11 questions to help you make sense of descriptive/cross-sectional studies 2025

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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.
Surveillance of changes in smoking habits or of other behavioral risk factors are sequential cross-sectional studies. The US National Health and Nutrition Examination Survey (NHANES) is one such example Similarly, surveillance of long lasting diseases such as AIDS is cross-sectional.
For example, if we want to measure current obesity levels in a population, we could draw a sample of 1,000 people randomly from that population (also known as a cross section of that population), measure their weight and height, and calculate what percentage of that sample is categorized as obese.
The main strength of cross-sectional studies is that they are relatively quick and inexpensive to conduct. They are the best way to determine the prevalence and can study the associations of multiple exposures and outcomes.
Researchers might use a cross-sectional study to understand why women older than 40 are more prone to a certain disease. Another example could be to determine how many people in a community smoke tobacco.
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Descriptive cross-sectional studies: These characterize the prevalence of one or more outcomes in a particular population, e.g., examining the prevalence of Alzheimers disease in a target population.
Characteristics of Cross-Sectional Survey Design Surveys are conducted with the same set of variables at a single point in time. Researchers can look at various characteristics at once (age, gender, race, etc). Theyre often used to look at the defining characteristics of a population at a given point in time.

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