Continuing my latest pursuit of data visualization exploration of health risk factors, it didn’t occur to me until after I had finished my animated scatter plot of sugar – BMI correlation that I could have done a static visual representation of that with a connected scatter plot. In these connected scatter plots, each dot represents a year for a country’s sugar consumption (x axis) and Body Mass Index (BMI) (y axis) and connecting the dots for a country results in a trail of their history for those variables.

Most connected scatter plots I’ve seen usually focus on one “trail” of data points. Representing 14 distinct countries in this visualization resulted in jumbled mess of dots and lines in the middle of the chart where most of the EU countries data sits. As a result, I decided to export multiple plots – small multiples – highlighting each EU country plus another to highlight the US and Canada.

US and Canada Connected Scatter Plot of Sugar Consumption to Average Body Mass Index – 1980 – 2004

Connected-Scatterplot-US-CA-01

Notice how Canada tracked with most EU countries for the first decade or so, but then broke free from emulating the EU and joined the US in a rapid rise in sugar consumption.

European Nations Connected Scatter Plots of Sugar Consumption to Average Body Mass Index – 1980 – 2004

For the 12 western EU nations represented in the data set, here’s a gallery of small multiples. Click on an image to see the full size.

 

For those interested in learning more about connected scatter plots, check out Alberto Cairo’s article, In praise of connected scatter plots.