Reducing Obesity in Rural Alabama: From Focus Groups to Community Coalitions

With an adult obesity rate of 35.6%, Alabama is the second most obese state in the United States. Alabama Extension and the Centers for Disease Control and Prevention (CDC) joined in the first collaboration between the CDC and land-grant institutions to prevent further incidence and reduce the prevalence of obesity. The objective of our study was to determine perceived barriers and assets related to nutrition education, food retail, and physical activity in 14 rural counties in Alabama where adult obesity rates are greater than 40%. Extension formed community coalitions in the counties to help identify community-specific needs and strategies related to obesity prevention and reduction

Development and Validation of the Short Healthy Eating Index Survey with a College Population to Assess Dietary Quality and Intake

Because diet quality (DQ) is associated with risk of chronic disease and is a common construct assessed in health-related research, validated tools to assess DQ are needed that have low respondent and researcher burden. Thus, content experts develop the Short Healthy Eating Index (sHEI) tool and an associated scoring system. The sHEI scoring system was then refined using a classification and regression tree (CRT) algorithm methodology with an iterative feedback process with expert review and input. The sHEI scoring system was then validated using a concurrent criterion validation process that included the sHEI DQ scores (calculated from responses from 50 participants) being compared to the participants’ Healthy Eating Index scores derived from 24 h recalls. The total HEI score from the CRT algorithm highly correlated with the 24 h recall HEI score (0.79). For individual food group items, the correlation between the CRT algorithm scoring and the 24 h recall data scoring ranged from 0.44 for refined grains to 0.64 for whole fruits. The sHEI appears to be a valid tool for estimating overall dietary quality and individual items (with correlations \u3e 0.49) for fruits, vegetables, dairy, added sugar, sugar from sugar-sweetened beverages, and calcium

Multilevel Structural Equation Modeling of Students’ Dietary Intentions/Behaviors, BMI, and the Healthfulness of Convenience Stores

When dietary behaviors are habitual, intentions are low, and environmental cues, such as the consumer food environment, might guide behavior. How might intentions to eat healthily and ultimately actual dietary behaviors, be influenced by the consumer food environment (including the availability and affordability of healthy foods) in convenience stores? This study will determine pathways between the healthfulness of convenience stores and college students' dietary intentions/behaviors, and body mass index (BMI)

Multilevel Structural Equation Modeling of Students\u27 Dietary Intentions/Behaviors, BMI, and the Healthfulness of Convenience Stores.

BACKGROUND: When dietary behaviors are habitual, intentions are low, and environmental cues, such as the consumer food environment, might guide behavior. How might intentions to eat healthily and ultimately actual dietary behaviors, be influenced by the consumer food environment (including the availability and affordability of healthy foods) in convenience stores? This study will determine pathways between the healthfulness of convenience stores and college students\u27 dietary intentions/behaviors, and body mass index (BMI).METHODS: Through multilevel structural equation modeling, a comparison was made of students\u27 healthful meal intentions (HMI); intake (fruits/vegetables, %kcal/fat, sugar-sweetened beverages (SSBs) and whole-grains); and measured BMI; as well as the healthfulness of convenience stores (fruits/vegetables availability/quality, healthy food availability/affordability). Data was collected on 1401 students and 41 convenience stores across 13 US college campuses.RESULTS: Controlling for gender, HMI was negatively associated with SSBs (β = -0.859) and %kcal/fat (β = -1.057) and positively with whole-grains (β = 0.186) and fruits/vegetables intake (β = 0.267); %Kcal/fat was positively (β = 0.098) and fruits/vegetables intake (β = -0.055) negatively associated with BMI. Campus level, fruits/vegetables availability were positively associated to HMI (β = 0.214, β = 0.129) and directly/negatively to BMI (β = -2.657, β = -1.124).CONCLUSIONS: HMI modifies dietary behaviors, with energy from fat and fruit/vegetable intake the most predictive of weight. Availability of fruit/vegetables in convenience stores make it easier for young adults to eat well

The Impact of COVID-19 on Perceived Barriers and Facilitators to the Healthfulness of Communities With Low-Income

Background: The COVID-19 pandemic brought new challenges affecting the wellbeing of individuals in communities with low income. Understanding where people live and how those environments can facilitate or hinder living a healthy lifestyle is essential for developing interventions that target behavior change and health promotion. Objective: This study compares Extension Nutrition Educators’ (NEs) perceptions of the barriers and facilitators impacting the healthfulness of the environment of communities with low income in eleven states before and during the COVID-19 pandemic

eB4CAST Approach Improves Science Communication With Stakeholders in a College-Based Health Program

Communicating scientific results with community partners is often lacking in intervention programs, thus eB4CAST was developed to facilitate impact sharing. This article investigated using the eB4CAST dissemination tool to communicate impact from a campus-based obesity prevention program. Data from Get Fruved RCT university sites collected at baseline were used to generate eB4CAST reports. Experts (n = 13) and RCT sites (n = 15) were asked to provide feedback on eB4CAST reports based on appeal, understanding, and clarity. On all Likert items, participants rated above 7 on each (out of 10). Positive responses from open-ended questions included eB4CAST reports being clear, visually appealing, and aid in program understanding. Overall, eB4CAST was successful in relaying data and information for the Get Fruved program, thus a means for science communication that could be used in interventions. Utilizing infographics to report data and information is a feasible way to disseminate and communicate in a cost-effective, timely manner

An Evaluation of the Relationship Between Physical Activity, Cooking, Dietary Behavior and Wellness Indicators in College Students: GetFRUVED Study

Objective:Determine the influence of modifiable lifestylefactors on college students’fruit and vegetable (FV) intakeand body mass index (BMI)

“Get Fruved”: the RCT Year

Objective: To describe the Get Fruved project through year 04.Description: Get Fruved is a health promotion intervention utilizing Community Based Participatory Research (CBPR) to develop and test a social marketing and environmental change intervention to prevent unwanted weight gain among older adolescents. Initially this included college campus students and then transitioned to college students mentoring high school students with the aim of conducting the intervention at the high school level. The five-year project has five phases. In phases I-III the CBPR partnerships were forged, college intervention developed, college intervention feasibility/pilot tested, and a high school intervention developed. During Phase IV (year 04), the college intervention is being tested utilizing a cluster randomized controlled trial (RCT) at 31 intervention and 32 control colleges and the high school intervention is being feasibility/pilot tested at five schools from four states.Evaluation: To date, 8,215 college students and 1,387 high school students have completed assessments. Prevention of unwanted weight gain is the primary outcome for the RCT, but since the intervention focused not on weight and instead on health-related behaviors associated with obesity prevention, numerous health-related behaviors were assessed. Assessments include dietary intake, stress, physical activity, sleep hours, perceptions of the campus environment, readiness to change, and students\u27 priorities.Conclusions and Implications: To date, 16 new instruments/methods have been developed and validated, three college courses created, 91 presentations conducted, three manuscripts published, and college and high school toolkits created (providing a systematic approach to promoting health for obesity prevention). Data are currently being analyzed. In Phase V, high school intervention effectiveness will be tested using an RCT model