what is cross sectional research study

Educational resources and simple solutions for your research journey

What is a Cross-Sectional Study? Definition, Advantages, Disadvantages, and Examples

Table of Contents

What is a cross-sectional study ?

So, “what is a cross-sectional study?” Here is a simple cross-sectional study definition: A cross-sectional study is an observational study design that examines data on various variables gathered at a single time point within a sample population or predefined subgroup, offering a depiction of the population’s characteristics.

It is a time-saving, cost-effective, and straightforward approach for gathering preliminary data, wherein a researcher collects data at a single point in time (there is no prospective or retrospective follow-up) and observes variables without influencing them. The prevalence of an outcome at a given point in time can be determined in this manner.

What is the purpose of a cross-sectional study?

The purpose of a cross-sectional study is basically to take a “slice” or a “snapshot” of a population. In the fields of epidemiology and public health research, cross-sectional studies are used to evaluate associations, e.g., between exposure and disease, and to compare disease and symptom rates between an exposed group and an unexposed group.

Another purpose of a cross-sectional study is to simultaneously describe multiple characteristics. For instance, it can be employed to explore whether factors like excessive screen time, social media use, and resulting social pressures are linked to specific outcomes such as anxiety.

While such studies cannot establish a causal link and do not quantify a variable, they can highlight a relationship that might be worth further investigation. One of the advantages of a cross-sectional study is that it plays a key role in developing hypotheses and in laying the foundation for a more comprehensive research project.

Characteristics of a cross-sectional study

Now, let’s delve into the key characteristics of a cross-sectional study:

• Cross-sectional studies examine a fixed set of variables within a specific timeframe. Researchers use the same measuring tools and data points throughout their investigation.
• Although different cross-sectional studies may focus on the same variable of interest, they do so by observing distinct groups of subjects; each study captures a fresh set of participants.
• Cross-sectional analyses focus on a single point in time, marked by a clear starting and stopping point.
• In a cross-sectional study, researchers can zero in on a single independent variable, while also accommodating one or more dependent variables in their examination.

These studies can map the prevailing variables that coexist at a specific point in time. For instance, cross-sectional data can reveal the buying preferences of a population at a given time and how they correlate with economic trends.

Cross-sectional study examples

From the following cross-sectional study examples, we see that these studies gather data from participants sharing similarity across most variables, except for the variable(s) under scrutiny.

Some fictional cross-sectional study examples across various fields are as follows:

Agriculture : Examining pesticide use and knowledge of smallholder farmers in a specific region.

Nutrition : Fruit and nut consumption in a region according to gender and educational level.

Psychology : Psychological impact of the COVID-19 pandemic on healthcare workers in a region.

Economics : Economic burden of unemployment during armed conflict in a particular region.

Psychology : Psychological status of male prisoners at a particular facility.

Healthcare and medicine : (i) Population-based surveys, e.g., the prevalence of twin births in a village, or (ii) prevalence in clinical studies, e.g., antibiotic resistance in Clostridium difficile isolates in a tertiary care hospital.

Cross-sectional studies equip scholars and policymakers with actionable data that can be acquired quickly, facilitating informed decision-making and the development of products or services.

T ypes of cross-sectional studies

The main types of cross-sectional studies are d

escriptive, analytical, and repeated/serial.

Descriptive cross-sectional studies: These characterize the prevalence of one or more outcomes in a particular population, e.g., examining the prevalence of Alzheimer’s disease in a target population.

Analytical cross-sectional studies: Data are obtained for both exposure and outcome at a specific point in time to compare the outcome differences between exposed and unexposed subjects. Such studies answer how or why a certain outcome might occur, e.g., looking at vascular disease, traumatic brain injury, and family history to explain why some adults are much more likely to get Alzheimer’s disease than others.

