Context Insulin resistance (IR) can progress to type 2 diabetes. Therefore, timely
identification of IR could facilitate disease prevention efforts. However, direct measurement …

To determine and formally compare the ability of simple indexes of insulin resistance (IR) to
predict type 2 diabetes, we used combined prospective data from the San Antonio Heart …

Background and purpose To investigate the clustering of insulin resistance syndrome with
hyperinsulinemia, hypertriglyceridemia, low high-density lipoprotein (HDL) cholesterol …

Objective: In our previous study, multivariate analysis showed that body mass index (BMI),
triglycerides (TG) levels, and systolic blood pressure (SBP), in addition to fasting plasma …

Objectives This study describes an unsupervised machine learning approach used to
estimate the homeostatic model assessment-insulin resistance (HOMA-IR) cut-off for …

Insulin resistance is highly prevalent in Asian Indians and contributes to worldwide public
health problems, including diabetes and related disorders. Surrogate measurements of …

Objective The aim of this study was to describe the minimum number of anthropometric
measures that will optimally predict insulin resistance (IR) and to characterize the utility of …

Background There were seven novel and easily accessed insulin resistance (IR) surrogates
established, including the Chinese visceral adiposity index (CVAI), the visceral adiposity …

Objective To determine whether insulin resistance (IR) measured by homeostasis model of
insulin resistance (HOMA-IR) can further stratify diabetes risk in African Americans (AAs) …

Objective The current methods available for determining insulin resistance are complicated;
hence, they are only applicable to small-scale studies. Therefore, this study aimed to classify …