Duration: 10/01/2021 to 09/30/2026

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

Statement of Issues and Justification

Statement of the Problem:

Emerging adulthood, or the transition through late adolescence and young adult years, is a distinct stage of life associated with declines in healthy lifestyle behaviors.^1-4 Young adults are at risk for unhealthy weight gain and dietary patterns, as well as more sedentary lifestyles. The dramatic changes in living and social situations associated with emerging adulthood have been linked to adverse health outcomes. These outcomes may be further challenged by the escalating cost of higher education and uncertainty in the global and local economies.^1-4 Campuses and communities where young adults reside will benefit from timely and personalized information, as well as utilization of evidence-based tools and programs to enhance the health and well-being of this population. The overarching goal of this multistate project is to support campuses and other communities in creating environments and opportunities that embrace young adults’ unique barriers to a healthy lifestyle, promote healthier weights, and reduce health disparities among vulnerable members, who are the fastest grown segments within the United States (US).

Statement of the Issues:

In 2020, over 30 million American adults are between the ages of 18-26 years.⁵ These years of emerging adulthood have long been recognized as a transformative period due to the numerous and significant transitions (e.g., completion of education, leaving the family home, securing full-time employment, living independently, partnering and cohabitation).^4,6,7 The Institute of Medicine and National Research Council published a report in 2014, following changes in the Affordable Care Act, to encourage scientists and policymakers to consider the age group of 18-26 years as a separate demographic with unique social, economic, and policy needs. ⁷  However, attention to and research about this distinct subpopulation is lacking overall; especially as it relates to lifestyle behaviors such as dietary patterns.^8-20 While the US surveillance systems may include all ages in their sampling protocols, methodologies limit the inclusion of those with transient residency status or young adults living outside traditional households. These data systems frequently combine young adult data with teenagers (e.g., 16-19 years) or older adults (e.g., 18-35 years), which fails to identify this group’s unique status adequately.

Today, young adults face unique challenges that differ from their parents and grandparents. For example, regardless of income level, young adults born between 1996-2001 have grown up with ubiquitous access to information (both accurate and misleading) through household computer, tablet or smartphone²¹ and have spent their entire adolescence navigating the advantages and disadvantages of social media.^22,23 Today’s young adults are more likely to identify as a race other than white (16% in 1976 to 44% in 2017)²⁴, and they are more likely to delay marriage and parenting much later than previous generations.^25,26 Young adulthood is an established time of psychological vulnerability with data from 2017 suggesting that the prevalence of any mental illness is highest in young adults (25.8%) when compared to older age groups. While previous generations have experienced economic uncertainties and/or global crises, today’s young adults report higher rates of anxiety than previous generations²⁷ and now face an unprecedented economic landscape^28,29 with the scope, duration, and impact of the global pandemic unknown. The impacts of this pandemic, along with other crises facing our nation’s young adults, which we have named influential disruptive factors (IDFs), on long-term health consequences are a much-needed focus of current health-related research.

While young adults experience diverse pathways, they are more likely to attend an institution of higher education post high school than previous generations. Currently, 40% of 18-24 year-old individuals enroll in a degree-granting postsecondary institution, representing an 11% increase since 2007.^26,30 This increase is largely attributable to the rising number of first-generation college students, a group more vulnerable to health disparities.^31-36 Despite the benefits of earning an advanced degree, today’s college students face higher dropout rates,²⁴ high rates of food insecurity^10,11,37-46, and difficulties repaying student debt⁴⁷ as compared to previous cohorts. In 2015-16, the average student had borrowed $24,480 by the time of degree completion compared to $14,260 in 1999-2000.³⁰ The influence of the additional debt facing college graduates on long-term health is unclear; however, college students with higher credit card debt are less likely to participate in healthier behaviors and more likely to have a higher Body Mass Index (BMI).⁴⁸

The emerging adult years are linked to declines in healthy behaviors and high rates of weight gain, yet existing interventions and assessment tools have not adequately addressed this population’s unique needs and challenges.⁴⁹ These individuals were born in a global obesity epidemic that has failed to wane. Nationally, 18% of young adults 18-24 years old report weight status that would be classified as obese.⁵⁰ Like all age groups, young adults have experienced rising rates of overweight/obesity; however, young adults gain weight faster than any other period of adulthood,⁵¹ and a majority (60%) of college students report weight gain (7.5 lbs) in their first year of college attendance.⁵² Young adults who experience excessive weight gain are at an increased risk of developing diet-related diseases, including obesity, heart disease, hypertension, and type 2 diabetes. Obesity alone currently affects 93.3 million adults in the US, with an estimated cost of $315.8 billion.⁵⁰

Obesity prevention programs have largely overlooked young adults and may not adequately consider their attitudes, motivations, and perceptions.^14,49,53,54 Emerging adulthood is a critical period for developing healthful weight management behaviors. Unfortunately, most obesity prevention programs have focused on changing individual behaviors and/or knowledge with limited attention on the environment. Environments with limited access to healthy foods, such as fruits and vegetables, or opportunities for physical activity make it difficult for individuals to engage in healthful behaviors. An individual’s perception (subjectivity) of the environment and resources available may differ from the actual (objective) environment, individuals may be unable to recognize opportunities that could support healthful behaviors. Therefore, investigating young adults’ eating behaviors and lifestyle choices as well as their perceptions have never been more important nor more urgent to reduce the burden of illness, increase the quality of life, and improve societal impact from obesity.

Justification of the Proposed Work:

Our Healthy Campus Research Consortium (HCRC) includes 17 accomplished researchers, along with 20-30 talented graduate students, who have more than two decades of collaborative experience working with young adults. Cumulatively, our interventions have improved young adults’ food, physical activity, and stress management behaviors, and our surveys have elucidated environmental conditions that make the healthful choice the easy choice for young adults at colleges and universities across the nation. Our integration of teaching, research, and extension leverage the expertise of members in many states, widening our scope and impact.

Consideration of the perceived and actual environment in obesity prevention programs has been hindered by a lack of efficient, reliable, and valid tools. To overcome this, HCRC has identified individual and environmental factors that predispose, enable, and reinforce healthy eating and activity behaviors among young adults.^{8,12,13,16,55,56} Valid, reliable, and efficient tools have been developed to assess the food, physical activity, and policy environments of college campuses.^17,19,57 These tools are being used by researchers and extension professionals around the US to benchmark and track environmental conditions and perceptions and create health promotion programs for young adults.⁵⁰ They are also helping stakeholders and decision makers who work with target communities to identify needs and efforts to develop healthier environments.^{9,14-16,18,20,58-63}

During the current global pandemic, the need to elucidate how IDFs (e.g., discrimination, pandemic/viral outbreak, natural disasters, opioid epidemic, recession/depression) interact with health promotion efforts and weight management interventions is paramount. As HCRC work continues, we will expand our understanding of the needs and perceptions of young adult groups at greatest risk to the impact of IDFs on weight-related behaviors and health outcomes.    

