Food insecurity and COVID-19 food-related perceptions practices and problems: A three-state descriptive study

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food-insecurity-and-covid-19-food-related-perceptions-practices-and-problems-a-three-state-descriptive-study.pdf (330.84 KB)

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https://www.cambridge.org/core/journals/disaster-medicine-and-public-health-preparedness/article/food-insecurity-and-covid19-foodrelated-perceptions-practices-and-problems-a-threestate-descriptive-study/D15AA3CC414E3CEE2BB0112D15984253

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https://doi.org/10.1017/dmp.2022.250
 http://hdl.handle.net/11603/26375

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UMBC Emergency and Distaster Health Systems
UMBC Faculty Collection

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https://orcid.org/0000-0001-6035-6920
 https://orcid.org/0000-0003-3334-9666

Date

2022-11-03

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journal articles
postprints
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Citation of Original Publication

Koyratty, Nadia, Lauren Clay, Samantha Penta, and Amber Silver. "Food Insecurity and COVID-19 Food-related Perceptions Practices and Problems: A Three-state Descriptive Study." Disaster Medicine and Public Health Preparedness, 2022, 1-24. doi:10.1017/dmp.2022.250.

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This accepted version of the article may differ from the final published version. This is an Accepted Manuscript for Disaster Medicine and Public Health Preparedness as part of the Cambridge Coronavirus Collection. © 2022 Society for Disaster Medicine and Public Health, Inc.
Access to this item will begin on 05-03-2023

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Abstract

Objective: To compare food insecurity (FI) risk, and food-related COVID-19 infection risk perceptions, practices, and problems (3P) in Washington (WA), New York (NY) and Louisiana (LA). Methods: Data from the RAPID Multi-Wave Risk Perception Study was collected via online surveys between 19 May to 14 July 2020 (N=1260). Multivariable-adjusted logistic and ordinal regressions were performed for odds of FI risk and 3P during these early months of the pandemic. Results: The determinants of FI risk in all states included income, age, and employment. Some determinants were state-specific: households with members at high risk for COVID-19 (WA and NY), ethnicity (NY), education and relationship status (LA). The odds of FI risk were higher among those who perceived higher likelihood of COVID-19 infection via in-store shopping (OR=1.34, 95%CI: 1.06, 1.70), and improperly cooked food (OR=1.87, 95%CI: 1.46, 2.41). FI risk was associated with higher odds of problems related to food affordability (OR=10.66, 95%CI: 7.87, 14.44), preference (OR=2.51, 95%CI: 1.86, 3.39), sufficiency (OR=2.63, 95%CI: 1.96, 3.54), food sources (OR=7.68, 95%CI: 5.73, 10.31), food storage capacity (OR=0.48, 95%CI: 0.36, 0.66), and knowing where to find help in obtaining food (OR=7.68, 95%CI: 5.73, 10.31), most of which did not differ by state. No association was found between food insecurity risk and food-related practices. Conclusion: Better food preparedness is needed to reduce FI risk during pandemics in specific groups in WA, NY, and LA. Specifically, food affordability, sufficiency, storage, sources and increasing knowledge on food programs are limitations that need to be addressed for emergency situations.