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      Racial/Ethnic Disparities in Household Food Insecurity During the COVID-19 Pandemic: a Nationally Representative Study

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          Abstract

          Previous research has demonstrated that the burden of household food insecurity is disproportionately high among racial/ethnic minority groups, yet no peer-reviewed studies have systematically examined racial/ethnic disparities in household food insecurity in the context of the COVID-19 pandemic. This cross-sectional study on household food insecurity during COVID-19 used data from a nationally representative sample of US households through the 2020 Household Pulse Survey (HPS) (including all 50 states and the District of Columbia, n = 74,413 households). Six generalized estimating equation (GEE) models were estimated, and the results indicated that households headed by Blacks, Asians, Hispanics, or other racial/ethnic minorities were not significantly more food insecure than White households during the pandemic. However, among food-insecure households, Black households were more likely to report that they could not afford to buy more food; Asian and Hispanic households were more likely to be afraid to go out to buy food; Asian households were more likely to face transportation issues when purchasing food; while White households were more likely to report that stores did not have the food they wanted. Moreover, racial/ethnic minorities were significantly less confident about their household food security for the next 4 weeks than Whites. The coronavirus pandemic crisis has exposed and exacerbated the food injustice in American society. Policymakers and local officials should take concerted actions to improve the capacity of food supply and ensure food equality across all racial/ethnic groups.

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          Most cited references48

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          Longitudinal data analysis using generalized linear models

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            Longitudinal Data Analysis for Discrete and Continuous Outcomes

            Longitudinal data sets are comprised of repeated observations of an outcome and a set of covariates for each of many subjects. One objective of statistical analysis is to describe the marginal expectation of the outcome variable as a function of the covariates while accounting for the correlation among the repeated observations for a given subject. This paper proposes a unifying approach to such analysis for a variety of discrete and continuous outcomes. A class of generalized estimating equations (GEEs) for the regression parameters is proposed. The equations are extensions of those used in quasi-likelihood (Wedderburn, 1974, Biometrika 61, 439-447) methods. The GEEs have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. A consistent variance estimate is presented. We illustrate the use of the GEE approach with longitudinal data from a study of the effect of mothers' stress on children's morbidity.
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              COVID-19 risks to global food security

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                Author and article information

                Contributors
                xdeng2@utep.edu
                smorales12@miners.utep.edu
                tfbeltran@miners.utep.edu
                Journal
                J Racial Ethn Health Disparities
                J Racial Ethn Health Disparities
                Journal of Racial and Ethnic Health Disparities
                Springer International Publishing (Cham )
                2197-3792
                2196-8837
                14 October 2020
                : 1-15
                Affiliations
                GRID grid.267324.6, ISNI 0000 0001 0668 0420, Department of Sociology and Anthropology, , The University of Texas at El Paso, ; 500 W. University Ave., El Paso, TX 79968 USA
                Author information
                http://orcid.org/0000-0002-0642-0378
                Article
                892
                10.1007/s40615-020-00892-7
                7556612
                33057998
                bd62509b-9e1d-40e7-a289-43151d82fd79
                © W. Montague Cobb-NMA Health Institute 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 27 July 2020
                : 28 September 2020
                : 4 October 2020
                Categories
                Article

                food insecurity,race/ethnicity,household pulse survey,covid-19

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