95%CI)P趋势dOR(95%CI)P趋势OR(95%CI)P趋势
TyG
 Q166616.82参照组<0.001参照组<0.001参照组<0.001
 Q266718.591.13(0.85~1.50)1.08(0.81~1.44)1.08(0.81~1.44)
 Q366725.041.65(1.26~2.16)1.51(1.15~1.99)1.46(1.10~1.94)
 Q466735.002.39(1.84~3.09)2.00(1.52~2.64)1.79(1.30~2.45)
TyG-BMI
 Q166614.86参照组<0.001参照组<0.001参照组<0.001
 Q266719.941.43(1.07~1.90)1.49(1.08~2.04)1.40(1.01~1.93)
 Q366725.041.91(1.45~2.52)2.05(1.42~2.97)1.74(1.18~2.56)
 Q466733.132.84(2.17~3.71)3.21(1.96~5.27)2.41(1.41~4.13)
TyG-WC
 Q166615.62参照组<0.001参照组<0.001参照组<0.001
 Q266718.291.21(0.91~1.61)1.15(0.85~1.54)1.09(0.81~1.47)
 Q366726.091.91(1.45~2.50)1.71(1.26~2.32)1.52(1.11~2.08)
 Q466732.982.66(2.04~3.46)2.24(1.58~3.16)1.84(1.27~2.67)
TyG-WHtR
 Q166616.22参照组<0.001参照组<0.001参照组<0.001
 Q266718.591.18(0.89~1.57)1.12(0.83~1.50)1.06(0.79~1.42)
 Q366723.091.55(1.18~2.04)1.41(1.03~1.91)1.28(0.93~1.76)
 Q466735.082.79(2.15~3.62)2.40(1.70~3.37)1.99(1.39~2.86)
TG/HDL-C
 Q166616.37参照组<0.001参照组<0.001参照组<0.001
 Q266718.591.17(0.88~1.55)1.11(0.83~1.47)1.10(0.82~1.46)
 Q366725.491.75(1.34~2.29)1.56(1.19~2.06)1.50(1.13~1.99)
 Q466732.532.46(1.90~3.20)2.04(1.55~2.69)1.81(1.31~2.50)
METS-IR
 Q166614.71参照组<0.001参照组<0.001参照组<0.001
 Q266720.391.48(1.12~1.97)1.49(1.09~2.03)1.42(1.03~1.94)
 Q366724.741.91(1.44~2.51)1.92(1.35~2.72)1.65(1.13~2.41)
 Q466733.132.87(2.20~3.76)2.90(1.85~4.54)2.20(1.32~3.69)
), ArticleFig(id=1320432013958566183, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=CN, label=表2, caption=

中国80岁以上高龄老人不同胰岛素抵抗指标与高尿酸血症的关系

, figureFileSmall=null, figureFileBig=null, tableContent=
胰岛素抵抗指标样本量模型1a模型2b模型3c
人数患病率/%OR(95%CI)P趋势dOR(95%CI)P趋势OR(95%CI)P趋势
TyG
 Q166616.82参照组<0.001参照组<0.001参照组<0.001
 Q266718.591.13(0.85~1.50)1.08(0.81~1.44)1.08(0.81~1.44)
 Q366725.041.65(1.26~2.16)1.51(1.15~1.99)1.46(1.10~1.94)
 Q466735.002.39(1.84~3.09)2.00(1.52~2.64)1.79(1.30~2.45)
TyG-BMI
 Q166614.86参照组<0.001参照组<0.001参照组<0.001
 Q266719.941.43(1.07~1.90)1.49(1.08~2.04)1.40(1.01~1.93)
 Q366725.041.91(1.45~2.52)2.05(1.42~2.97)1.74(1.18~2.56)
 Q466733.132.84(2.17~3.71)3.21(1.96~5.27)2.41(1.41~4.13)
TyG-WC
 Q166615.62参照组<0.001参照组<0.001参照组<0.001
 Q266718.291.21(0.91~1.61)1.15(0.85~1.54)1.09(0.81~1.47)
 Q366726.091.91(1.45~2.50)1.71(1.26~2.32)1.52(1.11~2.08)
 Q466732.982.66(2.04~3.46)2.24(1.58~3.16)1.84(1.27~2.67)
TyG-WHtR
 Q166616.22参照组<0.001参照组<0.001参照组<0.001
 Q266718.591.18(0.89~1.57)1.12(0.83~1.50)1.06(0.79~1.42)
 Q366723.091.55(1.18~2.04)1.41(1.03~1.91)1.28(0.93~1.76)
 Q466735.082.79(2.15~3.62)2.40(1.70~3.37)1.99(1.39~2.86)
TG/HDL-C
 Q166616.37参照组<0.001参照组<0.001参照组<0.001
 Q266718.591.17(0.88~1.55)1.11(0.83~1.47)1.10(0.82~1.46)
 Q366725.491.75(1.34~2.29)1.56(1.19~2.06)1.50(1.13~1.99)
 Q466732.532.46(1.90~3.20)2.04(1.55~2.69)1.81(1.31~2.50)
METS-IR
 Q166614.71参照组<0.001参照组<0.001参照组<0.001
 Q266720.391.48(1.12~1.97)1.49(1.09~2.03)1.42(1.03~1.94)
 Q366724.741.91(1.44~2.51)1.92(1.35~2.72)1.65(1.13~2.41)
 Q466733.132.87(2.20~3.76)2.90(1.85~4.54)2.20(1.32~3.69)
), ArticleFig(id=1320432014721929512, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=EN, label=Tab.3, caption=

