Abstract
Little is known about the complex patterning of weight-related health behaviors in 2- and 4-year college students. The objective of this study was to identify and describe unique classes of weight-related health behaviors among college students. Latent class analysis was used to identify homogenous, mutually exclusive classes of nine health behaviors that represent multiple theoretically/clinically relevant dimensions of obesity risk among 2- versus 4-year college students using cross-sectional statewide surveillance data (N = 17,584). Additionally, differences in class membership on selected sociodemographic characteristics were examined using a model-based approach. Analysis was conducted separately for both college groups, and five and four classes were identified for 2- and 4-year college students, respectively. Four classes were similar across 2- and 4-year college groups and were characterized as “mostly healthy dietary habits, active”; “moderately high screen time, active”; “moderately healthy dietary habits, inactive”; and “moderately high screen time, inactive.” “Moderately healthy dietary habits, high screen time” was the additional class unique to 2-year college students. These classes differed on a number of sociodemographic characteristics, including the proportion in each class who were classified as obese. Implications for prevention scientists and future intervention programs are considered.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 663-672 |
| Number of pages | 10 |
| Journal | Health Education and Behavior |
| Volume | 41 |
| Issue number | 6 |
| DOIs | |
| State | Published - Dec 24 2014 |
Bibliographical note
Publisher Copyright:© 2014 Society for Public Health Education.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- 2-and 4-year college students
- audience segmentation
- co-occurrence of health behaviors
- latent class analysis with a distal outcome
- obesity
- young adults
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