{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T15:21:00Z","timestamp":1778599260213,"version":"3.51.4"},"reference-count":43,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2018,2,9]],"date-time":"2018-02-09T00:00:00Z","timestamp":1518134400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81373074"],"award-info":[{"award-number":["81373074"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81402752"],"award-info":[{"award-number":["81402752"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81673260"],"award-info":[{"award-number":["81673260"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Diabetes"],"published-print":{"date-parts":[[2018,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Inexpensive and easily measured indices are needed for the early prediction of type 2 diabetes mellitus (T2DM) in rural areas of China. The aim of this study was to compare triglyceride glucose (TyG), visceral adiposity (VAI), and lipid accumulation product (LAP) with traditional individual measures and their ratios for predicting T2DM.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Data for 11\u2009113 people with baseline normal fasting glucose in a rural Chinese cohort were followed for a median of 6.0\u2009years. Cox proportional hazards regression was used to calculate covariate\u2010adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs) and receiver operating characteristic analysis was used to compare the ability of traditional measures and TyG, VAI, and LAP at baseline to predict T2DM at follow\u2010up.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Among individual measures, fasting plasma glucose (FPG) and waist circumference (WC) were strongly associated with T2DM. Of all lipid ratios, an elevated triglycerides (TG) to high\u2010density lipoprotein cholesterol (HDL\u2010C) ratio was associated the most with T2DM. Compared with the first quartiles of TyG, VAI, and LAP, their fourth quartiles were associated with T2DM for men (aHR 3.54 [95% CI 2.08\u20136.03], 2.89 [1.72\u20134.87], and 5.02 [2.85\u20138.85], respectively) and women (6.15 [3.48\u201310.85], 4.40 [2.61\u20137.42], and 6.49 [3.48\u201312.12], respectively). For predicting T2DM risk, TyG, VAI, and LAP were mostly superior to the TG:\u2009\u2009HDL\u2010C ratio, but did not differ from FPG and WC.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Prediction of T2DM was not improved by TyG, VAI, and LAP versus FPG or WC alone. Therefore, TyG, VAI, and LAP may not be inexpensive tools for predicting T2DM in rural Chinese people.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1753-0407.12642","type":"journal-article","created":{"date-parts":[[2018,1,11]],"date-time":"2018-01-11T07:13:00Z","timestamp":1515654780000},"page":"641-652","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Utility of three novel insulin resistance\u2010related lipid indices for predicting type 2 diabetes mellitus among people with normal fasting glucose in rural China"],"prefix":"10.1111","volume":"10","author":[{"given":"Bingyuan","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Health Statistics College of Public Health, Zhengzhou University  Zhengzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Preventive Medicine 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