A cross-sectional study is a type of observational research that analyzes and compares populations without manipulating variables within the study environment. Researchers carry out cross-sectional studies over a specific point in time. Social sciences, education and psychology are fields that frequently use cross-sectional studies.
Cross-sectional studies enable researchers to investigate many variables at once, such as gender, income, level of education, and age. Researchers apply the results of these studies to determine the prevalence of health-related outcomes within a population, such as exposure to specific risk factors. Because they take a short time and are relatively inexpensive, cross-sectional studies are popular ways to describe subgroups or whole populations in relation to a set of risk factors.
Public health planners find cross-sectional studies very useful in understanding the causes of various diseases and developing hypotheses for future studies. However, they are not used to establish cause-effect relationships between variables of interest. In cross-sectional studies, a snapshot of the population is taken. Therefore, identical studies provide different results when another time-frame is selected.
Cross-sectional studies may also result in prevalence-incidence bias, where lethal outcomes are excluded, especially when investigating chronic diseases. Furthermore, these studies are ineffective in studying rare diseases and in indicating the sequence of events, such as exposure, onset of illness and outcome.