Clustering and Combining Pattern of High-Risk Behaviors among Iranian University Students: A Latent Class Analysis

Sima Afrashteh, Haleh Ghaem, Abbas Abbasi-Ghahramanloo, Hamid Reza Tabatabaee

Abstract


Background: High-risk behaviors are increasing among young adults worldwide. We aimed to identify university students’ subgroups on the basis of high-risk behaviors and to assess the role of age, living alone, religious beliefs, and parental support in the membership of specific subgroups.

Study design: A cross-sectional study

Methods: The study was conducted in Bushehr (south of Iran) from November to December 2016. The sample included 977 university students selected through random sampling. The data were collected using a self-administered questionnaire. Then, latent class analysis was used to classify the students.

Results: Totally, five latent classes were identified as follows: low risk, high risk, somewhat low risk, hookah user, and very high risk. Notably, 7.7% and 2.5% of the students belonged to high risk and very high risk classes, respectively. The results suggested the protective effect of familial support and religiosity on high-risk behaviors.

Conclusions: This study indicated the co-occurrence of high-risk behaviors. The findings can be used to plan and evaluate interventions by considering risk factors and protective factors in universities.

 


Keywords


Latent class analysis; High-risk behaviors; Subgrouping; Iran

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