scholarly journals Triglycerides to High-Density Lipoprotein Cholesterol Ratio Is the Best Surrogate Marker for Insulin Resistance in Nonobese Middle-Aged and Elderly Population: A Cross-Sectional Study

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yumei Yang ◽  
Baomin Wang ◽  
Haoyue Yuan ◽  
Xiaomu Li
Keyword(s):  
Insulin Resistance ◽  
High Density Lipoprotein ◽  
High Density Lipoprotein Cholesterol ◽  
Chinese Population ◽  
Density Lipoprotein ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Middle Aged ◽  
Cross Sectional ◽  
Elderly Chinese

Objective. Insulin resistance (IR) is closely associated with metabolic profiles, including obesity and dyslipidemia. The aim of the present study was to examine how lipid profiles were associated with IR in nonobese middle-aged and elderly Chinese population. Methods. This cross-sectional study included 1608 subjects. IR was defined by homeostasis model assessment of insulin resistance (HOMA-IR) of at least 2.5. Results. In nonobese subjects (body mass index (BMI) < 25 kg/m2, n = 996), triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio (odds ratio (OR) = 1.43, 95% confidence interval (CI) 1.13–1.81, P = 0.003 ) was an independent risk factor for IR. The best marker for predicting IR in nonobese subjects was TG/HDL-C ratio with the areas under the receiver operating characteristic curves (AUC) of 0.73 ( P < 0.001 ). The optimal cut-off point to identifying IR for TG/HDL-C ratio was ≥1.50 in the nonobese population. Other markers like BMI, TG, and total cholesterol (TC)/HDL-C also had acceptable discriminatory power for predicting IR in nonobese population (AUC ≥ 0.7 and P < 0.001 ). BMI had the highest AUC of 0.647 ( P < 0.001 ) after being adjusted, but it was not effective enough to predict IR in obese subjects (BMI ≥ 25.0, n = 612). Conclusions. The TG/HDL-C ratio may be the best reliable marker for predicting IR in the nonobese middle-aged and elderly Chinese population.

scholarly journals Triglycerides to High-density Lipoprotein Cholesterol Ratio is the Best Surrogate Marker for Insulin Resistance in Non-obese Middle-aged and Elderly Population: A Cross-sectional Study

2020 ◽  
Author(s):  
Yumei Yang ◽  
Baomin Wang ◽  
Haoyue Yuan ◽  
Xiaomu Li
Keyword(s):  
Insulin Resistance ◽  
High Density Lipoprotein ◽  
High Density Lipoprotein Cholesterol ◽  
Density Lipoprotein ◽  
Cross Sectional Study ◽  
High Density ◽  
Lipoprotein Cholesterol ◽  
Sectional Study ◽  
Cross Sectional ◽  
Obese Subjects

Abstract BackgroundInsulin resistance is closely associated with metabolic profiles, including obesity and dyslipidemia. However, there are few studies to demonstrate a relationship between lipid profiles and insulin resistance, categorized by BMI, especially in Chinese. The aim of the present study was to examine how lipid profiles were associated with insulin resistance in non-obese middle-aged and elderly Chinese population.MethodsThis cross-sectional study included 1608 (596 men and 1012 women) subjects, without prior known diabetes mellitus and lipid regulating therapy history, older than 45 years. Insulin resistance was defined by homeostasis model assessment of insulin resistance (HOMA-IR) of at least 2.5. The areas under the curve of the receiver operating characteristic curves (AROC) were used to compare the power of these serum markers. SPSS 17.0 software was used for the statistical analysis.ResultsIn non-obese subjects (BMI < 25 kg/m2, n= 996), triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio (OR = 1.43, 95% CI 1.13-1.81, P = 0.003), and SBP (OR = 1.01, 95% CI 1.00-1.02, P = 0.03) were independently risk factors for the insulin resistance. The best marker for insulin resistance in non-obese subjects was triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio with the AROC of 0.73 (95% CI 0.68-0.77, P < 0.001), and the positive likelihood ratio was greatest for TG/HDL-C ratio in the metabolic profiles including BMI. The optimal cut-off point to identifying insulin resistance for TG/HDL-C ratio was ≥ 1.50 in the non-obese population. The BMI, TG, total cholesterol (TC)/HDL-C ratio and HDL-C also discriminated insulin resistance, as the values for AROC were 0.70 (95% CI 0.66-0.75, P < 0.001), 0.71 (95% CI 0.67-0.76, P < 0.001), 0.70 (95% CI 0.65-0.74, P < 0.001), 0.34 (95% CI 0.29-0.38, P < 0.001), respectively. In overweight subjects (BMI ≥ 25.0 kg/m2, n = 612), BMI was still the best marker for insulin resistance with the AROC of 0.65 (95% CI 0.60-0.69, P < 0.001). ConclusionsTG/HDL-C ratio may be the best reliable marker for insulin resistance in the non-obese population.

