If public health scientists want a quick and easy way to highlight clues about the cause of a new disease outbreak, they can compare two groups of people: Cases, the term for people who already have the disease, and controls, or people not affected by the disease.
Other terms used to describe case-control studies include epidemiological, retrospective, and observational.
What is a case-control study?
A case-control study can help provide extra insight on data that has already been collected.
A case-control study is a way of carrying out a medical investigation to confirm or indicate what is likely to have caused a condition.
They are usually retrospective, meaning that the researchers look at past data to test whether a particular outcome can be linked back to a suspected risk factor and prevent further outbreaks.
Prospective case-control studies are less common. These involve enrolling a specific selection of people and following that group while monitoring their health. Cases emerge as people who develop the disease or condition under investigation as the study progresses. Those unaffected by the disease form the control group.
To test for specific causes, the scientists need to create a hypothesis about possible causes of the outbreak or disease. These are known as risk factors.
They compare how often the people in the group of cases had been exposed to the suspected cause against how often members of the control group had been exposed. If more participants in the case group experience the risk factor, this suggests that it is a likely cause of the disease.
Researchers might also uncover likely risk factors not mentioned in their hypothesis by studying the medical and personal histories of the people in each group. A pattern may emerge that links the condition to certain factors.
If a specific risk factor has already been identified for a disease or condition, such as age, sex, smoking, or eating red meat, the researchers can use statistical methods to adjust the study to account for that risk factor, helping them to identify other possible risk factors more easily.
Case-control research is a vital tool used by epidemiologists, or researchers who look into the factors affecting health and illness of populations.
Just one risk factor could be investigated for a particular outcome. A good example of this is to compare the number people with lung cancer who have a history of smoking with the number who do not. This will indicate the link between lung cancer and smoking.
Why is it useful?
There are multiple reasons for the use of case-control studies.
Relatively quick and easy
Case-control studies are usually based on past data, so all of the necessary information is readily available, making them quick to carry out. Scientists can analyze existing data to look at health events that have already happened and risk factors that have already been observed.
A retrospective case-control study does not require scientists to wait and see what happens in a trial over a period of days, weeks, or years.
Case-control studies are quick and easy without requiring a large group of participants.
The fact that the data is already available for collation and analysis means that a case-control study is useful when quick results are desired, perhaps when clues are sought for what is causing a sudden disease outbreak.
A prospective case-control study may also be helpful in this scenario as researchers can collect data on suspected risk factors while they monitor for new cases.
The time-saving advantage offered by case-control studies also means they are more practical than other scientific trial designs if the exposure to a suspected cause occurs a long time before the outcome of a disease.
For example, if you wanted to test the hypothesis that a disease seen in adulthood is linked to factors occurring in young children, a prospective study would take decades to carry out. A case-control study is a far more feasible option.
Does not need large numbers of people
Numerous risk factors can be evaluated in case-control studies since they do not require large numbers of participants to be statistically meaningful. More resources can be dedicated to the analysis of fewer people.
Overcomes ethical challenges
As case-control studies are observational and usually about people who have already experienced a condition, they do not pose the ethical problems seen with some interventional studies.
For example, it would be unethical to deprive a group of children of a potentially lifesaving vaccine to see who developed the associated disease. However, analyzing a group of children with limited access to that vaccine can help determine who is at most risk of developing the disease, as well as helping to guide future vaccination efforts.
The correlations confirmed by case-control studies are weaker than in other types of investigation.
While a case-control study can help to test a hypothesis about the link between a risk factor and an outcome, it is not as powerful as other types of study in confirming a causal relationship.
Case-control studies are often used to provide early clues and inform further research using more rigorous scientific methods.
The main problem with case-control studies is that they are not as reliable as planned studies that record data in real time, because they look into data from the past.
The main limitations of case-control studies are:
When people answer questions about their previous exposure to certain risk factors their ability to recall may be unreliable. Compared to people not affected by a condition, individuals with a certain disease outcome may be more likely to recall a certain risk factor, even if it did not exist, because of a temptation to make their own subjective links to explain their condition.
This bias may be reduced if data about the risk factors - exposure to certain drugs, for example - had been entered into reliable records at the time. But this may not be possible for lifestyle factors, for example, because they are usually investigated by questionnaire.
An example of recall bias is the difference between asking study participants to recall the weather at the time of the onset of a certain symptom, versus an analysis of scientifically measured weather patterns around the time of a formal diagnosis.
Finding a measurement of exposure to a risk factor in the body is another way of making case-control studies more reliable and less subjective. These are known as biomarkers. For example, researchers may look at results of blood or urine tests for evidence of a specific drug, rather than asking a participant about drug use.
Cause and effect
An association found between a disease and a possible risk does not necessarily mean one factor directly caused the other.
In fact, a retrospective study can never definitively prove that a link represents a definite cause, as it is not an experiment. There are, though, questions that can be used to test the likelihood of a causal relationship, such as the extent of the association or whether there is a 'dose response' to increasing exposure to the risk factor.
One way of illustrating the limitations of cause-and-effect is to look at associations found between a cultural factor and a particular health effect. The cultural factor itself, such as a certain type of exercise, may not be causing the outcome if the same cultural group of cases shares another plausible common factor, such as a certain food preference.
Some risk factors are linked to others. Researchers have to take into account overlaps between risk factors, such as leading a sedentary lifestyle, being depressed, and living in poverty.
If researchers conducting a retrospective case-control study find an association between depression and weight gain over time, for example, they cannot say with any certainty that depression is a risk factor for weight gain without bringing in a control group containing people who follow a sedentary lifestyle.
The cases and controls selected for study may not truly represent the disease under investigation.
An example of this occurs when cases are seen in a teaching hospital, a highly specialized setting compared with most settings in which the disease may occur. The controls, too, may not be typical of the population. People volunteering their data for the study may have a particularly high level of health motivation.
There are other limitations to case-control studies. While they are good for studying rare conditions, as they do not require large groups of participants, they are less useful for examining rare risk factors, which are more clearly indicated by cohort studies.
Finally, case-control studies cannot confirm different levels or types of the disease being investigated. They can look at only one outcome because a case is defined by whether they did or did not have the condition.