BackgroundChildhood obesity rates in the U.S. have reached epidemic proportions, and an urgent need remains to identify evidence-based strategies for prevention and treatment. Multi-level, multi-component interventions are needed due to the multi-factorial nature of obesity, and its proven links to both the social and built environment. However, there are huge gaps in the literature related to doing these kinds of interventions among low-income, urban, minority groups.MethodsThe B’More Healthy Communities for Kids (BHCK) intervention is a multi-level, multi-component intervention, targeting low-income African American youth ages 10–14 and their families in Baltimore, Maryland. This intervention prevents childhood obesity by working at multiple levels of the food and social environments to increase access to, demand for, and consumption of healthier foods. BHCK works to create systems-level change by partnering with city policy-makers, multiple levels of the food environment (wholesalers, corner stores, carryout restaurants), and the social environment (peers and families). In addition, extensive evaluation will be conducted at each level of the intervention to assess intervention effectiveness via both process and impact measures.DiscussionThis project is novel in multiple ways, including: the inclusion of stakeholders at multiple levels (policy, institutional, and at multiple levels of the food system); that it uses novel computational modeling methodologies to engage policy makers and guide informed decisions of intervention effectiveness; it emphasizes both the built environment (intervening with food sources) and the social environment (intervening with families and peers). The design of the intervention and the evaluation plan of the BHCK project are documented here.Trial registrationNCT02181010 (July 2, 2014).

Obesity has become a truly global epidemic, affecting all age groups, all populations, and countries of all income levels. To date, existing policies and interventions have not reversed these trends, suggesting that innovative approaches are needed to transform obesity prevention and control. There are a number of indications that the obesity epidemic is a systems problem, as opposed to a simple problem with a linear cause-and-effect relationship. What may be needed to successfully address obesity is an approach that considers the entire system when making any important decision, observation, or change. A systems approach to obesity prevention and control has many benefits, including the potential to further understand indirect effects or to test policies virtually before implementing them in the real world. Discussed here are 5 key efforts to implement a systems approach for obesity prevention: 1) utilize more global approaches; 2) bring new experts from disciplines that do not traditionally work with obesity to share experiences and ideas with obesity experts; 3) utilize systems methods, such as systems mapping and modeling; 4) modify and combine traditional approaches to achieve a stronger systems orientation; and 5) bridge existing gaps between research, education, policy, and action. This article also provides an example of how a systems approach has been used to convene a multidisciplinary team and conduct systems mapping and modeling as part of an obesity prevention program in Baltimore, Maryland.

Little is known about the mechanisms through which neighborhood-level factors (e.g., social support, economic opportunity) relate to suboptimal availability of healthy foods in low-income urban communities. We engaged a diverse group of chain and local food outlet owners, residents, neighborhood organizations, and city agencies based in Baltimore, MD. Eighteen participants completed a series of exercises based on a set of pre-defined scripts through an interactive, iterative group model building process over a two-day community-based workshop. This process culminated in the development of causal loop diagrams, based on participants’ perspectives, illustrating the dynamic factors in an urban neighborhood food system. Synthesis of diagrams yielded 21 factors and their embedded feedback loops. Crime played a prominent role in several feedback loops within the neighborhood food system: contributing to healthy food being “risky food,” supporting unhealthy food stores, and severing social ties important for learning about healthy food. Findings shed light on a new framework for thinking about barriers related to healthy food access and pointed to potential new avenues for intervention, such as reducing neighborhood crime.

Systems modeling represents an innovative approach for addressing the obesity epidemic at the community level. We developed an agent-based model of the Baltimore City food environment that permits us to assess the relative impact of different programs and policies, alone and in combination, and potential unexpected consequences. Based on this experience, and a review of literature, we have identified a set of principles, potential benefits, and challenges. Some of the key principles include the importance of early and multilevel engagement with the community prior to initiating model development and continued engagement and testing with community stakeholders. Important benefits include improving community stakeholder understanding of the system, testing of interventions before implementation, and identification of unexpected consequences. Challenges in these models include deciding on the most important, yet parsimonious factors to consider, how to model food source and food selection behavior in a realistic yet transferable manner, and identifying the appropriate outcomes and limitations of the model.

