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Food insecurity (FI) is a significant risk factor in malnutrition which can lead to obesity and type 2 diabetes. The association of FI to undernutrition can additionally lead to impaired cognitive development in children. Nearly $100 billion is spent annually on federal nutrition programs yet FI still affects 1 in 8 American households pointing to the urgent need for the further refinement of our national/regional anti-hunger models. One notable and underutilized tool is the community food security assessment (CFA) which seeks to eliminate FI at the local level by improving food access throughout the community. A major limitation in knowledge about CFAs is the dearth of empirical studies of their effectiveness. The principal aim of this dissertation research was to statistically examine secondary data on U.S. counties where CFAs have been conducted and to determine whether they helped reduce individual FI over a two-year, post-test period. Repeated measures of ANOVA across the longitudinal time frame for n=66 counties revealed the main effect of FI was not statistically significant. A majority (56.9%) of 37 counties experienced a decrease in FI over the period. Linear regression found that unemployment was a significant influence in communities that experienced decreases in individual FI at the county level during the pre-test/post-test interval (β = .387 [.067], p<.01). This dissertation found that CFAs can be more effective in areas of higher unemployment as well as geographically where FI is initially higher, however further research is clearly needed in more communities over a longer time period. Also, the study suggests that proper development and structure of state and local-level food policy councils (FPCs) may lead CFAs to find better structure, funding and best practices to become more effective. Overlays prepared with ArcGIS mapping demonstrate that, in general, CFAs are not being performed in areas of highest FI when measured at the county level. The most

Food insecurity (FI) is a significant risk factor in malnutrition which can lead to obesity and type 2 diabetes. The association of FI to undernutrition can additionally lead to impaired cognitive development in children. Nearly $100 billion is spent annually on federal nutrition programs yet FI still affects 1 in 8 American households pointing to the urgent need for the further refinement of our national/regional anti-hunger models. One notable and underutilized tool is the community food security assessment (CFA) which seeks to eliminate FI at the local level by improving food access throughout the community. A major limitation in knowledge about CFAs is the dearth of empirical studies of their effectiveness. The principal aim of this dissertation research was to statistically examine secondary data on U.S. counties where CFAs have been conducted and to determine whether they helped reduce individual FI over a two-year, post-test period. Repeated measures of ANOVA across the longitudinal time frame for n=66 counties revealed the main effect of FI was not statistically significant. A majority (56.9%) of 37 counties experienced a decrease in FI over the period. Linear regression found that unemployment was a significant influence in communities that experienced decreases in individual FI at the county level during the pre-test/post-test interval (β = .387 [.067], p<.01). This dissertation found that CFAs can be more effective in areas of higher unemployment as well as geographically where FI is initially higher, however further research is clearly needed in more communities over a longer time period. Also, the study suggests that proper development and structure of state and local-level food policy councils (FPCs) may lead CFAs to find better structure, funding and best practices to become more effective. Overlays prepared with ArcGIS mapping demonstrate that, in general, CFAs are not being performed in areas of highest FI when measured at the county level. The most