Article(id=1320438226750386935, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320438168613138789, articleNumber=null, orderNo=null, doi=10.11847/zgggws1148607, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1754409600000, receivedDateStr=2025-08-06, revisedDate=1763308800000, revisedDateStr=2025-11-17, acceptedDate=1773158400000, acceptedDateStr=2026-03-11, onlineDate=1792746605812, onlineDateStr=2026-10-23, pubDate=1778342400000, pubDateStr=2026-05-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792746605812, onlineIssueDateStr=2026-10-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792746605812, creator=13701087609, updateTime=1792746605812, updator=13701087609, issue=Issue{id=1320438168613138789, tenantId=1146029695717560320, journalId=1319373219989389464, year='2026', volume='42', issue='5', pageStart='513', pageEnd='640', issueExtLink='null', onlineDate='null', pubDate='1778342400000', pubDateStr='2026-05-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792746591952, creator='13701087609', updateTime=1792748055079, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320444305479684446, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320438168613138789, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320444305479684447, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320438168613138789, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=570, endPage=577, ext={EN=ArticleExt(id=1320438226955907832, articleId=1320438226750386935, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Associations between serum triglyceride levels and multiple metabolic abnormalities among adults in five cities of western China: a cross-sectional study, 2023, columnId=1320427696342020970, journalTitle=Chinese Journal of Public Health, columnName=Epidemiological Research, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the associations of serum triglyceride (TG) levels with various metabolic abnormalities among adult residents in 5 cities of western China, thereby providing evidence for the prevention and management of metabolic syndrome in this region.

Methods

A multistage stratified cluster sampling method was used to recruit 990 adult permanent residents ≥18 years old from Chifeng, Hohhot, and Ordos in Inner Mongolia Autonomous Region, Lhasa in Xizang Autonomous Region, and Dali in Yunnan province between March and October 2023. Data were collected through questionnaires, physical examinations, and laboratory tests. Multivariate unconditional logistic regression models were used to analyze the associations between serum TG levels and various metabolic abnormalities, including overweight and obesity, central obesity, hypertension, elevated low-density lipoprotein cholesterol (LDL-C), decreased high-density lipoprotein cholesterol (HDL-C), elevated total cholesterol (TC), insulin resistance, diabetes, and hyperuricemia.

Results

A total of 939 adults were included in the final analysis. Among the surveyed population, 611 (65.0%), 163 (17.4%), and 165 (17.6%) had normal TG levels, borderline high TG, and elevated TG, respectively. The number (detection rates) of respondents with overweight and obesity, central obesity, hypertension, elevated LDL-C, decreased HDL-C, elevated TC, insulin resistance, diabetes, and hyperuricemia was 536 (57.1%), 432 (46.0%), 389 (41.4%), 94 (10.0%), 82 (8.7%), 237 (25.2%), 310 (33.0%), 227(24.2%), and 310 (33.0%), respectively. After adjusting for sex, age group, region, educational background, per capita monthly household income, smoking status, drinking status, physical activity level, and daily intake of cereals, tubers, vegetables, fruits, animal-based foods, dairy products, soy and nuts, salt, and oil, multivariate unconditional logistic regression analyses showed that adults with borderline high TG had higher detection rates of overweight and obesity (OR = 2.70, 95%CI: 1.80–4.04), central obesity (OR = 1.67, 95%CI: 1.13–2.48), hypertension (OR = 1.71, 95%CI: 1.15–2.54), elevated LDL-C (OR = 3.65, 95%CI: 2.03–6.59), elevated TC (OR = 3.42, 95%CI: 2.22–5.26), insulin resistance (OR = 2.65, 95%CI: 1.79–3.90), and hyperuricemia (OR = 2.31, 95%CI: 1.55–3.44) than the adults with normal serum TG levels. Adults with elevated TG had higher detection rates of overweight and obesity (OR = 4.68, 95%CI: 2.96–7.40), central obesity (OR = 4.25, 95%CI: 2.75–6.58), hypertension (OR = 1.83, 95%CI: 1.22–2.74), elevated LDL-C (OR = 4.66, 95%CI: 2.55–8.50), reduced HDL-C (OR = 5.85, 95%CI: 2.59–13.23), elevated TC (OR = 6.24, 95%CI: 3.98–9.79), insulin resistance (OR = 5.22, 95%CI: 3.47–7.83), diabetes (OR = 2.30, 95%CI: 1.50–3.52), and hyperuricemia (OR = 6.41, 95%CI: 4.22–9.73).

Conclusions

Elevated serum TG among adults in 5 cities of western China are positively associated with multiple metabolic abnormalities, including overweight and obesity, central obesity, hypertension, elevated LDL-C, decreased HDL-C, elevated TC, insulin resistance, diabetes, and hyperuricemia.

, authors=Zeyu JIANG1, 2, Xin LIU1, 3, Ting LI4, 5, Dong LIANG2, Sufang DUAN4, 5, Ignatius Man-Yau Szeto4, 5, Gang FENG4, 5, Wenxin LIANG1, Tingchao HE1, Hua JIANG6, Yumei ZHANG1, authorsList=Zeyu JIANG, Xin LIU, Ting LI, Dong LIANG, Sufang DUAN, Ignatius Man-Yau Szeto, Gang FENG, Wenxin LIANG, Tingchao HE, Hua JIANG, Yumei ZHANG, authorCompany=null, correspAuthors=Hua JIANG, Yumei ZHANG, authorNote=null, correspAuthorsNote=
JIANG Hua, E-mail:
ZHANG Yumei, 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=1320438227606024955, articleId=1320438226750386935, tenantId=1146029695717560320, journalId=1319373219989389464, language=CN, title=中国西部地区五城市成年居民血清甘油三酯升高与多种代谢异常状况关系:一项2023年横断面研究, columnId=1320427696509793132, journalTitle=中国公共卫生, columnName=流行病学研究, runingTitle=null, highlight=null, articleAbstract=
目的

了解中国西部地区五城市成年居民血清甘油三酯(TG)升高与多种代谢异常状态的关系,为该地区居民代谢综合征的管理及防治提供参考依据。

方法

于2023年3—10月采用多阶段分层随机抽样方法在中国西部地区内蒙古自治区赤峰市、呼和浩特市、鄂尔多斯市,西藏自治区拉萨市和云南省大理市抽取990名≥18岁成年常住居民进行问卷调查、体格检查和实验室检测,应用多因素非条件logistic回归模型分析其血清TG水平与超重肥胖、中心型肥胖、高血压、低密度脂蛋白胆固醇(LDL-C)升高、高密度脂蛋白胆固醇(HDL-C)降低、总胆固醇(TC)升高、胰岛素抵抗、糖尿病和高尿酸血症等多种代谢异常状态的关系。

结果

中国西部地区五城市最终纳入分析的939名成年居民检出血清TG正常者611人(65.0%),TG边缘升高者163人(17.4%),TG升高者165例(17.6%);检出超重肥胖、中心型肥胖、高血压、LDL-C升高、HDL-C降低、TC升高、胰岛素抵抗、糖尿病和高尿酸血症者分别为536、432、389、94、82、237、310、227和310例,检出率分别为57.1%、46.0%、41.4%、10.0%、8.7%、25.2%、33.0%、24.2%和33.0%;在调整了性别、年龄、地区、文化程度、家庭人均月收入、吸烟情况、饮酒情况、体力活动水平以及谷类、薯类、蔬菜、水果、动物性食物、奶及奶制品、大豆及坚果类、盐、油的日均摄入量后,多因素非条件logistic回归分析结果显示,以血清TG正常的成年居民为参照,中国西部地区五城市血清TG边缘升高成年居民超重肥胖(OR=2.70,95%CI=1.80~4.04)、中心型肥胖(OR=1.67,95%CI=1.13~2.48)、高血压(OR=1.71,95%CI=1.15~2.54)、LDL-C升高(OR=3.65,95%CI=2.03~6.59)、TC升高(OR=3.42,95%CI=2.22~5.26)、胰岛素抵抗(OR=2.65,95%CI=1.79~3.90)和高尿酸血症(OR=2.31,95%CI=1.55~3.44)检出率较高;中国西部地区五城市血清TG升高成年居民超重肥胖(OR=4.68,95%CI=2.96~7.40)、中心型肥胖(OR=4.25,95%CI=2.75~6.58)、高血压(OR=1.83,95%CI=1.22~2.74)、LDL-C升高(OR=4.66,95%CI=2.55~8.50)、HDL-C降低(OR=5.85,95%CI=2.59~13.23)、TC升高(OR=6.24,95%CI=3.98~9.79)、胰岛素抵抗(OR=5.22,95%CI=3.47~7.83)、糖尿病(OR=2.30,95%CI=1.50~3.52)和高尿酸血症(OR=6.41,95%CI=4.22~9.73)检出率较高。