Comparison of the Diagnostic Value Between Triglyceride-Glucose Index and Triglyceride-to-High Density Lipoprotein Cholesterol Ratio in MAFLD Patients: A Retrospective Cross-Sectional Study

2022 ◽  
Author(s):  
Zhi Liu ◽  
He He ◽  
Yuzhao Dai ◽  
Shenling Liao ◽  
Zhenmei An ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Density Lipoprotein ◽  
High Density Lipoprotein Cholesterol ◽  
Density Lipoprotein ◽  
Cross Sectional Study ◽  
High Density ◽  
Lipoprotein Cholesterol ◽  
Sectional Study ◽  
Cross Sectional ◽  
Cholesterol Ratio

Abstract Background The triglyceride and glucose index (TyG) and triglyceride-to-high density lipoprotein cholesterol ratio (TG/HDL-C) were found to be substitute markers of insulin resistance (IR). We aimed to compare the efficacy of the two indicators in the diagnosis of Metabolic-Associated Fatty Liver Disease (MAFLD), which was rarely covered in the literature, and to construct a novel disease diagnosis model.Methods A retrospective cross-sectional study was carried out in West China Hospital of Sichuan University and 229 people (97 MAFLD and 132 Non-MAFLD) were included. Biochemical indexes were collected and analyzed by logistic regression to screen out indicators that expressed differently in MAFLD patients and healthy controls and incorporate them into a diagnostic model. MAFLD was diagnosed by Ultrasound.Results After adjusting for age, gender and BMI, Serum ALT, AST, AST/ALT (A/A), FPG, Cys-C, URIC, TG, HDL-C, ALP, GGT, nonHDL-C, LDL-C/HDL-C, nonHDL-C/HDL-C, TG/HDL-C, TC/HDL-C, TyG and TyG-BMI were risk factors of MAFLD through binary logistics regression analysis. The odds ratio of TG/HDL-C and TyG were 5.387 (95%CI: 2.986-9,718) and 107.945 (95% CI: 25.824-451.222). In identifying MAFLD, TyG, TG/HDL-C and TG were found to be the most vital indexes by the random forest method and the area under the curve (AUC) of them are all greater than 0.9 respectively. In addition, the combination of gender, BMI, ALT, TG, HDL-C, TyG and TyG-BMI had a great diagnostic efficiency for MAFLD.Conclusions TyG and TG/HDL-C were potential risk factors for MAFLD and the former made a better performance in diagnosing MAFLD. The combination of gender, BMI, ALT, TG, HDL-C, TyG and TyG-BMI improved the diagnostic capability of MAFLD.

scholarly journals Associations of Sitting Behavior Patterns With Cardiometabolic Risk in Children: The Sit Less for Health Cross-Sectional Study

2019 ◽  
Vol 16 (10) ◽  
pp. 836-842
Author(s):  
Stephanie L. Stockwell ◽  
Lindsey R. Smith ◽  
Hannah M. Weaver ◽  
Daniella J. Hankins ◽  
Daniel P. Bailey
Keyword(s):  
High Density Lipoprotein ◽  
High Density Lipoprotein Cholesterol ◽  
Cardiometabolic Risk ◽  
Density Lipoprotein ◽  
Cross Sectional Study ◽  
High Density ◽  
Lipoprotein Cholesterol ◽  
Sectional Study ◽  
Cross Sectional ◽  
Negatively Associated

Background: The objective of this study was to investigate the associations between sedentary behavior patterns and cardiometabolic risk in children using a monitor that accurately distinguishes between different postures. Methods: In this cross-sectional study, 118 children (67 girls) aged 11–12 years had adiposity, blood pressure, lipids, and glucose measured, and then they wore an activPAL device to record sitting, standing, and stepping for 7 consecutive days. Data were analyzed using multiple linear regression. Results: After adjustment for potential confounders and moderate to vigorous physical activity, the number of breaks in sitting was significantly negatively associated with adiposity (standardized β ≥ −0.546; P ≤ .001) and significantly positively associated with high-density lipoprotein cholesterol (β = 0.415; P ≤ .01). Time in prolonged sitting bouts was significantly negatively associated with adiposity (β ≥ −0.577; P ≤ .001) and significantly positively associated with high-density lipoprotein cholesterol (β = 0.432; P ≤ .05). Standing time was significantly negatively associated with adiposity (β ≥ −0.270; P ≤ .05) and significantly positively associated with high-density lipoprotein cholesterol (β = 0.312; P ≤ .05). Conclusions: This study suggests that increasing the number of breaks in sitting and increasing standing time are beneficially associated with cardiometabolic risk and should be considered in health promotion interventions in children.

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