{"id":138630,"date":"2020-05-08T10:55:38","date_gmt":"2020-05-08T08:55:38","guid":{"rendered":"https:\/\/www.scribbr.nl\/?p=138630"},"modified":"2023-06-22T10:25:53","modified_gmt":"2023-06-22T08:25:53","slug":"cross-sectional-study","status":"publish","type":"post","link":"https:\/\/www.scribbr.com\/methodology\/cross-sectional-study\/","title":{"rendered":"Cross-Sectional Study | Definition, Uses & Examples"},"content":{"rendered":"

A cross-sectional study is a type of research design<\/a> in which you collect data from many different individuals at a single point in time. In cross-sectional research, you observe variables<\/a> without influencing them.<\/p>\n

Researchers in economics, psychology, medicine, epidemiology, and the other social sciences all make use of cross-sectional studies in their work. For example, epidemiologists who are interested in the current prevalence of a disease in a certain subset of the population might use a cross-sectional design to gather and analyze the relevant data.<\/p>\n

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Cross-sectional vs longitudinal studies<\/h2>\n

The opposite of a cross-sectional study is a longitudinal study<\/a>. While cross-sectional studies collect data<\/a> 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.<\/p>\n

\"Cross-sectional<\/p>\n

Both types are useful for answering different kinds of research questions<\/a>. A cross-sectional study is a cheap and easy way to gather initial data and identify correlations<\/a> that can then be investigated further in a longitudinal study.<\/p>\n

Cross-sectional vs longitudinal example<\/figcaption>You want to study the impact that a low-carb diet has on diabetes. 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. You discover that the diet correlates with weight loss in younger patients, but not older ones.<\/p>\n

You then decide to design a longitudinal study to further examine this link in younger patients. Without first conducting the cross-sectional study, you would not have known to focus on younger patients in particular.<\/figure>\n

When to use a cross-sectional design<\/h2>\n

When you want to examine the prevalence of some outcome at a certain moment in time, a cross-sectional study is the best choice.<\/p>\n

Example<\/figcaption>You 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. 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.<\/figure>\n

Sometimes a cross-sectional study is the best choice for practical reasons \u2013 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.<\/p>\n

As 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.<\/p>\n

Descriptive vs analytical studies<\/h3>\n

Cross-sectional studies can be used for both analytical and descriptive purposes:<\/p>\n