Related, Current and Previous Work

This current proposed research builds on more than 20 years of collaborative multistate research, which was rooted in the community based participatory research (CBPR) approach and addressed eating, physical activity, and stress management behaviors. The work not only focused on theory-based interventions to change individual behavior but also evaluated environmental changes to support lasting desired behaviors. We have examined and explored young adult behaviors, perceptions, and environments through the Stage-Tailored Multi-Modal Intervention Study⁶⁴, WebHealth⁶⁵, and Project YEAH^{8,12,13,16,55,56}. The Stage-Tailored Multi-Modal Intervention Study, a USDA/IFAFS study that partnered with extension, improved fruit and vegetable consumption in economically disadvantaged young adults⁵⁰.  Web Health⁶⁵, a USDA/NRI Integrated Project, tested the impact of a non-dieting online intervention for college students on biological and psychosocial health-indicators using a randomized, controlled design. This 10-week online nutrition and physical activity intervention encouraged competence in making healthful food and eating decisions, had positive and lasting effects on fruit and vegetable intake, and maintained baseline levels of physical activity in a population that otherwise experiences significant declines in healthful behaviors⁶⁵. Project YEAH (Young adults Eating and Active for Health)^{8,12,13,16,55,56}, a USDA/NRI Integrated Project and a web-based intervention for obesity prevention among college and non-college young adults, was developed using the PRECEDE-PROCEED process of CBPR. The experimental participants had significant improvements in cups of fruit and vegetable intake, minutes of vigorous physical activity in females, reduction in percentage of energy from fat, self-instruction, and regulation for mealtime behavior, and hours of sleep at six months (post-intervention) than control participants. There was also a significantly greater proportion of experimental participants than control participants in the action/maintenance stages for fruit and vegetable intake and physical activity⁶⁶.

In addition to developing interventions to promote healthful behaviors, we have also focused on promoting environmental changes to support these behaviors. One of the first steps in identifying needs is to assess the community for environmental supports and perceptions about environmental healthfulness. To assess the environment, we have developed the Healthy Campus Environmental Audit (HCEA)^{9,14-16,18,20,58-63}. The HCEA consists of seven validated and published tools to assess food (food access and availability in vending machines, convenience stores, dining halls, restaurants), physical activity (walkability, bike-ability, recreation), and health-related policy environment. HCEAs are used to assess, monitor, and advocate for environmental changes to improve health. To assess perceptions around the healthfulness of the environment, we developed and validated the Behavior Environment Perception Survey (BEPS)^17,19,57. BEPS is a tool used to assess environmental perceptions of physical activity, healthful eating, mental health, and peer influences. BEPS can be used to understand better the intersection between environment and individual perceptions to identify and prioritize the appropriate environmental changes to target.

Although most of the multistate research team interventions have been focused on young adults in college and/or from communities with low income, the researchers involved have a wide breadth of knowledge and experience developing, implementing, and evaluating healthy weight management and obesity prevention interventions with participants ranging in age from preschool to young adults^67-71. The most recent study conducted by the multistate team, Get FRUVED, focused on high school and college-age students⁷². This intervention was designed to help university and high school campuses use the environmental tools that were previously developed and to create a social marketing obesity prevention campaign called Get FRUVED (FRUit and Vegetable EDucation). Student-led activities promoted healthy eating, physical activity, and stress management. A Get FRUVED toolkit ⁷³ was developed and disseminated to over 90 college and university campuses and 22 high schools across the US. The toolkit provides guidance for using our assessments and tools, which help identify campus needs and create a locally targeted campaign to promote healthy behaviors, environments, and policies.

Another significant outcome from the Get FRUVED work was the development of a novel, evidence-based method for collecting public and intervention specific data called eB4CAST⁷⁴. Each campus or community was provided a personalized narrative describing needs and intervention impacts summarized from the data. This easy-to-use tool provides those who deliver public programming a means to disseminate their impact story to the communities, stakeholders, and administrators.

Objectives

1. Dissemination and implementation of Healthy Campus Research Consortium (HCRC’s) suite of tools that utilize a policy, systems, and environment (PSE) approach for campuses.
   
2. Development of policy, systems, environment (PSE) assessment tools for urban and rural communities with low income considering social determinants of health and influential disruptive factors (IDFs).
   
3. Expanded understanding of college students’ dietary patterns considering social determinants of health and influential disruptive factors (IDFs) with an emphasis on food insecurity, mental health, and the built environment.
   
4. Exploration and interpretation of interactions between lifestyle behaviors and environmental factors using big data analysis techniques with multiple data sets.
   

Methods

Objective 1: Dissemination and implementation of Healthy Campus Research Consortium (HCRC’s) suite of tools that utilize a policy, systems, and environment (PSE) approach for campuses. To accomplish Objective 1, assessment tools and materials created by this multistate collaborative team will be disseminated to partner organizations to enhance and increase adoption. Our unique suite of tools and communication materials assist community members through developing a PSE approach to promote health and wellness. Behavioral assessments (e.g., CEPS^18,75,76, BEPS^17,19,57, sHEI^77,78), policy and program assessments (e.g., Priorities and Readiness for Change⁷⁹, 41 Points), and a campus audit (e.g., HCEA^{9,14-16,18,20,58-63}, SHELF⁶⁰, VENDing⁶², PACES^15,63, POINTS⁶¹, Walkability/Bike-ability Audit²⁰) collectively assist members to evaluate their communities. Collected data are comprehensively summarized and reported through the eB4CAST communication tool⁷⁴ to assist community leaders to translate and share data with their community stakeholders. Data collected from using these assessment tools and communication materials can assist campuses and communities set priorities and advocate for change toward a more healthful environment. Further, the data can assist community members through post-implementation evaluation of impact, allowing them to track their progress toward positive change. In Year 1, training materials and approaches will be developed to educate others to use the assessment tools and communication materials. Development will focus on designing content for online platform delivery (websites and webinars) as delivery systems may need to be adjusted, as well as in-person workshops or conference settings (in-person or virtual). Training will be designed for individuals with different roles in the community, including national and international leaders, researchers, students, and community members. After these training and dissemination materials have been developed, existing organizations focused on college health will be approached for potential partnerships. These partners may include organizations such as Partnership for A Healthier America (PHA)⁸⁰, the Association for Advancement of Sustainability in Higher Education (AASHE)⁸¹, or the Sustainability Track, Assessment & Ranking System (STARS)⁸². Partnerships with established organizations will aim to expand the adoption, broader impact, and sustainability of our tools and materials. In Year 2, surveys will be developed to measure the effectiveness of the training and to conduct process evaluations of material adoption (rate, intensity, and pitfalls associated). Partnerships with existing organizations will also be formalized, and training activities for dissemination will be planned. In Year 3, the developed training will be implemented with individuals from across the nation and the effectiveness of the training will be assessed and reported. Also, in Year 3, the adoption and usage of materials will be tracked, and secondary data analysis of the material effectiveness and outcomes of the assessments will be collated and reported. In Year 4, while the use of tools and materials continue nationwide, based on the process evaluation findings from Year 3, the training and dissemination protocols will be refined and additional training with partner organizations will be planned. In Year 5, refined dissemination activities will be conducted in national settings with partner organizations in online, conference, and workshop settings. 

Objective 2: Development of policy, systems, environment (PSE) assessment tools for urban and rural communities with low income considering social determinants of health and influential disruptive factors (IDFs). To accomplish Objective 2, a CBPR⁸³ approach will be used to target communities where young adults live, with all aspects of the research project. Institutional advisory committees consisting of community members will partner with the research team to identify areas to include in the Behavior and Environmental Perception Survey (BEPS-community)^17,19,57 and adaptation and testing of the HCEA^{9,14-16,18,20,58-63}.  The research team will meet regularly with the advisory committee to share findings and obtain input and direction for future research. This partnership will increase the likelihood that the target community will embrace suggested improvements to promote health in the community. An eB4CAST report⁷⁴ will be generated for each community to share findings. The three-phase development of BEPS-community will happen concurrently with the community adaptation of the HCEA^{9,14-16,18,20,58-63} across all five years. Possible funding to support the following efforts include the NSF CIVIC Innovation Challenge⁸⁴ and other funding sources focused on IDF’s (e.g., the impact of COVID on communities). Year 1 will be a continuation of BEPS-community phase 1 work from our previous five-year project and involve repeating focus groups conducted with program assistants of federal nutrition programs that serve communities with low income. With these repeated focus groups, we will explore the impacts of COVID-19 on the perceived healthfulness of their communities. Questions will explore how COVID-19 affected the local food environment as well as resources that support healthy behaviors of members of the community. Each university will conduct three to five focus groups, transcribe focus groups, and analyze data for themes³¹.  In addition, during Year 1, each university will identify a community with low income and develop an advisory committee to guide the testing of HCEA audits^{9,14-16,18,20,58-63}.  Preliminary testing of the HCEA in these communities found that it does not contain tools to evaluate important community resources such as food banks/pantries⁵⁹, parks¹⁴, and community centers¹⁸. In Year 2 universities will complete phase 2 by conducting interviews with stakeholders who work directly with families with low income to explore the impact of COVID-19 on the perceived healthfulness of the communities in which they work as well as on available resources. Interviews will be transcribed, and data analyzed for themes. In addition, universities will again test each HCEA audit in the identified target community to determine which items are appropriate for community use and which audits are missing or need to be modified. The eB4CAST dissemination tool will be used to put findings, or each institution’s results, into a usable infographic story to be used with administration, faculty, staff, and students. In Year 3, universities will complete phase 3 of the BEPS-community development by conducting focus groups with adults who live in low-income communities to determine the perceived healthfulness of their communities, available resources, and how COVID-19 impacted this perception. Universities will transcribe focus groups and analyze data for themes⁸⁵.  Concurrently, universities will identify new tools or develop new tools for the HCEA to better evaluate the healthfulness of the target community to test them later in Year 3^{9,14-16,18,20,58-63}. In Year 4, the research team will utilize data collected in phases 1-3 to generate the first draft of the BEPS-community survey. Universities will conduct cognitive interviews using the compiled survey items with members of a low-income community. The cognitive interviews will be recorded, transcribed, and analyzed for content feedback⁸⁶. The survey items will be adjusted based on these data. Selected universities will administer the survey to a convenience sample of adults from communities with low income (n=400). Using exploratory factor analysis^87-89, the instrument will be refined to include items fitting into identifiable factors reflecting the breadth of constructs related to community perceptions of the environment.  Decisions will be made to determine other constituents that should be included in data assessment, including demographic as well as behavioral items. Concurrently, an HCEA training will be developed to train community members to utilize the developed community HCEA tools. In Year 5, the instrument will be administered to a wider audience of diverse community members (n=2,400) with additional behavioral validation items. Confirmatory analyses (factor analysis, structural equation modeling, internal consistency)⁹⁰ will validate the psychometric structure. Additional validation analyses will compare relationships between behaviors and perceptual scale scores. The product will be a validated Behavioral Environmental Perceptions Survey for communities with low income (BEPS-community). Using the eB4CAST approach for dissemination, the community can receive a summary of key findings that are ready for action. Further, the HCEA findings can also be incorporated into eB4CAST reports for communities interested in conducting a needs assessment for a nutrition-related intervention. 

Objective 3: Expanded understanding of college students’ dietary patterns considering social determinants of health and influential disruptive factors (IDFs) with an emphasis on food insecurity, mental health, and the built environment. To accomplish Objective 3, previously identified factors will be utilized to develop and validate a survey tool to assess college students’ perceptions about food security resources on college campuses and the intersection between perceived mental health resources and diet quality. This will happen concurrently with the expansion of the HCEA to capture resources on college campuses that support food security and mental health across all five years. Instrument development and the expansion of the HCEA^{9,14-16,18,20,58-63}, builds on work started in the previous five years (e.g., SHELF⁶⁰, VENDing⁶², PACES^15,63, POINTS⁶¹, Walkability/Bike-ability Audit²⁰). From the previously developed BEPS tool^17,19,57, two key issues were identified that require further exploration in young adults attending college, these are food security and the impact of mental health issues (e.g., stress, coping, personality traits, anxiety, health-related quality of life, sleep) has on diet quality¹⁷.  These findings will assist in developing a new tool to reflect the emerging and current issue of college student food security^10,11,91 and to assess the relationship with mental health and diet quality of college students. Further, the HCEA does not currently capture food security or mental health resources^{14,16,18,59,92-94}, such as food pantries and access to counseling, on college campuses. Therefore, previously collected data will be used to continue the development of survey items and the expansion of the HCEA to assess these factors that influence chronic disease risk and take into account IDFs (e.g., influence of current coronavirus pandemic on finances, food access, and overall HCEA tool outcomes). Year 1, phase 1 will identify assessment tools that already exist to evaluate food security and mental health and their appropriateness for use among college students. Each university will also conduct three to five focus groups, composed of students, faculty/staff, and/or administration, to explore topics related to food security, mental health, and IDFs. Universities will transcribe the focus groups with data analyzed at one of the institutions comprehensively to identify themes⁸⁵. Emergent themes will be used to generate additional items for the food security/mental health survey and HCEA. At the annual meeting, universities will identify the role they will play in further validating the survey items and testing the revised HCEA at their college campus. In Year 2, universities will complete phase 2 and employ cognitive interviews³² conducted with college students using the compiled survey items to further generate items and expand the HCEA. This phase will include training research teams to conduct the cognitive interview testing and data collection for the HCEA^{9,14-16,18,20,58-63}. The cognitive interviews will be recorded, transcribed, and analyzed for content feedback⁹⁵. The survey items will be adjusted based on these data. In addition, universities will train students to conduct the newly developed/adjusted HCEA tools (food security and mental health). In Year 3, the research team will utilize data collected in phases 1 and 2 to generate the first draft of the expanded BEPS survey. Selected universities will administer the survey to a convenience sample of college students (n=200). Using a random split sample, an Exploratory and Confirmatory Factor Analysis will be conducted to test and validate the tool⁸⁷. The instrument will be refined to include items fitting into identifiable factors reflecting the breadth of constructs related to food security, mental health, and IDFs’ consequences on the social determinants of health. Decisions will be made to determine other constituents that should be included in data assessment, including demographics as well as behavioral items. Concurrently, universities will test each HCEA audit and the newly developed audits (food security and the intersection of mental health issues on diet quality) to determine which items are appropriate to capture changes on college campuses that have occurred post-IDFs (e.g., grab-and-go in cafeterias). In Year 4 (2024-2025), the research team will administer the survey and HCEA to a wider audience of diverse college students (n=2400) at four universities (e.g., Historically Black Colleges, Tribal Colleges, 2-year community colleges) for additional item validation. Confirmatory analyses (e.g., factor analysis, structural equation modeling, internal consistency) will validate the psychometric structure. The instrument will be validated using additional items⁹⁰. Additional validation analyses will compare the relationship between previously identified behaviors, food security, and the intersection of mental health issues on diet quality. Partnering universities will conduct the HCEA (food security and mental health) audits on their campuses. The product will be a validated survey to assess food security and mental health in college students and a tested environmental audit to capture food security and mental health resources. In Year 5, the research team will disseminate findings. The survey tool and environmental assessments will be published, and colleges/universities interested in assessing these factors can use the tools when conducting a needs assessment or outcome assessment for a nutrition-related intervention. Understanding and assessing factors that are determinants of health will build resiliency of our systems during occurrences of IDFs to protect communities from the potential of exaggerating already existing health disparities. 

Objective 4: Exploration and interpretation of interactions between lifestyle behaviors and environmental factors using big data analysis techniques with multiple data sets. This group’s previous and ongoing datasets, as well as applicable external datasets, will be analyzed using big data techniques and approaches to continue the exploration of mechanisms of interaction between lifestyle behaviors and environmental factors in influencing healthful behaviors and health status of young adults. According to the PRECEDE-PROCEED planning^96-98, etiological factors and social determinants of health⁹⁹ for successful interventions include genetics, behavioral patterns, and environmental factors. Big data, which includes the primary components of volume, variety and velocity¹⁰⁰, can be analyzed for insights that lead to better decisions and strategic interventions¹⁰¹. The ability to process big data has numerous benefits, and for this project could help college campuses better utilize data to make informed decisions through translating research into reports^74,102-104, improve the campus experience for students (healthful behavior supports), identify strengths and areas for improvement, and increase efficiency regarding programs, policies, and environmental changes^{14,16,18,59,92-94}. Leveraging the unique resource of datasets collected over the past two decades by the multistate team, we will explore associations between young adult behaviors, perceptions, and environments that contribute to poor health outcomes. Exploration of the associations among identified variables and their contributions to weight-related factors will continue. These factors include, but are not limited to, diet and exercise behaviors, stress management, sleep, within-meal eating behavior, cognitions (cognitive restraint), susceptibility to emotional eating and external cues, personality, parental status, income level, and ethnicity. In Year 1, the team will explore funding opportunities to support big data analysis techniques/approaches and interpretation. An overview presentation during the annual meeting will occur with all members regarding applicable institution-specific and external data sets, as well as on the following multistate data sets collected to date, which range from longitudinal studies following young adults for at least one year to cross-sectional studies:

• The Stage-Tailored Multi-Modal Intervention Study⁶⁴ (S. Nitzke, PI, USDA/IFAFS, 2001-2005). The purpose was to assess effectiveness of an intervention to improve fruit and vegetable consumption in economically disadvantaged young adults. The study was a randomized treatment-control, pre-post, follow-up design conducted in 10 states. Young adults (n = 2024, ages 18–24) were recruited from non-college venues; 1255 (62%) completed assessment interviews at 0, 4 and 12 months. 
• WebHealth⁶⁵ (G. Greene, PI, USDA/NRI, 2005-2009). Project was designed to test the impact of a non-dieting online intervention for college students on biological and psychosocial indicators of health using a randomized, controlled design. College students (n= 1689, ages 18-24) were recruited from 8 universities; 1144 students (67.7%) completed the study, with assessments at baseline, 3 months and 15 months. 
• Project YEAH^{8,12,13,16,55,56,66}(Young Adults Eating & Active for Health) (K. Kattelmann, PI, USDA/NRI, 2008-2012). The purpose was to develop a web-based intervention for obesity prevention among young adults. Design was a 15-month (10-week intensive intervention with a 12-month follow-up) randomized, controlled trial delivered via internet and electronic mail. Young adults (n=1639, ages 18-24) were recruited from 13 college campuses; 973 participants (59%) completed the study with assessments at baseline, 3 months, and 15 months. 
• Get FRUVED^72,73 (Fruit and Vegetable Education) (S. Colby, PI, USDA/AFRI, 2014-2020). This project aimed to increase fruit and vegetable intake and improve health outcomes through a peer-mentoring social marketing campaign. Followed a nested cohort design using a control-treatment, pre-test, post-test trial with assessments.
• Healthy Campus Environmental Audit (HCEA)^{9,14-16,18,20,58-63}(Horacek, Lead, 2008-2020)^4,10-15. Includes a set of validated/published tools to assess the food (e.g., food access and availability in vending machines, convenience stores, cafeterias and restaurants), physical activity (e.g., walkability, bike-ability, recreation), and health-related policy environment. HCEAs are used to assess, monitor and advocate for environmental changes to improve health.
• Behavior, Environment, and Changeability survey (BECS)¹⁰⁵ (White, Lead, 2009-2011).The purpose was to develop and test the validity of BECS for identifying the importance and changeability of nutrition, exercise, and stress management behavior and related aspects of the environment. Cross-sectional, online survey design with 10 universities and included a convenience sample of college students (n = 1283, ages 18-24).
• College Environmental Perceptions Survey (CEPS) ⁵³, (Colby, Lead, 2012-2016). Designed to assess students’ perception of walkability/bike-ability, recreation facilities, health policies, stress management, health initiatives/programs, and food environment on campuses. Surveys completed by college students from 8 universities (N = 1147) were used to test internal structure (factor analysis) and internal consistency (Cronbach's alpha).
• Behavioral Environmental Perceptions Survey (BEPS)^17,19,57 (Greene/McNamara Lead, 2017-2019). The purpose was to create a tool to measure college students’ perception of the healthfulness of their environment. Cross-sectional, online survey design with 10 college campuses. Time point 1 (n = 120 cognitive interviews; n = 922 factor analysis); time point 2 (n = 2,676), convenience sample of undergraduate students.

In Year 2, the team will identify and pursue funding with identified resources from member institutions to continue data analysis work and graduate training. This will include a list of connecting data sets to contribute to a larger understanding of NC1193 work at the individual and environmental level (i.e. American College Health Assessment-ACHA). In Year 3 and Year 4, the team will conduct analysis of big data sets commensurate with funding secured at institutions (internal and external). We will utilize previous data sets and current data collection to continue bridge work of our behavior and environmental approach. In Year 5, dissemination of findings in refereed venues will occur and possible new paradigm approaches from findings. 

Measurement of Progress and Results

Outputs

• Output from Objective 1: Training approaches and materials for the dissemination of the toolkit and its components will be developed. A data set of communities using the health promotion tools, issues associated with using the tools, and findings from assessments gathered in communities will be available for analysis.
• Output from Objective 2: Using exploratory and confirmatory factor analyses, a community Behavioral Environmental Perceptions Survey (BEPS-community) will be refined to measure community perceptions of the environment’s support for healthful behaviors. Refinement of this survey can inform stakeholders in peer groups and in administration groups and allow them to target healthy behaviors to nudge in this population. In addition, the community HCEA audits can be used to measure a community’s support for healthful behaviors objectively.
• Output from Objective 3: Using exploratory and confirmatory factor analyses, survey tools will be developed to assess food security and mental health status of college students. The HCEA will be expanded to include assessments that capture food security and mental health resources on college campuses. These tools can inform stakeholders and administration on college campuses and identify areas where resources should be allocated to better the health of students. While the survey tools assess college students’ reported behaviors and perceived environment, the HCEA tool can be used to objectively measure how supportive the college environment is for healthful behaviors.
• Output from Objective 4: Continue statistical exploration of the associations among the following weight-related factors; dietary and exercise behaviors, coping with stress, sleep, within-meal eating behavior, susceptibility to emotional eating and external cues and cognitive restraint, personality, relationship with parents, current parental status, income level, and ethnicity. From the multistate team’s large data sets, continued work and products can be derived from this big data approach.

Outcomes or Projected Impacts

• As the goal of the HCRC is to support college campuses and communities where young adults live in creating healthier environments, promoting health, and reducing health disparities, the numerous outcomes of this project include evidence-based tools and programs to address the unique needs and health of today’s emerging adults. Overall, by disseminating evidence-based tools, assessing environmental perceptions, and evaluating environmental influences of health, this research team will make healthy habits an easier, more sustainable choice for more people. (54,106) Good health means better quality of life (67-71,107,108), reduced healthcare costs (109), and an able workforce in communities across the U.S.(110)
• The development and dissemination of a toolkit (noted in Objective 1) that empowers communities to assess and evaluate their own environments will improve the health of individuals and communities, and data will be collected that will be useful in tracking and understanding health promotion efforts. These data can be used to develop future interventions and programs to promote health as factors of influence facing individuals and communities evolve.
• Additionally, the community Healthy Campus Environmental Audit (HCEA) (9,14-16,18,20,58-63) will be adapted and tested, and the community Behavioral Environmental Perceptions Survey (BEPS-community) (17,19,57) will be created and tested in communities with low income to measure and monitor the community environment and population support for facilitating healthful behaviors (noted in Objective 2).
• Another project impact is the development and testing of a survey tool to assess food security and college students’ mental health with the addition of the expansion and testing of the HCEA to capture a wider breadth of determinants of health on college campuses (noted in Objective 3). These tools can be used on college campuses to measure health behaviors and identify environmental and population support for facilitating healthful behaviors.
• Finally, mechanisms of interaction between lifestyle behaviors and environmental factors in influencing healthful behaviors and health status of young adults will be determined and results disseminated for use in health and wellness programming (noted in Objective 4). Big data merging and analysis are necessary to continue the work of large collaborating groups. By exploring previous, current, and applicable external data sets, NC1193 could provide potential solutions regarding the health and wellness of students in the following areas for college campuses: cost-savings, recruitment and retention, marketing and promotion, understanding current and future needs of students, innovative intervention development, and/or customized and dynamic learning programs.

Milestones

(1):This milestone is an ongoing milestone and will continue through Year 5 regarding dissemination and implementation. In Year 1, activities will focus on developing training materials and activities, pursuing funding for dissemination activities, and exploring and developing potential partnerships. In Year 2, pursuing funding and exploring/developing partnerships will continue and in addition, develop tools to measure the effectiveness of the training and process evaluation tools for the adoption of the toolkit and toolkit components. In Year 3, pursuing funding and exploring/developing partnerships will continue and in addition, implement training and dissemination activities and track and evaluate training effectiveness and success in dissemination. In Years 4-5, the following activities will be conducted: pursue funding for dissemination activities, explore and develop potential partnerships, implement training and dissemination activities, track and evaluate training effectiveness and success in dissemination, and refine training and evaluation tools.

(2):This milestone is an ongoing milestone and will continue through Year 5 regarding community behaviors and environment. In Year 1, focus groups with program assistants will take place and advisory group development will occur. In Year 2, stakeholder interviews will be conducted and testing and adaptation of HCEA tools will take place. In Year 3, stakeholder interviews and testing and adaptation of HCEA tools will continue and focus groups with the target community will be initiated as well as testing of adapted HCEA tools. In Year 4, focus groups with the target community and testing of adapted HCEA tools will continue with the addition of BEPS-community item generation and testing and development of HCEA training. In Year 5, BEPS-community confirmatory analysis and dissemination of BEPS community and HCEA tools will occur.

(3):This milestone is an ongoing milestone and will continue through Year 5. In Year 1, item development will occur for the food security and mental health survey tool for the HCEA. In Year 2, item development will continue, with the initiation of training student research team members, conducting cognitive interviews, and survey and HCEA refinement . In Year 3, survey and HCEA refinement will continue along with draft 1 survey validation (EFA, CFA) and HCEA. In Year 4, survey and HCEA refinement will continue along with draft 2 survey validation and HCEA testing in a diverse sample. In Year 5, dissemination of findings will occur.

(4):This milestone is an ongoing milestone and will continue through Year 5 regarding bridging previous work to current and large data sets. In Year 1, review of applicable data sets and exploration of funding opportunities for big data analysis and interpretation will take place. In Year 2, identify and pursue funding with identified resources from member institutions to continue data analysis work and graduate student training. In Year 3, continue to pursue funding, data analysis work, and graduate student training. In addition, conduct analysis of big data sets commensurate with funding secured (internal and external). Use previous and current data sets to continue bridge work of behavior and environment approaches. In Year 4, continue analysis of big data sets commensurate with funding secured. In Years 4-5, dissemination of findings in refereed venues and possible new paradigm approach from big data findings will occur.

Projected Participation

View Appendix E: Participation

Outreach Plan

It is expected that the outcomes from the development of the tools will be disseminated through presentations at local, regional, and national meetings. Additionally, manuscripts will be submitted to appropriate peer-reviewed journals. To facilitate the collaboration and sharing of data and costs among the group members, we have established, as part of our multistate policies and procedures manual, a plan to facilitate the management of data and costs associated with data management and analysis.

In addition, an important aspect of the work among the five years is to apply the eB4CAST model⁷⁴, which will allow documentation of dissemination and sustainability of research endeavors. Through this model and the HCEA, the multistate team will provide reports to stakeholders on campuses and in communities with low income. This type of evidence-based community research is instrumental in driving change in awareness, behavior, and policy to impact our populations of interest for weight-related health promotion.

Organization/Governance

The NC1193 Multistate group has developed and adopted a policy and procedures manual that guides the functioning of the group. An Executive Committee (chair, chair-elect, and secretary) has the administrative oversight and organization for the multistate group. The chair, chair-elect, and secretary are elected by the members to serve for one-year terms. The term begins 1 Oct of each respective year. It is the responsibility of the chair to set the meetings, develop and post agendas, and run the meetings. The chair-elect completes the duties in the absence of the chair. The secretary maintains the minutes and posts on the multistate website. Additional administrative sub-committees with respective chairs and recorders have been developed to serve the research needs and functioning of the multistate group. The Policies and Procedures, Reports, and Awards sub-committee is responsible for maintaining the policy and procedure manual, submitting the annual report, chairing the renewal committee, and preparing additional documents such as awards submission. The Publications and Presentations sub-committee maintains a current list (including a copy of the document) of journal articles, abstracts, posters, and major presentations made by group members relevant to multistate objectives. This group is also responsible for maintaining and approving the respective requests to use multistate data (Project Submission) forms. The Data Management subcommittee is responsible to oversee the quality, storage, access, dissemination, archiving, and preservation of HCRC datasets. The Program Planning sub-committee plans and arranges for the annual meeting. The multistate members meet on a regularly (monthly) via teleconference and annually face-to-face at a date and place that is selected by the entire group.

To maintain a successful and productive multistate research group, members are expected to actively participate in, collaborate, and contribute to the HCRC research and administrative activities. Each member will be on at least one subcommittee related to committee management and one subcommittee related to research activities, participate in regularly scheduled teleconferences, and lead state-specific research activities. Members who choose not to actively participate will be asked to resign from the HCRC group, and the NC1193 Administrative Advisor will contact that member’s Ag Experiment Station Director. Active participation is defined as participating in at least 50% of teleconference calls and contributing to the collaborative research and administrative activities. Consideration for termination of group membership due to inactive status will be presented on agenda and discussed by full group membership followed by a vote by the full membership at the next group meeting (face-to-face or teleconference). If a vote is in favor of member termination, a request for formal removal from the project will be made to the respective State Ag Experiment Station Director and the regional NIMSS system administration.

