Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

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

topical section: Health Behavior, Health Promotion and Society

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.
  Figure/Table
  Supplementary
  Article Metrics

Keywords university students; gender; risk factors; health behaviors; cluster analysis

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

References

  • 1. Rahim HFA, Sibai A, Khader Y, et al. (2014) Non-communicable diseases in the Arab world. Lancet 383: 356–367.    
  • 2. Spring B, Moller AC, Coons MJ (2012) Multiple health behaviours: Overview and implications. ‎J Public Health 34: i3–i10.    
  • 3. Musaiger A, Al-Mannai M, Tayyem R, et al. (2012) Prevalence of overweight and obesity among adolescents in seven Arab countries: A cross-cultural study. J Obes 2012: 981390.
  • 4. Sachithananthan V, Buzgeia M, Awad F, et al. (2013) Nutritional status, dietary profile and selected lifestyle attributes of adolescents and early adults in Benghazi, Libya. J Food Nutr Disor d 3: 2.
  • 5. Salam A, Alshekteria A, Mohammed H, et al. (2012) Physical, mental, emotional and social health status of adolescents and youths in Benghazi, Libya. East Mediterr Health J 18: 586–598.    
  • 6. Tsouros A, Dowding G, Thompson J, et al. (1998) Health promoting universities: Concept, experience and framework for action. Copenhagen: World Health Organization.
  • 7. Education Audiovisual and Culture Executive Agency (EACEA), Higher Education in Libya, 2012. Available from: http://eacea.ec.europa.eu/tempus/participating_countries/overview/libya_overview_of_hes_final.pdf (accessed 20 April 2018).
  • 8. Tamtam A, Gallagher F, Olabi AG, et al. (2011) Higher education in Libya, system under stress. Proc Soc Behav Sci 29: 742–751.    
  • 9. Ansari WE, Khalil K, Stock C (2014) Symptoms and health complaints and their association with perceived stressors among students at nine Libyan universities. Int J Environ Res Public Health 11: 12088–12107.    
  • 10. Conry MC, Morgan K, Curry P, et al. (2011) The clustering of health behaviours in Ireland and their relationship with mental health, self-rated health and quality of life. BMC Public Health 11: 692.    
  • 11. So ES, Park BM (2016) Health behaviors and academic performance among Korean adolescents. Asian Nurs Res 10: 123–127.    
  • 12. Tucker P, Gilliland J (2007) The effect of season and weather on physical activity: A systematic review. Public Health 121: 909–922.    
  • 13. Molnar BE, Gortmaker SL, Bull FC, et al. (2004) Unsafe to play? Neighborhood disorder and lack of safety predict reduced physical activity among urban children and adolescents. Am J Health Promot 18: 378–386.
  • 14. Abbasi IN (2014) Socio-cultural barriers to attaining recommended levels of physical activity among females: A review of literature. Quest 66: 448–467.    
  • 15. Moodie R, Stuckler D, Monteiro C, et al. (2013) Profits and pandemics: Prevention of harmful effects of tobacco, alcohol, and ultra-processed food and drink industries. Lancet 381: 670–679.    
  • 16. El Ansari W, Khalil K, Crone D, et al. (2014) Physical activity and gender differences: Correlates of compliance with recommended levels of five forms of physical activity among students at nine universities in Libya. Cent Eur J Public Health 22: 98.    
  • 17. Baskin-Sommers A, Sommers I (2006) The co-occurrence of substance use and high-risk behaviors. J Adolesc Health 38: 609–611.    
  • 18. Willoughby T, Chalmers H, Busseri MA (2004) Where is the syndrome? Examining co-occurrence among multiple problem behaviors in adolescence. J Consult Clin Psychol 72: 1022.
  • 19. Zweig JM, Lindberg LD, Mcginley KA (2001) Adolescent health risk profiles: The co-occurrence of health risks among females and males. J Youth Adolesc 30: 707–728.
