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Amber Todd


Objective: This research study aims to determine the impact of food insecurity and healthy food availability in the state of Ohio. It investigates how food insecurity in Ohio has changed between 2016 and 2020. It also investigates how food insecurity correlates with education level by looking at high school graduation rates. It also investigates how Ohio, a state with a high level of food insecurity, compares to California which has low levels of food insecurity. This study also compares how food insecurity differs in rural and urban counties throughout the state of Ohio.

Methods: ANOVA with posthoc will be conducted to show how food insecurity rates changed in Ohio between 2016 and 2020. Unpaired t-tests will be used to compare the levels of food insecurity in rural and urban counties in Ohio. They will also be used to compare food insecurity and healthy food availability in Ohio and California. A Pearson correlation will be conducted to determine if a correlation exists between food insecurity and high school graduation rates in the state of Ohio. A stepwise linear regression will be used to determine how previous food insecurity rates can predict variance in food insecurity rates in Ohio.

Results: ANOVA with posthoc demonstrated multiple significant differences in food insecurity rates between 2016-2020. A Pearson correlation demonstrated a negative correlation of -0.659 with a p value < .001 between high school graduation rates and food insecurity rates in 2020. An unpaired t-test demonstrated a significant difference between food insecurity and healthy food availability between Ohio and California in the year 2020 with a p value < .001. Another unpaired t-test showed no statistical difference between food insecurity rates in rural vs. urban Ohio counties in 2020. A linear regression demonstrated that 97.8% and 97.7% of the variance in Ohio food insecurity rates in 2020 can be accounted for by 2016 and 2019 food insecurity rates.

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