Policies have been established on cost-sharing, establishing research topics, data sharing, publications, presentations, and research procedures. All NC1193 publications and related materials should give credit to the multistate project and other relevant grants. A password-protected website has been developed for archival of minutes and other documents used by the multistate members. A list-serv is also maintained by one of the members to facilitate communication.

Literature Cited

1.  Grabmeier J. 70 percent of college students stressed about finances.Ohio State University 2015.


2. Pascoe MC, Hetrick SE, Parker AG. The impact of stress on students in secondary school and higher education. http://mcmanuscriptcentralcom/rady. 2019.


3. Tuchscherer R. High tuition, living expenses and grades have college kids stressed, TD Ameritrade says. USA Today2019.


4. Arnett JJ. Emerging adulthood: What is it, and what is it good for? Child development perspectives. 2007;1(2):68-73.


5. Statastics NCfE. Population Distribution. United States Department of Education;2019.


6. Arnett JJ. Emerging adulthood: The winding road from the late teens through the twenties. - PsycNET. Oxford University Press; 2004.


7. Bonnie R, Brindis C, Carrion G, et al. Young Adults Ages 18 to 26 Should Be Viewed as Separate Subpopulation; In ‘Critical Development Period,’ They Face Economic and Social Challenges While Brain Is Still Maturing, Says New Report. 2014. Published October 30, 2014.


8. Colby S, Zhou W, Sowers MF, et al. College Students' Health Behavior Clusters: Differences by Sex. 2017.


9. Horacek TM, Erdman MB, Reznar MM, et al. Evaluation of the food store environment on and near the campus of 15 postsecondary institutions. American Journal of Health Promotion. 2013;27(4):e81-e90.


10. Hagedorn RL, McArthur LH, Hood LB, et al. Expenditure, Coping, and Academic Behaviors among Food-Insecure College Students at 10 Higher Education Institutes in the Appalachian and Southeastern Regions. Current Developments in Nutrition. 2019;3(6).


11. Hagedorn RL, Olfert MD. Food Insecurity and Behavioral Characteristics for Academic Success in Young Adults Attending an Appalachian University. Nutrients. 2018;10(3).


12. Olfert MD, Dent A, Wattick RA. Metabolic Syndrome Prevalence in Students Attending West Virginia University. Journal of Clinical Medicine. 2018;7(12):487.


13. Morrell JS, Byrd-Bredbenner C, Quick V, Olfert M, Dent A, Carey GB. Metabolic syndrome: comparison of prevalence in young adults at 3 land-grant universities. J Am Coll Health. 2014;62(1):1-9.


14. Horacek T, Yildirim ED, Kattelmann K, et al. Multilevel Structural Equation Modeling of Students’ Dietary Intentions/Behaviors, BMI, and the Healthfulness of Convenience Stores. Nutrients. 2018;10(11):1569.


15. Horacek TM, White AA, Byrd-Bredbenner C, et al. PACES: a physical activity campus environmental supports audit on university campuses. American Journal of Health Promotion. 2014;28(4):e104-e117.


16. Koenings MM, Olfert M, Kattelmann KK, Nitzke S. Pseudo-Underage Students' Access to Alcohol Surrounding Three College Campuses. http://dxdoiorg/101080/193202482012758064. 2013.


17. Wattick RA, Hagedorn RL, Olfert MD. Relationship between Diet and Mental Health in a Young Adult Appalachian College Population. Nutrients. 2018;10(8):957.


18. Sowers MF, Colby S, Greene GW, et al. Survey Development to Assess College Students' Perceptions of the Campus Environment. 2017.


19. McNamara J, Kunicki ZJ, Olfert MD, Byrd-Bredbenner C, Greene G. Revision and Psychometric Validation of a Survey Tool to Measure Critical Nutrition Literacy in Young Adults. Journal of Nutrition Education and Behavior. 2020;52(7):726-731.


20. Horacek TM, Yildirim ED, Kattelmann K, et al. Path Analysis of Campus Walkability/Bikeability and College Students’ Physical Activity Attitudes, Behaviors, and Body Mass Index. https://doiorg/101177/0890117116666357. 2016.


21. Center PR. Demographics of Mobile Device Ownership and Adoption in the United States. Washington, D.C.2019.


22. Wang Q, Chen, Wei & Liang, Yu. The Effects of Social Media on College Students, Johnson and Wales University; 2011.


23. Kumar SG, Vipul. Advantages and Disadvantages of Social Websites on Young Adults. Journal of Humanities Insights. 2017;1(1):34-36.


24. Statistics NCfE. The Condition of Education. 2018.


25. Goodwin P, McGill B, Chandra aA. Who Marries and When? Age at First Marriage in the United States: 200. Hyattsville, MD2009.


26. Vespa J. The changing economics and demographics of young adulthood: 1975-2016. US Department of Commerce, Economics and Statistics Administration, US …; 2017.


27. Substance Abuse and Mental Health Services Administration. (2018). Key substance use and mental health indicators in the United States: Results from the 2017 National Survey on Drug Use and Health (HHS Publication No. SMA 18-5068, NSUDH Series H-53). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Retrieved from https://www.samhsa.gov/data/sites/default/files/cbhsq-reports/NSDUHFFR2017/NSDUHFFR2017.pdf.


28. Atkeson A. What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios. In: the National Bureau of Economic Research; 2020.


29. Torales J, O’Higgins M, Castaldelli-Maia JM, Ventriglio A. The outbreak of COVID-19 coronavirus and its impact on global mental health:. https://doiorg/101177/0020764020915212. 2020.


30. Statastics NCfE. Digest of Education Statistics. United States Department of Education;2017.


31. Moore J. The Challenge of Coming in First: Helping First-Generation College Students Win Beyond Getting In | SpringerLink. 2017.


32. Ceballos N, Clark R, Hu Y, Easton J. Factors Influencing Academic Success in First Generation College Students. 2018.


33. Strayhorn TL. Factors Influencing the Academic Achievement of First-Generation College Students in: Journal of Student Affairs Research and Practice Volume 43 Issue 4 (2007). 2007.


34. Success CfF-GS. First-generation college students: Demographic characteristics and post secondary enrollment. 2018.


35. Aspelmeier JE, Love MM, McGill LA, Elliott AN, Pierce TW. Self-Esteem, Locus of Control, College Adjustment, and GPA Among First- and Continuing-Generation Students: A Moderator Model of Generational Status. Research in Higher Education. 2012;53(7):755-781.


36. Pratt IS, Harwood HB, Cavazos JT, Ditzfeld CP. Should I Stay or Should I Go? Retention in First-Generation College Students:. https://doiorg/101177/1521025117690868. 2017.


37. Diamond K, Stebleton M. "Do You Understand What It Means to be Hungry?" Food Insecurity on Campus and the Role of Higher Education Professionals. 2017.


38. Wooton R, Spence, Marsha, Colby, Sarah, Anderson Steeves, Elizabeth. Assessing food insecurity prevalence and associated factors among college students enrolled in a university in the Southeast USA - ProQuest. Public Health Nutrition. 2019;22(3):383-390.


