Causal inference in environmental epidemiology
Sanghyuk Bae, Hwan‐Cheol Kim, Byeongjin Ye, Won-Jun Choi, Young‐Seoub Hong, Mina Ha
Abstract
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Sanghyuk Bae, Hwan‐Cheol Kim, Byeongjin Ye, Won-Jun Choi, Young‐Seoub Hong, Mina Ha
Abstract
Open-access reader
Inferring causality is necessary to achieve the goal of epidemiology, which is to elucidate the cause of disease. Causal inference is conducted in three steps: evaluation of validity of the study, inference of general causality, and inference of individual causality. To evaluate validity of the study, we propose a checklist that focuses on biases and generalizability. For general causal inference, we recommend utilizing Hill's 9 viewpoints. Lastly, individual causality can be inferred based on the general causality and evidence of exposure. Additional considerations may be needed for social or legal purposes; however, these additional considerations should be based on the scientific truth elucidated by the causal inference described in the present article.
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Inferring causality is necessary to achieve the goal of epidemiology, which is to elucidate the cause of disease. Causal inference is conducted in three steps: evaluation of validity of the study, inference of general causality, and inference of individual causality. To evaluate validity of the study, we propose a checklist that focuses on biases and generalizability. For general causal inference, we recommend utilizing Hill's 9 viewpoints. Lastly, individual causality can be inferred based on the general causality and evidence of exposure. Additional considerations may be needed for social or legal purposes; however, these additional considerations should be based on the scientific truth elucidated by the causal inference described in the present article.
Key concepts: Causal inference, Inference, Epidemiology, Environmental epidemiology, Environmental health, Computer science, Medicine, Econometrics