Literature DB >> 21338738

Identifying clusters of college students at elevated health risk based on eating and exercise behaviors and psychosocial determinants of body weight.

Geoffrey W Greene1, Susan M Schembre, Adrienne A White, Sharon L Hoerr, Barbara Lohse, Suzanne Shoff, Tanya Horacek, Deborah Riebe, Jill Patterson, Beatrice W Phillips, Kendra K Kattelmann, Bryan Blissmer.   

Abstract

Weight gain and an increase in overweight and obesity in college students raise serious health concerns. Weight management interventions for college-age men and women might be more effective if they were tailored to subgroups of students with similar behavioral and psychosocial characteristics associated with body weight status. The purpose of this study was to use cluster analysis to identify homogenous subgroups of college-aged men and women enrolled in a weight gain prevention study (Project WebHealth) using baseline data collected in 2008. Project WebHealth was a 15-month nutrition and physical activity intervention designed to decrease the rate of unwanted weight gain in 1,689 college students at eight geographically diverse universities in the United States. Outcome measures included anthropometrics, fruit and vegetable intake, physical activity, cardiorespiratory fitness, and psychosocial variables associated with weight status in college students. Cluster analysis was performed separately by sex using a two-step clustering procedure using weight-related eating and exercise behaviors and psychosocial variables. Cluster groupings were validated against students' measured weight status and waist circumference as indicators of health risk. The study design was cross-sectional. Results showed that three similar clusters were identified for each sex. Validity of the cluster solution was supported by significant group differences in body mass index and waist circumference with the High Risk cluster at elevated health risk compared to the others. For men, variability in eating competence and cognitive restraint scores contributed most to the difference between clusters, whereas for women, emotional eating and uncontrolled eating scores did. These findings could be used to improve effectiveness of messages and interventions by tailoring them to subgroups of college students with similar behavioral and psychosocial characteristics associated with elevated health risk.
Copyright © 2011 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21338738     DOI: 10.1016/j.jada.2010.11.011

Source DB:  PubMed          Journal:  J Am Diet Assoc        ISSN: 0002-8223


  27 in total

1.  Stress and psychological constructs related to eating behavior are associated with anthropometry and body composition in young adults.

Authors:  Katie C Hootman; Kristin A Guertin; Patricia A Cassano
Journal:  Appetite       Date:  2018-01-05       Impact factor: 3.868

2.  Concordance of self-report and measured height and weight of college students.

Authors:  Virginia Quick; Carol Byrd-Bredbenner; Suzanne Shoff; Adrienne A White; Barbara Lohse; Tanya Horacek; Kendra Kattelmann; Beatrice Phillips; Sharon L Hoerr; Geoffrey Greene
Journal:  J Nutr Educ Behav       Date:  2014-10-12       Impact factor: 3.045

3.  College Students' Perception of Current and Projected 30-Year Cardiovascular Disease Risk Using Cluster Analysis with Internal Validation.

Authors:  Dieu-My T Tran
Journal:  J Community Health       Date:  2019-06

4.  Changes in eating and physical activity behaviors across seven semesters of college: living on or off campus matters.

Authors:  Meg Small; Lisa Bailey-Davis; Nicole Morgan; Jennifer Maggs
Journal:  Health Educ Behav       Date:  2012-12-10

5.  Relationships of eating competence, sleep behaviors and quality, and overweight status among college students.

Authors:  Virginia Quick; Suzanne Shoff; Barbara Lohse; Adrienne White; Tanya Horacek; Geoffrey Greene
Journal:  Eat Behav       Date:  2015-07-02

6.  Development and Validation of the Cognitive Behavioral Physical Activity Questionnaire.

Authors:  Susan M Schembre; Casey P Durand; Bryan J Blissmer; Geoffrey W Greene
Journal:  Am J Health Promot       Date:  2014-08-27

7.  Obesity-Related Differences between Women and Men in Brain Structure and Goal-Directed Behavior.

Authors:  Annette Horstmann; Franziska P Busse; David Mathar; Karsten Müller; Jöran Lepsien; Haiko Schlögl; Stefan Kabisch; Jürgen Kratzsch; Jane Neumann; Michael Stumvoll; Arno Villringer; Burkhard Pleger
Journal:  Front Hum Neurosci       Date:  2011-06-10       Impact factor: 3.169

8.  Changes over time in the relationship between weight, body fat, motivation, impulsivity and eating behaviour.

Authors:  Paula Foscarini-Craggs; Rob Lowe; Michelle Lee
Journal:  BMC Public Health       Date:  2021-07-08       Impact factor: 3.295

9.  Evaluation of About Being Active, an online lesson about physical activity shows that perception of being physically active is higher in eating competent low-income women.

Authors:  Barbara Lohse; Kristen Arnold; Patricia Wamboldt
Journal:  BMC Womens Health       Date:  2013-03-13       Impact factor: 2.809

10.  Health behaviors of German university freshmen during COVID-19 in association with health behaviors of close social ties, living arrangement, and time spent with peers.

Authors:  Chrys Gesualdo; Martin Pinquart
Journal:  Health Psychol Behav Med       Date:  2021-07-06
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