39. Freudenberg N, Goldrick-Rab S, Poppendieck J. College students and SNAP: The new face of food insecurity in the United States. American Journal of Public Health. 2019;109(12):1652-1658.


40. Henry L. Experiences of Hunger and Food Insecurity in College. Springer International Publishing; 2020.


41. Sackey J, Rutgers University SoHP, Pike K, et al. Factors Associated with Food Insecurity Among College Students at a Large Northeastern University. Current Developments in Nutrition. 2020;4(Supplement_2):274-274.


42. Nikolaus C, Ellison B, An R, Nickols-Richardson S. Food Insecurity Among College Students in the U.S.: A Systematic Review and Meta-Analysis (P04-072-19). Current Developments in Nutrition. 2020;3(Supplement_1).


43. Martinez SM, Webb K, Frongillo EA, Ritchie LD. Food insecurity in California’s public university system: What are the risk factors? https://doiorg/101080/1932024820171374901. 2017.


44. El Zein A, Shelnutt KP, Colby S, et al. Prevalence and correlates of food insecurity among U.S. college students: a multi-institutional study. BMC Public Health. 2019;19(1):660-660.


45. El Zein A, Mathews A, House L, Shelnutt K. Why Are Hungry College Students Not Seeking Help? Predictors of and Barriers to Using an On-Campus Food Pantry. Nutrients. 2018;10(9):1163-1163.


46. Goldrick-Rab S, Baker-Smith C, Coca V, Looker E, Williams T. College and University Basic Needs Insecurity: A National #RealCollege Survey Report. The Hope Center;2019.

47. Robinson JA. Did You Know? The Struggle to Repay Student Loans — The James G. Martin Center for Academic Renewal. James G. Martin Center for Aademic Renewal; 2020-01-02 2020.


48. Adams T, Moore M. High-Risk Health and Credit Behavior Among 18- to 25-Year-Old College Students. https://doiorg/103200/JACH562101-108. 2010.


49. Lanoye A, Gorin AA, LaRose JG. Young Adults’ Attitudes and Perceptions of Obesity and Weight Management: Implications for Treatment Development. Curr Obes Rep. 2016;5(1):14-22.


50. Prevention CfDCa. Percent of adults aged 18 and older who have obesity, National | Chronic Disease and Health Promotion Data & Indicators. 2020.


51. Nelson MC, I. MSN, Neumark‐Sztainer LaD, Lytle LA. Emerging Adulthood and College‐aged Youth: An Overlooked Age for Weight‐related Behavior Change - Nelson - 2008 - Obesity - Wiley Online Library. Obesity. 2012.


52. Mihalopoulos NL, Auinger P, Klein JD. The Freshman 15: Is it Real? J Am Coll Health. 2008;56(5):531-533.


53. White J. Campus Environmental Perceptions of Impact of Fruit and Vegetable and Vigorous Physical Activity in College Students. Journal of Nutrition Education and Behavior. 2016;48(75).


54. Caswell JA, Yaktine AL, Allotments CoEotAoFRaS, et al. Individual, Household, and Environmental Factors Affecting Food Choices and Access. 2013.


55. Kattelmann KK, White AA, Greene GW, et al. Development of Young Adults Eating and Active for Health (YEAH) internet-based intervention via a community-based participatory research model. Journal of nutrition education and behavior. 2014;46(2):S10-S25.


56. Onikia B, Virginia Q, Sarah C, et al. Recruitment lessons learned from a tailored web-based health intervention Project Y.E.A.H. (Young Adults Eating and Active for Health). Health Education. 2015;115(5):470-479.


57. McNamara J, Olfert MD, Sowers M, et al. Development of an Instrument Measuring Perceived Environmental Healthfulness: Behavior Environment Perception Survey (BEPS). Journal of Nutrition Education and Behavior. 2019;52(2):152-161.


58. Horacek TM, Erdman MB, Byrd-Bredbenner C, et al. Assessment of the dining environment on and near the campuses of fifteen post-secondary institutions. Public health nutrition. 2013;16(7):1186-1196.


59. Horacek TM, Dede Yildirim E, Simon M, et al. Development and validation of the Full Restaurant Evaluation Supporting a Healthy (FRESH) Dining Environment Audit. Journal of Hunger & Environmental Nutrition. 2018:1-20.


60. Horacek TM, Yildirim ED, Kelly E, et al. Development and Validation of a Simple Convenience Store SHELF Audit. International Journal of Environmental Research and Public Health. 2018;15(12):2676.


61. Horacek TM, Simon M, Dede Yildirim E, et al. Development and Validation of the Policies, Opportunities, Initiatives and Notable Topics (POINTS) Audit for Campuses and Worksites. Int J Environ Res Public Health. 2019;16(5).


62. Horacek TM, Yildirim ED, Matthews Schreiber M, et al. Development and Validation of the Vending Evaluation for Nutrient-Density (VEND)ing Audit. Int J Environ Res Public Health. 2019;16(3):514.


63. Horacek TM, Yildirim ED, Seidman D, et al. Redesign, Field-Testing, and Validation of the Physical Activity Campus Environmental Supports (PACES) Audit. Journal of Environmental and Public Health. 2019:13.


64. Nitzke S, Kritsch K, Boeckner L, et al. A stage-tailored multi-modal intervention increases fruit and vegetable intakes of low-income young adults. American Journal of Health Promotion. 2007;22(1):6-14.


65. Dour CA, Horacek TM, Schembre SM, et al. Process evaluation of Project WebHealth: a nondieting Web-based intervention for obesity prevention in college students. Journal of nutrition education and behavior. 2013;45(4):288-295.


66. Kattelmann KK, Bredbenner CB, White AA, et al. The effects of Young Adults Eating and Active for Health (YEAH): a theory-based Web-delivered intervention. Journal of nutrition education and behavior. 2014;46(6):S27-S41.


67. Donaldson AB, Colby SE, Flanagan SM, et al. Cooking Behavior and Self-Efficacy of 9-10 Year Old Youth: iCook 4-H. Journal of the Academy of Nutrition and Dietetics. 2014;114(9):A64-A64.


68. Olfert M, Famodu O, Flanagan S, Smith E, Leary M. The effect of icook 4-H, a childhood obesity prevention program, on blood pressure and quality of life in youth and adults: A randomized control trial. J Child Obes Vol. 2018(3).


69. Miller A, Franzen-Castle L, Aguirre T, et al. Food-related behavior and intake of adult main meal preparers of 9–10 year-old children participating in iCook 4-H: A five-state childhood obesity prevention pilot study. Appetite. 2016;101:163-170.


70. White AA, Colby S, Franzen-Castle L, Kattelmann K, Olfert M. iCook: A 4-H Program to Promote Culinary Skills and Family Meals for Obesity Prevention. Journal of Nutrition Education and Behavior. 2013;45(4):S91-S91.


71. R M, S C, A D, et al. Influencers of family meal experience: iCook 4-H. J Nutr Educ Behav. 2014;46:S102.


72. Colby S, Olfert M, Mathews A, et al. “Get Fruved”: the RCT Year. Journal of Nutrition Education and Behavior. 2018;50(7):S116-S117.


73. Colby S, Cattleman, Kendra, Olfert, Melissa, Mathews, Anne, Horacek, Tanya, Kidd, Tandalayo, White, Adrienne, Brown, Onikia,. Get Fruved Toolkit. Ballistic Websites. Published 2019. Accessed.


