Understanding intermediate variables is crucial in epidemiology because they help researchers uncover the underlying mechanisms of diseases. This knowledge can inform public health interventions and policies aimed at breaking the causal chain. For example, if we know that obesity is an intermediate variable between sedentary lifestyle and type 2 diabetes, interventions targeting physical activity could be highly effective in preventing diabetes.
