The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index; none of the 2 sources its claims cite is checked for support yet.
Cross-Sectional Studies
Open accessAbstract
Cross-sectional studies are observational studies that analyze data from a population at a single point in time. They are often used to measure the prevalence of health outcomes, understand determinants of health, and describe features of a population. Unlike other types of observational studies, cross-sectional studies do not follow individuals up over time. They are usually inexpensive and easy to conduct. They are useful for establishing preliminary evidence in planning a future advanced study. This article reviews the essential characteristics, describes strengths and weaknesses, discusses methodological issues, and gives our recommendations on design and statistical analysis for cross-sectional studies in pulmonary and critical care medicine. A list of considerations for reviewers is also provided.
Overview
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Claims the paper makes
11 Own interpretation · 1 Sources not found · 1 No full text of the sources
In the paper
“Prevalenceincidence bias (also called the Neyman bias) is also particularly common in cross-sectional studies.13”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Bias
What the sources say
- Not checked — no full text of the sourcecites [13] Tripepi, 2010, Selection bias and information bias in clinical research, Nephron Clin Pract source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“They cannot be used to look at individual change (as in a cohort study).”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Description of Subtypes of Cross-Sectional Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because the outcome and exposure variables are measured at the same time, it is relatively difficult to establish causal relationships from a cross-sectional study.”
- Also stated in: § Description of Subtypes of Cross-Sectional Studies · plain
“The exposures and outcomes are measured simultaneously; therefore, it is difficult to determine whether the exposures preceded or followed the outcomes in an analytical cross-sectional study.”
- Also stated in: § Benefits and Downside of Cross-Sectional Studies · plain
“The weaknesses of cross-sectional studies include the inability to assess incidence, to study rare diseases, and to make a causal inference.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > General Overview of Cross-Sectional Study Design
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Description of Subtypes of Cross-Sectional Studies · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, repeated cross-sectional studies can be used for analyzing population changes over time (also known as aggregate change over time).”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Description of Subtypes of Cross-Sectional Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“If one wants to compare two prevalence rates in an analytical cross-sectional study, the commonly used sample size formula is the same as is used when designing a cohort study.6”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Sample Size Determination
What the sources say
- Not matchedcites [6] Fleiss, 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Unlike studies starting from a series of patients, cross-sectional studies often need to select a sample of subjects from a large and heterogeneous study population.Thus, they are susceptible to sampling bias.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Benefits and Downside of Cross-Sectional Studies
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The subjects are neither deliberately exposed nor treated; thus, there are seldom ethical difficulties.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Benefits and Downside of Cross-Sectional Studies
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 4
- It may state two separate claims as one. 3
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Stepwise selection methods and P value-based criteria are discouraged due to overfitting and because they often allow too many parameters to be included, which reduces the generalizability of the model.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Additional information
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Confounding could result in a distortion of the association between exposure and outcome.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Confounding
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Note that the sample size in a descriptive study does not depend on statistical power because this concept only applies to statistical comparisons.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Sample Size Determination
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The weaknesses of cross-sectional studies include the inability to assess incidence, to study rare diseases, and to make a causal inference.”
- Also stated in: § 1. The study population and the research question. · plain
“Unable to measure the incidence”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Benefits and Downside of Cross-Sectional Studies
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Also stated in: § 1. The study population and the research question. · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Only with full and transparent reporting of information on all aspects of a cross-sectional study can potential usefulness of its findings and risk of bias be adequately assessed.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Additional information
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because exposure and outcome are measured simultaneously in a cross-sectional study, prior knowledge of the condition might influence the ascertainment of the exposure or the outcome, which results in recall bias.”
§ Cross-Sectional Studies Strengths, Weaknesses, and Recommendations > Bias
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
Cross-sectional studies are usually quick and inexpensive to conduct.
“They are usually inexpensive and easy to conduct.”
“The main strength of cross-sectional studies is that they are relatively quick and inexpensive to conduct.”
The paper relies on this without support.
Cross-sectional studies are the best way to determine prevalence.
“They are the best way to determine the prevalence and can study the associations of multiple exposures and outcomes.”
The paper relies on this without support.
Cross-sectional studies can study the associations of multiple exposures and outcomes.
“They are the best way to determine the prevalence and can study the associations of multiple exposures and outcomes.”
The paper relies on this without support.
Cross-sectional studies are useful for establishing preliminary evidence in planning a future advanced study.
“They are useful for establishing preliminary evidence in planning a future advanced study.”
The paper relies on this without support.
Cross-sectional studies are suitable for generating hypotheses and may provide information about the prevalence of outcomes and exposures that informs other study designs.
“They are suitable for generating hypotheses and may provide information about the prevalence of outcomes and exposures that informs other study designs.”
The paper relies on this without support.
Using questionnaires to reach a large sample of the population of interest is relatively inexpensive but can result in low response rates.
“Using questionnaires to reach a large sample of the population of interest is relatively inexpensive but can result in low response rates.”
The paper relies on this without support.
Interviews are more expensive and time-consuming than using questionnaires, potentially limiting the sample size but leading to a higher response rate.
“Interviews are more expensive and time-consuming than using questionnaires, potentially limiting the sample size but leading to a higher response rate.”
The paper relies on this without support.
Cross-sectional studies cannot study rare diseases.
“The weaknesses of cross-sectional studies include the inability to assess incidence, to study rare diseases, and to make a causal inference.”
The paper relies on this without support.
Probability sampling methods are more accurate and rigorous than nonprobability sampling methods.
“In general, probability sampling methods are preferred over nonprobability ones, as the former are considered to be more accurate and rigorous.”
The paper relies on this without support.
Nonresponse bias is usually encountered in cross-sectional survey studies with mailed questionnaires.
“A common type of selection bias is the nonresponse bias, which is usually encountered in crosssectional survey studies with mailed questionnaires.”
The paper relies on this without support.
Recall bias and detection bias are two common information biases.
“Recall bias and detection bias are two common information biases.”
Citations
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Farmers’ Adaptation to Climate Change in Nakuru County, Kenya
Karani, L. E., Ramkat, R. C., Serem, A., et al. (2025) · Springer eBooks · doi:10.1007/978-3-031-95781-9_6 · Cited by 1
Exploring Artificial Intelligence Anxiety Among Basic School Teachers in Ghana
Arthur, F., Boateng, E., Opoku, E., Gyedu, F. O., Asare-Bediako, S., Quayson, E., Salifu, I., Attom, E. R., & Nortey, S. A. (2026) · SAGE Open · doi:10.1177/21582440251410713 · Cited by 4
“…survey design describes a specific situation as it exists at a particular moment and necessitates direct contact with individuals whose behaviours, characteristics, and attitudes are relevant to the study (Bloomfield & Fisher, 2019; Jongbo, 2014; Rovai et al., 2014; X. Wang & Cheng, 2020).”
Ssemugenyi, F. (2021) · Education Research International · doi:10.1155/2021/5542558 · Cited by 1
Urban Noise Exposure and Cardiometabolic Diseases: An Exploratory Cross-Sectional Study in Lisbon
Pereira, G. M., Brito, J., Oliveira, M. J., & Oliveira, P. (2021) · Portuguese Journal of Public Health · doi:10.1159/000520263 · Cited by 1
“The cross-sectional design does not allow the establishment of a causal inference between the studied cardio-metabolic diseases and noise exposure [40], which may also constitute a limitation.”
BackgroundResultTimothy, S., Lokina, R. B., & Mgale, Y. J. (2022) · Open Journal of Social Sciences · doi:10.4236/jss.2022.105012
“The study used a descriptive survey design, and the design was preferred because it allows analysis of both quantitative and qualitative data (Cohen et al., 2005, 2006, 2016, 2020; Levin, 2006; Setia, 2016; Wang & Cheng, 2020).”
MethodAnnoyance toward landscaping equipment noise in Canada
Michaud, D. S., Marro, L., Denning, A., et al. (2022) · JASA Express Letters · doi:10.1121/10.0013012 · Cited by 1
Nurkalis, U., & Siswanto, S. (2022) · Intan Husada Jurnal Ilmiah Keperawatan · doi:10.52236/ih.v10i2.243 · Cited by 1
“Pendekatan penelitian menggunakan pendekatan cross sectional study yaitu variabel sebab atau risiko dan akibat atau kasus yang terjadi pada objek penelitian diukur atau dikumpulkan dalam waktu yang bersamaan (Notoatmodjo Soekidjo, 2010; Wang and Cheng, 2020).”
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Duarsa, A. C. P., Mardiah, A., Anulus, A., et al. (2023) · JURNAL KEDOKTERAN · doi:10.36679/kedokteran.v8i2.47 · Cited by 1
Dukungan Sosial sebagai Moderator Kecemasan Kematian dan Depresi pada Tenaga Medis Covid-19
Gusbet, R. A. (2023) · INSAN Jurnal Psikologi dan Kesehatan Mental · doi:10.20473/jpkm.v8i22023.195-215 · Cited by 4
WITHDRAWN: Human monkeypox infection knowledge in the Philippines: An online cross-sectional survey
Berdida, D. J. E. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e13864 · Cited by 1
“Cross-sectional designs are 129 observational studies that examine data from a population at one particular period [31].”
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Health Impacts of Micro- and Nanoplastics in Humans: Systematic Review of In Vivo EvidencePreprint
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Hepatitis C virus infection among the informal waste pickers in Aden, YemenPreprint
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Hepatitis B virus infection among the informal waste pickers in Aden, YemenPreprint
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Disrupted Diurnal Phase Variation in Circulating Factors as a Predictor of Disease and MortalityPreprint
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Precision medicine and schizophrenia: What about telomere length?
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The Concept of Causation and some common Epidemiological study Designs
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Faculty and Student Perceptions of Effective Techniques in Teaching Physiology
Jeter, B. (2021) · Aquila Digital Community (University of Southern Mississippi)
Predictors of Teenage Pregnancy in Zambia Between 2007-2018Preprint
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“…have not been intentionally exposed and treated by a particular medical facility because the present research was an online study of cross-sectional study design (Wang and Cheng, 2020).40 The limitations of the present study include the nature of the sample, the test format, and accessibility.”
BackgroundEvaluating the content of workplace wellness programmes in a manufacturing enterprise
Banda, N. G. (2021) · Boloka Institutional Repository (North-west University)
Mahadewi, L. P. P., Muslim, S., Tegeh, I. M., & Astawa, I. B. M. (2021) · Jurnal Edutech Undiksha · doi:10.23887/jeu.v9i2.42050
“This research is a descriptive type of cross-sectional study, that is descriptive research that involves one-time interaction with participants (Pandis, 2014; Wang & Cheng, 2020).”
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Risk of Food Insecurity and Cardiometabolic Health—What Can Be Done?
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“And, although cross-sectional studies are valuable in determining the prevalence and studying the associations of multiple outcomes, they are also susceptible to recall bias whereby participants may not accurately recall previous experiences (Wang & Cheng, 2020).”
BackgroundPredicting COVID-19 mortality in Zambia - an Application of Machine LearningPreprint
Mulenga, C., Musonda, P., & Kaonga, P. (2022) · doi:10.31237/osf.io/b5a6n
Meyer-Schwickerath, C., Köppel, M., Kühl, R., Huber, G., & Wiskemann, J. (2022) · Journal of Communications In Healthcare · doi:10.1080/17538068.2022.2117529
Berbeco, P., Blowers, J., Gioia, J. A., & Epstein, M. (2022) · Westcliff International Journal of Applied Research · doi:10.47670/wuwijar2022bbge
“The recruitment represented the non-probability sampling technique of purposive (e.g., target all employees) and snowball (e.g., refer others to the survey; Naderifar et al., 2017; Wang & Cheng, 2020).”
Method(2022) · Westcliff International Journal of Applied Research · doi:10.47670//wuwijar202261
HUBUNGAN FAKTOR DEMOGRAFI DENGAN MOTIVASI MENJADI GURU SEBAGAI PILIHAN KARIR : SELF-REPORTED SURVEY
Sudrajat, A. K., Wiharyanti, R., Aulia, F., et al. (2022) · JURNAL TARBIYAH · doi:10.30829/tar.v29i2.1863
Socioeconomics Status among Pahang Resident’s Perspectives on Fake News During the Covid 19 Pandemic
Rozali, W. N. A. W. B., Bakar, W. H. R. B. W. A., Misaridin, N. A. F. B., et al. (2023) · International Journal of Academic Research in Business and Social Sciences · doi:10.6007/ijarbss/v13-i1/15656
Metadata
- Authors
- Wang, X., & Cheng, Z.
- Affiliations
- Cleveland Clinic (US)
- Zhongnan Hospital of Wuhan University (CN)
- Corresponding author
- Wang, Xiaofeng
- Venue
- CHEST
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 158
- Issue
- 1
- Pages
- S65-S71
- ISSN
- 0012-3692 (ISSN-L)
- OpenAlex
- W3039445169
- Cited by
- 2,214
- References
- 29
- Citations by year
- 2026: 636 · 2025: 638 · 2024: 423 · 2023: 282 · 2022: 162 · 2021: 61 · 2020: 8
- FWCI
- 90.42
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- CHEST Journal (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Nursing › Research and Theory › Methodologies in Health Research and Practice
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- cross-sectional study, observational study design, prevalence, health determinants, methodological issues, statistical analysis, respiratory medicine, intensive care, research design recommendations, peer review
- MeSH terms
- Cross-Sectional Studies, Humans, Guidelines as Topic
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