Agent-based simulations showed how warning labels may decrease overweight and obesity prevalence in a variety of circumstances with label efficacy and literacy rate identified as potential drivers. Implementing a warning label policy may lead to a reduction in obesity prevalence. Focusing on warning label design and store compliance, especially at supermarkets, may further increase the health impact.

Background: Products in corner stores may be affected by the network of suppliers from which storeowners procure food and beverages. To date, this supplier network has not been well characterized. Methods: Using network analysis, we examined the connections between corner stores (n = 24) in food deserts of Baltimore City (MD, USA) and their food/beverage suppliers (n = 42), to determine how different store and supplier characteristics correlated. Results: Food and beverage suppliers fell into two categories: Those providing primarily healthy foods/beverages (n = 15) in the healthy supplier network (HSN) and those providing primarily unhealthy food/beverages (n = 41) in the unhealthy supplier network (UHSN). Corner store connections to suppliers in the UHSN were nearly two times greater (t = 5.23, p < 0.001), and key suppliers in the UHSN core were more diverse, compared to the HSN. The UHSN was significantly more cohesive and densely connected, with corner stores sharing a greater number of the same unhealthy suppliers, compared to HSN, which was less cohesive and sparsely connected (t = 5.82; p < 0.001). Compared to African Americans, Asian and Hispanic corner storeowners had on average −1.53 (p < 0.001) fewer connections to suppliers in the HSN (p < 0.001). Conclusions: Our findings indicate clear differences between corner stores’ HSN and UHSN. Addressing ethnic/cultural differences of storeowners may also be important to consider.

These findings suggest that the relation between the TSSD and macronutrient intake might be U-shaped, with higher intake of calories, fat, and protein in individuals in the very early and late stages of their SNAP cycles. Foods high in these nutrients might be cheaper, more accessible, and have a longer shelf-life than healthier options, such as fruit, vegetables, and whole grains, for SNAP participants when their benefits run out. Additional efforts are needed to investigate the effect of the TSSD on dietary intake by using a longitudinal design and to improve the quality of dietary intake in African American SNAP participants.

Objective: Investigate acquisition and mobility experiences of food-insecure individuals across urbanicity levels (i.e., urban, suburban, rural) in the early months of the COVID-19 pandemic. Design: Cross-sectional study using a nationally representative online panel to measure where food-insecure individuals acquired food, food acquisition barriers, and mobility to food sources, which were evaluated across urbanicity levels using chi-squared tests and 95% CIs. Setting: United States Participants: 2,011 adults (18 years or older) Results: Food insecurity impacted 62.3% of adults in urban areas, 40.5% in rural areas, and 36.7% in suburban areas (p<0.001). Food acquisition barriers that were significantly more prevalent among food-insecure adults in urban areas were a change in employment status (34.2%; 95% CI = 27.2%, 41.1%; p<0.0001) and limited availability of food in retailers (38.8%; 95% CI = 31.7%, 45.9%; p<0.001). In rural areas, food-insecure adults primarily acquired food for the household from supercenters (61.5%; 95% CI = 50.4%, 72.5%; p<0.05), while locally sourced foods were less common among food-insecure adults in rural areas (6.9%; 95% CI = 0.01%, 13.0%) compared to urban areas (19.8%; 95% CI = 14.3%, 25.4%; p<0.01). Transportation as a barrier did not vary significantly by urbanicity, but food-insecure adults across urbanicity levels reported utilizing a range of transportations modes to acquire food. Conclusions: A planning approach that links urban and rural areas could address food insecurity by enhancing the integration of food production, transportation, and food distribution, building toward a more resilient and equitable food system for all Americans.