Using Explainable Artificial Intelligence to Discover Interactions in an Ecological Model for Obesity

Ecological theories suggest that environmental, social, and individual factors interact to cause obesity. Yet, many analytic techniques, such as multilevel modeling, require manual specification of interacting factors, making them inept in their ability to search for interactions. This paper shows evidence that an explainable artificial intelligence approach, commonly employed in genomics research, can address this problem. The method entails using random intersection trees to decode interactions learned by random forest models. Here, this approach is used to extract interactions between features of a multi-level environment from random forest models of waist-to-height ratios using 11,112 participants from the Adolescent Brain Cognitive Development study. This study shows that methods used to discover interactions between genes can also discover interacting features of the environment that impact obesity. This new approach to modeling ecosystems may help shine a spotlight on combinations of environmental features that are important to obesity, as well as other health outcomes

Frequency of Vending Machine Usage as a Predictor of Weight Status Among College Students

Background: College students have identified frequent unhealthy snacking from vending machines as influencing their dietary intake and weight status. However, research on associations between vending usage and weight status is lacking. Objectives: 1.) Compare college students’ demographic characteristics by frequency of vending machine usage (FVU) and body mass index (BMI). 2.) Determine associations between FVU and BMI levels among college students. Methods: Using a cross-sectional study design, a convenience sample of college students (n=110) completed an online survey providing demographics, height and weight, and FVU – categorized as “none” (never or rarely), “low” (less than once per month, or “high” (once per month or more). Demographics were analyzed using descriptive statistics with comparisons by FVU and BMI levels. Associations between FVU and BMI levels, alone and controlling for sex and race/ethnicity, were tested using a proportional odds logistic model. Results: The majority of participants were in the lowest FVU (50%) and normal BMI (56%; M=24.2 kg/m2) levels. BMI was significantly different by FVU levels (p=.012). Logistic regression indicated the highest FVU category was associated with a 4.6 times greater odds of being overweight or obese (p=0.001). Conclusion: This study described a significant relationship between higher levels of FVU and higher levels of BMI among college students. This formative evidence can inform future vending interventions in this population

Barriers and Facilitators to Implementing Healthy Food Retail Programs: Extension Agents’ Perceptions

The purpose of this cross-sectional study was to understand the perceptions Extension professionals have about healthy food retail programs (HFRPs). Family and Consumer Science (FCS) agents from one state in the southeastern United States were interviewed about their definitions of HFRPs, what challenges and benefits existed, and strategies for successful HFRP implementation. Participants reported that HFRPs would bring immense benefits to their communities, including expanding the recognition of Extension. However, one specific suggestion that was identified was hands-on training needed before initiating HFRPs, particularly on strategies for relationship development with retail store owners

Youth Peers Put the “Invent” into NutriBee’s Online Intervention

Background: Early adolescents perceive peers as credible and relatable. Peers therefore have a unique conduit to engage early adolescents in positive health behaviors through nutrition learning such as that recommended by the U.S. Institute of Medicine (IOM). Purpose: We developed an online, peer leader component to an existing in-person preventive nutrition intervention called NutriBee. We reasoned that youth ages 13–18 could create intervention materials that could remain engaging, credible and relatable to younger peers ages 10–12 online. Peer leaders could potentially derive health benefits from their service-learning experience. Methods: From 2013–2014 youth could apply online to relate a personal interest to nutrition, an opportunity promoted at NutriBee pilot sites and through social media. The peer leaders with diverse backgrounds honed original ideas into tangible projects with the support of adult subject-matter experts chosen by the youth. Nutrition expertise was provided by NutriBee staff who then also converted the youth-invented projects from various media into an online curriculum. Results: 19 of 27 (70%) of selected youth from 12 states and diverse backgrounds, created an online curriculum comprising 10% of NutriBee’s 20-hour intervention. All 19 online projects modeled 1 or more of NutriBee’s 10 positive health behaviors; 8 evoked the chemosenses; 6 conveyed food texture; and 13 provided social context. Peer leaders perceived career advancement and service learning benefits. The dose, pedagogic approach, and project content align with the IOM recommendation. Conclusions: Youth created intervention materials which communicate positive health behaviors online in ways peers can adopt. In a customarily sight-sound digital platform, youth leveraged the senses of smell, taste and touch and social context important for food selection. Peer leaders derived health benefit, as indirectly assessed by IOM criteria

Online Pilot Grocery Intervention among Rural and Urban Residents Aimed to Improve Purchasing Habits

Online grocery shopping has the potential to improve access to food, particularly among low-income households located in urban food deserts and rural communities. The primary aim of this pilot intervention was to test whether a three-armed online grocery trial improved fruit and vegetable (F&V) purchases. Rural and urban adults across seven counties in Kentucky, Maryland, and North Carolina were recruited to participate in an 8-week intervention in fall 2021. A total of 184 adults were enrolled into the following groups: (1) brick-and-mortar “BM” (control participants only received reminders to submit weekly grocery shopping receipts); (2) online-only with no support “O” (participants received weekly reminders to grocery shop online and to submit itemized receipts); and (3) online shopping with intervention nudges “O+I” (participants received nudges three times per week to grocery shop online, meal ideas, recipes, Facebook group support, and weekly reminders to shop online and to submit itemized receipts). On average, reported food spending on F/V by the O+I participants was USD 6.84 more compared to the BM arm. Online shopping with behavioral nudges and nutrition information shows great promise for helping customers in diverse locations to navigate the increasing presence of online grocery shopping platforms and to improve F&V purchases

A Youth-Leader Program in Baltimore City Recreation Centers: Lessons Learned and Applications

Peer-led interventions may be an effective means of addressing the childhood obesity epidemichowever, few studies have looked at the long-term sustainability of such programs. As part of a multilevel obesity prevention intervention, B'More Healthy Communities for Kids, 16 Baltimore college students were trained as youth-leaders (YLs) to deliver a skill-based nutrition curriculum to low-income African American children (10-14 years old). In April 2015, formative research was used to inform sustainability of the YL program in recreation centers. In-depth interviews were conducted with recreation center directors (n = 4) and the YLs (n = 16). Two focus groups were conducted with YLs (n = 7) and community youth-advocates (n = 10). Barriers to this program included difficulties with transportation, time constraints, and recruiting youth. Lessons learned indicated that improving trainings and incentives to youth were identified as essential strategies to foster continuity of the youth-led program and capacity building. High school students living close to the centers were identified as potential candidates to lead the program. Based on our findings, the initial intervention will be expanded into a sustainable model for implementation, using a train-the-trainer approach to empower community youth to be change agents of the food environment and role models.Johns Hopkins Urban Health InstituteGlobal Obesity Prevention Center at Johns HopkinsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentOffice of the Director, National Institutes of Health [U54HD070725]646 CNPq [GDE: 249316/2013-7]Johns Hopkins Bloomberg Sch Publ Hlth, Baltimore, MD USAUniv Tennessee, Knoxville, TN USAUniv Fed Sao Paulo, Santos, SP, BrazilDept Recreat & Pk City Baltimore, Baltimore, MD USAUniv Maryland Extens, Ellicott City, MD USAUniv Fed Sao Paulo, Santos, SP, BrazilWeb of Scienc

More than Fast Food: Development of a Story Map to Compare Adolescent Perceptions and Observations of Their Food Environments and Related Food Behaviors

The purpose of this convergent, multiphase, mixed methods study was to better understand the perceptions of adolescents’ food environments and related food behaviors using grounded visualization and story mapping. Adolescents from one high school (13–16 years) in the southeastern United States were evaluated via data from health behavior surveys (n = 75), school environment maps, focus groups (n = 5 groups), and Photovoice (n = 6) from October 2016 to April 2017. Data from each phase were integrated using grounded visualization and new themes were identified (n = 7). A story map using ArcGIS Online was developed from data integration, depicting the newly identified themes. Participants failed to meet national recommendations for fruit and vegetable intake (2.71 cups). Focus group and Photovoice findings indicated the need for convenience food items in all environments. The story map is an online, interactive dissemination of information, with five maps, embedded quotes from focus groups, narrative passages with data interpretation, pictures to highlight themes, and a comparison of the participants’ food environments. Story mapping and qualitative geographic information systems (GIS) approaches may be useful when depicting adolescent food environments and related food behaviors. Further research is needed when evaluating story maps and how individuals can be trained to create their own maps

Expenditure, Coping, and Academic Behaviors Among Food-Insecure College Students at 10 Higher Education Institutes in the Appalachian and Southeastern Regions

Background A number of studies have measured college student food insecurity prevalence higher than the national average; however, no multicampus regional study among students at 4-y institutions has been undertaken in the Appalachian and Southeast regions of the United States. Objectives The aims of this study were to determine the prevalence of food insecurity among college students in the Appalachian and Southeastern regions of the United States, and to determine the association between food-insecurity status and money expenditures, coping strategies, and academic performance among a regional sample of college students. Methods This regional, cross-sectional, online survey study included 13,642 college students at 10 public universities. Food-insecurity status was measured through the use of the USDA Adult Food Security Survey. The outcomes were associations between food insecurity and behaviors determined with the use of the money expenditure scale (MES), the coping strategy scale (CSS), and the academic progress scale (APS). A forward-selection logistic regression model was used with all variables significant from individual Pearson chi-square and Wilcoxon analyses. The significance criterion α for all tests was 0.05. Results The prevalence of food insecurity at the universities ranged from 22.4% to 51.8% with an average prevalence of 30.5% for the full sample. From the forward-selection logistic regression model, MES (OR: 1.47; 95% CI: 1.40, 1.55), CSS (OR: 1.19; 95% CI: 1.18, 1.21), and APS (OR: 0.95; 95% CI: 0.91, 0.99) scores remained significant predictors of food insecurity. Grade point average, academic year, health, race/ethnicity, financial aid, cooking frequency, and health insurance also remained significant predictors of food security status. Conclusions Food insecurity prevalence was higher than the national average. Food-insecure college students were more likely to display high money expenditures and exhibit coping behaviors, and to have poor academic performance

Expenditure, Coping, and Academic Behaviors Among Food-Insecure College Students at 10 Higher Education Institutes in the Appalachian and Southeastern Regions

Background A number of studies have measured college student food insecurity prevalence higher than the national average; however, no multicampus regional study among students at 4-y institutions has been undertaken in the Appalachian and Southeast regions of the United States. Objectives The aims of this study were to determine the prevalence of food insecurity among college students in the Appalachian and Southeastern regions of the United States, and to determine the association between food-insecurity status and money expenditures, coping strategies, and academic performance among a regional sample of college students. Methods This regional, cross-sectional, online survey study included 13,642 college students at 10 public universities. Food-insecurity status was measured through the use of the USDA Adult Food Security Survey. The outcomes were associations between food insecurity and behaviors determined with the use of the money expenditure scale (MES), the coping strategy scale (CSS), and the academic progress scale (APS). A forward-selection logistic regression model was used with all variables significant from individual Pearson chi-square and Wilcoxon analyses. The significance criterion α for all tests was 0.05. Results The prevalence of food insecurity at the universities ranged from 22.4% to 51.8% with an average prevalence of 30.5% for the full sample. From the forward-selection logistic regression model, MES (OR: 1.47; 95% CI: 1.40, 1.55), CSS (OR: 1.19; 95% CI: 1.18, 1.21), and APS (OR: 0.95; 95% CI: 0.91, 0.99) scores remained significant predictors of food insecurity. Grade point average, academic year, health, race/ethnicity, financial aid, cooking frequency, and health insurance also remained significant predictors of food security status. Conclusions Food insecurity prevalence was higher than the national average. Food-insecure college students were more likely to display high money expenditures and exhibit coping behaviors, and to have poor academic performance

College student sleep quality and mental and physical health are associated with food insecurity in a multi-campus study

Objective: To assess the relationship between food insecurity, sleep quality, and days with mental and physical health issues among college students. Design: An online survey was administered. Food insecurity was assessed using the ten-item Adult Food Security Survey Module. Sleep was measured using the nineteen-item Pittsburgh Sleep Quality Index (PSQI). Mental health and physical health were measured using three items from the Healthy Days Core Module. Multivariate logistic regression was conducted to assess the relationship between food insecurity, sleep quality, and days with poor mental and physical health. Setting: Twenty-two higher education institutions. Participants: College students (n 17 686) enrolled at one of twenty-two participating universities. Results: Compared with food-secure students, those classified as food insecure (43·4 %) had higher PSQI scores indicating poorer sleep quality (P \u3c 0·0001) and reported more days with poor mental (P \u3c 0·0001) and physical (P \u3c 0·0001) health as well as days when mental and physical health prevented them from completing daily activities (P \u3c 0·0001). Food-insecure students had higher adjusted odds of having poor sleep quality (adjusted OR (AOR): 1·13; 95 % CI 1·12, 1·14), days with poor physical health (AOR: 1·01; 95 % CI 1·01, 1·02), days with poor mental health (AOR: 1·03; 95 % CI 1·02, 1·03) and days when poor mental or physical health prevented them from completing daily activities (AOR: 1·03; 95 % CI 1·02, 1·04). Conclusions: College students report high food insecurity which is associated with poor mental and physical health, and sleep quality. Multi-level policy changes and campus wellness programmes are needed to prevent food insecurity and improve student health-related outcomes