A confounder (or 'confounding factor') is something, other than the thing being studied, that could be causing the results seen in a study. 

It can be very difficult to account for every possible confounder when doing research with people, but researchers must try to account for anything that could influence their results when planning their research and analysing their data. confounders have the potential to change the results of research because they can influence the outcomes that the researchers are measuring.

Research that concludes that there is an association or a ‘correlation’ between a factor and an outcome (for example high alcohol consumption and liver disease) should also consider whether there might be any confounding factors. If researchers do not consider confounders, the results of their research might not be valid.

Example: Confounders

A group of researchers decide to study the causes of heart disease by carrying out an observational study. The researchers find that the people in their study who ate lots of red meat also developed heart disease. They believe they have found a link (or ‘correlation’) between eating red meat and developing heart disease, and they (or those reading their research) might be tempted to conclude that eating lots of red meat is a cause of heart disease. However, before making a conclusion like this, the researchers must think about confounding factors. 

In this example, the researchers are measuring red meat consumption and incidence of heart disease. However, it might be the case that everyone in the study who ate a lot of red meat may also have smoked cigarettes regularly or been overweight. In this case, one or both of those other factors could have influenced whether the participants developed heart disease or not. In other words, smoking and being overweight are possible confounders in this study.

Accounting for confounders is particularly important when undertaking surveys or observational research because it is harder for researchers to control variables in the same way as they can in randomised controlled trials, so these types of research are more vulnerable to confounders. In trials, researchers are able to create more controlled settings where outside factors can be limited. In surveys and observation research, outside factors can easily enter the research environment, which could potentially harm their research.