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      A Multi-Site Analysis of the Prevalence of Food Insecurity in the United States, before and during the COVID-19 Pandemic

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      Current Developments in Nutrition
      Oxford University Press
      food security, COVID-19, survey sampling, food insecurity, high-risk

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          ABSTRACT

          Background

          The coronavirus disease 2019 (COVID-19) pandemic profoundly affected food systems including food security. Understanding how the COVID-19 pandemic impacted food security is important to provide support and identify long-term impacts and needs.

          Objective

          The National Food Access and COVID research Team (NFACT) was formed to assess food security over different US study sites throughout the pandemic, using common instruments and measurements. This study presents results from 18 study sites across 15 states and nationally over the first year of the COVID-19 pandemic.

          Methods

          A validated survey instrument was developed and implemented in whole or part through an online survey of adults across the sites throughout the first year of the pandemic, representing 22 separate surveys. Sampling methods for each study site were convenience, representative, or high-risk targeted. Food security was measured using the USDA 6-item module. Food security prevalence was analyzed using ANOVA by sampling method to assess statistically significant differences.

          Results

          Respondents ( = 27,168) indicate higher prevalence of food insecurity (low or very low food security) since the COVID-19 pandemic, compared with before the pandemic. In nearly all study sites, there is a higher prevalence of food insecurity among Black, Indigenous, and People of Color (BIPOC), households with children, and those with job disruptions. The findings demonstrate lingering food insecurity, with high prevalence over time in sites with repeat cross-sectional surveys. There are no statistically significant differences between convenience and representative surveys, but a statistically higher prevalence of food insecurity among high-risk compared with convenience surveys.

          Conclusions

          This comprehensive study demonstrates a higher prevalence of food insecurity in the first year of the COVID-19 pandemic. These impacts were prevalent for certain demographic groups, and most pronounced for surveys targeting high-risk populations. Results especially document the continued high levels of food insecurity, as well as the variability in estimates due to the survey implementation method.

          Abstract

          Multi-site assessment demonstrates widespread food insecurity during COVID-19, especially for households with children, job loss, and Black, Indigenous, People of Color across multiple survey methods.

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          Most cited references57

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          The Early Food Insecurity Impacts of COVID-19

          COVID-19 has disrupted food access and impacted food insecurity, which is associated with numerous adverse individual and public health outcomes. To assess these challenges and understand their impact on food security, we conducted a statewide population-level survey using a convenience sample in Vermont from 29 March to 12 April 2020, during the beginning of a statewide stay-at-home order. We utilized the United States Department of Agriculture six-item validated food security module to measure food insecurity before COVID-19 and since COVID-19. We assessed food insecurity prevalence and reported food access challenges, coping strategies, and perceived helpful interventions among food secure, consistently food insecure (pre-and post-COVID-19), and newly food insecure (post COVID-19) respondents. Among 3219 respondents, there was nearly a one-third increase (32.3%) in household food insecurity since COVID-19 (p < 0.001), with 35.5% of food insecure households classified as newly food insecure. Respondents experiencing a job loss were at higher odds of experiencing food insecurity (OR 3.06; 95% CI, 2.114–0.46). We report multiple physical and economic barriers, as well as concerns related to food access during COVID-19. Respondents experiencing household food insecurity had higher odds of facing access challenges and utilizing coping strategies, including two-thirds of households eating less since COVID-19 (p < 0.001). Significant differences in coping strategies were documented between respondents in newly food insecure vs. consistently insecure households. These findings have important potential impacts on individual health, including mental health and malnutrition, as well as on future healthcare costs. We suggest proactive strategies to address food insecurity during this crisis.
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            Provisional Mortality Data — United States, 2020

            CDC’s National Vital Statistics System (NVSS) collects and reports annual mortality statistics using data from U.S. death certificates. Because of the time needed to investigate certain causes of death and to process and review data, final annual mortality data for a given year are typically released 11 months after the end of the calendar year. Daily totals reported by CDC COVID-19 case surveillance are timely but can underestimate numbers of deaths because of incomplete or delayed reporting. As a result of improvements in timeliness and the pressing need for updated, quality data during the global COVID-19 pandemic, NVSS expanded provisional data releases to produce near real-time U.S. mortality data.* This report presents an overview of provisional U.S. mortality data for 2020, including the first ranking of leading causes of death. In 2020, approximately 3,358,814 deaths † occurred in the United States. From 2019 to 2020, the estimated age-adjusted death rate increased by 15.9%, from 715.2 to 828.7 deaths per 100,000 population. COVID-19 was reported as the underlying cause of death or a contributing cause of death for an estimated 377,883 (11.3%) of those deaths (91.5 deaths per 100,000). The highest age-adjusted death rates by age, race/ethnicity, and sex occurred among adults aged ≥85 years, non-Hispanic Black or African American (Black) and non-Hispanic American Indian or Alaska Native (AI/AN) persons, and males. COVID-19 death rates were highest among adults aged ≥85 years, AI/AN and Hispanic persons, and males. COVID-19 was the third leading cause of death in 2020, after heart disease and cancer. Provisional death estimates provide an early indication of shifts in mortality trends and can guide public health policies and interventions aimed at reducing numbers of deaths that are directly or indirectly associated with the COVID-19 pandemic. CDC analyzed provisional NVSS death certificate data for deaths occurring among U.S. residents in the United States during January–December 2020. The numbers and rates of overall deaths and COVID-19 deaths were assessed by age, sex, and race/ethnicity (categorized as Hispanic, non-Hispanic White [White], Black, non-Hispanic Asian, non-Hispanic AI/AN, non-Hispanic Native Hawaiian or other Pacific Islander [NH/PI], non-Hispanic multiracial, and unknown). Causes of death were coded according to the International Classification of Diseases, Tenth Revision (ICD-10), which describes disease classification and the designation of underlying cause of death ( 1 , 2 ). Numbers and rates of COVID-19 deaths include deaths for which COVID-19 was listed on the death certificate as a confirmed or presumed underlying cause of death or contributing cause of death (ICD-10 code U07.1). COVID-19 was the underlying cause of approximately 91% (345,323) of COVID-19–associated deaths during 2020 ( 3 ). Leading underlying causes of death were calculated and ranked ( 4 ). Deaths that occurred in the United States among residents of U.S. territories and foreign countries were excluded. § Age was unknown for 86 (<0.01%) decedents, and race/ethnicity was unknown for 9,135 (0.27%). There were no records with unknown sex. To describe the trend in deaths during 2020, the number of deaths from all causes and from COVID-19 were calculated for each week. Midyear U.S. Census Bureau population estimates (July 1, 2020) were used to calculate estimated death rates per 100,000 standard population ( 5 ). Age-adjusted death rates were calculated for deaths by sex and race/ethnicity, and crude death rates were calculated by age. Age-adjusted death rates for 2020 were also compared with those from 2019 ( 6 ). In 2020, approximately 3,358,814 deaths occurred in the United States (Table). The age-adjusted rate was 828.7 deaths per 100,000 population, an increase of 15.9% from 715.2 in 2019. The highest overall numbers of deaths occurred during the weeks ending April 11, 2020, (78,917) and December 26, 2020 (80,656) (Figure 1). Death rates were lowest among persons aged 5–14 years (13.6) and highest among persons aged ≥85 years (15,007.4); age-adjusted death rates were higher among males (990.5) than among females (689.2). TABLE Provisional* number and rate of total deaths and COVID-19–related deaths, by demographic characteristics — National Vital Statistics System, United States, 2020 Characteristic No. (rate) † Total deaths COVID-19 deaths § Total 3,358,814 (828.7) 377,883 (91.5) Age group, yrs <1 19,146 (506.0) 43 (1.1) 1–4 3,469 (22.2) 24 (0.2) 5–14 5,556 (13.6) 67 (0.2) 15–24 35,470 (83.2) 587 (1.4) 25–34 72,678 (157.9) 2,527 (5.5) 35–44 103,389 (246.2) 6,617 (15.8) 45–54 189,397 (467.8) 17,905 (44.2) 55–64 436,886 (1,028.5) 44,631 (105.1) 65–74 669,316 (2,068.8) 80,617 (249.2) 75–84 816,307 (4,980.2) 104,212 (635.8) ≥85 1,007,114 (15,007.4) 120,648 (1,797.8) Unknown 86 (—) 5 (—) Sex Female 1,602,366 (689.2) 172,689 (72.5) Male 1,756,448 (990.5) 205,194 (115.0) Race/Ethnicity Hispanic 304,488 (724.1) 68,469 (164.3) White, non-Hispanic 2,467,419 (827.1) 228,328 (72.5) Black, non-Hispanic 443,116 (1,105.3) 59,871 (151.1) Asian, non-Hispanic 90,519 (457.9) 13,334 (66.7) American Indian or Alaska Native, non-Hispanic 24,279 (1,024.0) 4,504 (187.8) Native Hawaiian or other Pacific Islander, non-Hispanic 4,424 (828.4) 679 (122.3) Multiracial, non-Hispanic 15,434 (378.8) 1,125 (31.8) Unknown 9,135 (—) 1,573 (—) * National Vital Statistics System provisional data are incomplete. Data from December are less complete due to reporting lags. These data exclude deaths that occurred in the United States among residents of U.S. territories and foreign countries. † Deaths per 100,000 standard population. Age-adjusted death rates are provided by sex and race/ethnicity. § Deaths with confirmed or presumed COVID-19 as an underlying or contributing cause of death, with International Classification of Diseases, Tenth Revision code U07.1. FIGURE 1 Provisional* number of COVID-19–related deaths † and other deaths, by week — National Vital Statistics System, United States, 2020 * National Vital Statistics System provisional data are incomplete. Data from December are less complete due to reporting lags. Deaths that occurred in the United States among residents of U.S. territories and foreign countries were excluded. † Deaths with confirmed or presumed COVID-19 as an underlying or contributing cause of death, with International Classification of Diseases, Tenth Revision code U07.1. This figure is a bar chart showing the weekly number of COVID-19–related deaths in the United States during 2020. During 2020, COVID-19 was listed as the underlying or contributing cause of 377,883 deaths (91.5 per 100,000 population). COVID-19 death rates were lowest among children aged 1–4 years (0.2) and 5–14 years (0.2) and highest among those aged ≥85 years (1,797.8). Similar to the rate of overall deaths, the age-adjusted COVID-19–associated death rate among males (115.0) was higher than that among females (72.5). Age-adjusted death rates differed by race/ethnicity. Overall age-adjusted death rates were lowest among Asian (457.9 per 100,000 population) and Hispanic persons (724.1) and highest among Black (1,105.3) and AI/AN persons (1,024.0). COVID-19–associated death rates were lowest among multiracial (31.8) and Asian persons (66.7) and highest among AI/AN (187.8) and Hispanic persons (164.3). COVID-19 was listed as the underlying cause of 345,323 deaths during 2020 and was the third leading underlying cause of death, after heart disease (690,882 deaths) and cancer (598,932) (Figure 2). FIGURE 2 Provisional* number of leading underlying causes of death † — National Vital Statistics System, United States, 2020 * National Vital Statistics System provisional data are incomplete. Data from December are less complete due to reporting lags. Deaths that occurred in the United States among residents of U.S. territories and foreign countries were excluded. † Deaths for which COVID-19 was a contributing, but not the underlying, cause of death are not included in this figure. This figure is a bar chart showing the top 10 leading underlying causes of death in the United States during 2020, which were as follows: 1) heart disease, 2) cancer, 3) COVID-19, 4) unintentional injury, 5) stroke, 6) chronic lower respiratory disease, 7) Alzheimer disease, 8) diabetes, 9) influenza and pneumonia, and 10) kidney disease. Discussion During January–December 2020, the estimated 2020 age-adjusted death rate increased for the first time since 2017, with an increase of 15.9% compared with 2019, from 715.2 to 828.7 deaths per 100,000 population. COVID-19 was the underlying or a contributing cause of 377,883 deaths (91.5 deaths per 100,000). COVID-19 death rates were highest among males, older adults, and AI/AN and Hispanic persons. The highest numbers of overall deaths and COVID-19 deaths occurred during April and December. COVID-19 was the third leading underlying cause of death in 2020, replacing suicide as one of the top 10 leading causes of death ( 6 ). The findings in this report are subject to at least four limitations. First, data are provisional, and numbers and rates might change as additional information is received. Second, timeliness of death certificate submission can vary by jurisdiction. As a result, the national distribution of deaths might be affected by the distribution of deaths from jurisdictions reporting later, which might differ from those in the United States overall. Third, certain categories of race (i.e., AI/AN and Asian) and Hispanic ethnicity reported on death certificates might have been misclassified ( 7 ), possibly resulting in underestimates of death rates for some groups. Finally, the cause of death for certain persons might have been misclassified. Limited availability of testing for SARS-CoV-2, the virus that causes COVID-19, at the beginning of the COVID-19 pandemic might have resulted in an underestimation of COVID-19–associated deaths. This report provides an overview of provisional U.S. mortality data for 2020. Provisional death estimates can give researchers and policymakers an early indication of shifts in mortality trends and provide actionable information sooner than the final mortality data that are released approximately 11 months after the end of the data year. These data can guide public health policies and interventions aimed at reducing numbers of deaths that are directly or indirectly associated with the COVID-19 pandemic and among persons most affected, including those who are older, male, or from disproportionately affected racial/ethnic minority groups. Summary What is already known about this topic? The COVID-19 pandemic caused approximately 375,000 deaths in the United States during 2020. What is added by this report? The age-adjusted death rate increased by 15.9% in 2020. Overall death rates were highest among non-Hispanic Black persons and non-Hispanic American Indian or Alaska Native persons. COVID-19 was the third leading cause of death, and the COVID-19 death rate was highest among Hispanics. What are the implications for public health practice? Provisional death estimates provide an early indication of shifts in mortality trends. Timely and actionable data can guide public health policies and interventions for populations experiencing higher numbers of deaths that are directly or indirectly associated with the COVID-19 pandemic.
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              Pandemic precarity: COVID-19 is exposing and exacerbating inequalities in the American heartland

              Significance The 2008 Great Recession widened socioeconomic inequities among young adults, people of color, and those without a college degree. The COVID-19 pandemic raises renewed concerns about inequality. Leveraging pre–post data from a population-representative sample of Indiana residents, we examine employment and food, housing, and financial insecurity. Comparing data before COVID-19 reached the state and during the initial stay-at-home orders, we find socioeconomic shocks disproportionately affecting vulnerable groups, controlling for prepandemic status. Findings are consistent with patterns of inequality observed following other disasters, including Hurricane Katrina, the Chicago Heatwave, the Buffalo Creek Flood, and the Great Recession. As with these disasters, additional surges are likely to escalate short-term hardships, revealing the axes of social devastation that translate into durable inequality.
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                Author and article information

                Contributors
                Journal
                Curr Dev Nutr
                Curr Dev Nutr
                cdn
                Current Developments in Nutrition
                Oxford University Press
                2475-2991
                01 November 2021
                December 2021
                01 November 2021
                : 5
                : 12
                : nzab135
                Affiliations
                Department of Nutrition and Food Sciences, Gund Institute for Environment, University of Vermont , Burlington, VT
                Department of Nutrition and Food Science, Wayne State University , Detroit, MI
                Health Administration & Public Health Department, D'Youville College , Buffalo, NY
                Department of Public Health and Recreation, San José State University , San José, CA
                Department of Nutrition, Food Science, and Packaging, San José State University , San José, CA
                Department of Family and Consumer Sciences, New Mexico State University , Las Cruces, NM
                Department of Nutrition, Dietetics and Food Sciences, Utah State University , Logan, UT
                School of Food and Agriculture, University of Maine , Orono, ME
                Business and Data Analytics, The Greater Boston Food Bank , Boston, MA
                College of Health Solutions, Arizona State University , Phoenix, AZ
                Department of Kinesiology, Auburn University at Montgomery , Montgomery, AL
                Department of Nutrition and Food Sciences, Gund Institute for Environment, University of Vermont , Burlington, VT
                Department of Nutrition and Food Sciences, University of Vermont , Burlington, VT
                Johns Hopkins Center for a Livable Future, Johns Hopkins University , Baltimore, MD
                Business and Data Analytics, The Greater Boston Food Bank , Boston, MA
                Faculty Scholarship Collaborative, College of Liberal Arts and Social Sciences, DePaul University , Chicago, IL
                Health Policy, Management, and Behavior, University at Albany- State University of New York , Rensselaer, NY
                Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University , Baltimore, MD
                Center for Civic Engagement, Binghamton University , Binghamton, NY
                Department of Epidemiology, University of Washington , Seattle, WA
                Institute for Hunger Research & Solutions, Connecticut Food Bank/Foodshare , Bloomfield, CT
                Joseph J Zilber School of Public Health, University of Wisconsin-Milwaukee , Milwaukee, WI
                Department of Plant and Soil Science, University of Vermont , Burlington, VT
                Department of Individual, Family, and Community Education, University of New Mexico , Albuquerque, NM
                Department of Natural Resources, Cornell University , Ithaca, NY
                Department of Environmental and Occupational Health Sciences, University of Washington , Seattle, WA
                Department of Nutrition, Dietetics and Food Sciences, Utah State University , Logan, UT
                College of Nursing, University of Wisconsin-Milwaukee , Milwaukee, WI
                Department of Epidemiology, University of Washington , Seattle, WA
                School of Geography, Development and Environment, University of Arizona , Tucson, AZ
                Department of Environmental Health Sciences, University at Albany- State University of New York , Rensselaer, NY
                Department of Gastroenterology and Nutrition, MassGeneral Hospital for Children , Boston, MA
                Department of Population Medicine and Diagnostic Sciences and Master of Public Health Program, Cornell University , Ithaca, NY
                Alabama Cooperative Extension System, Auburn University , Auburn, AL
