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Background:

In recent decades, with the development of the global economy and the improvement of living standards, insulin resistance (IR) has become a common phenomenon. Current studies have shown that IR varies between races. Therefore, it is necessary to develop individual prediction models for each country. The purpose of this study was to develop a predictive model of IR applicable to the US population.

Method:

11 cycles of data from the NHANES database were selected for this study. Of these, participants from 1999 to 2010 (n= 14931) were used to establish the model, and participants from 2011 to 2020 (n= 13646) were used to validate the model. Univariate and multivariate logistic regression were used to analyze the factors associated with IR. Optimal subset regression was used to filter the best modeling variables. ROC curves, calibration curves, and decision curve analysis …