  • 20. Schuit AJ, van Loon AJM, Tijhuis M, et al. (2002) Clustering of lifestyle risk factors in a general adult population. Prev Med 35: 219–224.
  • 21. Costa E, Dias CM, Oliveira L, et al. (2014) Clustering of behavioural risk factors in the Portuguese population: Data from National Health Interview Survey. J Behav Health 3: 205–211.    
  • 22. Huang DY, Lanza HI, Murphy DA, et al. (2012) Parallel development of risk behaviors in adolescence: Potential pathways to co-occurrence. Int J Behav Dev 36: 247–257.    
  • 23. Hale D, Viner R (2012) Policy responses to multiple risk behaviours in adolescents. J Public Health 34: i11–i19.    
  • 24. Scott A, Knott M (1974) A cluster analysis method for grouping means in the analysis of variance. Biometrics 30: 507–512.    
  • 25. Kaufman L, Rousseeuw PJ (2009) Finding groups in data: An introduction to cluster analysis. New Jersey: John Wiley & Sons.
  • 26. Rapkin BD, Luke DA (1993) Cluster analysis in community research: Epistemology and practice. Am J Community Psychol 21: 247–277.    
  • 27. Lanza ST, Cooper BR (2016) Latent class analysis for developmental research. Child Dev Perspect 10: 59–64.    
  • 28. El Ansari W, Stock C (2010) Is the health and wellbeing of university students associated with their academic performance? Cross sectional findings from the United Kingdom. Int J Environ Res Public Health 7: 509–527.
  • 29. El Ansari W, Stock C, Mills C (2013) Is alcohol consumption associated with poor academic achievement in university students? Int J Prev Med 1: 1175–1188.
  • 30. American College Health Association (2007) American College Health Association National College Health Assessment (ACHA-NCHA): Spring 2006 Reference Group Report (abridged). J Am Coll Health 55: 195.    
  • 31. Stock C, Kücük N, Miseviciene I, et al. (2002) Differences in health complaints between university students from three European countries. Eur J Public Health 12: 26–27.
  • 32. Haskell WL, Lee IM, Pate RR, et al. (2007) Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation 116: 1081.    
  • 33. Mikolajczyk RT, El Ansari W, Maxwell AE (2009) Food consumption frequency and perceived stress and depressive symptoms among students in three European countries. Nutr J 8: 31.    
  • 34. Hurrelmann K, Kolip P (1994) The Youth Health Survey. Public Relations Service, SFB 227, No 11. Bielefeld: University of Bielefeld.
  • 35. El Ansari W, Stock C, John J, et al. (2011) Health promoting behaviours and lifestyle characteristics of students at seven universities in the UK. Cent Eur J Public Health 19: 197–204.
  • 36. Stock C, Mikolajczyk R, Bloomfield K, et al. (2009) Alcohol consumption and attitudes towards banning alcohol sales on campus among European university students. Public Health 123: 122–129.    
  • 37. Mchugh ML (2013) The chi-square test of independence. Biochem Med 23: 143–149.
  • 38. He FJ, Nowson CA, Macgregor GA (2006) Fruit and vegetable consumption and stroke: Meta-analysis of cohort studies. Lancet 367: 320–326.    
  • 39. World Health Organization, Global recommendations on physical activity for health, 2010. Available from: http://www.who.int/dietphysicalactivity/factsheet_recommendations/en/ (accesssed 9 January 2018).
  • 40. Murray CJ, Vos T, Lozano R, et al. (2012) Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 380: 2197–2223.    
  • 41. Buck D, Frosini F (2012) Clustering of unhealthy behaviours over time: Implications for policy and practice. Available from: http://www.haringey.gov.uk/sites/haringeygovuk/files/clustering-of-unhealthy-behaviours-over-time-aug-2013.pdf (accessed 2 Febraury 2018).
  • 42. Ye YL, Wang PG, Qu GC, et al. (2016) Associations between multiple health risk behaviors and mental health among Chinese college students. Psychol Health Med 21: 377–385.    
  • 43. Alzahrani SG, Watt RG, Sheiham A, et al. (2014) Patterns of clustering of six health-compromising behaviours in Saudi adolescents. BMC Public Health 14: 1215.    
  • 44. Quintiliani L, Allen J, Marino M, et al. (2010) Multiple health behavior clusters among female college students. Patient Educ Couns 79: 134–137.    
  • 45. Dodd LJ, Al-Nakeeb Y, Nevill A, et al. (2010) Lifestyle risk factors of students: A cluster analytical approach. Prev Med 51: 73–77.    
  • 46. Lv J, Liu Q, Ren Y, et al. (2011) Socio-demographic association of multiple modifiable lifestyle risk factors and their clustering in a representative urban population of adults: A cross-sectional study in Hangzhou, China. Int J Behav Nutr Phys Act 8: 40.    
  • 47. Galan I, Rodriguez-Artalejo F, Tobias A, et al. (2005) Clustering of behavior-related risk factors and its association with subjective health. Gac Sanit 19: 370–378.
  • 48. Kritsotakis G, Psarrou M, Vassilaki M, et al. (2016) Gender differences in the prevalence and clustering of multiple health risk behaviours in young adults. J Adv Nurs 72: 2098–2113.    
  • 49. Haug S, Schaub MP, Gross CS, et al. (2013) Predictors of hazardous drinking, tobacco smoking and physical inactivity in vocational school students. BMC Public Health 13: 475.    
  • 50. Idowu A, Fatusi AO, Olajide FO (2016) Clustering of behavioural risk factors for non-communicable diseases (NCDs) among rural-based adolescents in south-west Nigeria. Int J Adolesc Med Health.
  • 51. Lippke S, Nigg CR, Maddock JE (2012) Health-promoting and health-risk behaviors: Theory-driven analyses of multiple health behavior change in three international samples. Int J Behav Med 19: 1–13.
  • 52. Nigg CR, Lee H, Hubbard AE, et al. (2009) Gateway health behaviors in college students: Investigating transfer and compensation effects. J Am Coll Health 58: 39–44.    
  • 53. Costa FM, Jessor R, Turbin MS (2007) College student involvement in cigarette smoking: The role of psychosocial and behavioral protection and risk. Nicotine Tob Res 9: 213–224.    
  • 54. Raynor DA, Levine H (2005) Associations between the five-factor model of personality and health behaviors among college students. J Am Coll Health 58: 73–82.
  • 55. Busch V, Van Stel HF, Schrijvers AJ, et al. (2013) Clustering of health-related behaviors, health outcomes and demographics in Dutch adolescents: A cross-sectional study. BMC Public Health 13: 1118.    
  • 56. Li Y, Feng X, Zhang M, et al. (2016) Clustering of cardiovascular behavioral risk factors and blood pressure among people diagnosed with hypertension: A nationally representative survey in China. Sci Rep 6: 27627.    
  • 57. Jawad M, Lee JT, Millett C (2015) Waterpipe tobacco smoking prevalence and correlates in 25 Eastern Mediterranean and Eastern European countries: Cross-sectional analysis of the Global Youth Tobacco Survey. Nicotine Tob Res 18: 395–402.

 

This article has been cited by

  • 1. Walid El Ansari, Abdul Salam, Sakari Suominen, Is Alcohol Consumption Associated with Poor Perceived Academic Performance? Survey of Undergraduates in Finland, International Journal of Environmental Research and Public Health, 2020, 17, 4, 1369, 10.3390/ijerph17041369
  • 2. Walid El Ansari, Abdul Salam, Is Achieving the Guidelines of Four Forms of Physical Activity Associated with Less Self-Reported Health Complaints? Cross-Sectional Study of Undergraduates at the University of Turku, Finland, International Journal of Environmental Research and Public Health, 2020, 17, 15, 5595, 10.3390/ijerph17155595

Reader Comments

your name: *   your email: *  

© 2018 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved