Development of an Instrument Measuring Perceived Environmental Healthfulness: Behavior Environment Perception Survey (BEPS).

OBJECTIVE: To create a tool to measure college students' perception of the healthfulness of their environment. DESIGN: (1) Item generation, (2) cognitive interview testing and exploratory factor analysis, (3) item refinement/modification, (4) factor structure validation, and (5) criterion validation. SETTING: Ten college campuses. PARTICIPANTS: Time point 1 (n = 120 cognitive interviews; n = 922 factor analysis); time point 2 (n = 2,676), convenience sample of undergraduate students. MAIN OUTCOME MEASURES: Cognitive interviews and survey data were used to assess perceptions about the environment. ANALYSIS: Exploratory factor analysis, structural equation confirmatory factor analysis, correlations, and regressions. RESULTS: Item generation resulted in 93 items. Items were eliminated based on cognitive interviews, exploratory factor analysis of pilot data, and elimination of cross-loading or weak loading items. In confirmatory analyses, a 21-item, 5-factor structure was the best fit for the data (χ2 = 3,286.77, degrees of freedom = 189; comparative fit index = 0.840; root-mean-square error of approximation = 0.078). Environmental factors include physical activity (α = 0.68, 4 items), healthful eating (α = 0.86, 5 items), mental health (α = 0.85, 5 items), barriers to healthful eating (α = 0.70, 4 items), and peer influences (α = 0.73, 3 items). There were significant associations between scales and validation criteria (P < .05). CONCLUSIONS AND IMPLICATIONS: The Behavior Environment Perception Survey is a novel instrument measuring perceptions of the healthfulness of the campus environment. Strengths include a development process involving 10 different universities, strong psychometric properties, and breadth of constructs.

Food Choice Priorities Change Over Time and Predict Dietary Intake at the End of the First Year of College Among Students in the U.S.

This study assessed food choice priorities (FCP) and associations with consumption of fruits and vegetables (FV), fiber, added sugars from non-beverage sources, and sugar-sweetened beverages (SSB) among college students. Freshmen from eight U.S. universities (N = 1149) completed the Food Choice Priorities Survey, designed for college students to provide a way to determine the factors of greatest importance regarding food choices, and the NCI Dietary Screener Questionnaire. Changes in FCP and dietary intake from fall 2015 to spring 2016 were assessed. Multiple regression models examined associations between FCP and log-transformed dietary intake, controlling for sex, age, race, and BMI. Participant characteristics and FCP associations were also assessed. FCP importance changed across the freshmen year and significantly predicted dietary intake. The most important FCP were price, busy daily life and preferences, and healthy aesthetic. Students who endorsed healthy aesthetic factors (health, effect on physical appearance, freshness/quality/in season) as important for food choice, consumed more FV and fiber and less added sugar and SSB. Busy daily life and preferences (taste, convenience, routine, ability to feel full) predicted lower FV, higher added sugar, and higher SSB consumption. Price predicted lower FV, higher SSB, and more added sugar while the advertising environment was positively associated with SSB intake. FCP and demographic factors explained between 2%⁻17% of the variance in dietary intake across models. The strongest relationship was between healthy aesthetic factors and SSB (B = -0.37, p < 0.01). Self-rated importance of factors influencing food choice are related to dietary intake among students. Interventions that shift identified FCP may positively impact students' diet quality especially considering that some FCP increase in importance across the first year of college.

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.