Lesson 4: Displaying Public Health Data

Summary, References, and Websites

Much work has been done on other graphical methods of presentation.(33) One of the more creative is face plots.(34) Originally developed by Chernoff,(35) these give a way to display n variables on a two-dimensional surface. For instance, suppose you have several variables (x, y, z, etc.) that you have collected on each of n people, and for purposes of this illustration, suppose each variable can have one of 10 possible values. We can let x be eyebrow slant, y be eye size, z be nose length, etc. The figures below show faces produced using 10 characteristics — head eccentricity, eye size, eye spacing, eye eccentricity, pupil size, eyebrow slant, nose size, mouth shape, mouth size, and mouth opening) — each assigned one of 10 possible values.

Figure 4.39 Example of Face Plot Faces Produced Using 10 Characteristics

Source: Weisstein, Eric W. Chernoff Face. From MathWorld — Wolfram Web Resource. http://mathworld.wolfram.com/ChernoffFace.html.

To convey the messages of epidemiologic findings, you must first select the best illustration method. Tables are commonly used to display numbers, rates, proportions, and cumulative percents. Because tables are intended to communicate information, most tables should have no more than two variables and no more than eight categories (class intervals) for any variable. Printed tables should be properly titled, labeled, and referenced; that is, they should be able to stand alone if separated from the text.

Tables can be used with either nominal or continuous ordinal data. Nominal variables such as sex and state of residence have obvious categories. For continuous variables that do not have obvious categories, class intervals must be created. For some diseases, standard class intervals for age have been adopted. Otherwise a variety of methods are available for establishing reasonable class intervals. These include class intervals with an equal number of people or observations in each; class intervals with a constant width; and class intervals based on the mean and standard deviation.

Graphs can visually communicate data rapidly. Arithmetic-scale line graphs have traditionally been used to show trends in disease rates over time. Semilogarithmic-scale line graphs are preferred when the disease rates vary over two or more orders of magnitude. Histograms and frequency polygons are used to display frequency distributions. A special type of histogram known as an epidemic curve shows the number of cases by time of onset of illness or time of diagnosis during an epidemic period. The cases may be represented by squares that are stacked to form the columns of the histogram; the squares may be shaded to distinguish important characteristics of cases, such as fatal outcome.

Simple bar charts and pie charts are used to display the frequency distribution of a single variable. Grouped and stacked bar charts can display two or even three variables.

Spot maps pinpoint the location of each case or event. An area map uses shading or coloring to show different levels of disease numbers or rates in different areas.

The final pages of this lesson provide guidance in the selection of illustration methods and construction of tables and graphs. When using each of these methods, it is important to remember their purpose: to summarize and to communicate. Even the best method must be constructed properly or the message will be lost. Glitzy and colorful are not necessarily better; sometimes less is more!

References

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Websites