Food Insecurity Rate

Data were obtained from Feeding America, Map the Meal Gap Dataset. There is a two-step methodology for addressing overall food insecurity rates across counties. First, they constructed a model utilizing state-level data from 2009 to 2021, encompassing variables like unemployment, poverty, median income, household ethnicity, homeownership, and disability. Additionally, they employed the Core Food Security Module (CFSM) from the CPS, considering affirmative responses to three or more questions for identifying food-insecure households. This model incorporates fixed effects for state and year to control for latent influences. In the second step, they employ coefficient estimates from the first step and county-level data to estimate food insecurity rates and the number of food-insecure individuals per county. For more information on the methodology and calculations, please visit the source's site here.

Data were obtained from Feeding America, Map the Meal Gap Dataset. Their methodology to assess child (children under age 18) food insecurity rates at county and congressional district levels closely parallels that of the general population. They tailor variables to households with children and make exceptions for unemployment and disability variables. Child food insecurity is defined based on the measure "children in food-insecure households," which involves households affirming at least three of 18 questions from the CFSM in the CPS. We calculate the food insecurity rate as the ratio of such children to the total children in the area. Additionally, we estimate the proportion of children in food-insecure households above and below 185% of the federal poverty level, illuminating income eligibility for free or reduced-price school meals. For more information on the methodology and calculations, please visit the source's site, pages 11-13.

Data were obtained from Feeding America, Map the Meal Gap Dataset. Percentage of food-insecure households that meet the criteria for SNAP eligibility. A two-step method is employed for the overall population, limiting the sample to specific income ranges while keeping UN, BLACK, HISP, OWN, and DISBL variables defined for all individuals. With these variables available only at all income levels in the ACS, they derive estimates based on households below distinct thresholds. Using these figures, they identify the number of food-insecure individuals with incomes under the SNAP threshold and calculate the number above it. This is demonstrated with an illustrative example for clarity. They adapt these procedures to estimate SNAP eligibility in congressional districts and eligibility for subsidized school meals among food-insecure children. For more information on the methodology and calculations, please visit the source's site here.

Data were obtained from Feeding America, Map the Meal Gap Dataset. Their methodology employs a two-step approach and estimates food insecurity rates among diverse racial/ethnic groups within county and congressional district contexts. Initially, individuals are categorized by household based on race/ethnicity using responses from the Current Population Survey (CPS). By combining this data with Bureau of Labor Statistics (BLS) unemployment data, they model the relationship between food insecurity and variables like poverty rate, unemployment rate, median income, homeownership rate, and disability rate. They then apply the resulting coefficients to American Community Survey (ACS) data at the local level, estimating subgroup-specific food insecurity rates. This approach acknowledges data limitations, incorporates confidence intervals to quantify uncertainty, and highlights the intersection of racial/ethnic disparities and hunger for effective policy formulation.

For more information on the methodology and calculations, please visit the source's site here.