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Background: Visceral adiposity index (VAI) has been recognized as a reliable indicator for visceral adiposity. However, it remains largely unexplored on its association with fasting plasma glucose (FPG). The current study aims to explore the association between VAI and FPG using a representative dataset. Methods: A cross-sectional study was carried out based on the dataset from National Health and Nutrition Examination Survey (NHANES) 2017–2020. Univariate and Multiple linear regression analysis were performed to explore the relationship between VAI and FPG. Generalized additive model (GAM) and smooth curve fitting analysis were performed to explore the nonlinear relationship between VAI and FPG. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of VAI for FPG elevation. Results: A total of 4437 participants with complete data were finally included in the research. Individuals were divided into 4 quartiles according to the calculated VAI value: Q1 (VAI<0.69), Q2 (0.69 ≤ VAI < 1.18), Q3 (1.18 ≤ VAI < 2.02) and Q4 (VAI ≥ 2.02). FPG significantly increased with the increasing VAI quartile. Multiple linear regression analysis showed VAI was independently positively associated with FPG after adjusting confounding factors. As a continuous variable, an increase of one unit in VAI was correlated with 0.52 mmol/L (95% CI: 0.41–0.63, p < 0.0001) higher FPG level. As a categorical variable, 4th VAI quartile group was related to 0.71 mmol/L (95% CI: 0.47–0.95, p < 0.001) higher FPG level compared with 1st VAI group. GAM and smooth curve fitting analysis identified the non-linear relationship between VAI and FPG, and 4.02 was identified as the inflection point using two-piecewise linear regression. The positive association between VAI and FPG existed when VAI was lower (β = 0.73, p < 0.0001) and higher than 4.02 (β = 0.23, p = 0.0063). ROC analysis indicated VAI has a good predictive value for FPG elevation (AUC = 0.7169, 95% CI: 0.6948–0.7389), and the best threshold of VAI was 1.4315. Conclusion: VAI was an independently risk indicator for FPG, and VAI was nonlinearly positively associated with FPG. VAI had a good predictive value for elevated FPG. VAI might become a useful indicator for risk assessment and treatment of hyperglycemia in clinical practice. [ABSTRACT FROM AUTHOR]

Objective. To examine the relationship between admission random blood glucose (RBG), fasting blood glucose (FBG), and Gensini score in patients with acute myocardial infarction (AMI) to clarify the effects of RBG and FBG on the severity of coronary artery disease. Method. A total of 958 consecutive AMI patients who underwent emergency coronary angiography at the Cardiology Department of Zhongda Hospital (affiliated with Southeast University) were enrolled in this study from January 1, 2016, to December 31, 2018. The Gensini score of each patient was calculated according to the results of coronary angiography. The RBG, FBG, baseline data, hematological indexes, echocardiography parameters, coronary angiography data, and the use of intra-aortic balloon pump (IABP) were recorded. Patients with an RBG level >11.1 mmol/L were classified into the stress hyperglycemia group, and those with an FBG level >7.0 mmol/L were classified into the elevated FBG group. The Gensini scores in the stress hyperglycemia and elevated FBG groups were compared to those in the control group, and correlations between the RBG and FBG levels and the Gensini scores of AMI patients were evaluated. Independent risk factors for the Gensini score were analyzed by multiple linear and multiple logistic regression analyses. Results. The Gensini scores of the stress hyperglycemia group and the elevated FBG group were higher than those of the control group. RBG and FBG were positively correlated with the Gensini score, and there were significant differences between RBG and FBG in different Gensini score groups. After adjusting for confounding factors, multiple linear regression analysis showed that sex, diabetes, estimated glomerular filtration rate (eGFR), and FBG were independent risk factors for the Gensini score. Multiple logistic regression analysis showed that age and FBG were independent risk factors in group 2 compared to group 1, eGFR and FBG were independent risk factors in group 3, and eGFR and FBG were independent risk factors in group 4. Diabetes and RBG were not independent risk factors for the Gensini score. Conclusion. The Gensini scores of patients in the stress hyperglycemia group and the elevated FBG group were significantly higher than those in the control group. RBG and FBG were positively correlated with the Gensini score in AMI patients, and FBG was an independent risk factor for the Gensini score in AMI patients. [ABSTRACT FROM AUTHOR]