Seeking Causal Explanations in Epidemiology Subdisciplines

Much of the literature on causal inference in epidemiologic research has dealt with causal inference in the field of epidemiology as a whole, or has focused on causal inference in certain areas such as chronic diseases and environmental causes of diseases and adverse health outcomes. In recent years, however, several authors have dealt with causal inference within a variety of epidemiologic subdisciplines including nutritional epidemiology, genetic epidemiology, infectious disease epidemiology, and social epidemiology. Although criteriabased approaches are still widely cited and used, enthusiasm for the Bradford Hill criteria or subsets of the criteria appears to be waning in some areas of epidemiology (or among some groups of epidemiologists). An increasing number of authors have argued that traditional criteria for causal inference in observational research do not apply to particular epidemiology subdisciplines or that certain criteria should be modified. A large and growing literature has dealt with quantitative models for estimating causal parameters using data from observational studies (for example, counterfactual models and structural equation models).