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Would you like fries with your Bubble Plot?

by Amanda Shankle-Knowlton on Wednesday, February 16, 2011 3:38 PM

I was on the drive to work this morning and thought “I want to make a bubble plot!” Luckily, I was able to contain my enthusiasm and arrive at work without running any red lights. 

However, I did not know what information I wanted to show in my bubble plot. I’ve seen Hans Rosling present quite a few bubble charts, so using some kind of country data or US State data seemed like a natural choice. Then I remembered several news stories I heard or read early this morning. Food prices are rising. My state of Oklahoma is “on pace to lead the nation in obesity”. And apparently a study suggests that prominently posting calorie counts in fast food restaurants doesn’t really change eating habits. 

Depressing news, no doubt. But what’s the solution? 

To come up with solutions, it’s a good idea to understand your problem. 

So I grabbed some data on obesity from the Centers for Disease Control and Prevention that is broken down by state for 2009. I frequently hear that obesity is correlated with income levels, but I wanted to see it myself. So I pulled some 2009 income estimate information from the US Census bureau. And because my intention was to make a bubble plot, I found 2009 Census population estimates and used this for the “weight” variable in the plot.


As you can see, the populous states of Texas and California have the largest bubbles in the plot. The relationship here is fairly strong. Mississippi and Louisiana have the highest percentage of obesity and they are on the far left side of the graph (median income below $45,000). Colorado and Connecticut are the least obese states, and they are on the far right (median income of $60,000 or above). 

So where do we go from here? We can’t make any conclusions based on this graph alone, but it gives us some things to investigate. Why are the poor states also the most obese states? Are they obese because they are poor, are they poor because they are obese, or are there other variables at play such as culture/tradition or availability of information? 

I’d also like to look into why Montana has income levels similar to Louisiana, but less than a 24% obesity rate.   

I’ll Google that after lunch. For some reason, I’m feeling compelled to get a salad, lowfat dressing on the side. 

Note: If you’d like a copy of the spreadsheet I used to generate this plot, please email me.

Image Credit: Obesity Epidemic?



Amanda Shankle-Knowlton

Your data are speaking. Are you listening? A graph can help you find hidden patterns, and may also be able to tell a story better than a whole paper full of words. Please join me as I explore the world using pictures.


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