Data as a storyteller
Multiple mediums can be used to tell a story, such as film or text. However, numbers can provide a quantifiable story in their own right. Datasets can be used to identify trends that emerge in various topics, that a more qualitative method if inquiry could ignore. One such case is that of the rate of obesity in the United States. While obesity is a national problem and the rate is ever increasing, one region in particular seems to be hit exceptionally hard by this health problem. The data shows that southern states rank especially high in regards to their obesity rate. In fact, nine out of the top ten most obese states are located in the southern United States. The only exception is Kansas, which is firmly outside the southern United States according to the geography of Britannica. From looking at the data the other regions of the United States seem to be more varied in their obesity rates depending on the individual state. No other single region is as heavily represented as the Deep South. This implies that there is something within the socioeconomic or cultural factors in the southern states that leads to a higher rate of obesity than in other regions of the country.
Methodology
The data on obesity rates intrigued me as exercising and fitness are hobbies of mine, and I was able to source the relevant data from the local government of Lake County, Illinois via Data.GOV. I used Microsoft Excel in order to build the data out into a pivot chart, fortunately the data was looking at the obesity rate from a state level and there was not a lot that needed to be cleaned up for the purposes of this examination. I sorted the data by the sum of obesity in a descending order. I then noticed that many of the highest rates were in the southern United States. The chart posted above, helps to show the severity of the Deep South’s obesity rate by illustrating the rate being well over 30% in some of those states. Excel made it easy to load a dataset into a table and then turn said table into a chart.
Excel Spreadsheet: