Explainable machine learning-driven models for predicting Parkinson's disease and its prognosis: obesity patterns associations and models development using NHANES 1999-2018 data.

ABSTRACT:

Background

Parkinson's disease (PD) is a prevalent neurodegenerative condition, the effect of obesity on PD remains controversial. We aimed to investigate the associations of obesity patterns on PD and all-cause mortality, while developing machine learning (ML)-driven predictive and prognostic models for PD.

Methods

Fifty-one thousand, three hundred ninety-four adults from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 were classified into four obesity patterns via body mass index (BMI) and waist circumference (WC). Associations of obesity patterns with PD risk and all-cause mortality were evaluated via multivariable logistic and Cox proportional hazards regression across three adjusted models. Subgroup, sensitivity, and restricted cubic spline (RCS)

SUBMITTER: Fan J 

PROVIDER: S-EPMC12273281 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature