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AIMS Public Health

2018, Volume 5, Issue 3: 296-311. doi: 10.3934/publichealth.2018.3.296
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Behavioral risk factor clusters among university students at nine universities in Libya

  • 1.
    Department of Surgery, Hamad General Hospital, Hamad Medical Corporation, Doha, State of Qatar
  • 2.
    College of Medicine, Qatar University, Doha, State of Qatar
  • 3.
    School of Health and Education, University of Skövde, Skövde, Sweden
  • 4.
    Faculty of Applied Sciences, University of Gloucestershire, Gloucester GL2 9HW, UK#
  • 5.
    Faculty of Medical Technology, Misrata, Libya
  • 6.
    Utrecht Centre for Child and Adolescent Studies, Utrecht University, Netherlands
  • 7.
    Unit for Health Promotion Research, Institute of Public Health, University of Southern Denmark, Niels Bohrs Vej 9-10, 6700 Esbjerg, Denmark
  • Received: 14 March 2018 Accepted: 20 June 2018 Published: 10 August 2018

  • Objectives: This study identifies and describes the clustering of 5 behavioral risk factors (BRFs) among university students. We also investigated whether cluster membership is associated with the students’ self-rated academic performance and self-rated health. Material and methods: A sample of 1300 undergraduates at 6 universities and 3 colleges in Libya completed a self-administered questionnaire that assessed BRFs (nutrition, physical activity, alcohol consumption, smoking, illicit drug use, inadequate sleep). A two-step cluster analysis generated student clusters with similar lifestyles. Results: Two contrasting clusters of almost even size emerged (after exclusion of alcohol and illicit drug use due to very low prevalence). Cluster 1 comprised students with higher engagement in all forms of physical activity, higher levels of health consciousness, greater daily fruit/vegetable intake and better sleep patterns than students in cluster 2. Only as regards the consumption of sweets, cluster 1 students had less favorable practices than cluster 2 students. The prevalence of smoking was equally low in both clusters. Students in cluster 2, depicting a less healthy lifestyle, were characterized by a higher proportion of women, of students with less income and of higher years of study. Belonging to cluster 2 was associated with lower self-rated health (OR: 0.46, p < 0.001) and with lower self-rated academic performance (OR: 0.66, p < 0.001). Conclusion: Preventive programs should not address BRFs in isolation and should particularly target students with clustering of BRFs using specifically tailored approaches.

    Citation: Walid El Ansari, Khalid A Khalil, Derrick Ssewanyana, Christiane Stock. Behavioral risk factor clusters among university students at nine universities in Libya[J]. AIMS Public Health, 2018, 5(3): 296-311. doi: 10.3934/publichealth.2018.3.296

    Related Papers:

  • Objectives: This study identifies and describes the clustering of 5 behavioral risk factors (BRFs) among university students. We also investigated whether cluster membership is associated with the students’ self-rated academic performance and self-rated health. Material and methods: A sample of 1300 undergraduates at 6 universities and 3 colleges in Libya completed a self-administered questionnaire that assessed BRFs (nutrition, physical activity, alcohol consumption, smoking, illicit drug use, inadequate sleep). A two-step cluster analysis generated student clusters with similar lifestyles. Results: Two contrasting clusters of almost even size emerged (after exclusion of alcohol and illicit drug use due to very low prevalence). Cluster 1 comprised students with higher engagement in all forms of physical activity, higher levels of health consciousness, greater daily fruit/vegetable intake and better sleep patterns than students in cluster 2. Only as regards the consumption of sweets, cluster 1 students had less favorable practices than cluster 2 students. The prevalence of smoking was equally low in both clusters. Students in cluster 2, depicting a less healthy lifestyle, were characterized by a higher proportion of women, of students with less income and of higher years of study. Belonging to cluster 2 was associated with lower self-rated health (OR: 0.46, p < 0.001) and with lower self-rated academic performance (OR: 0.66, p < 0.001). Conclusion: Preventive programs should not address BRFs in isolation and should particularly target students with clustering of BRFs using specifically tailored approaches.


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