Cohort studies: What are they?

cohort study

Cohort studies are a form of study design in which a group of people is followed over time. Data from cohort studies is used by researchers to better understand human health and the environmental and social variables that impact it.

The term “cohort” refers to a group of people. Cohort studies can be both forward and backward in nature.

A prospective cohort study is also known as a forward-looking cohort study. It is “prospective” in the sense that it is concerned with the future.

A retrospective cohort study is another name for a backward-looking cohort study. It’s “retrospective,” which implies it’s about the past.

Prospective cohort studies are conducted when researchers pick a group of people to investigate and organize the research ahead of time, gathering data across time. Scientists utilize data that is already accessible for a specific population in retrospective cohort studies.

Continue reading to discover more about cohort studies, including their applications, benefits, and drawbacks. This article also compares cohort studies to other types of research.

Cohort study

cohort study

Cohort studies are an effective method for studying human populations. They’re a form of longitudinal research project. Participants in longitudinal research are followed for a length of time. People in cohort studies usually have certain features in common, such as where they live or how old they are.

Participants are recruited in a number of methods by researchers. They may, for example, contact people at random from a birth registry or by postal address.

When people participate in a cohort study, researchers collect information on them so that they may gain a better picture of the group they’re researching. Researchers offer inquiries to learn about the group’s demographics, or traits like age and race. They may also collect data on the following aspects:

  • medical
  • environmental
  • genetic
  • biological
  • social
  • psychological

This data serves as the study’s starting point. Researchers then gather data from the subjects at various periods throughout their life. The next term is referred to as the follow-up phase. The duration of the follow-up might be weeks, months, or years.

Researchers can assess how numerous factors have influenced the group members’ health by comparing data from the follow-up points to the baseline. Scientists employ cohort studies to uncover probable risk factors that cause disease or impact disease patterns, for example, in epidemiology, the study of disease.

Cohort studies are especially useful for identifying links between health and environmental issues such pollutants in the air, water, and food. The World Health Organization (WHO)Trusted Source assists researchers in investigating these concerns through large-scale cohort studies.

Types of cohort studies

There are several types of cohort studies.

Prospective cohort studies entail enlisting a group of people and following them throughout time in order to collect fresh information. Retrospective studies make use of previously collected data.

Researchers choose a topic to explore for a prospective cohort study. They next plan the study and select the volunteers who will best aid them in their research.

For example, if they wanted to research heart disease rates in older persons, they would utilize a baseline sample of younger adults with comparable features who did not have heart disease.

Researchers examine a group of people who already share certain traits in a retrospective cohort study. They then use historical data to travel back in time. They may, for example, examine at a group of elderly people who have heart disease. Then they’d look at data from the group members’ medical histories to discover what factors could have had a role.

Identifying causes

Cohort studies are a useful tool for determining disease risk factors and causes. Researchers can study baseline data for people who did not have a disease at the start to see what characteristics differentiated those who had the disease from those who did not.

A 2020 prospective cohort research, for example, discovered a link between physical inactivity and sadness. The researchers discovered that people who were not depressed at the start of the study were more likely to develop depressive symptoms many years later if they had lower fitness levels than those who had greater fitness levels.

Physical fitness and mental health, on the other hand, are influenced by a variety of factors. People with lesser earnings, for example, may have fewer opportunity to exercise in a healthy atmosphere, as well as a higher risk of depression. As a result, other factors might be at play.

Factors like these are referred regarded as “confounding” by scientists since they have the potential to skew the outcomes of a cohort research. To avoid this, scientists must take into account confounding factors while planning the study. Statistical approaches are one way to do this.

Researchers adjusted for wealth, as well as other possible confounding factors such baseline levels of depression, physical sickness, and gender, in the 2020 study. This indicates that none of these variables had an impact on their outcomes. A similar method may be used to investigate the risk factors and causes of a variety of illnesses.

Examples of cohort studies

There have been several extremely big and long-running cohort studies in the past that have supplied a wealth of data to researchers in many domains. These are some of them:

Nurses’ Health Study

The Nurses’ Health Study is a well-known example of a cohort study. This was a large-scale, long-term study of women’s health that began in 1976. It looked into the possible long-term effects of using oral contraceptives.

In 1989, researchers began recruiting the Nurses’ Health Study II’s second-generation cohort. Nurses from throughout the United States and Canada were recruited for the study’s third-generation cohort in 2010.

The first cohort consisted of married female nurses between the ages of 30 and 55. The second and third cohorts were designed to look at a wider range of people.

The Nurses’ Health Study generated a lot of information regarding the dangers and advantages of different factors, including particular types of food in the diet, because it queried participants about their lifestyle choices.

Framingham Heart Study

The Framingham Heart Study is another example of a long-running cohort study. In 1948, approximately 5,209 male and female volunteers from the Framingham, MA region were recruited for this research. The study has been used as a data source for cardiovascular risk factors since then.

In 1971, a second cohort began, followed by a third in 2002. The research has contributed significantly to our understanding of heart health. The scientists are currently investigating how hereditary variables may influence cardiovascular health risks.

Birth cohorts

A large-scale birth cohort study was initiated in 1958 by academics in the United Kingdom. A research that monitored 17,000 people born in the same week across the country was published in 2003.

Since then, researchers from the Centre for Longitudinal Studies in the United Kingdom have started additional studies with new big groups of newborns.

The Millennium Cohort Study, which follows 19,000 infants born in the United Kingdom between 2000 and 2001, is the most recent. The study is looking into child behavior and cognitive development, as well as a variety of social aspects, in addition to data on the health of these youngsters and their parents.

Advantages and disadvantages

One of the most reliable types of medical research is cohort studies. Because they examine at groups of people before they acquire an illness, they are well-suited to discovering disease causes. This allows scientists to investigate if there is a link between people’s lifestyle choices and their health results.

Cohort studies also have the benefit of collecting a wide range of data that researchers may utilize in a variety of ways. For example, a research on the effects of smoking might find correlations to a variety of diseases. Researchers can also determine how dangerous a component is when compared to others.

Researchers can also use cohort studies to undertake investigations that would otherwise be unethical. An experiment in which researchers purposefully expose subjects to cigarette smoke, for example, would be unethical. A cohort study allows researchers to look at the lives of people who have made the decision to smoke on their own.

However, there are several limits to this form of study. Cohort studies are defined as:

  • more time-consuming and frequently more costly than other sorts of research
  • Because uncommon diseases do not affect a significant number of people, they are less well-suited to uncovering information.
  • If participants drop out of the study over time or the researchers choose an unrepresentative sample of people, the study might be biased.
  • Unable to investigate how or why a component is linked to a disease – this necessitates the use of experimental research

Because the data is already accessible, retrospective research can be substantially less expensive than prospective investigations. These studies, on the other hand, might be less beneficial if the original data does not include all of the information that the researchers want.

Randomized controlled trials vs. cohort studies

Randomized controlled trials (RCTs) are one of the most effective and rigorous methods for studying medical treatments such as new medications. They do, however, differ from cohort studies in a few essential ways.

Observational cohort studies are the most common type of research. This implies that scientists watch rather than intervene in what occurs to a group of people. This permits researchers to investigate disease risk factors as they emerge in the wild.

RCTs, on the other hand, are interventional studies. They entail scientists affecting a group of people, usually by administering a medicine or therapy to see how it affects them. The data is then compared to data collected from a group of people who are being given a placebo.

RCTs are challenging to utilize to discover disease causes and risk factors since they require deliberately exposing participants to something that may make them sick. It would be unethical to do so.

While medication trials are not without danger, scientists only test pharmaceuticals on humans when they are relatively certain they would be effective and when volunteers are fully informed of the risks.

Cross-sectional vs. cohort vs. case control

Case-control studies include finding people who have previously been diagnosed with a disease (the “case”) and comparing them to people who are similar to the “case” but do not have the disease (the “control”). This allows scientists to uncover possible disease risk factors without having to follow the same group for an extended period of time.

Case-control studies, on the other hand, only allow scientists to quantify the risk of getting the disease. They don’t look at how frequently a certain component causes disease, which would help scientists figure out how risky it is.

Cross-sectional studies are similar to cohort studies in that they collect information from a single point in time or over a brief period of time. They can uncover possible disease risks or causes, but they can’t determine whether anything causes disease over time.

Many national surveys, such as the National Health and Nutrition Examination Survey, are cross-sectional.


Cohort studies are one of the most effective tools available to academics when it comes to gaining a better understanding of human health. They entail observing groups of people over extended periods of time and analyzing data patterns. These patterns may be important in identifying disease causes and risk factors.

When it comes to medical interventions, such as drugs, RCTs give more proof. Cohort studies, on the other hand, are more practical and ethical when it comes to investigating health hazards.

However, cohort studies have a number of drawbacks. They can take longer than other research methods, such as cross-sectional or case-control studies.