Confounding variables are factors that are related to both the exposure and the outcome of interest, potentially leading to spurious associations. For example, in a study examining the relationship between physical activity and heart disease, smoking could be a confounder if it is related to both physical activity and heart disease. Proper study design and statistical methods, such as multivariable regression, can help mitigate this issue.
