Predicting the 10-year incidence of dyslipidemia based on novel anthropometric indices, using data mining.

ABSTRACT:

Background

The aim was to establish a 10-year dyslipidemia incidence model, investigating novel anthropometric indices using exploratory regression and data mining.

Methods

This data mining study was conducted on people who were diagnosed with dyslipidemia in phase 2 (n = 1097) of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study, who were compared with healthy people in this phase (n = 679). The association of dyslipidemia with several novel anthropometric indices including Conicity Index (C-Index), Body Roundness Index (BRI), Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP), Abdominal Volume Index (AVI), Weight-Adjusted-Waist Index (WWI), A Body Shape Index (ABSI), Body Mass Index (BMI), Body Adiposity Index (BAI) and Body Surface Area (B

SUBMITTER: Takhttavous A 

PROVIDER: S-EPMC10829243 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature