Survey Development to Assess College Students' Perceptions of the Campus Environment

OBJECTIVE

We developed and tested a College Environmental Perceptions Survey (CEPS) to assess college students' perceptions of the healthfulness of their campus.

METHODS

CEPS was developed in 3 stages: questionnaire development, validity testing, and reliability testing. Questionnaire development was based on an extensive literature review and input from an expert panel to establish content validity. Face validity was established with the target population using cognitive interviews with 100 college students. Concurrent-criterion validity was established with in-depth interviews (N = 30) of college students compared to surveys completed by the same 30 students. Surveys completed by college students from 8 universities (N = 1147) were used to test internal structure (factor analysis) and internal consistency (Cronbach's alpha).

RESULTS

After development and testing, 15 items remained from the original 48 items. A 5-factor solution emerged: physical activity (4 items, α = .635), water (3 items, α = .773), vending (2 items, α = .680), healthy food (2 items, α = .631), and policy (2 items, α = .573). The mean total score for all universities was 62.71 (±11.16) on a 100-point scale.

CONCLUSION

CEPS appears to be a valid and reliable tool for assessing college students' perceptions of their health-related campus environment.

College Students' Health Behavior Clusters: Differences by Sex

OBJECTIVE

The study purpose was to identify clusters of weight-related behaviors by sex in a college student populations.

METHODS

We conducted secondary data analysis from online surveys and physical assessments collected in Project Young Adults Eating and Active for Health (YEAH) with a convenience sample of students on 13 college campuses in the United States. We performed 2-step cluster analysis by sex to identify subgroups with homogeneous characteristics and behaviors. We used 8 derivation variables: healthy eating; eating restraints; external cues; stress; fruit/vegetable intake; calories from fat; calories from sugar-sweetened beverages; and physical activity. Contribution of derivation variables to clusters was analyzed with a MANOVA test.

RESULTS

Data from 1594 students were included. Cluster analysis revealed 2-clusters labeled "Healthful Behavior" and "At-risk" for males and females with an additional "Laid Back" cluster for males. "At-risk" clusters had the highest BMI, waist circumference, elevated health risk, and stress and least healthy dietary intake and physical activity. The "Laid Back" cluster had normal weights and the lowest restrained eating, external cues sensitivity, and stress.

CONCLUSION

Identified differences in characteristics and attitudes towards weight-related behaviors between males and females can be used to tailor weight management programs.

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.

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 research is needed to determine successful recruitment methods for 18-24 years old college students.

Originality/value

– This paper lessens the gap regarding successful recruitment strategies for 18-24 years old 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.

The Challenges of Changing Dietary Behaviors of Underserved Populations

The dietary behaviors of underserved populations contribute to diet-related health disparities. Behavior change is affected by many factors that may be grouped in four main categories; individual, interpersonal, institutional, and community and public factors.6However, underserved populations experience additional stressors that create greater barriers to achieving dietary behavior change. Researchers and health professionals are encouraged to work with and within underserved communities to provide appropriate and acceptable programming. This article highlights other stressors that make behavior change more challenging for underserved populations. Additionally, guidance to developing and implementing successful interventions to improve dietary behavior change in underserved populations is included.