GIS for Public Health

METHODOLOGY

 

Following are the steps that were used in the analysis:

1. Downloaded and prepared the data needed for the analysis.

2. Created classifications and rankings for each factor.

3. Weighted each factor based on the overall score for food insecurity.

4. Determine which block groups are at high risk based on their classification.

 

These steps are explained in detail below.

 

Arrangement and Preparation of the Data

The State of South Carolina has only one state plane zone which is NAD_1983_2011_StatePlane_South_Carolina_FIPS_3900. The entire state of South Carolina was then clipped to our study area which was upstate South Carolina. The counties used in our study area were Spartanburg, Greenville, Pickens, Anderson, and Oconee. Each of the datasets had an original reference system and were projected to the same projection before starting the analysis so as to make sure that all the datasets have same projection.

The factors that we have chosen for this project are:

    a) Average Consumer Spending on food

    b) Accessibility to food

    c) Poverty level an

    d) Food stamps

 

Classification and Ranking of factors

The ranking of the factors was done in the ascending order starting from 1 to 10,

1 indicates less insecure and 10 indicates the most insecure block groups.

 

1. Average Consumer Spending on food​

This data was provided by Esri, Bureau of Labor Statistics and was used to look at consumer

spending on how much people spend on food at block group level of the counties in our

study area. The variables considered were total spending on food away from home, on

fast food restaurant, and on fresh fruits vegetables. Once we got all the variables we

clipped and then joined it to Upstate South Carolina. Then, we classified the each block

group on the basis of spending on food variables. Following are the classifications:

 

 

 

 

 

 

 

 

 

 

 

 

• Average Spending on Food away from home per household

In classifying this variable the more importance was given to the block group where spending was the greatest which is more the spending

on food away from home more is the food insecurity.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

• Average Spending on Fresh fruits and vegetables per household.

In classifying this variable the more importance was given to the block group where spending was the lowest which is less the spending on fresh fruits and vegetables more is the food insecurity. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

2. Average Consumer Spending on food​

The accessibility to food was considered as an important factor in analyzing the food insecurity in this project. We decided to look to use the farmer markets data, the available restaurants and grocery stores etc. and density of the streets and highways.

 

• Farmer’s Markets

The farmer’s markets data was obtained from the United States Department of Agriculture. The points were then geocoded using USA address points then clipped to upstate South Carolina. We created a trade area for farmer markets using Business Analyst to get the drive time access for these markets. Driving times of 10, 20, and 30, 40, 50, 60, and over 60 minutes were chosen to determine which area of the upstate would be considered food deserts. The more the distance to the markets more insecure the area is. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

• Food Facilities

We were able to acquire the food facility data from the Division of Food Protection, Bureau of Environmental Health found on American Fact Finder. The density of the food facilities was calculated by doing spatial join in counting the number of restaurants per block group. The less the food facilities per block group more food insecure that block group is which means people have more accessibility to fast food. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

• Streets and Highways

Esri had the streets and highways data. With this we summarized both the streets and highways to determine the length of each and find the density for each street and highway per each block group. With this we will then look at the area for each block group and then determine which block group has the most streets or highways going through it to allow for more accessibility to the farmer’s markets and food facilities. The more the number of streets and highways in the block group less is the food insecurity. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3. Poverty Level

We were able to get this data from ACS which provided us with the total number of household in each block group and the number of household living below poverty level. To get the poverty level per household we divided the number of household living under poverty by total number of household in that block group. The higher the value we got more food insecure that block group is. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

4. Food Stamps

We got this data from ACS which provided us with the total number of household in each block group and the number of household receiving food stamps. To get the food stamps per household we divided the number of household receiving food stamps by total number of households in that block group. The higher the value we got more food insecure that block group is.