Suchergebnisse

Purpose.To examine the appropriateness of the five-stage schema developed for addictive behaviors when applied to nonaddictive behaviors such as fruit and vegetable consumption.Design.A cross-sectional mail survey was conducted.Setting.Self-administered questionnaires were mailed to the home addresses of respondents recruited in 10 states and returned upon completion.Subjects.In all, 116 male and 185 female young adults (response rate = 70%) completed the questionnaires. Most respondents were Caucasian (74.4%) and college students (62.2%).Measures.Statistical analyses included analysis of variance with Scheffe's test, Pearson correlation and Cronbach's a coefficients, factor analysis, and cluster analysis.Results.Staging algorithms for fruits and vegetables were developed according to the five-stage schema, and their construct validity was verified by the incremental trend of food intakes. The algorithms identified more than 80% of the subjects as precontemplators, preparers, or maintainers for both food groups. This distribution pattern agreed well with the three-factor solution generated from the stages of change questionnaire, for which internal reliability and validity were confirmed. Seven cluster profiles of the respondents were derived based on the three generated factors and appeared to represent stage subgroupings of those factors. The two food groups shared marked similarities regarding the profiling of the clusters, which was validated by comparing food intake. The results, however, cannot be generalized because of limitations involved in the current sample.Conclusions.The original five stages of change and traditional staging measures may need to be adapted and/or extended for dietary change.

Purpose. To examine the stages of change, decisional balance, and self-efficacy constructs in relation to fruit and vegetable intakes by young adults 18–24 years old. Design. A cross-sectional project was conducted by 10 states in January–July 2000 to examine decisional balance and self-efficacy in relation to stage of change for increasing fruit and vegetable intake among young adults. Subjects. In all, 1545 usable surveys were returned (response rate = 55%). More non-respondents were men and precontemplators than respondents. Sixty-one percent of respondents were women, 90.3% were white, and 49.7% were current students. Setting. Alabama, Kansas, Maine, Michigan, Nebraska, New York, Rhode Island, Oregon, South Dakota, and Wisconsin. Measures. A telephone screening interview and a self-administered mail survey. Analysis. Analysis of variance, principal components analysis, cluster analysis, and χ2 test. Results. From precontemplation to maintenance, a significant linear trend was found toward higher food intake and self-efficacy for fruits and vegetables. The patterns of shifts in the pros and cons across the stages resembled those of other health behaviors. The decisional balance items were further classified into five component factors that varied significantly in importance across the stages. Four subject clusters were derived (unconcerned, reluctant, exploring, and action-oriented); distribution of the clusters agreed with that of the five stages. Conclusions. This study supports applicability of the Transtheoretical Model for assessing fruit and vegetable consumption by young adults. Derivation of the four clusters implies the importance of including decisional balance and self-efficacy as outcome measures besides dietary behavior for evaluating the effectiveness of nutrition interventions.

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.

Purpose. Assess effectiveness of an intervention to improve fruit and vegetable consumption in economically disadvantaged young adults. Design. Randomized treatment-control, pre-post design. Setting. Ten states. Subjects. Young adults (n = 2024, ages 18–24) were recruited from noncollege venues; 1255 (62%) completed assessment interviews at baseline and at 4 and 12 months. Intervention. Treatment participants received a series of mailed materials and two educational calls in 6 months. Controls received a mailed pamphlet. Measures. Assessment calls determined two measures of fruit and vegetable intakes, demographics and stage of change at baseline, 4 and 12 months, plus treatment participants' decisional balance, processes, and self-efficacy. Analysis. Repeated measure analysis of variance, intent-to-treat, χ2, and logistic regression. Results. At follow-up, participants in the experimental group had higher intakes of fruit and vegetables than controls (perceived daily intakes of 4.90 vs. 4.60 servings per day, F = 3.49, p < .05 and 4.31 vs. 3.92 servings/day via 5-A-Day Screener, F = 4.78, p < .01) and greater progression to action or maintenance stages (66% progress in fruit for intervention vs. 55% progress in fruit for controls; 47% vs. 32% progress for vegetables, p = .0080 and .0001, respectively). Lower education, non-White ethnicity, male gender, living with children, and experimental group assignment predicted attrition (X26df = 288, p < .001, Cox R2 = .132). Conclusions. Tailored educational messages and research-extension partnerships are advantageous for improving fruit and vegetable intakes of young adults.

Purpose.To identify impact of an online nutrition and physical activity program for college students.Design.Randomized, controlled trial using online questionnaires and on-site physical and fitness assessments with measurement intervals of 0 (baseline), 3 (postintervention), and 15 months (follow-up).Setting.Online intervention delivered to college students; a centralized Web site was used for recruitment, data collection, data management, and intervention delivery.Subjects.College students (18–24 years old, n = 1689), from eight universities (Michigan State University, South Dakota State University, Syracuse University, The Pennsylvania State University, Tuskegee University, University of Rhode Island, University of Maine, and University of Wisconsin).Intervention.A 10-lesson curriculum focusing on healthful eating and physical activity, stressing nondieting principles such as size acceptance and eating competence (software developer: Rainstorm, Inc, Orono, Maine).Measures.Measurements included anthropometrics, cardiorespiratory fitness, fruit/vegetable (FV) intake, eating competence, physical activity, and psychosocial stress.Analysis.Repeated measures analysis of variance for outcome variables.Results.Most subjects were white, undergraduate females (63%), with 25% either overweight or obese. Treatment group completion rate for the curriculum was 84%. Over 15 months, the treatment group had significantly higher FV intake (+.5 cups/d) and physical activity participation (+270 metabolic equivalent minutes per week) than controls. For both groups, anthropometric values and stress increased, and fitness levels decreased. Gender differences were present for most variables. First-year males and females gained more weight than participants in other school years.Conclusion.A 10-week online nutrition and physical activity intervention to encourage competence in making healthful food and eating decisions had a positive, lasting effect on FV intake and maintained baseline levels of physical activity in a population that otherwise experiences significant declines in these healthful behaviors.

Purpose. This study evaluated the food stores on and near postsecondary campuses varying in institutional size. Design. The design of the study is an environmental audit survey. Setting. Fifteen U.S. postsecondary education institutions participated in this study between 2009–2011. Subjects. Eighty-one stores (44% grocery, 17% campus, and 39% convenience/drug) were evaluated. Measures. The Nutrition Environment Measures Survey for Stores was modified to evaluate food stores. Analysis. Analysis of variance with post hoc Tukey B and t-tests assessed differences between store types and by institutional size. Results. Grocery stores had significantly higher scores than campus/convenience stores for healthy foods (19.5 ± 3.8 vs. 2.4 ± 1.7), and for the availability (19.5 ± 3.8 vs. 2.4 ± 1.7) and quality (5.9 ± 0.5 vs. 1.8 ± 2.2) of fruits/vegetables (p < .001). Healthy foods and beverages were significantly more expensive (–0.6 ± 3.4 vs. 0.9 ± 2.0; p < .031) than their less healthful alternatives in grocery stores, but not in convenience stores. There were no differences by institutional size for grocery stores; however, smaller institutions' convenience stores had significantly lower availability and quality of fruits/vegetables and total food store environment scores. Conclusion. A college campus provides a food environment with an array of shopping venues, most of which are not consistent with dietary recommendations for obesity prevention. The limited quality of healthy food in on-campus and convenience stores and the exacerbated deficiencies for small postsecondary institutions provide evidence to support environmental and policy initiatives to improve the quality of campus food store environments.

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.

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 Tukey's 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.