Benchmark dose profiles for bivariate exposures

Author:

Akkaya Hocagil Tugba12ORCID,Ryan Louise M.3,Cook Richard J.1,Dang Khue‐Dung4,Carter R. Colin5,Richardson Gale A.6,Day Nancy L.6,Coles Claire D.7,Carmichael Olson Heather8,Jacobson Sandra W.9,Jacobson Joseph L.9

Affiliation:

1. Department of Statistics and Actuarial Science University of Waterloo Waterloo Ontario Canada

2. Department of Biostatistics, School of Medicine Ankara University Ankara Turkiye

3. School of Mathematical and Physical Sciences University of Technology Sydney Sydney New South Wales Australia

4. School of Mathematics and Statistics University of Melbourne Melbourne Victoria Australia

5. Division of Pediatric Emergency Medicine Columbia University Medical Center New York New York USA

6. Department of Psychiatry University of Pittsburgh Pittsburgh, Pennsylvania USA

7. Department of Psychiatry and Behavioral Sciences Emory University Atlanta, Georgia USA

8. Department of Psychiatry and Behavioral Sciences University of Washington Washington, District of Columbia USA

9. Department of Psychiatry and Behavioral Neurosciences, School of Medicine Wayne State University Detroit Michigan USA

Abstract

AbstractWhile benchmark dose (BMD) methodology is well‐established for settings with a single exposure, these methods cannot easily handle multidimensional exposures with nonlinear effects. We propose a framework for BMD analysis to characterize the joint effect of a two‐dimensional exposure on a continuous outcome using a generalized additive model while adjusting for potential confounders via propensity scores. This leads to a dose–response surface which can be summarized in two dimensions by a contour plot in which combinations of exposures leading to the same expected effect are identified. In our motivating study of prenatal alcohol exposure, cognitive deficits in children are found to be associated with both the frequency of drinking as well as the amount of alcohol consumed on each drinking day during pregnancy. The general methodological framework is useful for a broad range of settings, including combinations of environmental stressors, such as chemical mixtures, and in explorations of the impact of dose rate rather than simply cumulative exposure on adverse outcomes.

Funder

Foundation for the National Institutes of Health

Publisher

Wiley

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