Machine learning for predicting metabolic-associated fatty liver disease including NHHR: a cross-sectional NHANES study.

ABSTRACT:

Objective

Metabolic - associated fatty liver disease (MAFLD) is a common hepatic disorder with increasing prevalence, and early detection remains inadequately achieved. This study aims to explore the relationship between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and MAFLD, and to establish a predictive model for MAFLD using NHHR as a key variable.

Methods

All participants were selected from the NHANES cohort, spanning from 2017 to March 2020. Multiple linear regression models were employed to examine the relationship between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and the controlled attenuation parameter (CAP). To explore the non-linear association between NHHR a

SUBMITTER: Lin L 

PROVIDER: S-EPMC11918377 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature