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An Analysis of the 100 Worst US Metropolitan Areas to Live with Spring Allergies

It’s that time of year. The birds are headed back north and the sun is shining brighter than ever. Even when it rains, a lingering smell of life breeds excitement for the months to come. Each drop grows flowers, brightens grass, and brings green life back to the trees. All of these things concerting in harmony are nature’s way of reminding us that the world is not dead, willing us to finally come out from under our blankets of crippling seasonal depression.

Unfortunately, for anyone who suffers from seasonal allergies, those same beautiful reminders that spring has sprung take on a very different connotation and create a sordid relationship with their arrival. The Asthma and Allergy Foundation of America (AAFA) estimates that more than 50 million Americans are living with seasonal nasal allergies (allergic rhinitis). This prompted an annual study conducted by the AAFA to determine the 100 worst metropolitan areas to live for spring allergy sufferers using three metrics to quantify “suffering”:

  • Because seasonal allergies in the spring are most commonly caused by pollen and mold spores, the AAFA used the pollen score for each metropolitan area that is created by the American Academy of Allergy, Asthma and Immunology (AAAAI).
  • Allergy medication purchases in each metropolitan area
  • The availability of board-certified allergists in each metropolitan area

An overall score was calculated using these three scores (at the risk of being too kitschy, I refer to this score as a suffer score). It was then used to compare all metropolitan areas, creating a list of the 100 worst nationwide.

When I stumbled upon this information, I thought it might be interesting to plot these metropolitan areas on a map of the US and compare them to one another (and it was!). With the help of some light analysis already conducted by the AAFA, I decided to create two different maps to showcase a few aspects of the dataset they created. Here’s the result!

Screen Shot 2016-06-15 at 11.12.02 AMFigure 1: 100 Worst Metropolitan Areas to Live with Spring Allergies, 2016

This map was fun to create. Each point on the map represents a different metropolitan area. The color of each point indicates whether a metropolitan area’s suffer score was above average, average, or below average when compared to all 100 metropolitan areas. Detroit and Grand Rapids are the only two Metropolitan Areas in Michigan that made the list. Although Detroit’s ranking increased 11 positions and Grand Rapids increased 3 since 2015, they both still rank near average on a national scale.

As we can see, many of the metro areas with an above-average suffer score are primarily located in the south moving north into the northeast. This makes sense considering the parameters used to define this dataset. Several of the worse-than-average suffer score areas lie within regions with high pollen scores and a climate that strongly supports mold spore growth.  HERE, you can find an NPR interview with Dr. Estelle Levetin from 2010 wherein she elaborates in more detail why that makes sense.

It’s important to keep in mind that the context of a suffer score is somewhat counter-intuitive: i.e., a below-average suffer score is a good thing (or at least better than an above-average suffer score)! Also, in order to achieve the final outcome of both maps, I converted a polygon shapefile of US metropolitan areas into a point shapefile. Because of this, some points appear to be slightly misplaced. This occurred because each point is actually representing a larger, abnormally-shaped area.

Figure 2: 100 Worst Metropolitan Areas to Live with Spring Allergies, by Region, 2016Screen Shot 2016-06-15 at 11.12.45 AM

This map offers insight into the ranking of each Metropolitan Area’s suffer score compared to its region. Each point on the map represents a Metropolitan Area and the color of the point represents a hierarchy of suffer score rankings. This hierarchy is then applied to each of the four US regions. The results are as follows:

South: This region holds 38 of the 100 metropolitan areas (38.0%). Of those 38, 10 have a suffer score that is worse than average (26.3%).

West: This region holds 23 of the 100 metropolitan areas (23.0%). Of those 23, none of them have a suffer score that is worse than average (0%).

Midwest: This region holds 21 of the 100 metropolitan areas (21.0%). Of those 21, 5 have a suffer score that is worse than average (23.8%).

Northeast: This region holds 18 of the 100 metropolitan areas (18.0%). Of those 18, 3 have a suffer score that is worse than average (16.7%).

It became apparent the moment I stumbled upon this dataset that there were several interesting things I could do with it. By the time my mind stopped racing in all directions, I had landed on five different analyses I wanted to depict. Unfortunately, I also had no concept of how long each one would take. This resulted in two maps with the potential of being completed before it was no longer spring and three maps of great promise, but no realistic life expectancy. Sad as it were, I am going to explain the concept of my favorite map that never came to be in my final section titled…

Figure 3 (Not Pictured). The Map That Got Away

The concept of this map was built upon a comparison between each metropolitan area’s overall rankings from 2015 to 2016. At first, I didn’t expect much difference in a one-year timeframe. Five years? Maybe. After a quick calculation, there were some serious trends that formed. My map was going to showcase the five areas whose conditions improved the most and the five areas where conditions declined the most. Even in just those 10 areas, there was a pattern that began to form. Areas of improvement trended in the south and areas of decline trended in the eastern Midwest and western Northeast. It would have been cool to visualize this comparison when applied to all 100 areas. Luckily, the AAFA conducts a similar study in the fall giving me ample time to prepare. I am looking forward to working more with similar data sets!