Bidirectional Relationship Between Sickle Cell Disease and Food Insecurity: Scoping Review.

Introduction: In the United States, sickle cell disease (SCD)-the homozygous inheritance of a point mutation within the beta-globin chain of hemoglobin-affects between 80,000 and 100,000 people. Adequate nutrition can influence the pathophysiology of SCD, and individuals with SCD who are undernourished are more likely to have impaired immune function and disease exacerbation. Undernourishment is often caused by food insecurity (FI), which is defined as "a household-level economic and social condition of limited or uncertain access to adequate food" by the USDA. FI disproportionately affects African Americans, a population disproportionately affected by SCD in the United States. Objectives: We performed a scoping review to better understand the relationship between FI and SCD severity. Methods: A comprehensive search for peer-reviewed research articles and meeting abstracts was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Selected studies were reviewed for descriptive analysis by three independent reviewers. Results: In total, 72 studies were identified, 62 were excluded for meeting inclusion criteria. The remaining 10 studies, 5 of which were meeting abstracts, were reviewed. Although limited evidence is available, the results of this scoping review suggest a bidirectional relationship between SCD and FI. Seven key themes were identified to help elucidate this relationship: 1) prevalence of FI among individuals with SCD, 2) child versus caregiver experiences of FI, 3) psychosocial factors, 4) food assistance benefits, 5) dietary intake, 6) external spending, 7) healthcare utilization. Conclusion: Findings from this scoping review suggest how SCD and FI work in tandem to exacerbate each other. Furthermore, the findings illustrate current gaps in the literature and opportunities for actions to address FI among individuals living with SCD.

Going virtual during the COVID-19 pandemic: adaptation of a mixed-methods dietary behavior study within a community-based participatory research study of African-American adults at risk for cardiovascular disease.

BACKGROUND: Identifying mechanisms to maintain CBPR studies during an infectious disease pandemic is vital. The current paper describes the changes in methods and processes conducted within a CBPR mixed-methods study to a virtual setting during the novel coronavirus (COVID-19) pandemic. METHOD: The DC Community Organizing for Optimal Culinary Knowledge study with Heart (DC COOKS with Heart) was designed to assess the feasibility of a dietary behavior intervention among African-American adults that are at risk for cardiovascular disease (CVD). The study is under the umbrella of an ongoing CBPR study and community advisory board that facilitates community involvement in study design and promotes ongoing engagement with community members and leaders. The study population for D.C. COOKS with Heart consists of adult African-American individuals who live in two low-resource neighborhoods in Washington, D.C., which were impacted disproportionately by COVID. Eligible study participants who previously participated in the DC CHOC community-based studies were contacted to participate in Phase 1. The quantitative part of the mixed-methods included survey data collection. RESULTS: Due to the pandemic, the mode of data collection for surveys changed from self-administered face-to-face to internet-based. All virtual study procedures were conducted between March and April, 2021. Anticipated benefits of the virtual setting included participant safety during the pandemic, ease of logistics for participants. Anticipated challenges included administration of electronic devices to participants, research team training, and potential threats to established trust related to the privacy and confidentiality of participants. CONCLUSION: The transition to a virtual setting for study procedures in a mixed-methods study was conducted successfully in terms of recruitment, retention of participants, and training of research team members. The virtual transition required established and ongoing engagement through the community advisory board and CBPR practices, institutional support through virtual research policies, collaborations with information technology-based teams, and equipment administration for the study. TRIALS REGISTRATION: NCT04305431 . Registered on March 12, 2020.

The effects of exploratory behavior on physical activity in a common animal model of human disease, zebrafish (Danio rerio).

Zebrafish (Danio rerio) are widely accepted as a multidisciplinary vertebrate model for neurobehavioral and clinical studies, and more recently have become established as a model for exercise physiology and behavior. Individual differences in activity level (e.g., exploration) have been characterized in zebrafish, however, how different levels of exploration correspond to differences in motivation to engage in swimming behavior has not yet been explored. We screened individual zebrafish in two tests of exploration: the open field and novel tank diving tests. The fish were then exposed to a tank in which they could choose to enter a compartment with a flow of water (as a means of testing voluntary motivation to exercise). After a 2-day habituation period, behavioral observations were conducted. We used correlative analyses to investigate the robustness of the different exploration tests. Due to the complexity of dependent behavioral variables, we used machine learning to determine the personality variables that were best at predicting swimming behavior. Our results show that contrary to our predictions, the correlation between novel tank diving test variables and open field test variables was relatively weak. Novel tank diving variables were more correlated with themselves than open field variables were to each other. Males exhibited stronger relationships between behavioral variables than did females. In terms of swimming behavior, fish that spent more time in the swimming zone spent more time actively swimming, however, swimming behavior was inconsistent across the time of the study. All relationships between swimming variables and exploration tests were relatively weak, though novel tank diving test variables had stronger correlations. Machine learning showed that three novel tank diving variables (entries top/bottom, movement rate, average top entry duration) and one open field variable (proportion of time spent frozen) were the best predictors of swimming behavior, demonstrating that the novel tank diving test is a powerful tool to investigate exploration. Increased knowledge about how individual differences in exploration may play a role in swimming behavior in zebrafish is fundamental to their utility as a model of exercise physiology and behavior.