Cohort Type Studies

A cohort is a "group." In epidemiology a cohort is a group of individuals who are followed over a period of time, primarily to assess what happens to them, i.e., their health outcomes. In cohort type studies one identifies individuals who do not have the outcome of interest initially, and groups them in subsets that differ in their exposure to some factor, e.g., smokers and non-smokers. The different exposure groups are then followed over time in order to compare the incidence of health outcomes, such as lung cancer or heart disease. As an example, the Framingham Heart Study enrolled a cohort of 5,209 residents of Framingham, MA who were between the ages of 30-62 and who did not have cardiovascular disease when they were enrolled. These subjects differed from one another in many ways: whether they smoked, how much they smoked, body mass index, eating habits, exercise habits, gender, family history of heart disease, etc. The researchers assessed these and many other characteristics or "exposures" soon after the subjects had been enrolled and before any of them had developed cardiovascular disease. The many "baseline characteristics" were assessed in a number of ways including questionnaires, physical exams, laboratory tests, and imaging studies (e.g., x-rays). They then began "following" the cohort, meaning that they kept in contact with the subjects by phone, mail, or clinic visits in order to determine if and when any of the subjects developed any of the "outcomes of interest," such as myocardial infarction (heart attack), angina, congestive heart failure, stroke, diabetes and many other cardiovascular outcomes.

Over time some subjects eventually began to develop some of the outcomes of interest. Having followed the cohort in this fashion, it was eventually possible to use the information collected to evaluate many hypotheses about what characteristics were associated with an increased risk of heart disease. For example, if one hypothesized that smoking increased the risk of heart attacks, the subjects in the cohort could be sorted based on their smoking habits, and one could compare the subset of the cohort that smoked to the subset who had never smoked. For each such comparison that one wanted to make the cohort could be grouped according to whether they had a given exposure or not, and one could measure and compare the frequency of heart attacks (i.e., the incidence) between the groups. Incidence provides an estimate of risk, so if the incidence of heart attacks is 3 times greater in smokers compared to non-smokers, it suggests an association between smoking and risk of developing a heart attack. (Various biases might also be an explanation for an apparent association. We will learn about these later in the course.) The hallmark of analytical studies, then, is that they collect information about both exposure status and outcome status, and they compare groups to identify whether there appears to be an association or a link.

The Population "At Risk"

From the discussion above, it should be obvious that one of the basic requirements of a cohort type study is that none of the subjects have the outcome of interest at the beginning of the follow-up period, and time must pass in order to determine the frequency of developing the outcome.

Eligible subjects have to meet certain criteria to be included as subjects in a study (inclusion criteria). One of these would be that they did not have any of the diseases or conditions that the investigators want to study, i.e., the subjects must be "at risk," of developing the outcome of interest, and the members of the cohort to be followed are sometimes referred to as "the population at risk."

However, at times decisions about who is "at risk" and eligible get complicated.

Example #1: Suppose the outcome of interest is development of measles. There may be subjects who:

In this case the eligibility criteria would be shaped by the specific scientific questions being asked. One might want to compare subjects known to have had clinically apparent measles to those who had not had clinical measles and had not had a measles vaccination. Or, one could take blood sample from all potential subjects in order to measure their antibody titers (levels) to the measles virus.

Example #2: Suppose you are studying an event that can occur more that once, such as a heart attack. Again, the eligibility criteria should be shaped to fit the scientific questions that are being answered. If one were interested in the risk of a first myocardial infarction, then obviously subjects who had already had a heart attack would not be eligible for study. On the other hand, if one were interested in tertiary prevention of heart attacks, the study cohort would include people who had had heart attacks or other clinical manifestations of heart disease, and the outcome of interest would be subsequent significant cardiac events or death.