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. 2020 May 1;35(5):1013-1018.
doi: 10.1093/humrep/deaa051.

Confounding and effect measure modification in reproductive medicine research

Affiliations

Confounding and effect measure modification in reproductive medicine research

Katharine Fb Correia et al. Hum Reprod. .

Abstract

The majority of research within reproductive and gynecologic health, or investigating ART, is observational in design. One of the most critical challenges for observational studies is confounding, while one of the most important for discovery and inference is effect modification. In this commentary, we explain what confounding and effect modification are and why they matter. We present examples illustrating how failing to adjust for a confounder leads to invalid conclusions, as well as examples where adjusting for a factor that is not a confounder also leads to invalid or imprecise conclusions. Careful consideration of which factors may act as confounders or modifiers of the association of interest is critical to conducting sound research, particularly with complex observational studies in reproductive medicine.

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Figures

Figure 1
Figure 1
A DAG illustrating relationships among sedentary behavior, obesity, and pregnancy. In this DAG, obesity is a confounder of the relationship between sedentary behavior and pregnancy. DAG: directed acyclic graph.
Figure 2
Figure 2
Example DAGs for four different scenarios.
Figure 3
Figure 3
A possible DAG to depict the association between sedentary behavior, number of embryos transferred and preterm delivery.
Figure 4
Figure 4
A possible DAG to depict the association between sedentary behavior, neighborhood green space and miscarriage. Neighborhood green space is not a confounder because it is not predictive of miscarriage. Adjusting for it in the model could reduce precision of the effect estimate for the association between sedentariness and miscarriage.

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