Gapminder Activity

Gapminder is a tool to produce visually appealing, dynamic graphs that are capable of displaying multiple data sets in a comprehensive manner. This holds potential for use on population studies at the global level to monitor multiple variables over time.   It would be useful to be able to modify the world map to more specific localities for localized population studies.

Our activity today centered around the use of Gapminder to monitor different global population trends of cancer with respect to income over time. We went to

Gapminder

and tinkered with changing axis variables and watching the changes over time by going to:

  • Health<Cancer, lung < lung cancer, new cases for every 100,000 women

And comparing to every 100, ooo men for lung cancer, liver cancer, and colon & rectum cancers.

Looking at the graphs, we noted some of the variable visualizations. Countries are represented as dots that vary in diameter based on population and in color based on which continent they belong to.

Moving from one cancer type and gender to the next, we noticed a few trends:

  • new cases of lung cancer appear to increase with increased income in both men and women, generally existing at higher rates in men
  • new cases liver cancer have little/no apparent correlation with increased income in either gender
  • new cases of colon & rectum can show an increase with increased income in both men and women

Since only the Nordic countries of Finland, Sweden, and Norway had significant data available from years prior to 2002, it is not possible to see global population trends over time. The trends that we do see likely have explanations in socio-economic factors specific to different populations. For example, while lung cancer shows a correlation with income, the most affluent countries do not necessarily have the most new lung cancer cases. This could be linked to the varying social statuses of smoking in different cultures as well as to other air quality factors, like the burning of coal for fuel in northern European countries.

Next, we toggled the lin (linear) and log (logarithmic) settings on both the x- and y-axes. Setting both axes to lin displays bunched data with few decipherable relationships. By forming a semi-log graph (one axis log and one axis lin), data is spread to reveal trends. It is even more widely spread with the use of a log graph (both axes log).

The secrets of Gapminder have been unlocked! This is a tool with the intriguing abilities  to hold many levels of data in a visually stimulating, dynamic way.  Enhanced by the use of changeable axes and movement over time in addition to country, continent, and population information, this program holds much potential for use with various population studies.