What is a cross-sectional study?

Researchers leverage different types of research studies to gather and analyze data. The characteristics you want to observe and your research goals dictate the best type of study to use. Cross-sectional studies, for instance, are vital when researching groups of people at a single point in time.

Read on to learn about cross-sectional studies. We’ll explore examples, types, advantages, and limitations of cross-sectional studies, plus when you might use them.

A cross-sectional study is also known as a prevalence or transverse study. It’s a tool that allows researchers to collect data across a pre-defined subset or sample population at a single point in time. The information is typically about many individuals with multiple variables, such as gender and age. Although researchers get to analyze these variables, they do not manipulate them.

This study type is commonly used in clinical research, business-related studies, and population studies.

Once the researcher has selected the ideal study period and participant group, the study usually takes place as a survey or physical experiment.

Primary characteristics of cross-sectional studies include the following:

• Consistent variables: Researchers carry out a cross-sectional study over a specific period with the same set of variables (income, gender, age, etc.).

• Observational nature: Researchers record findings about a specific population but do not alter variables—they just observe.

• Well-defined extremes: The analysis includes defined start and stop points which allow all variables to stay the same.

• Singular instances: Only one topic or instance can be analyzed with a cross-sectional study. This allows for more accurate data collection.

Variables remain the same during a cross-sectional study. This makes it a useful research tool in various sectors and circumstances across multiple industries.

Here are some examples to give you better clarity:

• Healthcare: Scientists might leverage cross-sectional research to assess how children aged 3–10 are prone to calcium deficiency.

• Retail: Researchers use cross-sectional studies to identify similarities and differences in spending habits between men and women within a specific age group.

• Education: These studies help reveal how students with a specific grade range perform when schools introduce a new curriculum.

• Business: Researchers might leverage cross-sectional studies to understand how a geographic segment responds to offers and discounts.

We can categorize cross-sectional studies into two distinct types: descriptive and analytical research. However, the researcher may use one or both types to gather and analyze data.

Here is a description of the two to help you understand how they may apply to your work.

Descriptive research

A descriptive cross-sectional survey or study assesses how commonly or frequently the primary variable occurs within a select demographic. This enables you to identify any problem areas within the group.

Descriptive research makes trend identification easy, facilitating the development of products and services that fit a particular population.

Analytical research

An analytical cross-sectional study investigates the relationship between two related or unrelated parameters. Outside variables may affect the study while the investigation is ongoing, however.

Note that the original results and data are studied together simultaneously in an analytical cross-sectional study.

Although longitudinal and cross-sectional studies are both observational, they are relatively different types of research design.

Below are the main differences between cross-sectional and longitudinal studies:

Sample group

A cross-sectional study will include several variables and sample groups, meaning it will collect data for all the different sample groups at once. However, in longitudinal studies, the same groups with similar variables can be observed repeatedly.

Cost

Cross-sectional studies are usually cheaper to conduct than longitudinal studies, so they are ideal if you have a limited budget.

Participants in longitudinal studies have to commit for an extended period, which significantly increases costs. Cross-sectional studies, on the other hand, are shorter and require less effort.

Length

Data is collected only once in cross-sectional research. In contrast, longitudinal research takes considerable time because data is collected across numerous periods (potentially decades).

Data

Researchers don’t necessarily seek causation in longitudinal research. This means the data will lack context regarding previous participant behavior.

Longitudinal research, on the other hand, clearly shows how data evolves. This means you can infer cause-and-effect relationships.

You will need to follow these steps to conduct a cross-sectional study:

• Formulate research questions and hypotheses. You will also need to identify your target population at this stage.

• Design the research. You will need to leverage observation rather than experiments when collecting data. However, you can always use non-experimental techniques such as questionnaires or surveys. As a result, this type of research will let you collect both quantitative and qualitative data.

• Conduct the research. You can collect your data or assemble it from another source. In most instances, governments make cross-sectional datasets available to the public (through censuses) that can help with your research. The World Bank and World Health Organization also provide cross-sectional datasets on their websites.

• Analyze the data. Data analysis will depend on the type of data collection method you use.

Are you considering whether a cross-sectional study is an ideal approach for your next research? It’s an efficient and effective way to gather data. Check out some of the key advantages and disadvantages of cross-sectional studies.

Advantages of cross-sectional research

• Quick to conduct

• Multiple outcomes are researched at once

• Relatively inexpensive

• Used as a basis for further research

• Researchers gather all variables at a single point in time

• It’s possible to measure the prevalence of all factors

• Ideal for descriptive analysis

Disadvantages of cross-sectional research

• Preventing other variables from influencing the study is challenging

• Researchers cannot infer cause-and-effect relationships

• Requires large, heterogeneous samples, which increases the chances of sampling bias

• The select population and period may not be representative

Cross-sectional studies are useful when:

• You need answers to questions regarding the prevalence and incidence of a situation, belief, or condition.

• Establishing the norm in a particular demographic at a specified time. For instance, what is the average age for completing studies in Dallas?

• Justifying the need to conduct further research on a specific topic. With cross-sectional research, you can infer a correlation without determining a direct cause. This makes it easier to justify conducting other investigations.

A cross-sectional study is essential when researching the prevailing characteristics in a given population at a single point in time. Cross-sectional studies are often used to analyze demography, financial reports, and election polls. You could also use them in medical research or when building a marketing strategy, for instance.

Cross-sectional research can be both qualitative and quantitative.

Cross-sectional studies don’t need a control group as the selected population is not based on exposure.

Limitations of cross-sectional studies include the inability to make causal inferences, study rare illnesses, and access incidence. Researchers select a subject sample from a large and heterogeneous population.