Interpretation involves making sense of the data in the context of existing knowledge, biological plausibility, and statistical significance. Epidemiologists must consider the study design, sample size, and potential biases when interpreting results. It's crucial to distinguish between correlation and causation and to be cautious of overgeneralizing findings.
