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Chemical mixture exposure patterns and obesity among U.S. adults in NHANES 2005–2012 by Yuqing Zhang; Xu Wang; Xu Yang; Qi Hu; Kuldeep Chawla; Bo Hang; Jian-Hua Mao; Antoine M. Snijders; Hang Chang; Yankai Xia is a Environmental Science article available to read on EtoBox.

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## Background: The effect of chemical exposure on obesity has raised great concerns. Real-world chemical exposure always imposes mixture impacts, however their exposure patterns and the corresponding associations with obesity have not been fully evaluated. ## Objectives: To discover obesity-related mixed chemical exposure patterns in the general U.S. population. ## Methods: Sparse Decompositional Regression (SDR), a model adapted from sparse representation learning technique, was developed to identify exposure patterns of chemical mixtures with exclusion (non-targeted model) and inclusion (targeted model) of health outcomes. We assessed the relationships between the identified chemical mixture patterns and obesity-related indexes. We also conducted a comprehensive evaluation of this SDR model by comparing to the existing models, including generalized linear regression model (GLM), principal component analysis (PCA), and Bayesian kernel machine regression (BKMR). ## Results: Eight core exposure patterns were identified using the non-targeted SDR model. Patterns of high levels of MEP, high levels of naphthalene metabolites (EOH-Nap), and a pattern of high exposure levels of MCOP, MCN

Who reads Chemical mixture exposure patterns and obesity among U.S. adults in NHANES 2005–2012?

Author

Yuqing Zhang; Xu Wang; Xu Yang; Qi Hu; Kuldeep Chawla; Bo Hang; Jian-Hua Mao; Antoine M. Snijders; Hang Chang; Yankai Xia

Publisher

Elsevier BV

Published

2022

Language

EN

Field

Environmental Science (Physical Sciences)