Subgroup analysis of the associations between different insulin resistance surrogate indices and the risk of hyperuricemia among Chinese older adults aged over 80 years

, figureFileSmall=null, figureFileBig=null, tableContent=
亚组TyGTyG-BMITyG-WCTyG-WHtRTG/HDL-CMETS-IR
OR(95%CI)aP交互OR(95%CI)P交互OR(95%CI)P交互OR(95%CI)P交互OR(95%CI)P交互OR(95%CI)P交互
性别0.0970.6080.5120.3810.6420.498
 男性1.69(1.06~2.69)4.10(1.78~9.44)2.00(1.16~3.46)3.01(1.73~5.23)2.09(1.28~3.41)2.86(1.25~6.51)
 女性1.90(1.21~2.98)2.01(0.97~4.20)1.90(1.13~3.17)1.47(0.89~2.41)1.70(1.09~2.65)2.24(1.13~4.44)
居住地0.0230.1070.1540.0130.7570.951
 城市1.13(0.67~1.90)1.18(0.51~2.74)1.77(0.92~3.40)1.87(0.97~3.58)1.39(0.83~2.33)1.63(0.73~3.65)
 农村2.69(1.79~4.06)4.72(2.24~9.93)2.23(1.39~3.57)2.46(1.56~3.90)2.30(1.50~3.52)3.34(1.64~6.80)
目前吸烟0.9280.0080.5200.4180.9680.216
 否1.64(1.15~2.34)2.45(1.35~4.44)1.71(1.13~2.58)1.66(1.11~2.48)1.76(1.23~2.53)2.53(1.44~4.46)
 是2.66(1.31~5.42)4.94(1.18~20.70)2.93(1.21~7.13)6.19(2.46~15.59)2.10(0.97~4.53)1.17(0.28~4.80)
目前饮酒0.2170.0940.2810.2560.1010.126
 否1.70(1.19~2.43)2.86(1.56~5.25)1.96(1.28~2.99)1.80(1.20~2.71)1.58(1.10~2.26)2.89(1.61~5.19)
 是2.07(1.03~4.16)1.67(0.48~5.83)1.97(0.86~4.54)3.47(1.49~8.06)3.00(1.39~6.50)0.92(0.28~3.01)
), ArticleFig(id=1320432015128777002, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=CN, label=表3, caption=

中国80岁以上高龄老人不同胰岛素抵抗指标与高尿酸血症关系的亚组分析

, figureFileSmall=null, figureFileBig=null, tableContent=
亚组TyGTyG-BMITyG-WCTyG-WHtRTG/HDL-CMETS-IR
OR(95%CI)aP交互OR(95%CI)P交互OR(95%CI)P交互OR(95%CI)P交互OR(95%CI)P交互OR(95%CI)P交互
性别0.0970.6080.5120.3810.6420.498
 男性1.69(1.06~2.69)4.10(1.78~9.44)2.00(1.16~3.46)3.01(1.73~5.23)2.09(1.28~3.41)2.86(1.25~6.51)
 女性1.90(1.21~2.98)2.01(0.97~4.20)1.90(1.13~3.17)1.47(0.89~2.41)1.70(1.09~2.65)2.24(1.13~4.44)
居住地0.0230.1070.1540.0130.7570.951
 城市1.13(0.67~1.90)1.18(0.51~2.74)1.77(0.92~3.40)1.87(0.97~3.58)1.39(0.83~2.33)1.63(0.73~3.65)
 农村2.69(1.79~4.06)4.72(2.24~9.93)2.23(1.39~3.57)2.46(1.56~3.90)2.30(1.50~3.52)3.34(1.64~6.80)
目前吸烟0.9280.0080.5200.4180.9680.216
 否1.64(1.15~2.34)2.45(1.35~4.44)1.71(1.13~2.58)1.66(1.11~2.48)1.76(1.23~2.53)2.53(1.44~4.46)
 是2.66(1.31~5.42)4.94(1.18~20.70)2.93(1.21~7.13)6.19(2.46~15.59)2.10(0.97~4.53)1.17(0.28~4.80)
目前饮酒0.2170.0940.2810.2560.1010.126
 否1.70(1.19~2.43)2.86(1.56~5.25)1.96(1.28~2.99)1.80(1.20~2.71)1.58(1.10~2.26)2.89(1.61~5.19)
 是2.07(1.03~4.16)1.67(0.48~5.83)1.97(0.86~4.54)3.47(1.49~8.06)3.00(1.39~6.50)0.92(0.28~3.01)
), ArticleFig(id=1320432015598539051, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=EN, label=Tab.4, caption=

Comparison of ROC curves of different insulin resistance surrogate indices for predicting hyperuricemia among Chinese older adults aged over 80 years

, figureFileSmall=null, figureFileBig=null, tableContent=
胰岛素抵抗指标AUC(95%CI)PAUC截断值灵敏度特异度约登指数
TyG0.60(0.57~0.62)参照8.530.600.571.17
TyG-BMI0.61(0.59~0.64)0.144202.980.520.661.17
TyG-WC0.62(0.59~0.64)0.049712.770.570.621.19
TyG-WHtR0.61(0.59~0.64)0.1304.600.580.591.17
TG/HDL-C0.61(0.58~0.63)0.1052.210.570.601.17
METS-IR0.61(0.59~0.64)0.18735.200.510.661.17
), ArticleFig(id=1320432016005386540, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320431967829610682, language=CN, label=表4, caption=

中国80岁以上高龄老人不同胰岛素抵抗指标预测高尿酸血症的ROC曲线比较

, figureFileSmall=null, figureFileBig=null, tableContent=
胰岛素抵抗指标AUC(95%CI)PAUC截断值灵敏度特异度约登指数
TyG0.60(0.57~0.62)参照8.530.600.571.17
TyG-BMI0.61(0.59~0.64)0.144202.980.520.661.17
TyG-WC0.62(0.59~0.64)0.049712.770.570.621.19
TyG-WHtR0.61(0.59~0.64)0.1304.600.580.591.17
TG/HDL-C0.61(0.58~0.63)0.1052.210.570.601.17
METS-IR0.61(0.59~0.64)0.18735.200.510.661.17
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中国≥80岁高龄老人胰岛素抵抗替代指数与高尿酸血症患病关系及其预测效能:基于2015—2017年中国居民营养与健康状况监测
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杨宇祥 1, 2 , 蔡姝雅 1, 3 , 郝佳锶 2 , 汪艳梅 2 , 南晶 1 , 王瑞莲 1 , 赵丽云 1 , 于冬梅 1, 3, *, *
中国公共卫生 | 专题报道——健康老龄化与积极老龄化 2026,42(7): 826-834
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中国公共卫生 |专题报道——健康老龄化与积极老龄化 2026 , 42 (7) : 826 -834
中国≥80岁高龄老人胰岛素抵抗替代指数与高尿酸血症患病关系及其预测效能:基于2015—2017年中国居民营养与健康状况监测
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杨宇祥1, 2, 蔡姝雅1, 3, 郝佳锶2, 汪艳梅2, 南晶1, 王瑞莲1, 赵丽云1, 于冬梅1, 3, *, *
作者信息
  • 1中国疾病预防控制中心营养与健康所,北京 100050
  • 2格罗宁根大学医学中心,荷兰 格罗宁根 9713GZ
  • 3国家卫生健康委公共营养与健康重点实验室,北京 100050
通讯作者:
于冬梅,E-mail:
作者简介:

杨宇祥(1996—),博士,研究方向:营养与健康流行病学

Predictive performance of insulin resistance surrogate indices for hyperuricemia among Chinese older adults aged over 80 years: based on the China nutrition and health surveillance, 2015–2017
Yuxiang YANG1, 2, Shuya CAI1, 3, Jiasi HAO2, Yanmei WANG2, Jing NAN1, Ruilian WANG1, Liyun ZHAO1, Dongmei YU1, 3
Affiliations
  • 1National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China
  • 2University Medical Center Groningen, University of Groningen, Groningen 9713GZ, the Netherlands
  • 3NHC Key Laboratory of Public Nutrition and Health, Beijing 100050, China
  • Corresponding Author:
    YU Dongmei, E-mail:
出版时间: 2026-07-10 doi: 10.11847/zgggws1148944
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目的

探索中国≥80岁高龄老人胰岛素抵抗替代指数与高尿酸血症的关系,并评价不同指标对高尿酸血症的预测效能,为该人群高尿酸血症防治提供科学依据。

方法

基于中国居民营养与健康状况监测(2015—2017年)数据,采用多阶段分层整群随机抽样,对我国31个省(自治区、直辖市)抽取的2 667名80岁以上高龄老人进行问卷调查、体格测量和实验室检测。使用甘油三酯葡萄糖(TyG)指数并结合体质指数(BMI)、腰围(WC)、腰高比(WHtR)衍生的TyG-BMI、TyG-WC、TyG-WHtR指数、甘油三酯/高密度脂蛋白胆固醇比值(TG/HDL-C)以及胰岛素抵抗代谢评分(MET-IR)作为胰岛素抵抗的评估指标,并分别按升序将人群按四分位法分组,将男性血尿酸浓度≥420 μmol/L及女性血尿酸浓度≥360 μmol/L者定义为患有高尿酸血症,使用多因素非条件logistic回归分析二者关系,并结合受试者工作特征曲线比较不同指标对高尿酸血症患病的预测效能。

结果

中国2 667名高龄老人中,患高尿酸血症者占23.24%,且高尿酸血症患病率与体质指数(χ2=38.167)、婚姻状况(χ2=4.012)、睡眠时间分组(χ2=6.452)及高血压(χ2=12.320)、糖尿病(χ2=4.922)、血脂异常患病情况(χ2=38.541)组间差异均有统计学意义(均P<0.05)。多因素非条件logistic回归结果显示,在调整年龄、性别、BMI、居住地、文化程度、婚姻状况、家庭人均年收入、目前吸烟、目前饮酒、身体活动水平、睡眠时间以及高血压、糖尿病和血脂异常的患病情况后,各胰岛素抵抗指数最高组与最低组相比,TyG(OR=1.79,95%CI=1.30~2.45)、TyG-BMI(OR=2.41,95%CI=1.41~4.13)、TyG-WC(OR=1.84,95%CI=1.27~2.67)、TyG-WHtR(OR=1.99,95%CI=1.39~2.86)、TG/HDL-C(OR=1.81,95%CI=1.31~2.50)、MET-IR(OR=2.20,95%CI=1.32~3.69),更高的胰岛素抵抗指数均与高尿酸血症的患病风险存在正向关联。ROC分析提示,TyG-WC指数对高龄老人高尿酸血症患病情况的预测效能最优。

结论

TyG、TyG-BMI、TyG-WC、TyG-WHtR、TG/HDL-C以及METS-IR为中国80岁以上高龄老人患有高尿酸血症的独立风险因素,且TyG-WC指数可作为中国高龄老人高尿酸血症患病风险的较优预测因子,为该人群高尿酸血症的防治工作提供新靶点。

高龄老人  /  高尿酸血症  /  胰岛素抵抗  /  TyG指数  /  预测效能
Objective

To explore the associations between insulin resistance surrogate indices and hyperuricemia among Chinese older adults aged over 80 years and evaluate the predictive performance of different indices for hyperuricemia, thus providing a scientific basis for the prevention and control of hyperuricemia in this population.

Methods

On the basis of the data from the China Nutrition and Health Surveillance (2015–2017), multistage stratified cluster random sampling was employed to select 2 667 participants aged over 80 years from 31 provinces (autonomous regions, municipalities) in China. A questionnaire survey, physical measurements, and laboratory tests were conducted. The triglyceride-glucose (TyG) index was combined with body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) to derive the TyG-BMI, TyG-WC, and TyG-WHtR indices, which, together with the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR), were used as insulin resistance surrogate indices. The participants were categorized by ascending quartiles. Hyperuricemia was defined as a serum uric acid concentration ≥ 420 μmol/L in men and ≥ 360 μmol/L in women. Multivariable unconditional logistic regression was adopted to explore the associations between insulin resistance surrogate indices and hyperuricemia. Receiver operating characteristic (ROC) curves were established to compare the predictive performance of different indices for hyperuricemia.

Results

Among the 2 667 Chinese older adults, 23.24% had hyperuricemia, and the prevalence of hyperuricemia was statistically different among different groups of body mass index (BMI) (χ2 = 38.167), marital status (χ2 = 4.012), sleep duration (χ2 = 6.452), hypertension (χ2 = 12.320), diabetes (χ2 = 4.922), and dyslipidemia (χ2 = 38.541) (all P < 0.05). The results of multivariable unconditional logistic regression showed that after adjusting for age, sex, BMI, place of residence, educational background, marital status, annual household income per capita, current smoking, current drinking, physical activity level, sleep duration, and the prevalence of hypertension, diabetes, and dyslipidemia, each insulin resistance surrogate index was positively associated with the risk of hyperuricemia. Compared with the lowest group, the highest group of TyG (OR = 1.79, 95%CI: 1.30–2.45), TyG-BMI (OR = 2.41, 95%CI: 1.41–4.13), TyG-WC (OR = 1.84, 95%CI: 1.27–2.67), TyG-WHtR (OR = 1.99, 95%CI: 1.39–2.86), TG/HDL-C (OR = 1.81, 95%CI: 1.31–2.50), and MET-IR (OR = 2.20, 95%CI: 1.32–3.69) had a significantly higher risk of hyperuricemia. ROC analysis suggested that the TyG-WC index had the best predictive performance for the prevalence of hyperuricemia in this population.

Conclusions

TyG, TyG-BMI, TyG-WC, TyG-WHtR, TG/HDL-C, and METS-IR are independent risk factors for hyperuricemia in the Chinese older adults aged over 80 years. The TyG-WC index could be used as an elite predictor of hyperuricemia risk, providing a new target for the prevention and treatment of hyperuricemia in this population.

older adults  /  hyperuricemia  /  insulin resistance  /  TyG index  /  predictive performance
杨宇祥, 蔡姝雅, 郝佳锶, 汪艳梅, 南晶, 王瑞莲, 赵丽云, 于冬梅. 中国≥80岁高龄老人胰岛素抵抗替代指数与高尿酸血症患病关系及其预测效能:基于2015—2017年中国居民营养与健康状况监测. 中国公共卫生, 2026 , 42 (7) : 826 -834 . DOI: 10.11847/zgggws1148944
Yuxiang YANG, Shuya CAI, Jiasi HAO, Yanmei WANG, Jing NAN, Ruilian WANG, Liyun ZHAO, Dongmei YU. Predictive performance of insulin resistance surrogate indices for hyperuricemia among Chinese older adults aged over 80 years: based on the China nutrition and health surveillance, 2015–2017[J]. Chinese Journal of Public Health, 2026 , 42 (7) : 826 -834 . DOI: 10.11847/zgggws1148944
高尿酸血症是一种以血清尿酸浓度升高为特征的代谢性疾病,主要由体内尿酸的合成增加和(或)排泄减少导致,并可能进一步引发机体多个器官的损伤和系统性代谢异常[1]。据报道,高尿酸血症已成为全球流行的第二大代谢性疾病,近20年来,我国成人高尿酸血症的患病率持续快速上升,据Zhang M等[2–4]学者研究,截至2019年已达到14%。因高尿酸血症与痛风、慢性肾病、心血管疾病以及糖尿病等多种疾病的发生风险密切相关,其所带来巨大的经济和医疗卫生负担不容忽视,亟需探索针对有效的早期防治靶点和措施[5]。一项基于孟德尔随机化分析的研究显示,胰岛素抵抗可导致高尿酸血症,而降低胰岛素抵抗水平可以降低血清尿酸浓度,进而降低高尿酸血症和痛风的发病风险,提示胰岛素抵抗水平是高尿酸血症发生发展的重要影响因素[6]。葡萄糖钳夹技术是评估机体胰岛素抵抗水平的金标准,但由于其有创伤、检测成本高且操作复杂,导致其在常规临床和健康监测中难以广泛使用[7]。近年来,一些基于常规血生化检测的替代性指标被广泛用于评估胰岛素抵抗水平,包括甘油三酯/高密度脂蛋白胆固醇比值(triglyceride/high-density lipoprotein cholesterol, TG/HDL-C)、胰岛素抵抗代谢评分(metabolic score for insulin resistance, MET-IR)、甘油三酯葡萄糖(triglyceride-glucose, TyG)指数及其结合体质指数(body mass index, BMI)、腰围(waist circumference, WC)以及腰高比(waist to height ratio, WHtR)衍生的TyG-BMI、TyG-WC以及TyG-WHtR,在评估胰岛素抵抗水平方面表现出较高的灵敏度和特异度,显示出在人群研究中良好的应用潜力[8]。伴随着我国老龄化进程不断加速,我国80岁以上高龄老人数量持续上升,高尿酸血症带来的潜在健康危害和疾病负担将更加突出,但尚缺少针对该人群胰岛素抵抗与高尿酸血症的关系研究[9–10]。综上,本研究基于中国居民营养与健康状况监测(2015—2017年)数据,探索高龄老人胰岛素抵抗与高尿酸血症患病风险的关联,并比较多种胰岛素抵抗替代指标对高尿酸血症患病的预测效能。
基于中国居民营养与健康状况监测(2015—2017年)数据,采用多阶段分层整群随机抽样,结合区域和城乡因素的分布均衡性和现有工作条件后,在31个省(自治区、直辖市)的298个监测点随机抽取189 605名18岁及以上常住居民,并提取80岁及以上者为调查对象。后续的排除标准包括:(1)存在人口学信息缺失者;(2)未完成生活行为方式及膳食信息调查者;(3)未参加或未完成体格测量和实验室检测者;(4)既往被诊断为慢性泌尿系统疾病者[11]。本研究最终纳入2 667名研究对象进入后续分析。本项目经中国疾病预防控制中心伦理委员会审查并批准(项目号:201519–B),研究对象均在调查前签署知情同意书;其他信息已在既往发表文献中说明[12]。
全部调查由经过统一培训和考核的调查员以面对面访谈的形式完成,采用统一的标准化调查问卷,调查包括人口学信息(性别、年龄、居住地、文化程度、家庭收入、婚姻状况)、生活行为方式(吸烟、饮酒、身体活动、睡眠时间及膳食摄入)以及慢性病史(基于社区卫生服务中心或乡镇卫生院及以上级别的医疗卫生机构的诊断)。其中,膳食调查通过询问研究对象过去一年的膳食消费习惯,记录其蔬菜类、水果类、畜肉类的膳食消费频率(次/天、周、月、年)以及单次平均摄入量(克/次),估计调查对象平均每日摄入量。
由调查员使用统一的检测工具并在严格的质量控制下进行。使用TZG型身高坐高计(cm,精确度0.1 cm)测量身高,百利达HD–390型电子体重秤(kg,精确度0.1 kg)测量体重,以国家工作组统一发放的腰围尺(cm,精确度0.1 cm)测量腰围,采用欧姆龙HBP1300型电子血压计(mmHg,精确度1 mmHg)测量血压。全部测量均在清晨空腹状态下进行。此外,根据研究对象的身高和体重计算体质指数(body mass index, BMI),并将人群分为消瘦(BMI<18.5 kg/m2)、正常(18.5 kg/m2≤BMI<24 kg/m2)、超重(24 kg/m2≤BMI<28 kg/m2)和肥胖(BMI≥28 kg/m2)4组[12]。
采集调查对象的空腹静脉血8 mL,测量空腹血糖(fasting plasma glucose, FPG, 己糖激酶法)、总胆固醇(胆固醇氧化酶法)、甘油三酯(去游离甘油法)、高密度脂蛋白胆固醇(直接测定法—抗体阻碍法)及低密度脂蛋白胆固醇(直接测定法—选择保护法)和血尿酸(尿酸酶法)。
共纳入6种替代性胰岛素抵抗评价指标,具体计算公式如下[11–13]:
$ \mathrm{TyG=ln[(TG(mg/dL)\times FPG(mg/dL)/2)]}\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\;\; $
$ \mathrm{TyG-BMI=ln[(TG(mg/dL)\times FPG(mg/dL)/2]\times BMI} $
$ \mathrm{TyG-WC=ln[(TG(mg/dL)\times FPG(mg/dL)/2]\times WC} \;\;\;$
$ \begin{split} \mathrm{TyG-WHtR}=&\ln[({\mathrm{TG(mg/dL)}}\times {\mathrm{FPG(mg/dL)}}/2]\times\;\;\;\;\;\;\;\; \\&{}({\mathrm{WC}}/身高)\end{split} $
$ \mathrm{TG/HDL-C=TG(mg/dL)/HDL-C(mg/dL)} \;\;\;\;\;\;$
$ \begin{split} \mathrm{METS-IR}=&\ln[2\times {\mathrm{FPG(mg/dL)+TG(mg/dL)}}]\times\;\;\;\;\;\;\;\; \\&{\mathrm{BMI}}({\mathrm{kg/m}}^{ \mathrm{2}} \mathrm{)/ln[HDL-C(mg/dL)]}\end{split} $
对于结局,除基于研究对象自我报告的既往诊断外,将两周内服用降压药物和(或)3次平均收缩压≥140 mmHg和(或)3次平均舒张压≥90 mmHg者定义为高血压[14],接受降糖治疗和(或)空腹血糖≥7.0 mmol/L者定义为糖尿病[15],接受降脂治疗和(或)血清总胆固醇≥6.2 mmol/L和(或)甘油三酯≥2.26 mmol/L和(或)低密度脂蛋白胆固醇≥4.14 mmol/L和(或)高密度脂蛋白胆固醇<1.04 mmol/L者定义为血脂异常[16],男性血尿酸浓度≥420 μmol/L及女性血尿酸浓度≥360 μmol/L者定义为高尿酸血症[17]。
基于既往文献报道[11],本研究将胰岛素抵抗、高尿酸血症及二者之间关联性的潜在混杂因素作为协变量纳入统计模型控制。包括:性别(男性/女性)、年龄(连续性变量)、BMI(连续性变量)、居住地(城市/农村)、文化程度(接受/未接受过正规学校教育)、家庭人均年收入(<10 000、10 000~24 999、≥25 000元/年或未报告)、婚姻状况(已婚/离异及其他)、目前吸烟(是/否)、目前饮酒(是/否)、身体活动水平(低/中/高)[18]、每日睡眠时长(<7、7~9、>9 h/d)以及高血压、糖尿病和血脂异常的患病情况(是/否)。
描述性分析中,使用均数(标准差)x̅ (s)描述连续性变量,使用例数和百分比(n,%)描述分类变量,分别使用t检验和χ2检验比较组间差异。使用多因素非条件logistic回归分析胰岛素抵抗相关指数与高尿酸血症的关联性,分别使用6种指数按升序将研究对象进行四分位法分组(Quartile 1~4,Q1~Q4),以Q1组为参照,计算其余各组的比值比及95%置信区间[OR(95%CI)]。逐步纳入协变量建立3个模型:模型1为未调整的粗模型,模型2调整年龄、性别和BMI,模型3进一步调整其余潜在的混杂因素。同时,以各指数的z标准化值作为连续变量,评估各指数每增加1个标准差与高尿酸血症患病风险的线性关联(P趋势)。此外,在模型3的基础上,将研究对象按性别、居住地、目前吸烟和饮酒情况分组,评估不同亚组中胰岛素抵抗相关指数与高尿酸血症之间的关联,并通过在模型中分别纳入胰岛素抵抗指标与各亚组因素的乘法交互项,采用似然比检验评估交互作用的统计学意义。采用受试者工作特征(receiver operating characteristic, ROC)曲线分析计算胰岛素抵抗指标与高尿酸血症患病风险的曲线下面积(area under curve, AUC),比较不同指标在高龄老人中对高尿酸血症的预测能力。TyG指数与其他指标的AUC之间的统计学差异则依据DeLong非参数检验进行比较[19]。本研究使用SAS 9.4以及R 4.4.2完成分析,以双侧P<0.05为差异有统计学意义。
纳入的2 667名80岁以上高龄老人中,男性1 267人(47.51%),女性1 400人(52.49%);按体质指数划分,消瘦254人(9.52%),正常1 514人(56.77%),超重695人(26.06%),肥胖204人(7.65%);居住地为城市1 072人(40.19%),农村1 595人(59.81%)。研究对象平均年龄为83.44岁,TyG指数为8.55,TyG-BMI为195.52,TyG-WC为698.36,TyG-WHtR为4.54,TG/HDL-C为2.74,METS-IR为33.94;蔬菜摄入量为278.63 g/d,水果摄入量为58.95 g/d,畜肉类摄入量为44.73 g/d;血清尿酸浓度为332.39 μmol/L。
在最终纳入分析的2 667名中国80岁以上高龄老人中,高尿酸血症患者620例(23.34%),其中男性284例、女性336例,平均年龄为83.44岁。高尿酸血症患者与非患者的不同体质指数(χ2=38.167)、婚姻状况(χ2=4.012)、睡眠时间分组(χ2=6.452)及高血压(χ2=12.320)、糖尿病(χ2=4.922)、血脂异常患病情况(χ2=38.541)的构成比差异均有统计学意义(均P<0.05),且在TyG(t=7.450)、TyG-BMI(t=8.480)、TyG-WC(t=8.740)、TyG-WHtR(t=8.380)、TG/HDL-C(t=7.680)、METS-IR(t=8.880)、水果摄入量(t=2.100)、畜肉类摄入量(t=2.010)以及血清尿酸浓度(t=56.220)差异也均有统计学意义(均P<0.001)。
logistic回归分析结果显示,在模型3中,各胰岛素抵抗指数均与高尿酸血症的患病风险存在正向关联。以不同指数的最低组(Q1)作为参照组,相应最高组(Q4)个体患高尿酸血症的风险均显著升高,Q4与Q1相比,高尿酸血症的患病风险为Q1的1.79~2.41倍,校正后OR值(95%CI)分别为:TyG(OR=1.79,95%CI=1.30~2.45,P趋势 < 0.001),TyG-BMI(OR=2.41,95%CI=1.41~4.13,P趋势<0.001),TyG-WC(OR=1.84,95%CI=1.27~2.67,P趋势<0.01),TyG-WHtR(OR=1.99,95%CI=1.39~2.86,P趋势 <0.01),TG/HDL-C(OR=1.81,95%CI=1.31~2.50,P趋势<0.001),MET-IR(OR=2.20,95%CI=1.32~3.69,P趋势<0.001)。
将研究对象进一步按性别、居住地、目前吸烟和目前饮酒分组,在各亚组内分析胰岛素抵抗指标与高尿酸血症患病风险的关联。结果显示,与Q1组相比,Q4组在多数亚组中各指数与高尿酸血症的正向关联仍具有统计学意义。此外,结果提示TyG指数与居住地(城市:OR=1.13,95%CI=0.67~1.90;农村:OR=2.69,95%CI=1.79~4.06,P交互=0.023)、TyG-BMI指数与目前吸烟(否:OR=2.45,95%CI=1.35~4.44;是:OR=4.94,95%CI=1.18~20.70,P交互<0.001)之间存在交互作用。
比较研究对象的不同胰岛素抵抗指数对高尿酸血症患病的预测能力,各指标预测高尿酸血症患病的AUC均高于0.5,其中TyG-WC的AUC值最高(AUC=0.62,95%CI=0.59~0.64),且与TyG指数相比差异具有统计学意义(PAUC=0.049),其余指标则未观察到与TyG指数AUC的显著差异(均PAUC≥0.05)。TyG-WC指数在预测高尿酸血症患病情况的灵敏度为0.57,特异度为0.62,约登指数为1.19。其余各指标的灵敏度和特异度分别在0.51~0.60和0.57~0.66之间波动,约登指数均为1.17。
由于高龄老人中患心血管疾病以及接受慢性病药物治疗的比例较高,导致该人群更容易患有高尿酸血症[20]。而又由于高尿酸血症与痛风、肾脏疾病、骨质疏松等严重影响高龄老人健康及生命质量的疾病密切相关,因此,亟需探究高龄老人高尿酸血症的防治靶点[21]。本研究针对中国80岁以上高龄老人胰岛素抵抗水平与高尿酸血症的关联性进行分析,结果显示,该人群的高尿酸血症患病率为23.24%,高于中国18岁以上成人的患病率[2]。作为评估胰岛素抵抗水平的重要替代工具,包括TyG、TyG-BMI、TyG-WC、TyG-WHtR、TG/HDL-C以及METS-IR在内的6种评估指标均与高尿酸血症的患病风险存在正向关联,且在多数亚组中,结果保持稳定。ROC分析结果提示,6种指标在预测该人群高尿酸血症患病风险的效能较为接近,且TyG-WC指数的预测能力相对最优。以上结果提示,胰岛素抵抗指标或可作为中国高龄老人高尿酸血症患病风险的重要预测因素。
本研究结果与既往研究一致。一项荟萃分析显示,在成人中,TyG指数与高尿酸血症的风险呈正向关联,且TyG指数每增加1个单位,患高尿酸血症的风险就会增加2.07倍[22]。Han Y等[11]学者基于中国中老年人群的研究显示,TyG、TG/HDL、METS-IR和TyG-BMI指数升高与该人群高尿酸血症患病风险增加有关。另一项基于中美两国成年人群的研究显示,TyG、TyG-BMI、TyG-WHtR、TyG-WC指数的升高均与高尿酸血症的患病风险增加有关,提示这些指标可作为人群中筛查高尿酸血症患病状况的潜在指标[23]。一些机制可能解释胰岛素抵抗与高尿酸血症的关系,胰岛素抵抗会引发炎症级联反应,影响肝脏对嘌呤的代谢,并增强参与尿酸合成的黄嘌呤氧化还原酶的活性,导致血尿酸浓度升高[24]。高胰岛素血症是胰岛素抵抗之后出现的代偿机制,而血中胰岛素浓度升高可通过影响肾小管对钠的重吸收功能进而降低肾脏对尿酸的排泄,导致血尿酸水平升高和高尿酸血症的发生[24]。动物和细胞学试验结果也证明了胰岛素对肾脏尿酸转运的直接影响,胰岛素水平升高可刺激葡萄糖转运蛋白–9(glucose transporter-9, GLUT9)的表达及GLUT9对尿酸盐的转运活性,进而导致近端小管对尿酸的重吸收功能增强及后续的血尿酸水平升高[25];且胰岛素可提高肾小管上皮细胞尿酸转运蛋白–1(urate transporter 1, URAT1)的表达水平,也可导致肾小管对尿酸的重吸收增加从而升高血尿酸水平[26]。
