Biomarkers and Data Visualization of Insulin Resistance and Metabolic Syndrome: An Applicable Approach

Abstract

Type 2 diabetes, prediabetes, and insulin resistance (IR) are widespread yet often undetected in their early stages, contributing to a silent epidemic. Metabolic Syndrome (MetS) is also highly prevalent, increasing the chronic disease burden. Annual check-ups are inadequate for early detection due to conventional result formats that lack specific markers and comprehensive visualization. The aim of this study was to evaluate low-budget biochemical and hematological parameters, with data visualization, for identifying IR and MetS in a community-based laboratory. In a cross-sectional study with 1870 participants in Patras, Greece, blood samples were analyzed for key cardiovascular and inflammatory markers. IR diagnostic markers (TyG-Index, TyG-BMI, Triglycerides/HDL ratio, NLR) were compared with HOMA-IR. Innovative data visualization techniques were used to present metabolic profiles. Notable differences in parameters of cardiovascular risk and inflammation were observed between normal-weight and obese people, highlighting BMI as a significant risk factor. Also, the inflammation marker NHR (Neutrophils to HDL-Cholesterol Ratio) Index was successful at distinguishing the obese individuals and those with MetS from normal individuals. Additionally, a new diagnostic index of IR, combining BMI (Body Mass Index) and NHR Index, demonstrated better performance than other well-known indices. Lastly, data visualization significantly helped individuals understand their metabolic health patterns more clearly. BMI and NHR Index could play an essential role in assessing metabolic health patterns. Integrating specific markers and data visualization in routine check-ups enhances the early detection of IR and MetS, aiding in better patient awareness and adherence.

Keywords

• insulin resistance
• metabolic syndrome
• BMI categorization
• NHR Index
• data visualization