Several key assumptions are central to epidemiological studies:
Causality: It is often assumed that there is a cause-and-effect relationship between an exposure and an outcome. Epidemiologists use various study designs to test these relationships. Consistency: This assumes that the observed associations are consistent across different studies, populations, and settings. Consistency strengthens the evidence of a causal relationship. Temporality: The exposure must occur before the outcome. This is crucial for establishing causality in observational studies. Biological Plausibility: The association between exposure and outcome should be biologically plausible based on current scientific knowledge. Dose-Response Relationship: An increasing amount of exposure should lead to an increasing risk of the outcome, further supporting the causal inference.
