Evidence-appraisal glossary
Cross-sectional study
A cross-sectional study measures exposure and outcome in a population at a single point in time, like a snapshot. It is useful for estimating how common something is (prevalence), but because it captures everything at once, it usually cannot show which came first.
Also called: prevalence study.
A cross-sectional study collects data on exposures and outcomes simultaneously, giving a snapshot of a population at one moment. It is well suited to estimating prevalence (what fraction of people have a condition right now) and to generating hypotheses about associations. Its central limitation is temporal ambiguity: because exposure and outcome are measured together, you usually cannot tell whether the exposure preceded the outcome or the reverse. When reading one, ask whether the sample represents the target population, whether the response rate was high enough to trust, and resist causal language, since an association here does not establish cause. A survey finding that people with more sedentary jobs also have higher body weight, both measured on the same day, cannot say whether inactivity led to weight gain or heavier people chose less active work. The question the design lets you ask: at this moment, are the exposure and the outcome statistically associated in this population?
Read the full Reading the Evidence blog.
This is a plain-language methodology definition for reading research. It is general education, not medical advice.