A cross-sectional study measures exposure and disease status at a single point in time.
Cross-sectional studies are sometimes called prevalence studies. Since exposure and disease status are measured at the same time point, it may not be possible to distinguish whether the exposure preceded or followed the disease. Therefore, cause and effect relationships are not certain in these studies. However, they are useful in public health planning as they provide information on the health status and needs of populations. Examples include census surveys and patient questionnaires.
- Can be completed quickly
- Inexpensive to conduct
- There is no loss to follow-up
- Many outcomes and risk factors can be measured at the same time
- Useful for understanding disease etiology and hypothesis generation
- Difficult to infer causation
- Response rates are often a problem
- May provide differing results if data are collected during different time frames
- Risk for prevalence-incidence bias, especially in the case of long-lasting diseases
- Cross-sectional studies – from the EBD series on study design by Kate Levin