Comprehensive Cross-Sectional Study of the Triglyceride Glucose Index, Organophosphate Pesticide Exposure, and Cardiovascular Diseases: A Machine Learning Integrated Approach.

ABSTRACT: Using NHANES data from 2003 to 2008, 2011 to 2012, and 2015 to 2020, we examined the relationship between urinary organophosphate pesticide (OPP) metabolites and the triglyceride glucose (TyG) index. The TyG index evaluates insulin resistance, a crucial factor in metabolic diseases. Linear regression analyzed urinary metabolites in relation to the TyG index and OPPs. An RCS (restricted cubic spline) model explored the nonlinear relationship of a single OPP metabolite to TyG. A weighted quantile regression and quantile-based g-computation assessed the impact of combined OPP exposure on the TyG index. XGBoost, Random Forest, Support Vector Machines, logistic regression, and SHapley Additive exPlanations models investigated the impact of OPPs on the TyG index and cardiovascular disease. Netwo

SUBMITTER: Wang X 

PROVIDER: S-EPMC11860532 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature