Dataset Information

Association between insulin resistance and metabolic syndrome risk factors in Japanese.

ABSTRACT:

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Aims/Introduction:? It is important to identify individuals at risk of metabolic syndrome (MetS), namely those with insulin resistance. Therefore, the aim of the present study was to find anthropometric and metabolic parameters that can better predict insulin resistance.

Subjects and methods

? We selected 3899 individuals (2058 men and 1841 women), excluding those with fasting plasma glucose (FPG) ?126?mg/dL, on medication for hypertension, dyslipidemia or diabetes, and those with a history of advanced macrovascular disease. Using multivariate analyses, we selected components for obesity, lipids, and blood pressure based on the strength of their association with the homeostasis model assessment of insulin resistance (HOMA-IR).

Results

? In multiple linear regression analysis, body mass index (BMI), waist circumference (WC), triglycerides (TG), high-density lipoprotein-cholesterol (HDL-C), and systolic blood pressure (SBP) were selected in men and women, and the effect of BMI on HOMA-IR outweighed that of WC. In multiple logistic regression analysis, BMI, TG, and SBP were significantly associated with HOMA-IR ?2.5 in both genders, but WC and HDL-C were only selected in men. Combinations of BMI, TG, SBP, and FPG showed higher HOMA-IR values than those of the existing MetS components, considered useful for the identification of individual with higher insulin resistance.

Conclusions

? Body mass index, TG and SBP were selected as components significantly related to insulin resistance. The selected components were fundamentally adherent to the existing MetS criteria, the only difference being the measure of obesity, in which a stronger association with insulin resistance was observed for BMI than WC. (J Diabetes Invest, doi: 10.1111/j.2040-1124.2011.00162.x, 2011).

SUBMITTER: Yamada C

PROVIDER: S-EPMC4020738 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Publications

Association between insulin resistance and metabolic syndrome risk factors in Japanese.

Yamada Chizumi C Moriyama Kengo K Takahashi Eiko E

Journal of diabetes investigation 20120301 2

<h4>Unlabelled</h4>Aims/Introduction: It is important to identify individuals at risk of metabolic syndrome (MetS), namely those with insulin resistance. Therefore, the aim of the present study was to find anthropometric and metabolic parameters that can better predict insulin resistance.<h4>Subjects and methods</h4> We selected 3899 individuals (2058 men and 1841 women), excluding those with fasting plasma glucose (FPG) ≥126 mg/dL, on medication for hypertension, dyslipidemia or diabetes, and ...[more]

PMID: 24843564

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Project description:BackgroundTo investigate the association of four insulin resistance (IR) indicators with hepatic steatosis and fibrosis in patients with metabolic syndrome (MetS), as well as to compare the diagnostic value of these indicators in identifying hepatic steatosis and fibrosis in individuals with MetS.MethodsThis cross-sectional study used the data from the National Health and Nutrition Examination Survey 2017-2018. IR indicators included homeostasis model assessment of IR (HOMA-IR), triglyceride/glucose (TyG) index, triglyceride glucose-waist-to-height ratio (TyG-WHtR), and metabolic score for IR (METS-IR). The main endpoints of this study were hepatic steatosis and hepatic fibrosis. Weighted univariate and multivariate logistic regression models were employed to evaluate the association between four IR indicators and both hepatic steatosis, hepatic fibrosis. The efficacy of various IR indicators in the detection of hepatic steatosis and hepatic fibrosis were assessed using receiver operating characteristics curve (ROC).ResultsA total of 876 participants with MetS were enrolled. Among the participants, hepatic steatosis was observed in 587 MetS individuals, while hepatic fibrosis was identified in 151 MetS individuals. In multivariate logistic regression model, HOMA-IR, TyG, TyG-WHtR, and METS-IR were related to the increased odd of hepatic steatosis. Additionally, HOMA-IR, TyG-WHtR, and METS-IR were associated with increased odd of hepatic fibrosis. According to the ROC analysis, the area under the curve (AUC) of the TyG-WHtR (AUC = 0.705, 95%CI: 0.668-0.743) was higher than HOMA-IR (AUC = 0.693, 95%CI: 0.656-0.730), TyG (AUC = 0.627, 95%CI: 0.587-0.666), and METS-IR (AUC = 0.685, 95%CI: 0.648-0.722) for identifying hepatic steatosis of MetS patients. Likewise, TyG-WHtR was also higher than HOMA-IR, TyG, and METS-IR for identifying hepatic fibrosis of MetS patients.ConclusionHOMA-IR, TyG-WHtR, and METS-IR may be associated with the risk of hepatic steatosis and fibrosis among the U.S. adult population with MetS. In addition, TyG-WHtR may have a good predictive value for hepatic steatosis and hepatic fibrosis.

Dataset Information

Association between insulin resistance and metabolic syndrome risk factors in Japanese.

Unlabelled

Subjects and methods

Results

Conclusions

Publications

Association between insulin resistance and metabolic syndrome risk factors in Japanese.

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