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Causation refers to a process wherein an initial or inciting event (exposure) affects the probability of a subsequent or resulting event (outcome) occurring. Epidemiologists' definitions of causation and methods for establishing causal relationships (causality) have evolved. Contemporary studies involving causality require strong assumptions, causal-structural subject-matter knowledge, careful statistical analysis, and considerations for alternative explanations. The following models demonstrate the core principles of causation.
Hernán MA, Robins JM. Estimating causal effects from epidemiological data. J Epidemiol Community Health. 2006 Jul;60(7):578-86.
-
PMC
-
PubMed
VanderWeele TJ, Shpitser I. On the definition of a confounder. Ann Stat. 2013 Feb;41(1):196-220.
-
PMC
-
PubMed
Joffe M, Gambhir M, Chadeau-Hyam M, Vineis P. Causal diagrams in systems epidemiology. Emerg Themes Epidemiol. 2012 Mar 19;9(1):1.
-
PMC
-
PubMed
Fedak KM, Bernal A, Capshaw ZA, Gross S. Applying the Bradford Hill criteria in the 21st century: how data integration has changed causal inference in molecular epidemiology. Emerg Themes Epidemiol. 2015;12:14.
-
PMC
-
PubMed
Shimonovich M, Pearce A, Thomson H, Keyes K, Katikireddi SV. Assessing causality in epidemiology: revisiting Bradford Hill to incorporate developments in causal thinking. Eur J Epidemiol. 2021 Sep;36(9):873-887.
-
PMC
-
PubMed