Bias can distort the true relationship between exposure and outcome. This can result in either an exaggerated or diminished perceived effect, leading to incorrect public health recommendations. For example, if a study on smoking and lung cancer is biased, it may incorrectly estimate the strength of the association, thus affecting smoking cessation programs.
