This letter aims to provide valuable insights into broader evidence triangulation (i.e., a well-designed primary association analysis followed by elaborate approaches to control residual confounding effects from various design and modeling perspectives) for clarifying the association between air pollutants and health outcomes. It also highlights the importance of selecting appropriate instrumental variable for instrument-based causal modeling, emphasizing that all causal questions can be effectively addressed within the Mendelian randomization framework.
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| http://dx.doi.org/10.1111/cns.70207 | DOI Listing |
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