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Abstract:
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As modern assaying technologies continue to improve, environmental health studies are increasingly measuring endogenous omics data to study intermediary biological pathways of outcome-exposure associations. Mediation analysis is often carried out when there is a well-established literature showing statistical and practical significance of the association between an exogenous exposure and a health outcome of interest, or the total effect. For example, there are a plethora of studies associating maternal phthalate exposure with preterm delivery, and researchers are now trying to characterize the mechanisms by which phthalate exposure impacts final gestational age. Existing methodology for performing mediation analyses does not leverage the rich external information available on the total effect. We show that incorporating external summary-level information on the total effect improves estimation efficiency of the direct and indirect effects, provided that the outcome-mediator association conditional on exposure is non-zero, and discuss how to handle incongruous external information. The proposed framework blends mediation analysis with data integration techniques.
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