在本研究的亚组分析中,还观察到居住地和目前吸烟状况对胰岛素抵抗指标与高尿酸血症患病关联性的修饰作用,其中,在农村居民与目前吸烟人群中,二者的关联性更强。而比较不同特征高龄老人的高尿酸血症患病情况时,并未观察到高尿酸血症患病率在居住地和目前吸烟状况分布的差异有统计学意义。原因可能为,与城市地区相比,农村地区由于生活中(如烹饪、取暖等)固态燃料(如煤炭、木材等)使用率更高,其燃烧产生的可吸入颗粒物及其有害组分会诱发机体的炎症反应和氧化应激,进而影响肾功能并导致血尿酸浓度升高,从而增加高尿酸血症的发病风险[27–28]。此外,农村地区医疗水平较低、医疗卫生资源可及性相对较差,可能影响农村地区高龄老人的整体健康水平和慢性病管理效果,从而增强胰岛素抵抗与高尿酸血症患病的关系[29]。既往研究显示,吸烟可作为高尿酸血症的独立危险因素,且可通过影响血流动力学和(或)造成肾脏内皮细胞慢性损伤,从而影响肾脏的结构和功能,降低机体对尿酸的排泄能力[30–31]。
既往研究结果显示,与其他代谢性指标相比,TyG指数在高尿酸血症的识别方面效果更优[32]。因此,本研究进一步比较了6种胰岛素抵抗指标在预测中国高龄老人高尿酸血症患病方面的效能。与既往结果近似,Han Y等[11]学者比较了TyG、TG/HDL、METS-IR和TyG-BMI指标对中国中老年人群高尿酸血症发病风险的预测能力,提示上述4种指标表现出相似的预测性能。而一项美国的人群研究同样比较了上述4种指标对该人群高尿酸血症的识别能力,但结果提示,TyG-BMI和METS-IR对高尿酸血症的识别能力更优[33],不同研究结果的差异可能与研究设计和人种差异有关[11]。本研究还发现,与TyG指数相比,TyG-WC指数的预测性能更优,该结果与一项基于中国高血压患者的研究结果一致,其比较了TyG、TyG-BMI、TyG-WHtR和TyG-WC对5年内高尿酸血症发病风险的预测能力,同样发现TyG-WC指数具有最优的预测性能[34]。例如,BMI和WC等肥胖评价指标可介导TyG指数与高尿酸血症的关联[35],也提示将TyG指数与肥胖指标相结合可能提高对高尿酸血症的预测效能。结合本研究结果,并考虑到我国高龄老人的BMI总体水平较低,且存在随年龄增加而下降的趋势,因此,将TyG与以腰围为代表的中心型肥胖指标相结合可能更有助于识别该人群高尿酸血症的风险[10]。
本研究尚具有一定的局限性,首先,由于此研究基于横断面设计,因此难以对胰岛素抵抗与高尿酸血症的关系作出因果推断;第二,本研究未能排除既往有痛风病史的研究对象,可能对关联性分析的结果造成一定的偏倚;第三,由于人力及物力的限制,本研究未测量与肾功能有关的指标(如肾小球滤过率等)[36]。因此,无法在关联性分析中进一步校正肾功能。
综上,本研究基于中国居民营养与健康状况监测(2015—2017年)数据,发现TyG、TyG-BMI、TyG-WC、TyG-WHtR、TG/HDL-C以及METS-IR与中国高龄老人高尿酸血症患病风险存在正向关联。且TyG-WC指数可作为该人群高尿酸血症患病风险的较优预测因子。结果提示,胰岛素抵抗替代性指标可作为一种实用、可靠且具有成本效益的工具,为防治高龄人群高尿酸血症提供识别和干预靶点。通过评估胰岛素抵抗水平识别重点关注人群,有望为进一步提升高龄老人的健康水平和生活质量提供新的思路与依据。

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2026年第42卷第7期
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doi: 10.11847/zgggws1148944
  • 接收时间:2025-09-19
  • 首发时间:2026-10-23
  • 出版时间:2026-07-10
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  • 收稿日期:2025-09-19
  • 修回日期:2025-10-17
  • 录用日期:2026-03-07
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    1中国疾病预防控制中心营养与健康所,北京 100050
    2格罗宁根大学医学中心,荷兰 格罗宁根 9713GZ
    3国家卫生健康委公共营养与健康重点实验室,北京 100050

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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
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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