

Several days ago, we posted a chart that attempted to visualize risk-of-death data from various causes. Though ambitious and interactive, that particular visualization (reproduced after the jump) was criticized as unintuitive and roundly confusing. Readers responded with tons of suggestions and two of you took matters into your own hands, building new charts to look at the data in new ways. Here, we present their efforts.

The data came from the work of Steven Woloshin, Lisa Schwarz and H. Gilbert Welch re-calculating risk data based on gender, age and smoking status. It appeared this week in the Journal of the National Cancer Institute.

First up are two new charts from Robert Kosara, a computer science professor at UNC-Charlotte who runs a blog, Eager Eyes, primarily about visualization. He explains his general approach to the visualization, "In both images, there are three bars for each age, showing these groups in that order. I have added gray bars in the background to group them, but that could clearly use more work."

The two images differ in that one is normalized, while the other presents absolute numbers. In the end, Kosara ended up preferring the normalized image to the left.

"I think this makes the most sense, because it shows how smoking shortens your life, and it also shows that smokers don’t just die from the expected diseases (lung cancer, pneumonia, heart disease), but also tons of others," he wrote.

Dermot Balson, who runs Modelling Excel, also built a set of charts of his own. Balson is an actuary tasked with calculating death risks for a living. His initial charts also employ the "stacked bar" approach, but are broken into a series of smaller charts that can be quickly compared.

"It is difficult to visualize four-dimensional data effectively. In addition, the death rates vary so much by age that if you put them all on a chart, the younger rates will be hard to read because they get squashed so flat," he wrote. "We actuaries have this problem all the time, so I have learned to rescale charts — as you will see here.

Balson also included a second chart, which shows the percentage increase in each cause of death. "This is very effective in showing which causes are most affected, and at what ages," he wrote.

And here is my messy, grandiose chart, with some of the tweaks that readers requested. It shows the risk of death data for men as a time series, in which the time (the big number in the lower right) is actually "year of birth".

I couldn’t make all the requested changes, primarily because the Google widget I used, Motion Chart, doesn’t really allow a lot of customization. So, I could only make a couple of the requested changes: 1) Renaming of the axes 2) Matching the horizontal and vertical dimensions of the graph. I couldn’t figure out how to make the default scale be logarithmic instead of linear. Any tips appreciated.

One thing I’d LOVE to add is cigarette company profit margins/profit/revenue for the years listed, but I couldn’t find that historical data (anyone got a source for that? I’d want it to go back until at least 1950). Voila, the new chart:

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