What is a Cohort Study?
A cohort study is a longitudinal experimental design that follows a group of participants who share a defining characteristic. For example, a cohort study can select subjects who have exposure to a risk factor, are in the same profession, population or generation, or experience a particular event, such as a medical procedure. This design determines whether exposure to a risk factor affects an outcome. Cohort studies are a type of longitudinal study because they track the same set of subjects over time.
For example, if researchers hypothesize that exposure to a chemical increases skin cancer, they can form a cohort based on exposure to that chemical. Then they follow the cohort and assess cancer rates relative to a comparison group without the exposure.
Cohort studies are observational designs, meaning that the researchers do not manipulate experimental or environmental conditions. Instead, they collect data over time and try to understand how various factors affect the outcome. These projects can last for periods ranging from weeks to decades, depending on the research questions.
Learn more about Experimental Design: Definition, Types, and Examples.
Examples of Cohort Studies
Researchers frequently use cohort studies to identify disease risk factors and understand how they affect disease incidence rates.
British Doctors
This cohort study ran from 1951 to 2001 and tracked 60,000 participants with various smoking habits. The researchers found a link between smoking, lung cancer, and death rates.
Nurses’ Health
This cohort study started in 1976 and tracks over 120,000 nurses. It assesses risk factors for many major chronic diseases in women.
Framingham Heart
The study tracks 15,000 participants from three generations and started in 1948. It has identified risk factors for high blood pressure and high cholesterol, among others.
Types of Cohort Studies
Cohort designs can be retrospective or prospective.
Retrospective Cohort Study
In a retrospective cohort study, the scientists identify subjects where the outcomes are known when the project starts. For example, they can find patients who already have the condition of interest and compare them to those who do not. They look for patterns in predicting those who developed the disease.
In retrospective designs, the researchers collect their data using existing records. Consequently, they can complete their study more quickly and inexpensively than prospective designs. However, the various factors and other variables might not have been measured consistently or accurately because they weren’t explicitly designed to be part of a cohort study.
Researchers using a retrospective design have to make do with data that other people recorded in the past for other purposes. Those data were not chosen and measured with the project’s needs in mind. Alternatively, some studies might ask the subjects to recall exposure information or use other subjective evaluations, which introduces a variety of biases.
Learn more about Retrospective Studies.
Prospective Cohort Study
In a prospective cohort study, researchers identify subjects based on the cohort, but the outcomes are unknown when the study begins. Typically, the study recruits people with and without exposure to facilitate comparisons. Then, they track the participants over time, record all the necessary data, and watch for patterns in those who develop the outcome of interest.
Prospective designs are more expensive and time consuming than retrospective studies. However, the researchers can measure all the required data at regular intervals.
Generally, conclusions from a prospective cohort study are superior to those from a retrospective design.
Learn more about Prospective Studies.
Benefits of a Cohort Study
Scientists frequently use cohort studies in epidemiological studies, psychology, social sciences, and nursing. This design is great for identifying both protective and risk factors in natural settings and understanding how they affect incident rates.
In other words, this design helps develop an understanding of the variables that increase and decrease the probability of contracting a disease or other condition. Additionally, researchers can track multiple outcomes (e.g., several diseases) in a single cohort. For example, do smokers have an increased incidence of both lung cancer and emphysema?
Typically, researchers recruit a group where some participants have exposure to a risk factor while others do not. Researchers can include multiple subgroups related to various risk and protective factors in the cohort study. In this manner, analysts can track those factors and link them to occurrences of the outcome they’re studying.
When a risk factor is rare, a cohort study can specifically recruit participants with exposure and follow them. In contrast, other methods are unlikely to obtain a sufficient number of subjects exposed to the risk factor, making it difficult to produce meaningful results.
The longitudinal nature of this design allows a cohort study to understand how exposure and timing relate to the outcome. The scientists don’t need to understand those relationships fully to conduct the research. Instead, they can collect data and evaluate relationships as they appear. Additionally, exposure can change over time, providing insight into its relationship with the outcome.
Weaknesses of a Cohort Study
As mentioned earlier, a prospective cohort study can be expensive and time consuming. In some cases, they involve tens of thousands of participants and last for years or decades. The researchers must track these subjects, perform follow-up evaluations regularly, and record all the data. Over this time, participants will drop out, making the results sensitive to attrition bias.
A cohort study is not a true experiment. It’s a type of observational design and, as such, it opens the door to the problem of confounding variables and spurious correlations. The observed relationships between risk factors and the outcome might be only correlational and not causal. Confounders can bias the results. While these studies are an excellent way to identify potential factors, they require follow-up experiments to verify causal relationships. Learn more about Correlation vs. Causation: Understanding the Differences.
Because cohort studies are observational, they do not use random assignment. Researchers must be wary of confounding factors and take appropriate countermeasures.
For more information, read my posts about Observational Studies Explained and Confounding Variables.
Cohort Study vs. Case-Control Study
Cohort and case-control studies are observational designs that medical and epidemiological researchers use to evaluate risk factors. While they are similar, there are crucial differences.
Cohort
A cohort study evaluates the frequency of a disease/condition by exposure. The researchers assess differences in exposure and see how that relates to differences in the incidence rate.
Does exposure affect the incidence rate?
To answer this question, cohort studies often use regression models to estimate the relationships and control for confounders.
Case-Control
In contrast, a case-control design focuses on the comparative exposure for those who have the condition relative to those without it.
Do people with a condition have greater exposure?
To answer this question, case-control studies typically report an odds ratio.
Case-control designs are always retrospective, whereas cohort research can be retrospective or prospective.
For more information, read my post about Case-Control Studies.
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