Special issue on novel statistical approaches for modeling exposure mixtures and health outcomes

We invite submissions to the special issue of Statistics in Biosciences dedicated to statistical approaches for modeling exposure mixtures and health outcomes. Recent literature has seen an increased interest in modeling numerous exposures and their relations with various health outcomes. For example, cancer epidemiologists are often interested in human exposures to environmental pollutants and their associations with mortality and morbidity of lung cancer, and researchers in human reproduction are interested in how maternal metabolites are associated with neonatal anthropometries. Common challenges in these analyses include numerous potential exposures of interest, high degrees of correlation between some of these exposures, non-uniform data distributions, non-linear relationships between exposures and outcomes as well as complex interactions, and a prevalence of measurements below the limit of detections, among many others. New methods for exposure mixtures are being developed, yet more work is needed in comparing these methods from both a theoretical and applications perspective. Moreover, with ubiquitous availability of big exposure data and increased desire in understanding biological mechanisms from exposures to diseases, new methodological developments are needed in many fronts of exposure mixtures modeling, including causal mediation analysis and sparse and scalable analytical procedures.

The special issue welcomes new methodological developments as well as interesting applications in modeling exposure mixtures. It also welcomes up-to-date reviews of current tools in this area. All submissions must contain original unpublished work not being considered for publication elsewhere. Submissions will be refereed according to the standard procedures for Statistics in Biosciences. The deadline for submissions is June 30, 2022.

Papers for the special issue should be submitted using the journal’s submission system at https://www.editorialmanager.com/sibs/default1.aspx. In the system, please choose the special issue Novel Statistical Approaches for Modeling Exposure Mixtures and Health Outcomes.

Co-Editors for the special issue:

• Zhen Chen, PhD, National Institutes of Health. Email: zhen.chen@nih.gov
• Paul S Albert, PhD, National Institutes of Health. Email: albertp@mail.nih.gov