The multifactorial causes of obesity require multilevel and multicomponent solutions, but such combined strategies have not been tested to improve the community food environment. We evaluated the impact of a multilevel (operating at different levels of the food environment) multicomponent (interventions occurring at the same level) community intervention. The B’more Healthy Communities for Kids (BHCK) intervention worked at the wholesaler (n = 3), corner store (n = 50), carryout (n = 30), recreation center (n = 28), household (n = 365) levels to improve availability, purchasing, and consumption of healthier foods and beverages (low-sugar, low-fat) in low-income food desert predominantly African American zones in the city of Baltimore (MD, USA), ultimately intending to lead to decreased weight gain in children (not reported in this manuscript). For this paper, we focus on more proximal impacts on the food environment, and measure change in stocking, sales and purchase of promoted foods at the different levels of the food system in 14 intervention neighborhoods, as compared to 14 comparison neighborhoods. Sales of promoted products increased in wholesalers. Stocking of these products improved in corner stores, but not in carryouts, and we did not find any change in total sales. Children more exposed to the intervention increased their frequency of purchase of promoted products, although improvement was not seen for adult caregivers. A multilevel food environment intervention in a low-income urban setting improved aspects of the food system, leading to increased healthy food purchasing behavior in children.

One of the most basic needs globally, food assistance refers to the multitude of programs, both governmental and non-governmental, to improve food access and consumption by food-insecure individuals and families. Despite the importance of digital and mobile Health (mHealth) strategies in food insecurity contexts, little is known about their specific use in food assistance programs. Therefore, the purpose of this study was to address that gap by conducting a scoping review of the literature. Keywords were defined within the concepts of food assistance and digital technology. The search included relevant peer-reviewed and grey literature from 2011 to 2021. Excluded articles related to agriculture and non-digital strategies. PRISMA guidelines were followed to perform a partnered, two-round scoping literature review. The final synthesis included 39 studies of which most (84.6%) were from the last five years and United States-based (93.2%). The top three types of articles or studies included text and opinion, qualitative research, and website, application, or model development (17.9%). The top three types of digital tools were websites (56.4%), smartphone applications (20.5%), and chatbots (5.1%). Nineteen digital features were identified as desirable. Most tools included just one or two features. The most popular feature to include was online shopping (n = 14), followed by inventory management, and client tracking. Digital tools for individual food assistance represent an opportunity for equitable and stable access to programs that can enhance or replace in-person services. While this review identified 39 tools, all are in early development and/or implementation stages. Review findings highlight an overall lack of these tools, an absence of user-centered design in their development, and a critical need for research on their effectiveness globally. Further analysis and testing of current digital tool usage and interventions examining the health and food security impacts of such tools should be explored in future studies, including in the context of pandemics, where digital tools allow for help from a distance.

Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) redemption rates have been declining in many low-income urban settings, potentially related to aspects of the food environment. B’more Healthy Corner Stores for Moms and Kids was a feasibility trial in Baltimore City that aimed to test multiple behavioral economic (BE) strategies in 10 corner stores (intervention = eight stores, comparison = two stores), to evaluate their influence on the stocking and redemptions of WIC foods. Tested strategies included in-person storeowner training, point of purchase promotion, product placement, and grouping of products in a display. All four strategies were feasible and implemented with high reach, dose delivered, and fidelity. Additionally, text messaging was found to be an acceptable form of intervention reinforcement for storeowners. Analyses to assess change in stocking of WIC foods, total sales of WIC foods, and sales of WIC foods to WIC clients, revealed consistent positive changes after implementation of the store owner training strategy, while changes after the implementation of other strategies were mixed. Furthermore, WIC food sales to WIC clients significantly increased after the simultaneous implementation of two strategies, compared to one (p > 0.05). Results suggest that store owner training was the most influential strategy and that the implementation of more BE strategies does not necessarily lead to proportional increases in stocking and sales. Selected BE strategies appear to be an effective way of increasing stocking and sales of WIC foods in small urban food stores.

This study aimed to evaluate the association of the overall nutritional quality and the weight share of specific types of foods received by food pantry clients with food pantry size and distribution method. Data on healthy food weights using the gross weight share (GWS) of select foods and the validated Food Assortment Score Tool (FAST) were collected from 75 food pantry clients in Baltimore, Maryland. The average FAST score across the study population was 63.0 (SD: 10.4). Overall, no statistically significant differences in average FAST scores by pantry size and distribution method were found. However, among client-choice pantries, clients of small pantries had higher scores (p < 0.05) while among medium pantries, clients of traditional pantries had higher scores (p < 0.01). Subgroup analysis of GWS was stratified by pantry size and distribution methods. Findings suggested multi-level, multi-component interventions combining environmental strategies are needed to enhance the healthfulness of foods received by clients. Our analysis provided data to consider further refinements of pantry interventions and planning of more rigorous research on factors influencing the effectiveness of pantry interventions.

Objective: Food security during public health emergencies relies on situational awareness of needs and resources. Artificial intelligence (AI) has revolutionized situational awareness during crises, allowing the allocation of resources to needs through machine learning algorithms. Limited research exists monitoring Twitter for changes in the food security-related public discourse during the COVID-19 pandemic. We aim to address that gap with AI by classifying food security topics on Twitter and showing topic frequency per day. Methods: Tweets were scraped from Twitter from January 2020 through December 2021 using food security keywords. Latent Dirichlet Allocation (LDA) topic modeling was performed, followed by time-series analyses on topic frequency per day. Results: 237,107 tweets were scraped and classified into topics, including food needs and resources, emergency preparedness and response, and mental/physical health. After the WHO’s pandemic declaration, there were relative increases in topic density per day regarding food pantries, food banks, economic and food security crises, essential services, and emergency preparedness advice. Threats to food security in Tigray emerged in 2021. Conclusions: AI is a powerful yet underused tool to monitor food insecurity on social media. Machine learning tools to improve emergency response should be prioritized, along with measurement of impact. Further food insecurity word patterns testing, as generated by this research, with supervised machine learning models can accelerate the uptake of these tools by policymakers and aid organizations.

Low-income urban communities in the United States commonly lack ready access to healthy foods. This is due in part to a food distribution system that favors the provision of high-fat, high-sugar, high-sodium processed foods to small retail food stores, and impedes their healthier alternatives, such as fresh produce. The Baltimore Urban food Distribution (BUD) study is a multilevel, multicomponent systems intervention that aims to improve healthy food access in low-income neighborhoods of Baltimore, Maryland. The primary intervention is the BUD application (app), which uses the power of collective purchasing and delivery to affordably move foods from local producers and wholesalers to the city’s many corner stores. We will implement the BUD app in a sample of 38 corner stores, randomized to intervention and comparison. Extensive evaluation will be conducted at each level of the intervention to assess overall feasibility and effectiveness via mixed methods, including app usage data, and process and impact measures on suppliers, corner stores, and consumers. BUD represents one of the first attempts to implement an intervention that engages multiple levels of a local food system. We anticipate that the app will provide a financially viable alternative for Baltimore corner stores to increase their stocking and sales of healthier foods, subsequently increasing healthy food access and improving diet-related health outcomes for under-resourced consumers. The design of the intervention and the evaluation plan of the BUD project are documented here, including future steps for scale-up. Trial registration #: NCT05010018.