Why is confounding considered a problem in studies?

Confounding is considered a problem in studies primarily because it can create or obscure associations between exposure and outcome. When a confounding variable is present, it may be related to both the exposure and the outcome, leading to conclusions that are not truly reflective of the relationship being studied. For instance, if a study is examining the impact of a new medication on health outcomes, and age is a confounder, any observed effect may be due to age differences instead of the medication itself. This can mislead researchers and affect the validity of the study findings.

By accurately identifying and addressing confounding variables, researchers can clarify the true nature of the relationships they are investigating. In this way, option B highlights the fundamental issue of confounding, which can distort the interpretation of data and lead to incorrect conclusions about causality or effectiveness in the studied population.