Confounding factors are variables that are related to both the exposure and the outcome of interest, potentially distorting the true association between them. For example, consider a study investigating the relationship between coffee consumption and heart disease. If smoking is not accounted for, it could confound the results, as smokers may drink more coffee and also have a higher risk of heart disease.
