# Determining Insulin Resistance Cutoffs in Mexican Adults: Percentile Distribution vs. Receiver Operating Characteristic Curve Analysis

## TL;DR

This study compares two methods for determining insulin resistance cutoffs in Mexican adults, finding that percentile-based analysis identifies at-risk individuals earlier than ROC curve analysis.

## Contribution

The study provides population-specific HOMA-IR cutoffs for Mexican adults using percentile distribution and ROC curve analysis.

## Key findings

- Percentile-based cutoffs identified insulin resistance earlier than ROC analysis in preclinical stages.
- ROC curve analysis produced higher HOMA-IR cutoff values for diagnosing metabolic syndrome.
- The 75th and 90th HOMA-IR percentiles in the reference group were 2.72 and 3.71, respectively.

## Abstract

Introduction

Insulin resistance (IR) plays a key role in the development of metabolic syndrome (MetS), type 2 diabetes, and cardiovascular disease. The Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) is widely used to estimate IR, but there is no consensus on the optimal cutoff values for identifying individuals at risk. This study aims to compare two methodologies, percentile distributions and receiver operating characteristic (ROC) curve analysis, for determining optimal HOMA-IR cutoff values in a population from Mexico City.

Methods

This cross-sectional study included 765 adults recruited from a hospital outpatient clinic in Mexico City. Participants were divided into two groups: a reference group of individuals with healthy weight and fasting plasma glucose and a MetS group of overweight or obese individuals classified based on the presence or absence of MetS. HOMA-IR values were analyzed using the 75th percentile in the reference group and ROC curve analysis in the MetS group. Optimal cutoffs were determined using the Youden index.

Results

We include a total of 765 patients, 218 subjects in the reference group and 547 for the ROC curve analysis. HOMA-IR percentiles 75th and 90th were 2.72 and 3.71, respectively. ROC curve analysis yielded higher cutoff values for MetS diagnosis than the percentile-based method. The percentile-based approach allowed for earlier identification of individuals at risk, including those without clinical manifestations of MetS.

Conclusions

This study highlights the variability in HOMA-IR cutoff values across methodologies and emphasizes the importance of population-specific reference values. A percentile-based approach proves effective for early detection of IR, facilitating preventive interventions during the preclinical stage. These findings support using percentile-based cutoffs as a practical tool for improving risk assessment and guiding clinical decision-making.