结论

中国西部地区五城市成年居民血清TG升高与超重肥胖、中心型肥胖、高血压、LDL-C升高、HDL-C降低、TC升高、胰岛素抵抗、糖尿病和高尿酸血症等多种代谢异常状态均呈正相关。

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蒋泽宇(2001—),硕士在读,研究方向:人群营养

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江华,E-mail:
张玉梅,E-mail:
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蒋泽宇(2001—),硕士在读,研究方向:人群营养

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Frontiers in Public Health, 2022, 10: 865870., articleTitle=null, refAbstract=null), Reference(id=1320438243015897977, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=27, rfOrder=26, authorNames=null, journalName=null, refType=null, unstructuredReference=叶春丽, 王丽敏, 赵艳芳, 等. 2010—2018年中国成年居民胰岛素抵抗变化趋势分析[J]. 中华流行病学杂志, 2025, 46(2): 179-187., articleTitle=null, refAbstract=null), Reference(id=1320438243078812538, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=28, rfOrder=27, authorNames=null, journalName=null, refType=null, unstructuredReference=Zhao J, Zhang Y, Wei F J, et al. Triglyceride is an independent predictor of type 2 diabetes among middle-aged and older adults: a prospective study with 8-year follow-ups in two cohorts[J]. Journal of Translational Medicine, 2019, 17(1): 403., articleTitle=null, refAbstract=null), Reference(id=1320438243242390395, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=29, rfOrder=28, authorNames=null, journalName=null, refType=null, unstructuredReference=Guo R B, Wei L H, Cao Y T, et al. Normal triglyceride concentration and the risk of diabetes mellitus type 2 in the general population of China[J]. Frontiers in Endocrinology, 2024, 15: 1330650., articleTitle=null, refAbstract=null), Reference(id=1320438243326276476, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=30, rfOrder=29, authorNames=null, journalName=null, refType=null, unstructuredReference=Subramanian S. Hypertriglyceridemia: pathophysiology, role of genetics, consequences, and treatment[EB/OL]. (2024-01-08)[2025-11-11]. https://www.ncbi.nlm.nih.gov/books/NBK326743/., articleTitle=null, refAbstract=null), Reference(id=1320438243384996733, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=31, rfOrder=30, authorNames=null, journalName=null, refType=null, unstructuredReference=Gesteiro E, Megía A, Guadalupe-Grau A, et al. Early identification of metabolic syndrome risk: a review of reviews and proposal for defining pre-metabolic syndrome status[J]. Nutrition, Metabolism & Cardiovascular Diseases, 2021, 31(9): 2557-2574., articleTitle=null, refAbstract=null), Reference(id=1320438243443716990, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=32, rfOrder=31, authorNames=null, journalName=null, refType=null, unstructuredReference=Moon J H, Kim Y, Oh T J, et al. Triglyceride-glucose index predicts future atherosclerotic cardiovascular diseases: a 16-year follow-up in a prospective, community-dwelling cohort study[J]. Endocrinology and Metabolism, 2023, 38(4): 406-417., articleTitle=null, refAbstract=null), Reference(id=1320438243510825855, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=33, rfOrder=32, authorNames=null, journalName=null, refType=null, unstructuredReference=Luna-Castillo K P, Olivares-Ochoa X C, Hernández-Ruiz R G, et al. The effect of dietary interventions on hypertriglyceridemia: from public health to molecular nutrition evidence[J]. Nutrients, 2022, 14(5): 1104., articleTitle=null, refAbstract=null), Reference(id=1320438243640849280, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=34, rfOrder=33, authorNames=null, journalName=null, refType=null, unstructuredReference=Sullivan S, Kirk E P, Mittendorfer B, et al. Randomized trial of exercise effect on intrahepatic triglyceride content and lipid kinetics in nonalcoholic fatty liver disease[J]. Hepatology, 2012, 55(6): 1738-1745., articleTitle=null, refAbstract=null), Reference(id=1320438243707958145, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=35, rfOrder=34, authorNames=null, journalName=null, refType=null, unstructuredReference=Van Der Plas A, Antunes M, Pouly S, et al. Meta-analysis of the effects of smoking and smoking cessation on triglyceride levels[J]. Toxicology Reports, 2023, 10: 367-375., articleTitle=null, refAbstract=null), Reference(id=1320438243766678402, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=36, rfOrder=35, authorNames=null, journalName=null, refType=null, unstructuredReference=Choi S, Kim K, Lee J K, et al. Association between change in alcohol consumption and metabolic syndrome: analysis from the health examinees study[J]. Diabetes & Metabolism Journal, 2019, 43(5): 615-626., articleTitle=null, refAbstract=null), Reference(id=1320438243842175875, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=37, rfOrder=36, authorNames=null, journalName=null, refType=null, unstructuredReference=于跃, 晋美曲珍, 白国霞, 等. 西藏高原地区中老年人静息心率与代谢性综合征关系[J]. 中国公共卫生, 2025, 41(7): 829-833., articleTitle=null, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1320438229392798460, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, xref=1, ext=[AuthorCompanyExt(id=1320438229401187069, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, companyId=1320438229392798460, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, 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Comparison of the detection rates of various metabolic abnormalities among adult residents with different characteristics in five cities in western China

, figureFileSmall=null, figureFileBig=null, tableContent=
特征分类调查人数超重肥胖中心型肥胖高血压LDL-C升高HDL-C降低TC升高胰岛素抵抗糖尿病高尿酸血症
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性别男性30819563.3115851.3015450.003110.063812.346922.4011437.0110433.7712440.26
女性63134154.04 b27443.42 a23537.24 c639.98446.97 b16826.6219631.0612319.49 c18629.48 b
年龄/岁18~4431912940.447322.883811.91103.135617.553510.976219.443410.669128.53
45~6431421167.2017154.4615649.684213.38103.189730.8912640.137423.579831.21
65~8030619664.05 c18861.44 c19563.73 c4213.73 c165.23 c10534.31 c12239.87 c11938.89 c12139.54 a
文化程度初中及以下41828167.2225260.2923455.985312.68163.8313833.0115637.3213632.5415537.08
高中/中专/技校28717560.9812844.6012041.813512.20248.367626.4810937.987225.099432.75
本科及以上2348034.19 c5222.22 c3514.96 c62.56 c4217.95 c239.83 c4519.23 c198.126126.07 a
家庭人均月收入/元≤500059634457.7229349.1626844.976611.07467.7216828.1920834.9015225.5018631.21
5000~10 00027715154.5111039.719534.30259.033010.835820.948129.246021.6610136.46
>10 000664162.122943.94 a2639.39 a34.5569.091116.67 a2131.821522.732334.85
地区赤峰市17210259.308951.746638.3784.655632.562112.217141.284123.843620.93
大理市1937739.904623.838544.04126.2294.663216.584221.763920.216935.75
鄂尔多斯市19912160.809748.748944.722412.0663.025427.147035.184120.605829.15
呼和浩特市18611059.149551.087640.862412.9042.157841.947942.473418.285730.65
拉萨市18912666.67 c10555.56 c7338.622613.76 b73.70 a5227.51 c4825.40 c7238.10 c9047.62 c
吸烟情况从不吸烟71739755.3731944.4927738.63628.65588.0917724.6922731.6615621.7621930.54
当前吸烟1247056.455342.745745.97118.87129.682822.584637.103830.654435.48
已戒烟986970.41 a6061.22 b5556.12 b2121.43 c1212.243232.653737.763333.67 b4747.96 b
饮酒情况从不饮酒56330654.3525845.8323441.565810.30417.2815126.8218432.6812722.5616829.84
当前饮酒29217258.9013044.5211639.73299.933110.626823.299231.517425.3411238.36
已戒酒845869.05 a4452.383946.4378.331011.901821.433440.482630.953035.71 a
体力活动水平轻度23014462.6111349.139440.872410.4393.916628.708135.225724.788536.96
中度48927856.8522646.2221143.155210.634910.0212224.9516834.3612124.7415431.49
重度22011451.829342.278438.18188.182410.91 a4922.276127.734922.277132.27
血清TG水平正常61128947.3023137.8120633.72335.40569.179315.2213622.2613021.2815124.71
边缘升高16311469.948552.158652.762716.5674.296238.047244.173823.316439.26
升高16513380.61 c11670.30 c9758.79 c3420.61 c1911.52 a8249.70 c10261.82 c5935.76 b9557.58 c
), ArticleFig(id=1320438238972588892, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, language=CN, label=表1, caption=

中国西部地区五城市不同特征成年居民各种代谢异常状态检出情况比较

, figureFileSmall=null, figureFileBig=null, tableContent=
特征分类调查人数超重肥胖中心型肥胖高血压LDL-C升高HDL-C降低TC升高胰岛素抵抗糖尿病高尿酸血症
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性别男性30819563.3115851.3015450.003110.063812.346922.4011437.0110433.7712440.26
女性63134154.04 b27443.42 a23537.24 c639.98446.97 b16826.6219631.0612319.49 c18629.48 b
年龄/岁18~4431912940.447322.883811.91103.135617.553510.976219.443410.669128.53
45~6431421167.2017154.4615649.684213.38103.189730.8912640.137423.579831.21
65~8030619664.05 c18861.44 c19563.73 c4213.73 c165.23 c10534.31 c12239.87 c11938.89 c12139.54 a
文化程度初中及以下41828167.2225260.2923455.985312.68163.8313833.0115637.3213632.5415537.08
高中/中专/技校28717560.9812844.6012041.813512.20248.367626.4810937.987225.099432.75
本科及以上2348034.19 c5222.22 c3514.96 c62.56 c4217.95 c239.83 c4519.23 c198.126126.07 a
家庭人均月收入/元≤500059634457.7229349.1626844.976611.07467.7216828.1920834.9015225.5018631.21
5000~10 00027715154.5111039.719534.30259.033010.835820.948129.246021.6610136.46
>10 000664162.122943.94 a2639.39 a34.5569.091116.67 a2131.821522.732334.85
地区赤峰市17210259.308951.746638.3784.655632.562112.217141.284123.843620.93
大理市1937739.904623.838544.04126.2294.663216.584221.763920.216935.75
鄂尔多斯市19912160.809748.748944.722412.0663.025427.147035.184120.605829.15
呼和浩特市18611059.149551.087640.862412.9042.157841.947942.473418.285730.65
拉萨市18912666.67 c10555.56 c7338.622613.76 b73.70 a5227.51 c4825.40 c7238.10 c9047.62 c
吸烟情况从不吸烟71739755.3731944.4927738.63628.65588.0917724.6922731.6615621.7621930.54
当前吸烟1247056.455342.745745.97118.87129.682822.584637.103830.654435.48
已戒烟986970.41 a6061.22 b5556.12 b2121.43 c1212.243232.653737.763333.67 b4747.96 b
饮酒情况从不饮酒56330654.3525845.8323441.565810.30417.2815126.8218432.6812722.5616829.84
当前饮酒29217258.9013044.5211639.73299.933110.626823.299231.517425.3411238.36
已戒酒845869.05 a4452.383946.4378.331011.901821.433440.482630.953035.71 a
体力活动水平轻度23014462.6111349.139440.872410.4393.916628.708135.225724.788536.96
中度48927856.8522646.2221143.155210.634910.0212224.9516834.3612124.7415431.49
重度22011451.829342.278438.18188.182410.91 a4922.276127.734922.277132.27
血清TG水平正常61128947.3023137.8120633.72335.40569.179315.2213622.2613021.2815124.71
边缘升高16311469.948552.158652.762716.5674.296238.047244.173823.316439.26
升高16513380.61 c11670.30 c9758.79 c3420.61 c1911.52 a8249.70 c10261.82 c5935.76 b9557.58 c
), ArticleFig(id=1320438239056474973, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, language=EN, label=Tab.2, caption=

Comparison of the average daily intake (g/d) of various foods among adult residents of different groups with various metabolic abnormalities in five cities in western China

, figureFileSmall=null, figureFileBig=null, tableContent=
代谢异常状态组别谷类薯类蔬菜水果动物性食物奶及奶制品大豆及坚果类盐油
超重肥胖否200.00
(100.00,300.00)
25.71
(11.43,57.14)
120.00
(60.00,200.00)
85.71
(42.86,172.21)
114.29
(71.10,210.00)
275.80
(126.30,546.59)
21.43
(7.93,49.46)
9.00
(8.00,10.00)
36.00
(20.00,40.00)
是200.00
(100.00,300.00)
32.14
(14.29,60.00)a
100.00
(57.14,200.00)
80.00
(34.29,162.50)
121.43
(77.94,187.76)
300.51
(132.82,709.68)
18.57
(5.93,43.04)
9.90
(8.00,10.00)
36.60
(30.00,40.00)a
中心型肥胖否200.00
(100.00, 300.00)
28.57
(11.43, 53.45)
120.00
(60.00, 200.00)
98.57
(42.86, 177.29)
120.72
(75.62, 210.00)
292.04
(132.44, 598.99)
20.86
(7.74,47.96)
9.90
(8.00,10.60)
36.00
(24.00,40.00)
是200.00
(100.00, 300.00)
32.32
(14.29, 60.00)a
100.00
(50.00, 200.00)a
75.00
(32.86, 150.00)b
116.09
(73.93, 177.39)
291.37
(126.86, 690.73)
19.29
(5.71,42.86)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
高血压否200.00
(100.00,300.00)
28.57
(12.86,56.79)
100.00
(57.86,200.00)
88.25
(42.86,172.61)
119.52
(71.98,207.14)
292.73
(134.33,596.01)
18.36
(6.67,42.62)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
是200.00
(120.00,300.00)
33.71
(14.29,60.00)
120.00
(60.00,200.00)
75.00
(28.57,160.00)a
118.38
(80.00,189.62)
289.56
(125.00,704.15)
22.86
(8.74,50.00)a
9.90
(7.50,10.00)
36.00
(24.00,40.00)
LDL-C升高否200.00
(100.00, 300.00)
28.57
(14.29, 57.14)
120.00
(60.00, 200.00)
80.00
(40.00, 170.00)
120.00
(75.00, 200.00)
290.62
(127.43, 616.71)
20.00
(7.14,45.00)
9.90
(8.00,10.00)
36.00
(25.00,40.00)
是200.00
(100.00, 300.00)
34.00
(14.29, 60.00)
100.00
(60.00, 179.00)
88.57
(34.64, 172.25)
110.83
(75.72, 180.77)
318.73
(180.18, 767.99)
18.93
(7.18,44.46)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
HDL-C降低否200.00
(100.00, 300.00)
28.57
(14.29, 60.00)
100.00
(57.14, 200.00)
80.00
(35.71, 170.00)
118.57
(75.00, 198.57)
299.96
(131.83, 660.57)
20.71
(7.14,44.52)
9.90
(8.00,10.00)
36.00
(25.00,40.00)
是200.00
(100.00, 300.00)
28.57
(14.29, 50.00)
150.00
(100.00,300.00)c
100.00
(50.00,200.00)
130.24
(73.69, 219.19)
216.34
(102.91, 466.33)b
15.00
(4.21,45.08)
9.00
(8.00,10.00)
40.00
(30.00,42.00)a
TC升高否200.00
(100.00, 300.00)
28.57
(13.33, 57.14)
120.00
(60.00, 200.00)
80.00
(42.86, 173.00)
121.43
(74.82, 208.57)
291.79
(130.29, 627.79)
20.00
(6.67,44.11)
9.90
(8.00,10.00)
36.00
(25.00,40.00)
是200.00
(120.00, 300.00)
34.29
(14.29, 60.00)
100.00
(50.00, 179.00)a
80.00
(34.29, 160.00)
110.67
(75.00, 169.81)
291.54
(127.43, 612.64)
20.70
(8.33,48.07)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
胰岛素抵抗否200.00
(100.00, 300.00)
28.57
(13.43, 60.00)
100.00
(60.00,200.00)
85.71
(40.71, 171.43)
116.19
(72.86,201.90)
304.45
(133.05, 673.58)
20.00
(6.67,42.86)
9.90
(8.00,10.00)
36.00
(22.00,40.00)
是200.00
(100.00, 300.00)
28.57
(14.29, 57.14)
120.00
(53.57,200.00)
77.57
(31.79, 160.00)
125.36
(80.53,196.79)
267.00
(124.68, 585.45)
21.43
(8.33,50.00)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
糖尿病否200.00
(100.00, 300.00)
29.75
(14.29, 57.14)
100.00
(56.61, 200.00)
85.71
(42.86, 173.00)
116.21
(75.52, 198.21)
289.07
(118.76, 597.32)
20.00
(7.14,42.86)
9.90
(8.00,10.00)
36.00
(30.00,40.00)
是200.00
(150.00, 300.00)a
28.29
(13.81, 63.71)
140.00
(62.50, 250.00)a
71.43
(32.50, 147.50)a
126.43
(69.85, 208.21)
316.10
(166.00, 812.32)a
20.95
(5.48,60.00)
9.90
(8.00,10.00)
36.60
(20.00,40.00)
高尿酸血症否200.00
(100.00, 300.00)
28.57
(12.86, 57.14)
100.00
(60.00, 200.00)
80.00
(42.86, 160.00)
116.43
(74.29, 200.00)
266.99
(125.00, 548.29)
21.43
(7.86,45.71)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
是200.00
(120.00, 300.00)
30.00
(14.29, 60.00)
120.00
(60.00, 200.00)
80.00
(34.29, 180.00)
122.26
(76.07, 198.93)
359.15
(146.48, 862.43)c
16.83
(5.00,44.11)a
9.90
(8.00,10.00)
36.00
(20.25,40.00)
), ArticleFig(id=1320438239148749662, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320438226750386935, language=CN, label=表2, caption=

中国西部地区五城市多种代谢异常状态不同组别成年居民各类食物日均摄入量(g/d)比较

, figureFileSmall=null, figureFileBig=null, tableContent=
代谢异常状态组别谷类薯类蔬菜水果动物性食物奶及奶制品大豆及坚果类盐油
超重肥胖否200.00
(100.00,300.00)
25.71
(11.43,57.14)
120.00
(60.00,200.00)
85.71
(42.86,172.21)
114.29
(71.10,210.00)
275.80
(126.30,546.59)
21.43
(7.93,49.46)
9.00
(8.00,10.00)
36.00
(20.00,40.00)
是200.00
(100.00,300.00)
32.14
(14.29,60.00)a
100.00
(57.14,200.00)
80.00
(34.29,162.50)
121.43
(77.94,187.76)
300.51
(132.82,709.68)
18.57
(5.93,43.04)
9.90
(8.00,10.00)
36.60
(30.00,40.00)a
中心型肥胖否200.00
(100.00, 300.00)
28.57
(11.43, 53.45)
120.00
(60.00, 200.00)
98.57
(42.86, 177.29)
120.72
(75.62, 210.00)
292.04
(132.44, 598.99)
20.86
(7.74,47.96)
9.90
(8.00,10.60)
36.00
(24.00,40.00)
是200.00
(100.00, 300.00)
32.32
(14.29, 60.00)a
100.00
(50.00, 200.00)a
75.00
(32.86, 150.00)b
116.09
(73.93, 177.39)
291.37
(126.86, 690.73)
19.29
(5.71,42.86)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
高血压否200.00
(100.00,300.00)
28.57
(12.86,56.79)
100.00
(57.86,200.00)
88.25
(42.86,172.61)
119.52
(71.98,207.14)
292.73
(134.33,596.01)
18.36
(6.67,42.62)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
是200.00
(120.00,300.00)
33.71
(14.29,60.00)
120.00
(60.00,200.00)
75.00
(28.57,160.00)a
118.38
(80.00,189.62)
289.56
(125.00,704.15)
22.86
(8.74,50.00)a
9.90
(7.50,10.00)
36.00
(24.00,40.00)
LDL-C升高否200.00
(100.00, 300.00)
28.57
(14.29, 57.14)
120.00
(60.00, 200.00)
80.00
(40.00, 170.00)
120.00
(75.00, 200.00)
290.62
(127.43, 616.71)
20.00
(7.14,45.00)
9.90
(8.00,10.00)
36.00
(25.00,40.00)
是200.00
(100.00, 300.00)
34.00
(14.29, 60.00)
100.00
(60.00, 179.00)
88.57
(34.64, 172.25)
110.83
(75.72, 180.77)
318.73
(180.18, 767.99)
18.93
(7.18,44.46)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
HDL-C降低否200.00
(100.00, 300.00)
28.57
(14.29, 60.00)
100.00
(57.14, 200.00)
80.00
(35.71, 170.00)
118.57
(75.00, 198.57)
299.96
(131.83, 660.57)
20.71
(7.14,44.52)
9.90
(8.00,10.00)
36.00
(25.00,40.00)
是200.00
(100.00, 300.00)
28.57
(14.29, 50.00)
150.00
(100.00,300.00)c
100.00
(50.00,200.00)
130.24
(73.69, 219.19)
216.34
(102.91, 466.33)b
15.00
(4.21,45.08)
9.00
(8.00,10.00)
40.00
(30.00,42.00)a
TC升高否200.00
(100.00, 300.00)
28.57
(13.33, 57.14)
120.00
(60.00, 200.00)
80.00
(42.86, 173.00)
121.43
(74.82, 208.57)
291.79
(130.29, 627.79)
20.00
(6.67,44.11)
9.90
(8.00,10.00)
36.00
(25.00,40.00)
是200.00
(120.00, 300.00)
34.29
(14.29, 60.00)
100.00
(50.00, 179.00)a
80.00
(34.29, 160.00)
110.67
(75.00, 169.81)
291.54
(127.43, 612.64)
20.70
(8.33,48.07)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
胰岛素抵抗否200.00
(100.00, 300.00)
28.57
(13.43, 60.00)
100.00
(60.00,200.00)
85.71
(40.71, 171.43)
116.19
(72.86,201.90)
304.45
(133.05, 673.58)
20.00
(6.67,42.86)
9.90
(8.00,10.00)
36.00
(22.00,40.00)
是200.00
(100.00, 300.00)
28.57
(14.29, 57.14)
120.00
(53.57,200.00)
77.57
(31.79, 160.00)
125.36
(80.53,196.79)
267.00
(124.68, 585.45)
21.43
(8.33,50.00)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
糖尿病否200.00
(100.00, 300.00)
29.75
(14.29, 57.14)
100.00
(56.61, 200.00)
85.71
(42.86, 173.00)
116.21
(75.52, 198.21)
289.07
(118.76, 597.32)
20.00
(7.14,42.86)
9.90
(8.00,10.00)
36.00
(30.00,40.00)
是200.00
(150.00, 300.00)a
28.29
(13.81, 63.71)
140.00
(62.50, 250.00)a
71.43
(32.50, 147.50)a
126.43
(69.85, 208.21)
316.10
(166.00, 812.32)a
20.95
(5.48,60.00)
9.90
(8.00,10.00)
36.60
(20.00,40.00)
高尿酸血症否200.00
(100.00, 300.00)
28.57
(12.86, 57.14)
100.00
(60.00, 200.00)
80.00
(42.86, 160.00)
116.43
(74.29, 200.00)
266.99
(125.00, 548.29)
21.43
(7.86,45.71)
9.90
(8.00,10.00)
36.60
(30.00,40.00)
是200.00
(120.00, 300.00)
30.00
(14.29, 60.00)
120.00
(60.00, 200.00)
80.00
(34.29, 180.00)
122.26
(76.07, 198.93)
359.15
(146.48, 862.43)c
16.83
(5.00,44.11)a
9.90
(8.00,10.00)
36.00
(20.25,40.00)
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中国西部地区五城市成年居民血清甘油三酯升高与多种代谢异常状况关系:一项2023年横断面研究
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蒋泽宇 1, 2 , 刘鑫 1, 3 , 李婷 4, 5 , 梁栋 2 , 段素芳 4, 5 , 司徒文佑 4, 5 , 冯罡 4, 5 , 梁文欣 1 , 何婷超 1 , 江华 6, *, * , 张玉梅 1, *, *
中国公共卫生 | 流行病学研究 2026,42(5): 570-577
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中国公共卫生 |流行病学研究 2026 , 42 (5) : 570 -577
中国西部地区五城市成年居民血清甘油三酯升高与多种代谢异常状况关系:一项2023年横断面研究
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蒋泽宇1, 2, 刘鑫1, 3, 李婷4, 5, 梁栋2, 段素芳4, 5, 司徒文佑4, 5, 冯罡4, 5, 梁文欣1, 何婷超1, 江华6, *, * , 张玉梅1, *, *
作者信息
  • 1北京大学公共卫生学院营养与食品卫生学系,北京 100191
  • 2国家食品安全风险评估中心,北京 100022
  • 3佳木斯市中心医院,佳木斯 154002
  • 4内蒙古乳业技术研究院有限责任公司,呼和浩特 010110
  • 5国家乳业技术创新中心,呼和浩特 010000
  • 6北京大学护理学院,北京 100191
通讯作者:
江华,E-mail:
张玉梅,E-mail:
作者简介:

蒋泽宇(2001—),硕士在读,研究方向:人群营养

Associations between serum triglyceride levels and multiple metabolic abnormalities among adults in five cities of western China: a cross-sectional study, 2023
Zeyu JIANG1, 2, Xin LIU1, 3, Ting LI4, 5, Dong LIANG2, Sufang DUAN4, 5, Ignatius Man-Yau Szeto4, 5, Gang FENG4, 5, Wenxin LIANG1, Tingchao HE1, Hua JIANG6 , Yumei ZHANG1
Affiliations
  • 1Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100191, China
  • 2China National Center for Food Safety Risk Assessment, Beijing 100022, China
  • 3Jiamusi Central Hospital, Jiamusi 154002, China
  • 4Inner Mongolia Dairy Technology Research Institute Co., Ltd., Hohhot 010110, China
  • 5National Center of Technology Innovation for Dairy, Hohhot 010000, China
  • 6School of Nursing, Peking University, Beijing 100191, China
  • Corresponding Author:
    JIANG Hua, E-mail:
    ZHANG Yumei, E-mail:
出版时间: 2026-05-10 doi: 10.11847/zgggws1148607
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目的

了解中国西部地区五城市成年居民血清甘油三酯(TG)升高与多种代谢异常状态的关系,为该地区居民代谢综合征的管理及防治提供参考依据。

方法

于2023年3—10月采用多阶段分层随机抽样方法在中国西部地区内蒙古自治区赤峰市、呼和浩特市、鄂尔多斯市,西藏自治区拉萨市和云南省大理市抽取990名≥18岁成年常住居民进行问卷调查、体格检查和实验室检测,应用多因素非条件logistic回归模型分析其血清TG水平与超重肥胖、中心型肥胖、高血压、低密度脂蛋白胆固醇(LDL-C)升高、高密度脂蛋白胆固醇(HDL-C)降低、总胆固醇(TC)升高、胰岛素抵抗、糖尿病和高尿酸血症等多种代谢异常状态的关系。

结果

中国西部地区五城市最终纳入分析的939名成年居民检出血清TG正常者611人(65.0%),TG边缘升高者163人(17.4%),TG升高者165例(17.6%);检出超重肥胖、中心型肥胖、高血压、LDL-C升高、HDL-C降低、TC升高、胰岛素抵抗、糖尿病和高尿酸血症者分别为536、432、389、94、82、237、310、227和310例,检出率分别为57.1%、46.0%、41.4%、10.0%、8.7%、25.2%、33.0%、24.2%和33.0%;在调整了性别、年龄、地区、文化程度、家庭人均月收入、吸烟情况、饮酒情况、体力活动水平以及谷类、薯类、蔬菜、水果、动物性食物、奶及奶制品、大豆及坚果类、盐、油的日均摄入量后,多因素非条件logistic回归分析结果显示,以血清TG正常的成年居民为参照,中国西部地区五城市血清TG边缘升高成年居民超重肥胖(OR=2.70,95%CI=1.80~4.04)、中心型肥胖(OR=1.67,95%CI=1.13~2.48)、高血压(OR=1.71,95%CI=1.15~2.54)、LDL-C升高(OR=3.65,95%CI=2.03~6.59)、TC升高(OR=3.42,95%CI=2.22~5.26)、胰岛素抵抗(OR=2.65,95%CI=1.79~3.90)和高尿酸血症(OR=2.31,95%CI=1.55~3.44)检出率较高;中国西部地区五城市血清TG升高成年居民超重肥胖(OR=4.68,95%CI=2.96~7.40)、中心型肥胖(OR=4.25,95%CI=2.75~6.58)、高血压(OR=1.83,95%CI=1.22~2.74)、LDL-C升高(OR=4.66,95%CI=2.55~8.50)、HDL-C降低(OR=5.85,95%CI=2.59~13.23)、TC升高(OR=6.24,95%CI=3.98~9.79)、胰岛素抵抗(OR=5.22,95%CI=3.47~7.83)、糖尿病(OR=2.30,95%CI=1.50~3.52)和高尿酸血症(OR=6.41,95%CI=4.22~9.73)检出率较高。

结论

中国西部地区五城市成年居民血清TG升高与超重肥胖、中心型肥胖、高血压、LDL-C升高、HDL-C降低、TC升高、胰岛素抵抗、糖尿病和高尿酸血症等多种代谢异常状态均呈正相关。

血清甘油三酯(TG)  /  升高  /  代谢异常状态  /  关系  /  成年居民  /  横断面研究  /  西部地区  /  中国
Objective

To investigate the associations of serum triglyceride (TG) levels with various metabolic abnormalities among adult residents in 5 cities of western China, thereby providing evidence for the prevention and management of metabolic syndrome in this region.

Methods

A multistage stratified cluster sampling method was used to recruit 990 adult permanent residents ≥18 years old from Chifeng, Hohhot, and Ordos in Inner Mongolia Autonomous Region, Lhasa in Xizang Autonomous Region, and Dali in Yunnan province between March and October 2023. Data were collected through questionnaires, physical examinations, and laboratory tests. Multivariate unconditional logistic regression models were used to analyze the associations between serum TG levels and various metabolic abnormalities, including overweight and obesity, central obesity, hypertension, elevated low-density lipoprotein cholesterol (LDL-C), decreased high-density lipoprotein cholesterol (HDL-C), elevated total cholesterol (TC), insulin resistance, diabetes, and hyperuricemia.

Results

A total of 939 adults were included in the final analysis. Among the surveyed population, 611 (65.0%), 163 (17.4%), and 165 (17.6%) had normal TG levels, borderline high TG, and elevated TG, respectively. The number (detection rates) of respondents with overweight and obesity, central obesity, hypertension, elevated LDL-C, decreased HDL-C, elevated TC, insulin resistance, diabetes, and hyperuricemia was 536 (57.1%), 432 (46.0%), 389 (41.4%), 94 (10.0%), 82 (8.7%), 237 (25.2%), 310 (33.0%), 227(24.2%), and 310 (33.0%), respectively. After adjusting for sex, age group, region, educational background, per capita monthly household income, smoking status, drinking status, physical activity level, and daily intake of cereals, tubers, vegetables, fruits, animal-based foods, dairy products, soy and nuts, salt, and oil, multivariate unconditional logistic regression analyses showed that adults with borderline high TG had higher detection rates of overweight and obesity (OR = 2.70, 95%CI: 1.80–4.04), central obesity (OR = 1.67, 95%CI: 1.13–2.48), hypertension (OR = 1.71, 95%CI: 1.15–2.54), elevated LDL-C (OR = 3.65, 95%CI: 2.03–6.59), elevated TC (OR = 3.42, 95%CI: 2.22–5.26), insulin resistance (OR = 2.65, 95%CI: 1.79–3.90), and hyperuricemia (OR = 2.31, 95%CI: 1.55–3.44) than the adults with normal serum TG levels. Adults with elevated TG had higher detection rates of overweight and obesity (OR = 4.68, 95%CI: 2.96–7.40), central obesity (OR = 4.25, 95%CI: 2.75–6.58), hypertension (OR = 1.83, 95%CI: 1.22–2.74), elevated LDL-C (OR = 4.66, 95%CI: 2.55–8.50), reduced HDL-C (OR = 5.85, 95%CI: 2.59–13.23), elevated TC (OR = 6.24, 95%CI: 3.98–9.79), insulin resistance (OR = 5.22, 95%CI: 3.47–7.83), diabetes (OR = 2.30, 95%CI: 1.50–3.52), and hyperuricemia (OR = 6.41, 95%CI: 4.22–9.73).

Conclusions

Elevated serum TG among adults in 5 cities of western China are positively associated with multiple metabolic abnormalities, including overweight and obesity, central obesity, hypertension, elevated LDL-C, decreased HDL-C, elevated TC, insulin resistance, diabetes, and hyperuricemia.

serum triglyceride (TG)  /  elevation  /  metabolic abnormalities  /  association  /  adult resident  /  cross-sectional study  /  western China  /  China
蒋泽宇, 刘鑫, 李婷, 梁栋, 段素芳, 司徒文佑, 冯罡, 梁文欣, 何婷超, 江华, 张玉梅. 中国西部地区五城市成年居民血清甘油三酯升高与多种代谢异常状况关系:一项2023年横断面研究. 中国公共卫生, 2026 , 42 (5) : 570 -577 . DOI: 10.11847/zgggws1148607
Zeyu JIANG, Xin LIU, Ting LI, Dong LIANG, Sufang DUAN, Ignatius Man-Yau Szeto, Gang FENG, Wenxin LIANG, Tingchao HE, Hua JIANG, Yumei ZHANG. Associations between serum triglyceride levels and multiple metabolic abnormalities among adults in five cities of western China: a cross-sectional study, 2023[J]. Chinese Journal of Public Health, 2026 , 42 (5) : 570 -577 . DOI: 10.11847/zgggws1148607
高甘油三酯血症(hypertriglyceridemia, HTG)是一类以血液中甘油三酯(triglyceride, TG)水平升高为特征的、常见的脂质代谢异常疾病[1]。有研究表明,HTG与动脉粥样硬化性心血管疾病(atherosclerotic cardiovascular disease, ASCVD)、急性胰腺炎、非酒精性脂肪肝病(non-alcoholic fatty liver disease, NAFLD)和2型糖尿病等疾病的患病风险密切相关[2–4]。近年来,随着中国经济的发展、生活方式的改变和社会人口结构的改变,成年人血脂异常患病率呈显著上升趋势,其中HTG患病率由2002年的5.7%上升到2015年的15.0%[5–6],其作为心血管疾病的重要危险因素,间接加重了疾病负担。Meta分析结果显示,每降低1 mmol/L的血清TG水平可使主要心血管事件的发生风险降低约16%,且这一关联在控制低密度脂蛋白胆固醇(low-density lipoprotein cholesterol,LDL-C)水平后仍然显著,提示血清TG可能是独立的心血管危险因素,控制血清TG水平对防治心血管疾病具有重要意义[7]。相较于我国东部和中部地区,西部地区公共卫生资源有限[8–9],为了解该地区居民血清TG水平与多种代谢异常状态的关系,为该地区居民代谢综合征的管理及防治提供参考依据,本研究于2023年3—10月采用多阶段分层随机抽样方法在中国西部地区内蒙古自治区赤峰市、呼和浩特市、鄂尔多斯市,西藏自治区拉萨市和云南省大理市抽取990名≥18岁成年常住居民进行问卷调查、体格检查和实验室检测,采用多因素非条件logistic回归模型分析其血清TG水平与超重肥胖、中心型肥胖、高血压、LDL-C升高、高密度脂蛋白胆固醇(high-density lipoprotein cholesterol, HDL-C)降低、总胆固醇(total cholesterol, TC)升高、胰岛素抵抗、糖尿病和高尿酸血症等多种代谢异常状态的关系。结果报告如下。
采用多阶段分层随机抽样方法,首先采用立意抽样方法,根据西部地区地理、经济和生活习惯等因素选取内蒙古自治区东部(赤峰市)、中部(呼和浩特市)和西部(鄂尔多斯市)各1个代表性城市以及西藏自治区拉萨市、云南省大理市共5个市作为样本市;其次在选取的这5个样本市中每个市各随机抽取1个社区或居委会作为调查点共5个调查点;最后采用分层随机抽样方法在每个调查点按年龄18~44岁、45~64岁和65~80岁分为3层,每层分别随机抽取≥60名在当地居住≥1年且无感染性疾病、精神疾病和记忆障碍者,妊娠期或哺乳期女性以及因其他原因不能配合本次调查的常住居民作为调查对象进行问卷调查、体格检查和实验室检测。本次共调查990人,其中有效样本为979人,有效应答率为98.9%。在排除了40名因血检数据、体检数据和膳食调查数据等关键变量缺失的调查对象后,最终纳入939名调查对象相关数据进行分析。本研究经北京大学生物医学伦理委员会审查批准(批号:No. IRB000001052–21105),且所有调查对象均签署了知情同意书。
采用自行设计的调查问卷,由经过统一培训且考核合格的调查员进行面访调查,内容包括性别、年龄、文化程度、家庭人均月收入、地区、吸烟情况、饮酒情况、体力活动水平和膳食及营养信息。其中,现在吸烟指目前仍在吸烟者(包括每天吸烟者和偶尔吸烟者),已戒烟指过去吸烟但目前已停止吸烟≥6个月者[10–11];现在饮酒指近6个月内有饮酒行为者,已戒酒指过去饮酒但目前已停止饮酒≥6个月者[10–11];体力活动水平使用国际体力活动问卷短卷(International Physical Activity Questionnaire-Short Form, IPAQ-SF)[12]对调查对象的体力活动水平进行评价,身体活动量=身体活动对应的代谢当量(metabolic equivalents, MET)赋值×每周活动天数(d)×每天活动时间(min),高强度活动赋值为8.0 METs,中等强度活动赋值为4.0 METs,步行赋值为3.3 METs,高体力活动水平组指每周高强度身体活动≥3 d且每周身体活动量≥1 500 METs·min,或各类身体活动总时间≥7 d且每周身体活动量≥3 000 METs·min;中等水平组指每周高强度身体活动≥3 d且每天至少20 min,或中等强度身体活动≥5 d且每天≥30 min,或各类身体活动≥5 d且每周身体活动量≥600 METs·min;低水平组指每周身体活动量未达到高水平组和中等水平组水平;膳食及营养信息采用包含47个食物条目的食物频率调查问卷(food frequency questionnaire, FFQ)收集调查对象过去1个月内各类食物的摄入频次与摄入量,并计算日均摄入量。根据《中国居民膳食指南(2022)》[13],将同类食物条目合并计算获得谷类、薯类、蔬菜、水果、动物性食物、奶及奶制品、大豆及坚果类、盐和油的日均摄入量。
由培训合格、遵循统一调查程序和标准操作流程的调查员进行身高、体重、腰围和血压的测量。其中,身高和体重使用金属立柱式身高计和双标尺杠杆体重秤进行测量,读数分别精确到0.1 cm和0.1 kg。根据测量得到的身高和体重计算体质量指数(body mass index, BMI)=体重(kg)/[身高(m)]2,BMI<18.5 kg/m2为体重过低,18.5~23.9 kg/m2为正常体重,24.0~27.9 kg/m2为超重,≥28.0 kg/m2为肥胖[14];腰围使用软尺进行测量,读数精确到0.1 cm,男性腰围≥90 cm、女性腰围≥85 cm为中心型肥胖[14];血压使用欧姆龙HEM-7124电子血压计[欧姆龙(大连)有限公司]进行测量,测量时每位调查对象在未服用降压药状态下测量2次,每次间隔1~2 min,取2次测量的均值作为最终血压值,高血压指收缩压≥140 mmHg(1 mmHg=0.133 3 kPa)或舒张压≥90 mmHg,或调查对象自报既往曾明确诊断患有高血压[15]。
采集调查对象空腹12 h肘静脉血5 mL,置于4 ℃冰箱保存,送当地社区医院进行糖化血红蛋白检测;促凝管血液于2 h内采用3 000 r/min离心15 min,析出血清分装并置于−80 ℃冰箱保存,送北京豪思医学检验实验室检测TG、TC、LDL-C、HDL-C、空腹血糖(fasting blood glucose, FBG)、空腹血清胰岛素(fasting insulin, FINS)和血清尿酸(uric acid, UA)等。其中,血清TG采用磷酸甘油氧化酶4–氯酸法测定,并按TG<1.7 mmol/L、1.7~2.2 mmol/L和≥2.3 mmol/L将调查对象分为TG正常组、TG边缘升高组和TG升高组[16];TC采用胆固醇氧化酶氨基安替吡啉酚法测定,TC≥6.2 mmol/L为TC升高[16];LDL-C和HDL-C采用直接法测定,LDL-C≥4.1 mmol/L为LDL-C升高,HDL-C<1.0 mmol/L为HDL-C降低[16];FBG采用葡萄糖氧化酶法测定,糖化血红蛋白采用高压液相色谱法测定,糖尿病指FBG≥7.0 mmol/L和/或糖化血红蛋白≥6.5%,或调查对象自报既往曾明确诊断患有糖尿病[17];FINS采用酶联免疫吸附法测定,胰岛素抵抗指数(Homeostatic Model Assessment of Insulin Resistance, HOMA-IR)根据FBG和FINS计算,HOMA-IR=FINS(μIU/mL)×FBG(mmol/L)/22.5,HOMA-IR高于非糖尿病患者数值的P75为有胰岛素抵抗[18];UA采用尿酸酶法测定,高尿酸血症指男性UA>420 μmol/L、女性UA>360 μmol/L,或调查对象自报既往曾明确诊断患有高尿酸血症[19]。
采用R 4.4.2软件进行统计分析。计数资料采用人数和率(%)描述,采用χ2检验进行组间比较。符合正态分布的计量资料采用$ \overline{x}\pm s $描述,采用方差分析进行组间比较;不符合正态分布的计量资料采用[M(P25,P75)] 描述,组间的比较采用Mann-Whitney U检验。应用多因素非条件logistic回归模型分析中国西部地区五城市居民血清TG水平与超重肥胖、中心型肥胖、高血压、LDL-C升高、HDL-C降低、TC升高、胰岛素抵抗、糖尿病和高尿酸血症等多种代谢异常状态的关系。检验水准为双侧检验α=0.05。
中国西部地区五城市最终纳入分析的939名成年居民中,男性308人(32.8%),女性631人(67.2%);年龄18~80岁,平均年龄(50.8±17.6)岁,其中18~44岁319人(34.0%),45~64岁314人(33.4%),65~80岁306人(32.6%);文化程度初中及以下418人(44.5%),高中/中专/技校287人(30.6%),大专及以上234人(24.9%);家庭人均月收入≤5 000元596人(63.5%),5000~10 000元277人(29.5%),>10 000元66人(7.0%);赤峰市172人(18.3%),鄂尔多斯市199人(21.2%),呼和浩特市186人(19.8%),大理市193人(20.6%),拉萨市189人(20.1%);从不吸烟717人(76.4%),现在吸烟124人(13.2%),已戒烟98人(10.4%);从不饮酒563人(60.0%),现在饮酒292人(31.1%),已戒酒84人(8.9%);体力活动低水平230人(24.5%),中等水平489人(52.1%),高水平220人(23.4%);TG正常611人(65.0%),TG边缘升高163人(17.4%),TG升高165例(17.6%);谷类、薯类、蔬菜、水果、动物性食物、奶及奶制品、大豆及坚果类、盐和油的日均摄入量分别为[200.00(100.00,300.00)]、[28.57(14.29,60.00)]、[107.14(60.00,200.00)]、[80.00(38.57,170.00)]、[118.90(75.00,200.00)]、[291.54 (130.18,627.02)]、[20.00 (7.14,44.76)]、[9.90(8.00,10.00)]和[36.60(26.00,40.00)]g/d。
中国西部地区五城市最终纳入分析的939名成年居民中,检出超重肥胖、中心型肥胖、高血压、LDL-C升高、HDL-C降低、TC升高、胰岛素抵抗、糖尿病和高尿酸血症者分别为536、432、389、94、82、237、310、227和310例,检出率分别为57.1%、46.0%、41.4%、10.0%、8.7%、25.2%、33.0%、24.2%和33.0%。中国西部地区五城市不同特征成年居民比较,不同性别、年龄、文化程度、地区、吸烟情况、饮酒情况和TG状态成年居民超重肥胖检出率不同,不同性别、年龄、文化程度、家庭人均月收入、地区、吸烟情况和TG状态成年居民中心型肥胖检出率不同,不同性别、年龄、文化程度、家庭人均月收入、吸烟情况和TG状态成年居民高血压检出率不同,不同年龄、文化程度、地区、吸烟情况和TG状态成年居民LDL-C升高检出率不同,不同性别、年龄、文化程度、地区、体力活动水平和TG状态成年居民HDL-C降低检出率不同,不同年龄、文化程度、家庭人均月收入、地区和TG状态成年居民TC升高检出率不同,不同年龄、文化程度、地区和TG状态成年居民胰岛素抵抗检出率不同,不同性别、年龄、地区、吸烟情况和TG状态成年居民糖尿病检出率不同,不同性别、年龄、文化程度、地区、吸烟情况、饮酒情况和TG状态成年居民高尿酸血症检出率不同,差异均有统计学意义(均P<0.05)。
中国西部地区五城市各种代谢异常状态不同组别成年居民比较,超重肥胖组成年居民薯类和油的日均摄入量均高于非超重肥胖组成年居民(均P<0.05);中心型肥胖组成年居民薯类的日均摄入量均高于非中心型肥胖组成年居民,蔬菜和水果的日均摄入量均低于非中心型肥胖组成年居民(均P<0.05);高血压组成年居民大豆及坚果类的日均摄入量高于非高血压组成年居民,蔬菜的日均摄入量低于非高血压组成年居民(均P<0.05);HDL-C降低组成年居民蔬菜和油的日均摄入量高于非HDL-C降低组成年居民,奶及奶制品的日均摄入量低于非HDL-C降低组成年居民(均P<0.05);TC升高组成年居民蔬菜的日均摄入量低于非TC升高组成年居民(Z= –2.228,P=0.026);糖尿病组成年居民谷类、蔬菜和奶及奶制品的日均摄入量高于非糖尿病组成年居民,水果的日均摄入量低于非糖尿病组成年居民(均P<0.05);高尿酸血症组成年居民奶及奶制品的日均摄入量高于非高尿酸血症组成年居民,大豆及坚果类的日均摄入量低于非高尿酸血症组成年居民(均P<0.05)。
在调整了性别、年龄、文化程度、家庭人均月收入、地区、吸烟情况、饮酒情况、体力活动水平以及谷类、薯类、蔬菜、水果、动物性食物、奶及奶制品、大豆及坚果类、盐、油的日均摄入量等混杂因素后,多因素非条件logistic回归分析结果显示,中国西部地区五城市血清TG边缘升高成年居民超重肥胖(OR=2.70,95%CI=1.80~4.04)、中心型肥胖(OR=1.67,95%CI=1.13~2.48)、高血压(OR=1.71,95%CI=1.15~2.54)、LDL-C升高(OR=3.65,95%CI=2.03~6.59)、TC升高(OR=3.42,95%CI=2.22~5.26)、胰岛素抵抗(OR=2.65,95%CI=1.79~3.90)和高尿酸血症(OR=2.31,95%CI=1.55~3.44)检出率较高;中国西部地区五城市血清TG升高成年居民超重肥胖(OR=4.68,95%CI=2.96~7.40)、中心型肥胖(OR=4.25,95%CI=2.75~6.58)、高血压(OR=1.83,95%CI=1.22~2.74)、LDL-C升高(OR=4.66,95%CI=2.55~8.50)、HDL-C降低(OR=5.85,95%CI=2.59~13.23)、TC升高(OR=6.24,95%CI=3.98~9.79)、胰岛素抵抗(OR=5.22,95%CI=3.47~7.83)、糖尿病(OR=2.30,95%CI=1.50~3.52)和高尿酸血症(OR=6.41,95%CI=4.22~9.73)检出率较高。
本次调查的赤峰市、呼和浩特市、鄂尔多斯市、拉萨市和大理市5个城市位于中国经济相对欠发达的西部地区,近年来国家实施西部大开发战略,旨在提升该区域居民的生活水平,因此其健康状况亦应得到充分重视。本次调查结果显示,上述西部 5 个城市成年居民的 TG 边缘升高率(17.4%)和 TG 升高率(17.6%)均高于 Song P K等[5]2015年中国成人调查报告的 TG 升高患病率(15.0%)以及李倩雨等[20]2024年河北省成人调查结果(14.0%),提示西部地区成年居民 TG 水平可能存在一定的区域差异。此外,LDL-C 升高率为10.0%,亦高于上述报告的7.2%[5]和4.8%[20]。值得注意的是,TC升高比例高达25.2%,明显高于全国水平(5.8%)[5]和河北地区(5.4%)[20];而HDL-C降低比例为8.7%,则明显低于全国水平(24.9%)[5]和河北地区(15.5%)[20]。这一差异可能与我国西部地区特殊的饮食模式相关,Song P K等[5]的研究结果显示,富含奶制品和红肉的膳食模式对BMI正常成人的HDL-C具有保护作用[21]。Zhang J G等[22]的研究结果显示,以畜肉、快餐和奶制品为特征的中国西部膳食可明显增加TG和TC升高的风险。本研究认为,尽管调查人群 LDL-C升高的比例较高,但 HDL-C 水平下降并不明显,同时 TG的升高亦可能导致极低密度蛋白胆固醇(VLDL-C)水平上升[23],从而共同推动 TC 水平的显著上升,因此与全国血脂异常情况存在差异。
Ruiz-García A等[24]2020年在西班牙开展的横断面研究结果显示,与高甘油三酯血症(HTG)相关性最高的因素是TC升高、HDL-C下降、脂肪肝、糖尿病和肥胖,与本研究结果相一致。本研究进一步将TG异常分组发现,所测量的各项代谢指标在不同 TG 水平分组中均表现出随 TG 水平升高而逐步恶化的趋势,与既往研究[25–27]结果相似。值得注意的是,在调整了性别、年龄、文化程度、家庭人均月收入、地区、吸烟情况、饮酒情况、体力活动水平以及谷类、薯类、蔬菜、水果、动物性食物、奶及奶制品、大豆及坚果类、盐、油的日均摄入量等混杂因素后,多种代谢异常的检出率均随血清TG水平的升高呈梯度上升趋势,且多数指标的升幅较为明显。总体来看,TG 正常、TG 边缘升高和 TG 升高人群的代谢异常检出率呈现出逐级递增的分布特征,且TG边缘升高成年居民检出率同样普遍高于TG 正常人群。其中,TG边缘升高成年居民在HDL-C 降低和糖尿病方面的检出率并未显著增加,但其与胰岛素抵抗之间已存在显著关联,提示该阶段可能已处于糖代谢异常的早期阶段。Zhao J等[28]和Guo R B等[29]基于中国成人的研究发现,即使在TG 边缘升高的水平下,个体发生糖尿病的风险亦较正常者明显增加,而高TG人群的风险更为突出,说明 TG 水平的轻度上升阶段即可能是代谢紊乱的早期信号。相较之下,TG 升高人群在所有代谢异常状态中均表现出显著且幅度较大的检出率升高,进一步强调了持续 TG 升高对整体代谢健康的不利影响。该结果提示,即使尚未达到 TG 明显升高的临床诊断标准,TG 边缘升高阶段已与多种代谢异常存在显著关联,该阶段往往处于代谢紊乱发展早期,具有一定的可逆性和干预窗口。因此,及时发现并管理 TG 边缘升高个体,有助于阻断或延缓代谢综合征的发生发展[16, 30]。
综上所述,中国西部地区五城市成年居民血清TG升高与超重肥胖、中心型肥胖、高血压、LDL-C升高、HDL-C降低、TC升高、胰岛素抵抗、糖尿病和高尿酸血症等多种代谢异常状态均呈正相关。值得注意的是,TG 水平与上述代谢异常之间普遍存在显著的梯度关联,提示TG水平可能在代谢综合征的发生发展中发挥关键作用,因此针对 TG 异常的早期识别与干预具有重要的公共卫生意义。一方面,TG 水平升高往往在临床早期阶段即出现,是代谢异常的敏感预警指标[31–32];另一方面,早期TG的升高具有一定的可逆性[30],生活方式的干预,如控制体重、改善膳食结构、规律运动及限制酒精摄入在降低 TG 水平方面均被大量研究证实有效[16, 33–36]。需要强调的是,代谢综合征往往表现为多指标、多系统的协同失衡状态,干预 TG 升高不仅有助于控制血脂水平,也对控制血糖、血压、体重和高尿酸血症等具有协同益处[37]。对于我国西部地区人群,应加强血脂筛查、健康宣教和个体化管理,推动从“被动治疗”向“主动预防”转变,从源头上延缓乃至阻断代谢综合征的发生发展。因此,将 TG 管理纳入慢性病综合防控体系,对于提升整体人群的代谢健康水平、减轻慢性病负担,具有重要的现实意义和长期价值。但本研究仍存在一定的局限性:首先,由于横断面研究的固有限制,结果仅能提示TG异常与多种代谢异常状态之间的关联性,无法明确其因果关系;其次,部分变量如慢性病病史和膳食摄入等均来源于调查对象自我报告,可能受到回忆偏倚和报告偏倚的影响,存在一定信息偏倚;再次,尽管模型已调整了多项混杂因素,但仍无法完全排除其他潜在混杂因素如家族遗传背景和药物使用等对结果的干扰;最后,本研究样本来源于中国西部5个城市的成年居民,每个城市仅抽取1个社区进行调查,样本代表性相对有限且存在一定地域局限性,研究结论的外推应谨慎。因此,未来仍需开展更大样本、具有纵向随访设计的研究进一步验证相关结果。

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2026年第42卷第5期
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doi: 10.11847/zgggws1148607
  • 接收时间:2025-08-06
  • 首发时间:2026-10-23
  • 出版时间:2026-05-10
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  • 收稿日期:2025-08-06
  • 修回日期:2025-11-17
  • 录用日期:2026-03-11
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    1北京大学公共卫生学院营养与食品卫生学系,北京 100191
    2国家食品安全风险评估中心,北京 100022
    3佳木斯市中心医院,佳木斯 154002
    4内蒙古乳业技术研究院有限责任公司,呼和浩特 010110
    5国家乳业技术创新中心,呼和浩特 010000
    6北京大学护理学院,北京 100191

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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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