Data mining approaches for type 2 diabetes mellitus prediction using anthropometric measurements.

ABSTRACT:

Background

The aim of this study was to evaluate the anthropometric measurements most associated with type 2 diabetes mellitus (T2DM) using machine learning approaches.

Methods

A prospective study was designed for a total population of 9354 (43% men and 57% women) aged 35-65. Anthropometric measurements include weight, height, demispan, Hip Circumference (HC), Mid-arm Circumference (MAC), Waist Circumference (WC), Body Roundness Index (BRI), Body Adiposity Index (BAI), A Body Shape Index (ABSI), Body Mass Index (BMI), Waist-to-height Ratio (WHtR), and Waist-to-hip Ratio (WHR) were completed for all participants. The association was assessed using logistic regression (LR) and decision tree (DT) analysis. Receiver operating characteristic (ROC) curve was performed to evaluate

SUBMITTER: Saberi-Karimian M 

PROVIDER: S-EPMC9833979 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature