O. Brown

The Effects of Young Adults Eating and Active for Health (YEAH): A Theory-Based Web-Delivered Intervention

OBJECTIVE To assess the effectiveness of a tailored theory-based, Web-delivered intervention (Young Adults Eating and Active for Health) developed using community-based participatory research process. DESIGN A 15-month (10-week intensive intervention with a 12-month follow-up) randomized, controlled trial delivered via Internet and e-mail. SETTING Thirteen college campuses. PARTICIPANTS A total of 1,639 college students. INTERVENTION Twenty-one mini-educational lessons and e-mail messages (called nudges) developed with the non-diet approach and focusing on eating behavior, physical activity, stress management, and healthy weight management. Nudges were short, frequent, entertaining, and stage-tailored to each behavior, and reinforced lesson content. MAIN OUTCOME MEASURE All participants were assessed at baseline, postintervention (3 months from baseline), and follow-up (15 months from baseline) for primary outcomes of weight, body mass index (BMI), fruit and vegetable intake (FVI), physical activity (PA), and perceived stress; and secondary outcomes of waist circumference, percent dietary fat, energy from sugar-sweetened beverages, servings of whole grains, self-instruction and regulation for mealtime behavior, hours of sleep, and stage of readiness for change for consuming 5 cups of FVI, completing 150 minutes of PA/wk, and managing stress on most days of the week. Demographics were collected at baseline. ANALYSIS Chi-square analysis and mixed-models repeated measures analysis were performed to determine differences between experimental and control outcomes. RESULTS There were no differences between experimental and control participants in BMI, weight, and waist circumference. There were small improvements in FVI (P = .001), vigorous PA in females (P = .05), fat intake (P = .002), self-instruction (P = .001), and regulation (P = .004) for mealtime behavior, and hours of sleep (P = .05) at postintervention, but improvements were not maintained at follow-up. At postintervention, a greater proportion of experimental participants were in the action/maintenance stages for FVI (P = .019) and PA (P = .002) than control. CONCLUSIONS AND IMPLICATIONS Young Adults Eating and Active for Health is one of the first studies to use the community-based participatory research process of PRECEDE-PROCEED to develop a non-diet approach intervention. Although there were no differences between experimental and control participants in weight change or BMI, the intervention supported positive change in behaviors that may mediate excessive weight gain, such as increasing FVI and more healthful self-regulation mealtime behaviors immediately postintervention. Additional strategies to maintain the behavior changes need to be explored.

Mobile MyPlate: A Pilot Study Using Text Messaging to Provide Nutrition Education and Promote Better Dietary Choices in College Students

Abstract Objective: To evaluate the acceptance and effectiveness of repetitive nutrition-related text messages on college students’ nutrition knowledge and fruit and vegetable consumption. Participants: One hundred fifty undergraduate (18–24 years old) non–health major students with a texting mobile phone. Methods: The intervention group received biweekly text messages of the MyPlate icon and the United States Department of Agricultures Dietary Guidelines (DGs) for 7 weeks. The control group received the same information in a mailed brochure. A pre and post online survey assessed the students’ knowledge and behavior. Results: The intervention resulted in greater MyPlate food group recognition (p <.05) compared with control and a trend toward improved knowledge of the DGs. In the intervention group, fruit consumption was elevated (p <.05) and a trend toward elevated vegetable consumption was determined. No gender differences in intervention effectiveness exist. Conclusion: Texting repeated messages appears to be an acceptable and effective way to increase nutrition knowledge and promote positive diet-related behaviors in college students.

Eat, Sleep, Work, Play: Associations of Weight Status and Health-Related Behaviors Among Young Adult College Students

Purpose. To examine relationships of sleep, eating, and exercise behaviors; work time pressures; and sociodemographic characteristics by weight status (healthy weight [body mass index or BMI < 25] vs. overweight [BMI ≥ 25]) of young adults. Design. Cross-sectional. Setting. Nine U.S. universities. Subjects. Enrolled college students (N = 1252; 18–24 years; 80% white; 59% female). Measures. Survey included the Pittsburgh Sleep Quality Index (PSQI), Three-Factor Eating Questionnaire (TFEQ), Satter Eating Competence Inventory (ecSI), National Cancer Institute Fruit/Vegetable Screener, International Physical Activity Questionnaire, Work Time Pressure items, and sociodemographic characteristics. Analysis. Chi-square and t-tests determined significant bivariate associations of sociodemographics, sleep behaviors, eating behaviors, physical activity behavior, and work time pressures with weight status (i.e., healthy vs. overweight/obese). Statistically significant bivariate associations with weight status were then entered into a multivariate logistic regression model that estimated associations with being overweight/obese. Results. Sex (female), race (nonwhite), older age, higher Global PSQI score, lower ecSI total score, and higher TFEQ Emotional Eating Scale score were significantly (p < .05) associated with overweight/obesity in bivariate analyses. Multivariate logistic regression analysis showed that sex (female; odds ratio [OR] = 2.05, confidence interval [CI] = 1.54–2.74), older age (OR = 1.35, CI= 1.21–1.50), higher Global PSQI score (OR = 1.07, CI = 1.01–1.13), and lower ecSI score (OR = .96, CI = .94–.98), were significantly (p < .05) associated with overweight/obesity. Conclusion. Findings suggest that obesity prevention interventions for college students should include an education component to emphasize the importance of overall sleep quality and improving eating competence.

Development of Young Adults Eating and Active for Health (YEAH) Internet-Based Intervention via a Community-Based Participatory Research Model

OBJECTIVE To develop a tailored, theory-based, Web-delivered intervention to prevent excessive weight gain in young adults using a Community-Based Participatory Research model. DESIGN Investigators from 14 universities developed the intervention and supporting administrative portal using the 4 phases of the PRECEDE model. Steering committees were composed of the target audience (aged 19-24 years) and key health/wellness personnel were formed at each institution and provided information during each phase that was used to guide development of the intervention, Project YEAH (Young Adults Eating and Active for Health). Piloting results were used to refine the curriculum and identify and avoid barriers to delivery. RESULTS Qualitative and quantitative data collected at each phase informed Project YEAH development. In Phase 1, factors of highest priority to young adults were identified. In Phase 2, environmental supports for healthful lifestyles were elucidated. In Phase 3, behavior and environmental changes considered important and changeable were identified. In Phase 4, the 10-week, theory-based, stage-tailored, interactive-learning intervention with a 10-month reinforcement period was developed. CONCLUSIONS AND IMPLICATIONS Applying the PRECEDE model with fidelity during development of Project YEAH resulted in an intervention that pilot participants found relevant and useful, gained attention, instilled confidence in the ability to apply the information, and provided a sense of satisfaction.

Relationships of Sleep Duration With Weight-Related Behaviors of U.S. College Students

This study describes sleep behaviors of U.S. college students (N = 1,252; 18–24 years old; 59% female) and examines associations of sleep duration with weight-related behaviors. More than one quarter of participants slept < 7 hr/night and had mean Pittsburgh Sleep Quality Index (PSQI) scores indicating poor sleep quality. There were significant differences for all PSQI scales among sleep duration categories, < 7 hr (n = 344), 7–8 hr (n = 449), ≥ 8 hr (n = 459) sleep/night. Compared to those who slept ≥ 8 hr, those who slept < 8 hr had significantly more negative eating attitudes (2% higher), poorer internal regulation of food (4% lower), and greater binge eating (4% higher) scores. Findings advocate for health care professionals to evaluate sleep behaviors of college students during office visits and promote good sleep behaviors.

Recruitment lessons learned from a tailored web-based health intervention project Y.E.A.H. (young adults eating and Active for health)

Purpose – Recruiting college students for research studies can be challenging. The purpose of this paper is to describe the lessons learned in the various recruitment strategies used for enrolling college students in a theory-based, tailored, and web-delivered health intervention at 13 US universities. Design/methodology/approach – The community-based participatory research (CBPR) model was used to develop a staged-tailored, web-based, randomized control trial, focussing on eating behavior, physical activity, and stress management. Participant feedback during baseline assessments was used to evaluate recruitment strategies. Findings – Findings from this feedback suggest that traditional recruitment strategies, such as newspaper ads and flyers, may not be the best approach for recruiting college students; instead, web-based efforts proved to be a better recruitment strategy. Research limitations/implications – This project included results from 13 US universities and thus may not be generalizable: more res...

PACES: A Physical Activity Campus Environmental Supports Audit on University Campuses

Purpose. This study evaluated the policy and built and recreation environmental supports for physical activity on 13 university campuses. Design. Environmental audit survey. Setting. Thirteen U.S. universities, 2009. Subjects. University policies, recreation programs and facilities, and at least five additional buildings per campus. Measures. The Physical Activity Campus Environmental Supports Audit was developed for this study. Analysis. Analysis of variance with post hoc Tukeys B and χ2 assessed differences by institution and building type. Results. The mean obesogenic policy score was significantly lower than the desired score, ≥ 7 (p = .002), with only one campus scoring 10. The mean built environment audit score (5.4 ± 1.7) was low, with significant differences between institutions (p < .001) and only three campuses scoring above the desired score, ≥ 7. Although generally stairwells were clean and well lighted, there was a lack of signage to encourage stair use (p < .001). Overall, recreation programs (7.1 ± .7) and facilities (7.1 ± 1.2) scored well, but amenities scores were lower for satellite (2.8 ± 1.6) versus main (4.1 ± 1.8) recreation facilities (p = .04). Conclusion. On these 13 university campuses, recreation programs and facilities were supportive of healthful lifestyles for obesity prevention, but policies and the built environment were not. This physical activity environmental audit survey requires testing in a wider sample of postsecondary institutions to corroborate its utility and provide evidence to support initiatives to improve campus environments for physical activity.

Path Analysis of Campus Walkability/Bikeability and College Students’ Physical Activity Attitudes, Behaviors, and Body Mass Index:

Purpose: The purpose of this study was to assess the relationship between the walkability/bikeability of college campuses and students’ body mass index (BMI) with student physical activity (PA) attitudes and behaviors as potential mediators. Design: Cross-sectional. Setting: Thirteen university campuses. Participants: A total of 1384 student participants. Measures: Walkability/bikeability environmental score (ES): 12-item audit assessed an average of 44 path segments per campus. Students were measured for height and weight and completed online surveys. Physical activity stage of change/behavior intentions were assessed using the transtheoretical model. The Cognitive Behavioral Physical Activity Questionnaire assessed outcome expectations, self-regulation, and personal barriers. International Physical Activity Questionnaire assessed walking-, moderate-, and vigorous-intensity PA. Analysis: Descriptive statistics, zero-order correlations, and path analysis with maximum likelihood estimation. Results: The overall model fit was good with χ2 of 171.388 (df = 18), P < .001, comparative fit index value of .95, and a root mean square of approximation of .079. After controlling for gender, there was a direct negative association between walkability/bikeability ES and BMI (β = −.085) and positive association between personal barriers and BMI (β = .134). Walkability/bikeability ES was positively associated with walking-intensity PA (β = .010). Self-regulation was positively associated with moderate-intensity PA (β = .213), which, in turn, was negatively associated with BMI (β = −.057). Conclusions: The ease of walking and biking on a campus was related to college students’ walking behavior and their BMI. Students’ PA behavioral intentions were associated with moderate PA and lower BMI. These results provide evidence to focus on policies and structural supports for walkable/bikeable environments to supplement and enhance interventions encouraging individual behavior change for PA and weight management.

Development and validation of the Full Restaurant Evaluation Supporting a Healthy (FRESH) Dining Environment Audit

ABSTRACT The Full Restaurant Evaluation Supporting a Healthy (FRESH) Dining Environment Audit was developed and validated to assess cafeterias and restaurants (n = 362). Each scale item was scored using a 5-point semantic-differential rating (1 = little/no options/support to 5 = extensive options/high support for healthy food selection). Statistical analysis included factor analysis, analysis of variance, and correlations. The Healthfulness of Foods (HF) sub-scale assessed menu descriptions to determine healthful foods availability (12 items, α = .82, possible = 60). The Dining Environmental Supports (ES) sub-scale assessed nutrition information/labeling, signage/posters, and portion/cup sizes (eight items, α = .78; possible = 40). Cafeterias consistently scored higher than other restaurant types on HF (29.45 ± 12.17 SD) and ES (22.10 ± 5.27 SD). Convergent validity was confirmed (n = 91; HF: r = .854, p ≤ .001 and ES: r = .529, p ≤ .01). The FRESH audit is a simple tool that effectively assessed differences in the healthfulness of foods and environmental supports between a variety of dining venues.

Multilevel Structural Equation Modeling of Students’ 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’ dietary intentions/behaviors, and body mass index (BMI). Methods: Through multilevel structural equation modeling, a comparison was made of students’ 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.