New Methods for Evaluating Effects of Exposure to Environmental Complex Mixtures on Human Health

Dear Colleagues,

Humans are rarely exposed to a single agent; rather, they experience concurrent, time-varying mixtures spanning air pollutants, metals, pharmaceuticals/biocides, PFAS, nanomaterials, micro- and mesoplastics, noise, heat, and built-environment features. This Special Issue focuses on new methods, models, or approaches to treat data and evaluate the health risk of exposure to these different agents. Studies that provide clear implications for decision making across the human life course are also welcomed. We consider methodological advances in (1) risk assessment and inference methods with interaction (synergy/antagonism), (2) featured exposure–response modeling such as high-dimensional inference regarding Bayesian Kernel Machine Regression, g-computation, etc., and (3) evaluation of intervention measures targeting these mixtures based on causal frameworks. We also encourage applications that bridge epidemiology, toxicology, and risk assessment, with open code/data and rigid modeling techniques to unveil the link behind complex environmental mixtures and human health. Situating within the existing literature on comparative risk assessment and health impact assessment, this Special Issue extends beyond single-pollutant paradigms and advances mixture-based exposure–response functions and counterfactual analysis suitable for estimating population health burdens. Submissions spanning cohort, panel, and case-crossover, as well as experimental designs, and contributions covering diverse populations and environmental determinant perspectives, are especially encouraged.

Dr. Wangjian Zhang
Dr. Xiao Lin
Guest Editors

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