Cross-sectional studies allow you to collect data from a large pool of subjects and compare differences between groups.Because you only collect data at a single point in time, cross-sectional studies are relatively cheap and less time-consuming than other types of research.Like any research design, cross-sectional studies have various benefits and drawbacks. Advantages and disadvantages of cross-sectional studies It’s important to carefully design your questions and choose your sample. If you want to choose the variables in your study and analyze your data on an individual level, you can collect your own data using research methods such as surveys. You will also be restricted to whichever variables the original researchers decided to study. However, these datasets are often aggregated to a regional level, which may prevent the investigation of certain research questions. International organizations like the World Health Organization or the World Bank also provide access to cross-sectional datasets on their websites. Prominent examples include the censuses of several countries like the US or France, which survey a cross-sectional snapshot of the country’s residents on important measures. Governments often make cross-sectional datasets freely available online. To implement a cross-sectional study, you can rely on data assembled by another source or collect your own. A descriptive study might look at the prevalence of obesity in children, while an analytical study might examine exercise and food habits in addition to obesity levels to explain why some children are much more likely to be obese than others. A descriptive study only summarizes said outcome using descriptive statistics.ĭescriptive vs analytical exampleYou are studying child obesity.An analytical study tries to answer how or why a certain outcome might occur.Descriptive vs analytical studiesĬross-sectional studies can be used for both analytical and descriptive purposes: Sometimes a cross-sectional study is the best choice for practical reasons – for instance, if you only have the time or money to collect cross-sectional data, or if the only data you can find to answer your research question was gathered at a single point in time.Īs cross-sectional studies are cheaper and less time-consuming than many other types of study, they allow you to easily collect data that can be used as a basis for further research. Because all you need to know is the current number of low-income families, a cross-sectional study should provide you with all the data you require.
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ExampleYou want to know how many families with children in New York City are currently low-income so you can estimate how much money is required to fund a free lunch program in public schools. When you want to examine the prevalence of some outcome at a certain moment in time, a cross-sectional study is the best choice. Without first conducting the cross-sectional study, you would not have known to focus on younger patients in particular. You then decide to design a longitudinal study to further examine this link in younger patients. You discover that the diet correlates with weight loss in younger patients, but not older ones.
You first conduct a cross-sectional study with a sample of diabetes patients to see if there are differences in health outcomes like weight or blood sugar in those who follow a low-carb diet. Cross-sectional vs longitudinal exampleYou want to study the impact that a low-carb diet has on diabetes. A cross-sectional study is a cheap and easy way to gather initial data and identify correlations that can then be investigated further in a longitudinal study. While cross-sectional studies collect data from many subjects at a single point in time, longitudinal studies collect data repeatedly from the same subjects over time, often focusing on a smaller group of individuals that are connected by a common trait.īoth types are useful for answering different kinds of research questions. The opposite of a cross-sectional study is a longitudinal study.
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