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

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 (n = 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

The Relationship between Food Security Status and Fruit and Vegetable Intake during the COVID-19 Pandemic

The coronavirus disease 2019 (COVID-19) pandemic has drastically altered food shopping behaviors, and the resulting economic recession has caused a spike in food insecurity. Since food insecurity is associated with poor diet, especially low intake of fruits and vegetables, food-insecure individuals may disproportionately experience negative health impacts related to poor diet during the pandemic. To assess the relationship between food security status and fruit and vegetable intake during the COVID-19 pandemic, we conducted an online survey of adult residents of the US state of Michigan in June of 2020. Among the 484 survey respondents, 36.2% were classified as food-insecure. Food-insecure respondents consumed fruits and vegetables fewer times per day than food-secure respondents and were more likely to report decreasing their consumption of any type of fruits and vegetables (total, fresh, frozen, and canned) since the pandemic started. For those who reduced their purchase of fresh fruit and vegetable, reasons included poor quality, poor availability, high price, reduced store trips, and concerns of contamination. These findings highlight the need for adequate food assistance during the COVID-19 pandemic and in future pandemics, as well as public health messages that promote healthy eating

Feasibility of collection and analysis of microbiome data in a longitudinal randomized trial of community gardening

Aim: We explored the feasibility of collecting and analyzing human microbiome data in a longitudinal randomized controlled trial of community gardening. Methods & materials: Participants were randomly assigned to gardening (N = 8) or control (N = 8). Participants provided stool, mouth, hand and forehead microbiome samples at six timepoints. Analyses combined mixed models with Qiita output. Results: Participant satisfaction was high, with 75% of participants completing evaluations. While no microbial effects were statistically significant due to small sample size, the analysis pipeline utility was tested. Conclusion: Longitudinal collection and analysis of microbiome data in a community gardening randomized controlled trial is feasible. The analysis pipeline will be useful in larger studies for assessment of the pathway between microbiota, gardening and health outcomes.This study was funded by the University of Colorado Boulder Population Center (CUPC, J Litt, PI), through the National Institute of Child Health & Human Development of the NIH under award number P2CHD066613-06 and the Center for Microbiome Innovation at the University of California San Diego. We also received supplemental funding through the Clinical & Translational Research Center (CTRC) to cover all laboratory costs (J Litt, PI). M Gascon received a fellowship from the Societat Econòmica Barcelonesa d'Amics del País (SEBAP) in 2018, Barcelona (Catalonia), for her research stay at the University of Colorado to conduct the statistical analysis for this work. DH Glueck was supported, in part, by R01GM121-81 and R25 GM11190

Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines.

Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics