Overfitting is problematic because it can lead to incorrect conclusions about the relationship between variables and result in poor decision-making. For epidemiologists, this means that interventions or policies might be designed based on misleading evidence, potentially causing harm instead of benefit. Additionally, overfitted models can obscure the true effect of risk factors and lead to wasted resources on ineffective measures.