Repeated (or serial) cross-sectional studies: Data are obtained from the same target population at different time points. At each time point, researchers select a different sample (different subjects) from the same target population. Repeated cross-sectional studies can therefore examine changes in a population over time. An example of serial cross-sectional study could be one that investigates the prevalence and risk factors of Alzheimer’s disease in adults aged 50-80 years in a specific decade.

Advantages and disadvantages of cross-sectional studies

Let’s look at the pros and cons of cross-sectional studies.

Advantages of a cross-sectional study

• Relatively quick and inexpensive to conduct
• No potential ethical issues
• Multiple outcomes and exposures can be studied
• Helpful for generating hypotheses
• Many findings can be used to create an in-depth research study
• Data are obtained from a large pool of subjects, and differences between groups can be compared.

Disadvantages of a cross-sectional study

• Cannot measure incidence
• Deriving causal inferences is challenging as it is a one-time measurement of the apparent cause and effect
• Associations identified might be difficult to interpret
• Cannot determine temporal relations between outcomes and risk factors
• Not suitable for studying rare diseases or sporadic events
• Susceptible to biases
• Cannot be used to analyze trends over a period of time.

Limitations of cross-sectional studies

It is important to know the limitations of cross-sectional studies. Here are some important limitations:

• A cross-sectional study is a one-time measurement of exposure and outcome. Therefore, it does not determine cause-and-effect relationships.
• Such studies are prone to certain biases: report bias (because surveys and questionnaires might not result in accurate reporting) and sampling bias (owing to the need to select a sample of subjects from a large and heterogeneous study population).
• Researchers need to be extremely careful about interpreting the associations and direction of associations from cross-sectional studies.
• Cross-sectional surveys may not be sufficient to understand disease trends. In clinical studies, the prevalence of an outcome depends on disease incidence and length of survival following the outcome.
• One of the disadvantages of a cross-sectional study is that it does not provide information from before or after the data were obtained.
• Cross-sectional studies cannot be used to analyze behavior or trends over time.

Cross-sectional vs. longitudinal studies

It is critical to understand the key features of cross-sectional vs. longitudinal studies before you choose the study design to answer your research question. While both cross-sectional and longitudinal studies are observational, not requiring manipulation of the study environment, they differ in a number of ways (Table).

Table: Cross-sectional vs. longitudinal studies

Frequently asked questions

A cross-sectional study is a type of observational research design that involves collecting data from a group of participants at a single point in time to assess various characteristics or variables of interest.

The primary goal of a cross-sectional study is to describe the prevalence of a specific condition or characteristic within a defined population at a particular moment in time.

What are some advantages of cross-sectional studies?

Cross-sectional studies are relatively quick and cost-effective. They are useful for generating hypotheses and identifying potential research directions.

What are the limitations of a cross-sectional study?

Cross-sectional studies do not allow researchers to track changes over time, making them unsuitable for studying temporal relationships. They cannot establish cause-and-effect relationships.

Can cross-sectional studies be used to study rare conditions or events?

Cross-sectional studies are not the best choice for studying rare events because of the need for a sufficiently large sample size to obtain meaningful results.

What are some suitable cross-sectional study examples?

Some potential cross-sectional study examples could be determining (i) the prevalence of obesity in teenagers from high-income families; (ii) the prevalence of accelerated skin aging, and the association between skin wrinkles and sunscreen application in women; or (iii) the prevalence and risk factors and geographic of reduced visual acuity in secondary students in a specific decade.

Setia, M. S. Methodology Series Module 3: Cross-sectional studies. Indian J Dermatol . (2016) 61(3): 261–264. doi: 10.4103/0019-5154.182410

Wang, X., & Cheng, Z. Cross-sectional studies: strengths, weaknesses, and recommendations. Chest (2020) 158(1) Suppl , S65–S71. https://doi.org/10.1016/j.chest.2020.03.012

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

Related Posts

How Long Should Your Essay Be? Essential Tips for Every Type of Essay

What is a Research Paper Appendix? 

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Cross-Sectional Study | Definitions, Uses & Examples

Cross-Sectional Study | Definitions, Uses & Examples

Published on 5 May 2022 by Lauren Thomas .

A cross-sectional study is a type of research design in which you collect data from many different individuals at a single point in time. In cross-sectional research, you observe variables without influencing them.

Researchers in economics, psychology, medicine, epidemiology, and the other social sciences all make use of cross-sectional studies in their work. For example, epidemiologists who are interested in the current prevalence of a disease in a certain subset of the population might use a cross-sectional design to gather and analyse the relevant data.

Table of contents

Cross-sectional vs longitudinal studies, when to use a cross-sectional design, how to perform a cross-sectional study, advantages and disadvantages of cross-sectional studies, frequently asked questions about cross-sectional studies.

The opposite of a cross-sectional study is a longitudinal study . While cross-sectional studies collect data from many subjects at a single point in time, longitudinal studies collect data repeatedly from the same subjects over time, often focusing on a smaller group of individuals connected by a common trait.

Both types are useful for answering different kinds of research questions . A cross-sectional study is a cheap and easy way to gather initial data and identify correlations that can then be investigated further in a longitudinal study.

Prevent plagiarism, run a free check.

When you want to examine the prevalence of some outcome at a certain moment in time, a cross-sectional study is the best choice.

Sometimes a cross-sectional study is the best choice for practical reasons – for instance, if you only have the time or money to collect cross-sectional data, or if the only data you can find to answer your research question were gathered at a single point in time.

As cross-sectional studies are cheaper and less time-consuming than many other types of study, they allow you to easily collect data that can be used as a basis for further research.

Descriptive vs analytical studies

Cross-sectional studies can be used for both analytical and descriptive purposes:

• An analytical study tries to answer how or why a certain outcome might occur.
• A descriptive study only summarises said outcome using descriptive statistics.

To implement a cross-sectional study, you can rely on data assembled by another source or collect your own. Governments often make cross-sectional datasets freely available online.

Prominent examples include the censuses of several countries like the US or France , which survey a cross-sectional snapshot of the country’s residents on important measures. International organisations like the World Health Organization or the World Bank also provide access to cross-sectional datasets on their websites.

However, these datasets are often aggregated to a regional level, which may prevent the investigation of certain research questions. You will also be restricted to whichever variables the original researchers decided to study.

If you want to choose the variables in your study and analyse your data on an individual level, you can collect your own data using research methods such as surveys . It’s important to carefully design your questions and choose your sample .

Like any research design , cross-sectional studies have various benefits and drawbacks.

• Because you only collect data at a single point in time, cross-sectional studies are relatively cheap and less time-consuming than other types of research.
• Cross-sectional studies allow you to collect data from a large pool of subjects and compare differences between groups.
• Cross-sectional studies capture a specific moment in time. National censuses, for instance, provide a snapshot of conditions in that country at that time.

Disadvantages

• It is difficult to establish cause-and-effect relationships using cross-sectional studies, since they only represent a one-time measurement of both the alleged cause and effect.
• Since cross-sectional studies only study a single moment in time, they cannot be used to analyse behavior over a period of time or establish long-term trends.
• The timing of the cross-sectional snapshot may be unrepresentative of behaviour of the group as a whole. For instance, imagine you are looking at the impact of psychotherapy on an illness like depression. If the depressed individuals in your sample began therapy shortly before the data collection, then it might appear that therapy causes depression even if it is effective in the long term.

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data are available for analysis; other times your research question may only require a cross-sectional study to answer it.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyse behaviour over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

Thomas, L. (2022, May 05). Cross-Sectional Study | Definitions, Uses & Examples. Scribbr. Retrieved 18 November 2024, from https://www.scribbr.co.uk/research-methods/cross-sectional-design/

Is this article helpful?

Lauren Thomas

Other students also liked, longitudinal study | definition, approaches & examples, descriptive research design | definition, methods & examples, correlational research | guide, design & examples.