Abstract
Challenges arise in researching health effects associated with chemical mixtures. Several methods have recently been proposed for estimating the association between health outcomes and exposure to chemical mixtures, but a formal simulation study comparing broad-ranging methods is lacking. We select five recently developed methods and evaluate their performance in estimating the exposure-response function, identifying active mixture components, and identifying interactions in a simulation study. Bayesian kernel machine regression (BKMR) and nonparametric Bayes shrinkage (NPB) were top-performing methods in our simulation study. BKMR and NPB outperformed other contemporary methods and traditional linear models in estimating the exposure-response function and identifying active mixture components. BKMR and NPB produced similar results in a data analysis of the effects of multipollutant exposure on lung function in children with asthma.
Highlights
Individuals are continuously exposed to complex mixtures of environmental chemicals
Interest is rapidly growing in estimating the association between exposure to mixtures of environmental chemicals and health outcomes
New statistical approaches have been developed for studying health outcomes associated with exposure to mixtures
Summary
Individuals are continuously exposed to complex mixtures of environmental chemicals. Mounting evidence from epidemiological studies links environmental exposures to increased morbidity and mortality [1,2,3,4,5]. Traditional epidemiological studies have focused on a single pollutant and additive models with a small number of exposures; studying pollutants in isolation can lead to biased estimates [6, 7] and does not reflect the reality that people are jointly exposed to mixtures of pollutants. Interest is rapidly growing in studying health outcomes associated with simultaneous exposure to mixtures of pollutants [8, 9]. The National Institute for Environmental Health Sciences (NIEHS) identified the study of mixtures as a goal in its 2012-2017 strategic plan while noting that this will require novel quantitative approaches [10]. There is a need to identify the most appropriate statistical methods currently available for estimating health outcomes associated with exposure to mixtures [11, 12]
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