Abstract

BackgroundFood insecurity impacts 13.5 million US households yearly. Although food security instability (FS-I) can have many temporal presentations, these are not measured in the current US Household Food Security Survey Module. ObjectiveExplore sociodemographic and chronic disease correlates of 4 FS-I types (chronic, seasonal, intramonthly, and intermittent) using a 3-item US Household Food Security Survey Module instability supplement. DesignThis study was a secondary analysis of cross-sectional survey pilot data collected to validate the US Household Food Security Survey Module instability supplement. Participants and settingAdults at risk for food insecurity (n = 420) were recruited and answered the survey on their households’ behalf from April to June 2021. The participants were recruited from 7 community organizations from 5 states (California, Florida, Maryland, North Carolina, and Washington). Main outcome measuresThe main outcomes were the odds of having a chronic, seasonal, intramonthly, or intermittent FS-I score ≥1 based on several sociodemographic factors and having ≥1 chronic disease. Statistical analyses performedDifferences among the 4 FS-I types were analyzed using contingency tables and χ2 tests of independence. Then, mixed-effects logistic binary and conditional regressions were run for each FS-I type using clustering by state and odds ratios and 95% CI to interpret results. ResultsThe most common FS-I type experienced by the sample was intramonthly (n = 183 [43%]). Nonchronic food insecurity was most likely to happen during the winter, at the end of the month, or randomly with no certain time frame. FS-I in any form was associated with low income, chronic FS-I was associated with younger age and male sex, seasonal FS-I was associated with having no government-subsidized health insurance and females, intramonthly FS-I was associated with participation in nutrition assistance programs, and intermittent FS-I had lower odds among Hispanic/Latino households. ConclusionsFurther research is needed to explore other FS-I correlates and establish causative relationships; however, these results can be used with clinical judgment for targeted food insecurity screening and treatment.

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