Cross-Sectional Study: Definition, Designs & Examples

A cross-sectional study is a type of observational study, or descriptive research, that involves analyzing information about a population at a specific point in time.


Typically, these studies are used to measure the prevalence of health outcomes and describe the characteristics of a population. In this type of study, researchers are simply examining a group of participants and depicting what already exists in the population without manipulating any variables or interfering with the environment.

Cross-sectional studies aim to describe a variable, not measure it. They can be beneficial for describing a population or “taking a snapshot” of a group of individuals at a single moment in time.

In epidemiology and public health research, cross-sectional studies are used to assess exposure (cause) and disease (effect) and compare the rates of diseases and symptoms of an exposed group with an unexposed group.

Cross-sectional studies are also unique because researchers are able to look at numerous characteristics at once.

For example, a cross-sectional study could be used to investigate whether exposure to certain factors, such as overeating, might correlate to particular outcomes, such as obesity.

While this study cannot prove that overeating causes obesity, it can draw attention to a relationship that might be worth investigating.


Analytical Studies

  • In analytical cross-sectional studies, researchers investigate an association between two parameters. They collect data for exposures and outcomes at one specific time to measure an association between an exposure and a condition within a defined population.
  • The purpose of this type of study is to compare health outcome differences between exposed and unexposed individuals.

Descriptive Studies

  • Descriptive cross-sectional studies are purely used to characterize and assess the prevalence and distribution of one or many health outcomes in a defined population.
  • They can assess how frequently, widely, or severely a specific variable occurs throughout a specific demographic.


Simple and Inexpensive

These studies are quick, cheap, and easy to conduct as they do not require any follow-up with subjects and can be done through self-report surveys.

Minimal room for error

Because all of the variables are analyzed at once, and data does not need to be collected multiple times, there will likely be fewer mistakes as a higher level of control is obtained.

Multiple variables and outcomes can be researched and compared at once

Researchers are able to look at numerous characteristics (ie, age, gender, ethnicity, and education level) in one study.

The data can be a starting point for future research

The information obtained from cross-sectional studies enables researchers to conduct further data analyses to explore any causal relationships in more depth.


Does not help determine cause and effect

Cross-sectional studies can be influenced by an antecedent consequent bias which occurs when it cannot be determined whether exposure preceded disease. (Alexander et al.)

Report bias is probable

Cross-sectional studies rely on surveys and questionnaires, which might not result in accurate reporting as there is no way to verify the information presented.

The timing of the snapshot is not always representative

Cross-sectional studies do not provide information from before or after the report was recorded and only offer a single snapshot of a point in time.

It cannot be used to analyze behavior over a period of time

Cross-sectional studies are designed to look at a variable at a particular moment, while longitudinal studies are more beneficial for analyzing relationships over extended periods.


  • Evaluating the COVID-19 positivity rates among vaccinated and unvaccinated adolescents
  • Investigating the prevalence of dysfunctional breathing in patients treated for asthma in primary care (Wang & Cheng, 2020)
  • Analyzing whether individuals in a community have any history of mental illness and whether they have used therapy to help with their mental health
  • Comparing grades of elementary school students whose parents come from different income levels
  • Determining the association between gender and HIV status (Setia, 2016)
  • Investigating suicide rates among individuals who have at least one parent with chronic depression
  • Assessing the prevalence of HIV and risk behaviors in male sex workers (Shinde et al., 2009)
  • Examining sleep quality and its demographic and psychological correlates among university students in Ethiopia (Lemma et al., 2012)
  • Calculating what proportion of people served by a health clinic in a particular year have high cholesterol
  • Analyzing college students’ distress levels with regard to their year level (Leahy et al., 2010)

Cross-Sectional vs. Longitudinal

Both cross-sectional and longitudinal studies are observational and do not require any interference or manipulation of the study environment.

However, cross-sectional studies differ from longitudinal studies in that cross-sectional studies look at a characteristic of a population at a specific point in time, while longitudinal studies involve studying a population over an extended period.

Longitudinal studies require more time and resources and can be less valid as participants might quit the study before the data has been fully collected.

Unlike cross-sectional studies, researchers can use longitudinal data to detect changes in a population and, over time, establish patterns among subjects.

Cross-sectional studies can be done much quicker than longitudinal studies and are a good starting point to establish any associations between variables, while longitudinal studies are more timely but are necessary for studying cause and effect.

Frequently asked questions

1. Are cross-sectional studies qualitative or quantitative?

Both! Cross-sectional studies can be either quantitative or qualitative.

2. What’s the difference between cross-sectional and cohort studies?

A cohort study is a type of longitudinal study that samples a group of people with a common characteristic. One key difference is that cross-sectional studies measure a specific moment in time, whereas cohort studies follow individuals over extended periods.

Another difference between these two types of studies is the subject pool. In cross-sectional studies, researchers select a sample population and gather data to determine the prevalence of a problem.

Cohort studies, on the other hand, begin by selecting a population of individuals who are already at risk for a specific disease.

3. What’s the difference between cross-sectional and case-control studies?

Case-control studies differ from cross-sectional studies in that case-control studies compare groups retrospectively and cannot be used to calculate relative risk.

In these studies, researchers study one group of people who have developed a particular condition and compare them to a sample without the disease.

Case-control studies are used to determine what factors might be associated with the condition and help researchers form hypotheses about a population.

4. Does a cross-sectional study have a control group?

A cross-sectional study does not need to have a control group, as the population studied is not selected based on exposure.

5. Is a cross-sectional study prospective or retrospective?

No, cross-sectional studies assess a population at one specific point in time, and thus there is no prospective or retrospective follow-up.


Alexander, L. K., Lopez, B., Ricchetti-Masterson, K., & Yeatts, K. B. (n.d.). Cross-sectional Studies. Eric Notebook. Retrieved from

Cherry, K. (2019, October 10). How Does the Cross-Sectional Research Method Work? Verywell Mind. Retrieved from

Cross-sectional vs. longitudinal studies. Institute for Work & Health. (2015, August). Retrieved from

Leahy, C. M., Peterson, R. F., Wilson, I. G., Newbury, J. W., Tonkin, A. L., & Turnbull, D. (2010). Distress levels and self-reported treatment rates for medicine, law, psychology and mechanical engineering tertiary students: cross-sectional study. The Australian and New Zealand journal of psychiatry, 44(7), 608–615.

Lemma, S., Gelaye, B., Berhane, Y. et al. Sleep quality and its psychological correlates among university students in Ethiopia: a cross-sectional study. BMC Psychiatry 12, 237 (2012).

Wang, X., & Cheng, Z. (2020). Cross-Sectional Studies: Strengths, Weaknesses, and Recommendations. Chest, 158(1S), S65–S71.

Setia M. S. (2016). Methodology Series Module 3: Cross-sectional Studies. Indian journal of dermatology, 61(3), 261–264.htt

Shinde S, Setia MS, Row-Kavi A, Anand V, Jerajani H. Male sex workers: Are we ignoring a risk group in Mumbai, India? Indian J Dermatol Venereol Leprol. 2009;75:41–6.

Saul Mcleod, PhD

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Educator, Researcher

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education.

Julia Simkus

Research Assistant at Princeton University

Undergraduate at Princeton University

Julia Simkus is a Psychology student at Princeton University. She will graduate in May of 2023 and go on to pursue her doctorate in Clinical Psychology.