Types of Epidemiology Studies

Below is a flow chart to help us understand how study types are classified. Each type is then discussed individually below.

Observational Studies: Descriptive & Analytical Types

Observational studies involve no intervention other than asking questions and carrying out medical examinations and simple laboratory tests or X-ray examinations. In epidemiology, observational studies are more common than experimental ones, particularly if an investigator wants to determine whether an agent or exposure causes cases or effects in humans. 

Descriptive studies can provide the background from which analytical studies emerge. They help to generate hypotheses, as opposed to testing them while the analytical studies measure both disease-related outcomes and risk factors (Tests hypothesis generated through descriptive studies).

These are the best method for determining the incidence and natural history of a condition. The studies may be prospective or retrospective and sometimes two cohorts are compared. 

Prospective cohort studies

A group of people is chosen who do not have the outcome of interest (for example, diabetes). The investigator then measures a variety of variables that might be relevant to the development of the condition. Over a period of time the people in the sample are observed to see whether they develop the outcome of interest (that is, diabetes).  In single cohort studies those people who do not develop the outcome of interest are used as internal controls.

Where two cohorts are used, one group has been exposed to or treated with the agent of interest and the other has not, thereby acting as an external control. 

Retrospective cohort studies

These use data already collected for other purposes. The methodology is the same but the study is performed posthoc. The cohort is “followed up” retrospectively. The study period may be many years but the time to complete the study is only as long as it takes to collate and analyze the data. 

Advantages 

1. The use of cohorts is often mandatory as a randomized controlled trial may be unethical; for example, you cannot deliberately expose people to cigarette smoke or asbestos. Thus research on risk factors relies heavily on cohort studies. 
2. As cohort studies measure potential causes before the outcome has occurred, the study can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is cause and which is effect. 
3. A single study can examine various outcome variables. For example, cohort studies of smokers can simultaneously look at deaths from lung, cardiovascular, and cerebrovascular disease. This contrasts with case-control studies as they assess only one outcome variable (that is, whatever outcome the cases have entered the study with).
4. Cohorts permit calculation of the effect of each variable on the probability of developing the outcome of interest (relative risk). 
5. Retrospective studies are much cheaper as the data have already been collected. One advantage of such a study design is the lack of bias because the outcome of current interest was not the original reason for the data to be collected.

Disadvantages

1. Where a certain outcome is rare then a prospective cohort study is inefficient. For example, studying 100 A&E attendees with minor injuries for the outcome of diabetes mellitus will probably produce only one patient with the outcome of interest. The efficiency of a prospective cohort study increases as the incidence of any particular outcome increases. Thus a study of patients with a diagnosis of deliberate self harm in the 12 months after initial presentation would be efficiently studied using a cohort design.
2. Loss of some subjects to follow up. This can significantly affect the outcome. Taking incidence analysis as an example (incidence = cases/per period of time), it can be seen that the loss of a few cases will seriously affect the numerator and hence the calculated incidence. The rarer the condition, the more significant this effect. 
3. Because the retrospective cohort was originally constructed for another purpose it is unlikely that all the relevant information will have been rigorously collected.
4. Retrospective cohorts also suffer the disadvantage that people with the outcome of interest are more likely to remember certain antecedents, or exaggerate or minimize what they now consider to be risk factors (recall bias). Where two cohorts are compared one will have been exposed to the agent of interest and one will not. 
5. The major disadvantage is the inability to control for all other factors that might differ between the two groups. These factors are known as confounding variables. 

A confounding variable is independently associated with both the variable of interest and the outcome of interest. For example, lung cancer (outcome) is less common in people with asthma (variable). However, it is unlikely that asthma in itself confers any protection against lung cancer. It is more probable that the incidence of lung cancer is lower in people with asthma because fewer asthmatics smoke cigarettes (confounding variable). The only way to eliminate all possibility of a confounding variable is via a prospective randomized controlled study. In this type of study each type of exposure is assigned by chance and so confounding variables should be present in equal numbers in both groups. 

Finally, problems can arise as a result of bias. Bias can occur in any research and reflects the potential that the sample studied is not representative of the population it was drawn from and/or the population at large. A classic example is using employed people, as employment is itself associated with generally better health than unemployed people. Similarly people who respond to questionnaires tend to be fitter and more motivated than those who do not. People attending A&E departments should not be presumed to be representative of the population at large. 

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