5.6: Types of Research Studies - Retrospective or Case-Control Studies

Case-control studies start by identifying a group of people who have experienced a specific outcome, and then look for specific exposures, health behaviors or other factors to try to determine the cause or causes. Looking backwards like this is termed retrospective. Although we can perform other studies that are retrospective, case-control studies are always retrospective because they start with the outcome and work backwards. Let’s say for example we wanted to find out if smoking was a risk factor for lung cancer. For a case-control study, we would start by identifying cases - perhaps find a group of lung cancer patients at a hospital - and then ask them whether or not they had ever smoked. If we found that a large number of them had smoked, we might think that this indicates that smoking is a risk factor for lung cancer.

But wait - what if lung cancer rates were also high in non-smokers too? This identifies the need for the control part of the case-control study. We’ll have to find similar people for our control group who don’t have lung cancer, and ask them if they have ever smoked. If the number of smokers is much greater in the cancer group vs. the non-cancer group, then we might conclude there is an association between smoking and lung cancer after all.

Sometimes a single exposure of any amount is the risk factor, but other times the “devil is in the dose”. If there is a dose-response relationship between smoking and lung cancer, then those people who smoked more would have a higher risk of lung cancer. So perhaps instead of asking our cases and our controls whether or not they had ever smoked, we would ask them how many cigarettes they smoked per day, and for how many years. We would probably also want to know if they had quit smoking, and if so, how long ago.

There can be many issues that a researcher has to consider when performing a case-control study. We might have a selection bias for example. Perhaps the control group was selected from the same hospital and the controls were exposed to second-hand smoke or air pollution in that city or neighborhood. Perhaps the controls aren’t similar enough to the cases in terms of age, sex, socioeconomic status, etc. If we were to compare a young control group with an older case group for example, the younger controls might just not have developed the disease yet. Thus, the selection of the controls can cause a bias in the research.

Another issue is that researchers must control for other variables that could influence the outcome instead of the one being studied. For example, if a researcher wanted to find out if coffee consumption decreased the risk of obesity, they might find a case group of individuals with obesity, and a control group of individuals without obesity, and then ask them about coffee consumption. Maybe those people who drink coffee tend to also exercise or eat more pastries. If the researchers do not ask their study subjects about those habits, those could be affecting the person’s body weight independent of the coffee consumption. Yet another pitfall is called reverse causality; when the variable is actually caused by the outcome. Taking the coffee/obesity example, it could be that people who have obesity often try to lose weight, and may do so by consuming coffee (since it is a mild stimulant). Therefore, it wouldn't be the coffee consumption that had an effect on obesity, but obesity that had an effect on coffee consumption.

Last but not least, all humans tend to have some recall bias. As case-control studies often depend on surveys or interviews, it’s important to identify which participants might be inclined to remember or not remember certain details, or perhaps fudge some of what they report on a survey. For example, many people overestimate their height and underestimate their weight on self-reported data (Jain, 2010). If the study uses self-reported height and weight to determine obesity, then this data could be inaccurate. When someone has received a diagnosis, they are often “looking” for something in their past that caused it, which might make them more likely to remember specific things that happened to them - simply because they are “looking” through their memory for a cause (Lewallen, 2018).

Case-control studies are often considered simple and inexpensive to perform, since data can be gathered from interviews, surveys, or databases. They can help a researcher develop or confirm a suspicion, and if the study is designed well, they may even allow for an association to be inferred. However, typically they need to be replicated and/or bolstered by other types of studies (like randomized controlled trials) in order for a causal association to be confirmed. Many times, case-controlled studies may actually contradict each other, depending on the methods used and how well the researchers controlled for biases and other variables. It’s important to review the methods used, and keep in mind common biases and confounding factors when reading a case-control study article. See Fig. \(\PageIndex{1}\) for a diagram of case-control studies.

Figure \(\PageIndex{1}\): Case-Control Study