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## Principles of Epidemiology in Public Health Practice, 3rd Edition

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# Lesson 4: Displaying Public Health Data

## Section 1: Introduction to Tables and Graphs

Data analysis is an important component of public health practice. In examining data, one must first determine the data type in order to select the appropriate display format. The data to be displayed will be in one of the following categories:

• Nominal
• Ordinal
• Discrete
• Continuous

Nominal measurements have no intrinsic order and the difference between levels of the variable have no meaning. In epidemiology, sex, race, or exposure category (yes/no) are examples of nominal measurements. Ordinal variables do have an intrinsic order, but, again, differences between levels are not relevant. Examples of ordinal variables are “low, medium, high” or perhaps categories of other variables (e.g., age ranges). Discrete variables have values that are integers (e.g., number of ill persons who were exposed to a risk factor). Finally, continuous variables can have any value in a range (e.g., amount of time between meal being served and onset of gastro-intestinal symptoms; infant mortality rate).

Before constructing any display of epidemiologic data, it is important to first determine the point to be conveyed. Are you highlighting a change from past patterns in the data? Are you showing a difference in incidence by geographic area or by some predetermined risk factor? What is the interpretation you want the reader to reach? Your answer to these questions will help to determine the choice of display.

To analyze data effectively, an epidemiologist must become familiar with the data before applying analytic techniques. The epidemiologist may begin by examining individual records such as those contained in a line listing. This review will be followed by production of a table to summarize the data. Sometimes, the resulting tables are the only analysis that is needed, particularly when the amount of data is small and relationships are straightforward.

When the data are more complex, graphs and charts can help the epidemiologist visualize broader patterns and trends and identify variations from those trends. Variations in data may represent important new findings or only errors in typing or coding which need to be corrected. Thus, tables and graphs can be helpful tools to aid in verifying and analyzing the data.

Once an analysis is complete, tables and graphs further serve as useful visual aids for describing the data to others. When preparing tables and graphs, keep in mind that your primary purpose is to communicate information.

Tables and graphs can be presented using a variety of media. In epidemiology, the most common media are print and projection. This lesson will focus on creating effective and attractive tables and graphs for print and will also offer suggestions for projection. At the end, we present tables that summarize all techniques presented and guidelines for use.

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