Using a new method of measuring community food security to inform practice and policy

1)INTROUDCTION: This study extends the knowledge of food security beyond sociodemographic predictors to include food environment indicators (access to food stores, availability of various food stores, affordability, availability and use of public and private food assistance programs, and local food production). 2)METHODS: Secondary data was analyzed from the USDA Food Environment Atlas and the American Community Survey for 114 counties in a Midwest state. A validated model estimation technique was used to estimate county level food insecurity based on nine state-level sociodemographic predictors and USDA food security rates. A PCA was used to reduce the food environment data into components. Extracted component scores were used to 1) identify the most important food environment predictors, and 2) produce estimates of community food insecure households. 3)RESULTS: The PCA reduced the data from 46 to 22 indicators. Six components (food programs, access, agricultural production, direct farm sales, program usage, affordability and availability) were retained, accounting for 76.43% of variance. The model explained 58.7% of variance of community food security. Availability and affordability contributed the most, followed by program usage, access, and agricultural production. Transportation limitations and distance to food stores were risk factors. Housing affordability protected communities. Low community food insecure counties distributed more emergency food and had more Community Supported Agriculture (CSA) programs. 4)DISCUSSION: This method for measuring community food security allows a way to conceptualize systems components that can be manipulated through interventions. Examples include increasing affordable housing stock, piloting a CSA program, improving public transportation, or increasing emergency food supplies.