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Objectives. To examine the impact of COVID-19 shutdowns on food insecurity among a predominantly African American cohort residing in low-income racially isolated neighborhoods. Methods. Residents of 2 low-income African American food desert neighborhoods in Pittsburgh, Pennsylvania, were surveyed from March 23 to May 22, 2020, drawing on a longitudinal cohort (n = 605) previously followed from 2011 to 2018. We examined longitudinal trends in food insecurity from 2011 to 2020 and compared them with national trends. We also assessed use of food assistance in our sample in 2018 versus 2020. Results. From 2018 to 2020, food insecurity increased from 20.7% to 36.9% (t = 7.63; P < .001) after steady declines since 2011. As a result of COVID-19, the United States has experienced a 60% increase in food insecurity, whereas this sample showed a nearly 80% increase, widening a preexisting disparity. Participation in the Supplemental Nutrition Assistance Program (52.2%) and food bank use (35.9%) did not change significantly during the early weeks of the pandemic. Conclusions. Longitudinal data highlight profound inequities that have been exacerbated by COVID-19. Existing policies appear inadequate to address the widening gap. (Am J Public Health. Published online ahead of print January 21, 2021: e1–e4. https://doi.org/10.2105/AJPH.2020.306041 )

Objectives The coronavirus disease 2019 (COVID-19) pandemic has disproportionately strained households experiencing poverty, particularly Black and Latino households. Food insecurity, which entails having limited or uncertain access to a sufficient quantity of nutritious food, is a key pandemic-related consequence. We examined how people enrolled in the Supplemental Nutrition Assistance Program (SNAP) have been affected by the pandemic, particularly Black participants and participants residing in food deserts. Methods Using survey data from a longitudinal cohort study of predominantly Black low-income adults aged ≥18 residing in urban food deserts in Pittsburgh, Pennsylvania, we examined changes in food insecurity and SNAP participation before COVID-19 (2018) and early in the COVID-19 pandemic (March–May 2020). We modeled changes in food insecurity from 2018 to 2020 via covariate-adjusted logistic regression. Results Food insecurity increased significantly among participants enrolled in SNAP and surveyed in both 2018 and 2020 (from 25.9% in 2018 to 46.9% in 2020; P < .001). Compared with cohort participants not enrolled in SNAP at both points, cohort participants enrolled in SNAP in 2018 and 2020 had the highest rates of using a food bank in 2020 (44.4%) and being newly food insecure in 2020 (28.9%) (ie, they were food insecure in 2020 but not in 2018). Conclusions Food insecurity during the COVID-19 pandemic increased among low-income Black households enrolled in SNAP and residing in a food desert. Public health recovery efforts might focus on modifying SNAP to improve the food security of people experiencing poverty.

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Background: Few studies have assessed objectively measured physical activity (PA), active transportation, psychological distress and neighborhood perceptions among residents of a neighborhood before and after substantial improvements in its physical environment. Also, most research-to-date has employed study designs subject to neighborhood selection, which may introduce bias in reported findings. We built upon a previously enrolled cohort of households from two low-income predominantly African American Pittsburgh neighborhoods, matched on socio-demographic composition including race/ethnicity, income and education. One of the two neighborhoods received substantial neighborhood investments over the course of this study including, but not limited to public housing development and greenspace/landscaping. We implemented a natural experiment using matched intervention and control neighborhoods and conducted pre-post assessments among the cohort. Our comprehensive assessments included accelerometry-based PA, active transportation, psychological distress and perceptions of the neighborhood, with assessments conducted both prior to and following the neighborhood changes. In 2013, we collected data from 1003 neighborhood participants and in 2016, we re-interviewed 676 of those participants. We conducted an intent to treat analysis, with a difference-indifference estimator using attrition weighting to account for nonresponse between 2013 and 2016. In addition, we derived an individual-level indicator of exposure to neighbourhood investment and estimated effect of exposure to investment on the same set of outcomes using covariate-adjusted models. Results: We observed no statistically significant differences in activity, psychological distress, satisfaction with one's neighborhood as a place to live or any of the other measures we observed prior to and after the neighborhood investments between the intervention and control neighborhoods or those exposed vs not exposed to investments.