                Department of Pharmacy Administration and Public Health, College of Pharmacy and Health Sciences, St. John's University (at the time of study administration) , Jamaica, NY
                Department of Individual, Family, and Community Education, University of New Mexico , Albuquerque, NM
                Department of Population Medicine and Diagnostic Sciences and Master of Public Health Program, Cornell University , Ithaca, NY
                Department of Pharmacy Administration and Public Health, College of Pharmacy and Health Sciences, St. John's University (at the time of study administration) , Jamaica, NY
                Department of Population Medicine and Diagnostic Sciences and Master of Public Health Program, Cornell University , Ithaca, NY
                Joseph J Zilber School of Public Health, University of Wisconsin-Milwaukee , Milwaukee, WI
                Department of International Health, Bloomberg School of Public Health, Johns Hopkins University , Baltimore, MD
                Department of Epidemiology and Biostatistics, University at Albany- State University of New York , Rensselaer, NY
                Department of Environmental and Occupational Health Sciences, University of Washington , Seattle, WA
                Department of Agricultural and Resource Economics, University of Arizona , Tucson, AZ
                Joseph J Zilber School of Public Health, University of Wisconsin-Milwaukee , Milwaukee, WI
                Department of Nutrition, Dietetics and Food Sciences, Utah State University , Logan, UT
                Community and Economic Development, Washington State University , Port Hadlock, WA
                Department of Nutrition and Food Science, Wayne State University , Detroit, MI
                Institute for Hunger Research & Solutions, Connecticut Food Bank/Foodshare , Bloomfield, CT
                Department of Family and Consumer Sciences, New Mexico State University , Las Cruces, NM
                College of Health Solutions, Arizona State University , Phoenix, AZ
                Master of Public Health Program, College of Liberal Arts and Social Sciences, DePaul University , Chicago, IL
                Department of Plant and Soil Science, Gund Institute for Environment, University of Vermont , Burlington, VT
                Department of Environmental Health & Engineering, Bloomberg School of Public Health; Johns Hopkins Center for a Livable Future, Johns Hopkins University , Baltimore, MD
                Center for Public Health Nutrition, University of Washington , Seattle, WA
                College of Health Solutions, Arizona State University , Phoenix, AZ
                Institute for Hunger Research & Solutions, Connecticut Food Bank/Foodshare , Bloomfield, CT
                Department of Environmental and Occupational Health Sciences, University of Washington , Seattle, WA
                Alabama Cooperative Extension System, Auburn University , Auburn, AL
                Hunter College, City University of New York , New York, NY
                Master of Public Health Program, College of Liberal Arts and Social Sciences, DePaul University , Chicago, IL
                Master of Public Health Program, College of Liberal Arts and Social Sciences, DePaul University , Chicago, IL
                Department of Health, Behavior and Society, Bloomberg School of Public Health, Johns Hopkins University , Baltimore, MD
                Department of Epidemiology, University of Washington , Seattle, WA
                School of Management, Binghamton University , Binghamton, NY
                Health, Business, & Professional Services, Tacoma Community College , Tacoma, WA
                Department of Environmental Health Sciences, University at Albany- State University of New York , Rensselaer, NY
                Department of Nutrition, Dietetics and Food Sciences, Utah State University , Logan, UT
                Cooperative Extension, University of Maine , Orono, ME
                Author notes
                Address correspondence to MTN (e-mail: mtniles@ 123456uvm.edu )
                Author information
                https://orcid.org/0000-0002-8323-1351
                https://orcid.org/0000-0002-7919-7103
                https://orcid.org/0000-0003-3272-9317
                Article
                nzab135
                10.1093/cdn/nzab135
                8677520
                34934898
                fceed421-41be-4c2e-8f8d-a163aeeb282f
                © The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 09 August 2021
                : 21 October 2021
                : 29 October 2021
                Page count
                Pages: 18
                Categories
                ORIGINAL RESEARCH
                Community and Global Nutrition
                AcademicSubjects/MED00060

                food security,covid-19,survey sampling,food insecurity,high-risk

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