Socioecological Path Analytic Model of Diet Quality among Residents in Two Urban Food Deserts.

BACKGROUND: Diet is critical to chronic disease prevention, yet there are persistent disparities in diet quality among Americans. The socioecological model suggests multiple factors, operating at multiple levels, influence diet quality. OBJECTIVE: The goal was to model direct and indirect relationships among healthy eating identity, perceived control of healthy eating, social support for healthy eating, food retail choice block scores, perceptions of healthy food availability, and food shopping behaviors and diet quality measured using Healthy Eating Index-2010 scores (HEI-2010) for residents living in two urban communities defined as food deserts. DESIGN: A cross-sectional design was used including data collected via self-reported surveys, 24-dietary recalls, and through objective observations of food retail environments. PARTICIPANTS/SETTING: Data collection occurred in 2015-2016 in two low-income communities in Cleveland (n=243) and Columbus (n=244), OH. MAIN OUTCOME MEASURE: HEI-2010 scores were calculated based on the average of three 24-hour dietary recalls using the Nutrition Data System for Research. ANALYSIS: Separate path models, controlled for income, were run for each community. Analysis was guided by a conceptual model with 15 hypothesized direct and indirect effects on HEI-2010 scores. Associations were considered statistically significant at P<0.05 and P<0.10 because of modest sample sizes in each community. RESULTS: Across both models, significant direct effects on HEI-2010 scores included healthy eating identity (ß=.295, Cleveland; ß=.297, Columbus, P<0.05) and distance traveled to primary food store (ß=.111, Cleveland, P<0.10; ß=.175, Columbus, P<0.05). Perceptions of healthy food availability had a significant, inverse effect in the Columbus model (ß=-.125, P<0.05). The models explained greater variance in HEI-2010 scores for the Columbus community compared with Cleveland (R2=.282 and R2=.152, respectively). CONCLUSIONS: Findings highlight the need for tailored dietary intervention approaches even within demographically comparable communities. Interventions aimed at improving diet quality among residents living in food deserts may need to focus on enhancing healthy eating identity using culturally relevant approaches while at the same time addressing the need for transportation supports to access healthy food retailers located farther away.

A food hub to address healthy food access gaps: Residents' preferences.

Interventions aimed at improving access to healthy food in low-income communities should consider the preferences of residents. Household food shoppers in two urban, low-income communities were asked about their preferences for vendors at, and qualities of, a potential nearby food hub. Universally, participants preferred availability of whole foods, primarily fruits and vegetables. They also favored cleanliness, quality, and affordability. The demographics and preferences of potential customers raise central issues that would need to be integrated into the development of a food hub, namely affordability (likely through subsidization), attention to accommodation and cultural accessibility, and programming that builds community.

Food Melt in Consumer Food Environments in Low-income Urban Neighborhoods.

OBJECTIVES: We systematically evaluated changes in availability, price, and quality of perishable food items from the beginning to the end of the month in lowincome, urban neighborhoods. METHODS: The sample included grocery stores or supermarkets in Cleveland, Ohio, within neighborhoods with >30% of population receiving food assistance. We collected data for 2 sequential months during the first and fourth weeks of each month. Two coders evaluated stores, collecting measures of availability, price, and quality for 50 items. We examined difference in number and proportion of items available at the beginning of the month (BOM) to items remaining available at the end of the month (EOM), as well as quality and price of those items. RESULTS: Across 48 stores, availability at EOM was lower than BOM; as store size increased, reduction in availability (ie, food melt) was significantly (p < .01) less pronounced. Overall, items became less expensive at the EOM whereas quality remained consistent; we noted no statistically significant differences by store type for price or quality. CONCLUSIONS: Food melt differentially affects individuals in neighborhoods without grocery stores. Findings reveal composition of food environments is dynamic rather than static, influencing food-purchasing choices among lowincome consumers.

Dissemination of Technology to Evaluate Healthy Food Incentive Programs.

INTRODUCTION: Federal policy supports increased implementation of monetary incentive interventions for chronic disease prevention among low-income populations. This study describes how a Prevention Research Center, working with a dissemination partner, developed and distributed technology to support nationwide implementation and evaluation of healthy food incentive programming focused on Supplemental Nutrition Assistance Program recipients. METHODS: FM Tracks, an iOS-based application and website, was developed to standardize evaluation methods for healthy food incentive program implementation at direct-to-consumer markets. This evaluation examined diffusion and adoption of the technology over 9 months (July 2015-March 2016). Data were analyzed in 2016. RESULTS: FM Tracks was disseminated to 273 markets affiliated with 37 regional networks in 18 states and Washington, DC. All markets adopted the sales transaction data collection feature, with nearly all recording at least one Supplemental Nutrition Assistance Program (99.3%) and healthy food incentive (97.1%) transaction. A total of 43,493 sales transactions were recorded. By the ninth month of technology dissemination, markets were entering individual sales transactions using the application (34.5%) and website (29.9%) and aggregated transactions via website (35.6%) at similar rates. Use of optional evaluation features like recording a customer ID with individual transactions increased successively with a low of 22.2% during the first month to a high of 69.2% in the ninth month. CONCLUSIONS: Systematic and widely used evaluation technology creates possibilities for pragmatic research embedded within ongoing, real-world implementation of food access interventions. Technology dissemination requires supportive technical assistance and continuous refinement that can be advanced through academic-practitioner partnerships.