Disciplines
Applied Statistics | Biology | Community Health and Preventive Medicine | Data Science | Dietetics and Clinical Nutrition | Health and Medical Administration | Public Health Education and Promotion | Quality Improvement | Statistical Methodology
Abstract (300 words maximum)
In 2010, the United States Department of Agriculture (USDA) reported that 23.5 million people in the United States live in food deserts. As defined by the USDA, a “food desert” is a neighborhood that lacks healthy food sources. This can be measured by distance to a store, number of stores in an area, individual-level resources such as family income or vehicle availability, and neighborhood-level resources such as availability of public transportation. Past research provides evidence that food deserts are especially likely to occur in communities heavily populated by minorities. As a Black Indian pre-med student aiming to join the world of healthcare innovation, I am passionate about factors that affect the quality of life for commonly disenfranchised communities. However, are there more factors than race to predict the demographics of where a food desert will occur?
The Food Access Research Atlas provided by the USDA provides census tract information for the state of Georgia. I analyzed 1,965 census tracts with roughly 4000 people in each. Variables include population size, median family income, poverty rate, low vehicular accessibility, and demographics of seniors, children and ethnic groups.
I will investigate the following relationships. Are rural areas more likely to be food deserts? Are certain counties in Georgia more likely to be food deserts? Are low-income census tracts more likely to be associated with food deserts? Are the poverty rates and median incomes the same for census tracts that are classified as food deserts and not? The methods used to investigate these relationships included both nonparametric and parametric hypothesis tests with corresponding post hoc comparisons. Stratified box plots and stacked bar charts will be used to display these findings. Is there more than race to tell the story of food deserts? Insights into these relationships may foster new ideas to solve the problem.
Academic department under which the project should be listed
CCSE - Data Science and Analytics
Primary Investigator (PI) Name
Susan Mathews Hardy
Included in
Applied Statistics Commons, Biology Commons, Community Health and Preventive Medicine Commons, Data Science Commons, Dietetics and Clinical Nutrition Commons, Public Health Education and Promotion Commons, Quality Improvement Commons, Statistical Methodology Commons
Food Deserts: Hungry for Answers
In 2010, the United States Department of Agriculture (USDA) reported that 23.5 million people in the United States live in food deserts. As defined by the USDA, a “food desert” is a neighborhood that lacks healthy food sources. This can be measured by distance to a store, number of stores in an area, individual-level resources such as family income or vehicle availability, and neighborhood-level resources such as availability of public transportation. Past research provides evidence that food deserts are especially likely to occur in communities heavily populated by minorities. As a Black Indian pre-med student aiming to join the world of healthcare innovation, I am passionate about factors that affect the quality of life for commonly disenfranchised communities. However, are there more factors than race to predict the demographics of where a food desert will occur?
The Food Access Research Atlas provided by the USDA provides census tract information for the state of Georgia. I analyzed 1,965 census tracts with roughly 4000 people in each. Variables include population size, median family income, poverty rate, low vehicular accessibility, and demographics of seniors, children and ethnic groups.
I will investigate the following relationships. Are rural areas more likely to be food deserts? Are certain counties in Georgia more likely to be food deserts? Are low-income census tracts more likely to be associated with food deserts? Are the poverty rates and median incomes the same for census tracts that are classified as food deserts and not? The methods used to investigate these relationships included both nonparametric and parametric hypothesis tests with corresponding post hoc comparisons. Stratified box plots and stacked bar charts will be used to display these findings. Is there more than race to tell the story of food deserts? Insights into these relationships may foster new ideas to solve the problem.