74. Olfert M, Hagedorn R, Barr M, Famodu O, Rubino J, White J. eB4CAST: An Evidence-Based Tool to Promote Dissemination and Implementation in Community-Based, Public Health Research. International Journal of Environmental Research and Public Health. 2018;15(10):2142-2142.


75. Larson LR, Green GT, Castleberry SB. Construction and Validation of an Instrument to Measure Environmental Orientations in a Diverse Group of Children:. http://dxdoiorg/101177/0013916509345212. 2009.


76. Flowers AA, Carroll JP, Green GT, Larson LR. Using art to assess environmental education outcomes. http://dxdoiorg/101080/135046222014959473. 2014.


77. Service USDoAFaN. Healthy Eating Index (HEI). https://www.fns.usda.gov/resource/healthy-eating-index-hei. Published 2020. Accessed.


78. Schneider J, jmschneider@csuchico.edu, Clifford D, et al. Development and Reliability Testing of the Childhood Feeding Experiences Survey. Journal of Nutrition Education and Behavior. 2010;42(4).


79. Treatment CfSA. Chapter 8—Measuring Components of Client Motivation. In: Substance Abuse and Mental Health Services Administration (US); 1999.


80. America PfH. About Us. https://www.ahealthieramerica.org/articles/about-us-5. Published 2020. Accessed.


81. Education TAftAoSiH. AASHE, the Association for the Advancement of Sustainability in Higher Education. https://www.aashe.org/. Published 2020. Accessed.


82. Education AftAoSiH. STARS, Sustainability Tracking Assessment & Rating System. https://stars.aashe.org/. Published 2019. Accessed.


83. Minkler MW, Nina. Community-Based Participatory Research for Health. 2 ed. San Francisco, CA: John Wiley and Sons; 2008.


84. Foundation NS. Civic Innovation Challenge | NSF. https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505728. Published 2020. Accessed.


85. Boyatzis RE. Transforming Qualitative Information: thematic Analysis and Code Development. SAGE Publications; 1998.


86. Krippendorff K. Content Analysis: An introduction to its methodology. 4 ed. Thousand Oaks, CA: Sage Publications; 2018.


87. Williams B, Onsman A, Brown T. Exploratory factor analysis: A five-step guide for novices. Journal of Emergency Primary Health Care. 2010.


88. Beavers AS, Lounsbury, John W., Richards, Jennifer K., Huck, Schuyler W., Skolity, Gary J. Practical Consider actical Considerations for Using Explor ations for Using Exploratory Factor Analysis in or Analysis in Educational Research. Practical Assessment, Research, and Evaluation. 2013;18.


89. Pett MA, LAckey, Nancy A., Sullivan, John J. Making Sense of Factor Analysis: The use of factor analysis for instrument development in health care research. Thousand Oaks, CA: Sage Publications; 2003.


90. Brown TA. Confirmatory Factor Analysis for Applied Research. 4 ed. New York, New York: Guilford Publications; 2015.


91. Hagedorn RL, Pampalone AL, Hood LB, Yura CA, Morrow DF, Olfert MD. Higher Education Food Insecurity Toolkit Development and Feedback. Journal of Nutrition Education and Behavior. 2019.


92. TM H, MB E, C B-B, et al. Assessment of the Dining Environment on and Near the Campuses of Fifteen Post-Secondary Institutions. Public health nutrition. 2013;16(7).


93. Horacek TM, Erdman MB, Reznar MM, et al. Evaluation of the food store environment on and near the campus of 15 postsecondary institutions. Am J Health Promot. 2013;27(4):e81-90.


94. Horacek T, Szklany K, Byrd-Bredbenner C, et al. Development and Testing of a Healthy Campus Environmental Audit and the LEAN Index. Journal of Nutrition Education and Behavior. 2011;43(4):S22-S22.


95. Fisher RPG, Edward R. MEMORY ENHANCING TECHNIQUES FOR INVESTIGATIVE INTERVIEWING. Springfield, Illinois: Charles C. Thomas; 1992.


96. P.H. DLWG, Health MWKDo. CDC's Planned Approach to Community Health as an Application of PRECEED and an Inspiration for PROCEED. http://dxdoiorg/101080/10556699199210616277. 2013.


97. Green LWK, Marshall W. HEalth Promotion Planning: an Education and Environmental Approach. 2 ed. Mountain View, CA: Mayfield Publishing; 1991.


98. Hale JF. Application of the Precede-Proceed Model for Comprehensive Community Assessment, Education Programming, and Evaluation in a Combat Hospital Community during the Gulf War:. http://dxdoiorg/101177/108482239801100112. 2016.


99. Promotion OoDPaH. Healhty People 2020: Social Determinants of Health. https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health. Published 2020. Accessed.


100. Daniel BK. Big Data and data science: A critical review of issues for educational research - Daniel - 2019 - British Journal of Educational Technology - Wiley Online Library. 2020.


101. Sivarajah U, Kamal MM, Irani Z, Weerakkody V. Critical analysis of Big Data challenges and analytical methods. Journal of Business Research. 2017;70:263-286.


102. Olfert MD, melissa.olfert@mail.wvu.edu, 0000-0002-6686-3891, et al. Dissemination Using Infographic Reports Depicting Program Impact of a Community-Based Research Program: eB4CAST in iCook 4-H. Journal of Nutrition Education and Behavior. 2018;51(3).


103. Olfert MD, Barr ML, Hagedorn RL, et al. eB4CAST Approach Improves Science Communication With Stakeholders in a College-Based Health Program. Front Public Health. 2020;8.


104. Olfert MD, Hagedorn RL, Walker AE, Wattick RA. Rapid Dissemination of College Food Insecurity Findings in A Multi-Institutional Study Using the eB4CAST Approach. Nutrients. 2020;12(6):1646.


105. Walsh JR, Hebert A, Byrd-Bredbenner C, et al. The development and preliminary validation of the behavior, environment, and changeability survey (BECS). Journal of nutrition education and behavior. 2012;44(6):490-499.


106. White K, Habib R, Hardisty DJ. How to SHIFT Consumer Behaviors to be More Sustainable: A Literature Review and Guiding Framework:. https://doiorg/101177/0022242919825649. 2019.


107. White A, Colby S, Franzen-Castle L, Kattelmann K, Olfert MD. iCook: A 4-H program to promote culinary skills and family meals for obesity prevention. J Nutr Educ Behav. 2013;45:S91.


108. Eck KM, Delaney CL, Olfert MD, Shelnutt KP, Byrd-Bredbenner C. “If my family is happy, then I am happy”: Quality-of-life determinants of parents of school-age children:. https://doiorg/101177/2050312119828535. 2019.


109. Services USDoHaH. Americans poor diet drives $50 billion a year in health care costs | NHLBI, NIH. https://www.ncbi.nlm.nih.gov/pubmed/. Published 2019. Accessed.


110. Dornsife DaD, David. Promoting Health and Wellness at Work. 2017-01-31 2017.

Attachments

Land Grant Participating States/Institutions

AL, CA, FL, KS, KY, LA, ME, MN, MO, MS, NE, NH, NJ, OH, RI, SD, TN, TX, WV

Non Land Grant Participating States/Institutions

University of California, Davis, Veterinary Medicine Teaching and Research Center, University of Tenessee