A cross-sectional study design is a type of observational study, or descriptive research, that involves analyzing information about a population at a specific point in time.
This design measures the prevalence of an outcome of interest in a defined population. It provides a snapshot of the characteristics of the population at a single point in time.
It can be used to assess the prevalence of outcomes and exposures, determine relationships among variables, and generate hypotheses about causal connections between factors to be explored in experimental designs.
Purpose
Typically, these studies are used to measure the prevalence of health outcomes and describe the characteristics of a population.
In this study, researchers examine a group of participants and depict 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.
Designs
Cross-sectional studies can be categorized based on the nature of the data collection and the type of data being sought.
| Cross-Sectional Study | Purpose | Example |
|---|---|---|
| Descriptive | To describe the characteristics of a population. | Examining the dietary habits of high school students. |
| Analytical | To investigate associations between variables. | Studying the correlation between smoking and lung disease in adults. |
| Community Survey/Population-Based Survey | To gather information on a population or a subset. | Conducting a survey on the use of public transportation in a city. |
| Prevalence Study | To determine the proportion of a population with a specific characteristic, condition, or disease. | Assessing the prevalence of obesity in a country. |
| Occupational or Environmental | To examine the effects of certain occupational or environmental exposures. | Studying the impact of air pollution on respiratory health in industrial workers. |
| Occupational or Environmental | To generate hypotheses for future research. | Investigating relationships between various lifestyle factors and mental health conditions. |
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.
- This is the most common type of cross-sectional study.
Examples
- 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)
Advantages
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.
Limitations
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.
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.
References
Alexander, L. K., Lopez, B., Ricchetti-Masterson, K., & Yeatts, K. B. (n.d.). Cross-sectional Studies. Eric Notebook. Retrieved from https://sph.unc.edu/wp-content/uploads/sites/112/2015/07/nciph_ERIC8.pdf
Cherry, K. (2019, October 10). How Does the Cross-Sectional Research Method Work? Verywell Mind. Retrieved from https://www.verywellmind.com/what-is-a-cross-sectional-study-2794978
Cross-sectional vs. longitudinal studies. Institute for Work & Health. (2015, August). Retrieved from https://www.iwh.on.ca/what-researchers-mean-by/cross-sectional-vs-longitudinal-studies
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.
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.
1. Are cross-sectional studies qualitative or quantitative?
Cross-sectional studies can be either qualitative or quantitative, depending on the type of data they collect and how they analyze it. Often, the two approaches are combined in mixed-methods research to get a more comprehensive understanding of the research problem.
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, whereascohort studiesfollow 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.
In a cross-sectional study, data are collected from a sample of the target population at a specific point in time, and everyone in the sample is assessed in the same way. There isn’t a manipulation of variables or a control group as there would be in an experimental study design.
5. Is a cross-sectional study prospective or retrospective?
A cross-sectional study is generally considered neither prospective nor retrospective because it provides a “snapshot” of a population at a single point in time.
Cross-sectional studies are not designed to follow individuals forward in time (prospective) or look back at historical data (retrospective), as they analyze data from a specific point in time.
