by Annette Gerritsen, Ph.D.

Two designs commonly used in epidemiology are the cohort and case-control studies. Both study causal relationships between a risk factor and a disease. What is the difference between these two designs? And when should you opt for the one or the other?

Cohort studies

Cohort studies begin with a group of people (a cohort) free of disease. The people in the cohort are grouped by whether or not they are exposed to a potential cause of disease. The whole cohort is followed over time to see if the development of new cases of the disease (or other outcome) differs between the groups with and without exposure.

For example, you could do a cohort study if you suspect there might be a causal relationship between the use of a certain water source and the incidence of diarrhea among children under five in a village with different water sources.

You  select a group of children under five years, either all children of that age in the village, a random sample taken from the population register, or e.g. children living in the same area, or attending the same clinic. Then you  classify them as either using the suspected water source or other water sources. You check e.g. after two weeks whether the children have had diarrhea.

You can then calculate how many diarrhea cases there were among those children using the suspected water source and those using other sources of water supply (cumulative incidence of diarrhea).  How to compare the cumulative incidence rates of the two groups, in order to conclude whether the suspected water source is a risk factor for the disease or not, will be discussed in  a future blog.

Case-control studies

The same problem could also be studied in a case-control study. A case-control study begins with the selection of cases (people with a disease) and controls (people without the disease).  The controls should represent people who would have been study cases if they had developed the disease (population at risk).

The exposure status to a potential cause of disease is determined for both cases and controls. Then the occurrence of the possible cause of the disease could be calculated for both the cases and controls. To come back to the example, you may compare children who present themselves at a health center with diarrhea (cases) with children with other complaints, for example acute respiratory infections (controls). You determine which source of drinking water they had used.  Then calculate the proportion of cases and controls that were exposed to the suspected water source.

Pro’s and con’s

On what basis do you decide to choose a cohort design or a case-control design?

Cohort studies provide the best information about the causation of disease, because you follow persons from exposure to the occurrence of the disease. With data from cohort studies you can calculate cumulative incidences, which are the most direct measurement of the risk of developing disease.

An added advantage is that you can examine a range of outcomes/diseases caused by one exposure (e.g. heart disease, lung disease, renal disease caused by smoking).

However, cohort studies are major undertakings. They may require long periods of follow-up since disease may occur a long time after exposure. Therefore, it is a very expensive study design.

Cohort studies work well for rare exposures–you can specifically select people exposed to a certain factor.  But this design does not work for rare diseases–you would then need a large study group to find sufficient disease cases.

Case-control studies are relatively simple to conduct. They do not require a long follow-up period (as the disease has already developed), and are hence much cheaper. This design is especially useful for rare diseases (as you select the cases yourself), but not for rare causes (as you will probably not find these in sufficient number in your study). It is also very suitable for diseases with a long latent period, such as cancer.

However, case-control studies are less adept at showing a causal relationship than cohort studies. They are more prone to bias.

One example is recall bias:  cases might recall certain exposures more clearly than controls, simply due to the fact that they have thought about what could have caused their disease.

Next time, an article will show how cross-tabulations are calculated, used, and interpreted in cohort and case-control studies.

About the Author: With expertise in epidemiology, biostatistics and quantitative research projects, Annette Gerritsen, Ph.D. provides services to her clients focussing on the methodological soundness of each phase of an epidemiological study to ensure getting valid answers to the proposed research questions. She is the founder of Epi Result.

Tags: Case-Control Design, Cohort Design

This entry was posted on Monday, June 7th, 2010 at 12:23 pm and is filed under General. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.