Food insecurity by race/ethnicity in South Carolina

For the second year as part of the 2023 release, Map the Meal Gap includes food insecurity estimates disaggregated by race and ethnicity for some groups: people who identified themselves as Black (all ethnicities), Latino or Hispanic (all races), and white non-Hispanic in the federal data used in the study. Due to constraints with the available federal data, we assumed that the race or ethnicity of the household respondent matched the race/ethnicity of all members of the household when calculating these numbers. We have included these estimates to further illuminate the relationship that food insecurity has to racism and structural oppression, and we believe developing effective strategies to reach people at risk of hunger requires access to the numbers that reflect the experiences of specific populations.

While all local estimates within the Map the Meal Gap study are approximations, it should be noted that the estimates for specific race or ethnicity groups are less certain than the overall population level estimates due to smaller sample sizes. At this time, we have opted to exclude the estimated number of people experiencing food insecurity by race or ethnicity and are sharing only rates that have been rounded. We have made this decision to avoid conveying a false sense of precision and to encourage users of the data to focus on relative disparities, both within and across geographies. Additionally, we wish to emphasize that these data are directional and should be considered in conjunction with other local data as well as insights from the individuals who live in these communities. 

At this time, results are not available for individuals who identify as Asian, Native American, Pacific Islander, or multiple races. There are two main reasons this is the case. First, these populations are smaller in size, and there are not enough observations in the Current Population Survey to allow us to generate reliable estimates. Secondly, because our approach for producing local estimates relies on having local data by race/ethnicity for all of the drivers of food insecurity (i.e., unemployment, poverty, etc.), unavailability of these federal data further prevents us from creating these estimates.