The goal of this preliminary tutorial was to create a single hot spot map of heart disease in the southeastern USA and solidify integral GIS analytical skills. The temporal scale of this analysis was from 1999 to 2016, where a time series was created with maps from each year. I chose 2016 to focus my report on because it is the most recent year available from this dataset.
As you can see from the map above, the largest concentration of heart disease is within Oklahoma and significant hot spots also located in Arkansas, Louisiana, and Mississippi. The most significant cold spots located in Texas, Maryland, and Virginia. The general pattern that seems to arise, with Florida as an exception, are hot spots are based inland while cold spots seem to crop up near coastlines. One of the more interesting aspects of this map is that there is an extremely large concentration of heart disease hot spots within Oklahoma running along its border with Texas, but that trend does not spillover across state lines. This hard border likely means that there is a deeper underlying reason and perhaps another correlating factor missing that would further explain these effects, such as insufficient state healthcare, inadequate number of healthcare facilities, lack of childhood education on diet and exercise, or even food desert density to name a few. However, it is important to note that this hot spot analysis was derived from the mean of these 16 states, so it only shows a regional trend not a country-wide trend.
To do this analysis data on mortality by heart disease data per county was obtained from CDC Wonder. One of the most important lessons here was how to correct for numbers that are the same numerically but are different as text (i.e. “1003” and “01003”). This problem is quite small and detail oriented, so being aware of it as an issue will result in faster problem solving in the future. Another important aspect was using Feature Datasets as repositories of data so to create multiple outputs. I had never actually done this, so I was introduced to it and using field calculator to extract particular field IDs into a Feature Dataset in the geodatabase. I had some difficulties with getting this tutorial to work properly, but what seemed to solve the issue was patience and closing and reopening the program multiple times. One might even call me an expert troubleshooter.