Journal of Education and Health Promotion

Estimating the prevalence of high‑risk behaviors using network scale‑up method in medical university students

Document Type : Original Article

Authors

. Fatemeh Moghaddam Tabrizi 1
. Rahim Sharafkhani 2
. Zeynab Heydari 3
. Abdolah Khorami Markani 4
. Najaf Ahmadi Aghziyarat 5
. Hamid Reza Khalkhali 6

1 Reproductive Health Research Center, Urmia University of Medical Sciences, Urmia, Iran

2 Department of Public Health Khoy University of Medical Sciences, Khoy, Iran

3 Department of Noncommunicable Diseases, Fasa University of Medical Sciences, Fasa, Iran

4 Department of Nursing, Khoy University of Medical Sciences, Khoy, Iran

5 Department of Biostatistics and Epidemiology, Kerman University of Medical Sciences, Kerman, Iran

6 Department of Biostatistics and Epidemiology, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran

Abstract
BACKGROUND: There is not much information about high‑risk behaviors in young groups, especially
students. This study was conducted to estimate the prevalence of high‑risk behaviors in students of
universities of medical sciences in West Azerbaijan Province, Iran, by network scale‑up (NSU) method.
MATERIALS AND METHODS: This cross‑sectional study was performed on 450 students from the
universities of medical sciences. A researcher‑developed checklist was used to collect the data.
We considered number 16 for the social network size of students according to a previous study.
Based on the response of individuals to each of the high‑risk behaviors (including cigarette smoking,
hookah use, opium consumption, alcohol drinking, tramadol/ecstasy taking, and extramarital sex)
in their social network, the prevalence of these behaviors was estimated. The required calculations
were performed using the NSU method. Furthermore, 95% uncertainty interval (UI) was calculated
using the bootstrap method.
RESULTS: Totally, 196 (44%) participants were male. The mean age (standard deviation) of the
participants was 22 ± 2 years. Results showed that hookah use (20% 95% UI [18.9–21.1]) and
opium consumption (0.4% 95% UI [0.24–0.6]) had the highest and lowest frequencies, respectively.
Cigarette smoking (17% 95% UI [15.8–18]), alcohol use (8.3% 95% UI [7.5–9.1]), extramarital
sex (8.2% 95% UI [7.4–9]), and tramadol/ecstasy taking (4% 95% UI [6.4–4.6]) were the next most
common high‑risk behaviors, respectively.
CONCLUSIONS: Given that hookah use and cigarette smoking are the most common high‑risk
behaviors in students, especially males, appropriate cultural activities and educational programs
should be employed by relevant authorities to reduce these behaviors.

Keywords

Dangerous behavior
health occupation students
prevalence
  1. Ziaii S. Assessment Risky Behaviors among Students in Islamic
    Azad University. Tehran: Iran University of Medical Sciences;
    2010.
    2. Hamdye M, Matlabi N, Hasheri H, Berojerdi A. Prevalence of
    stimulant drugs, alcohol and psychoactive drugs Youth and
    adolescents 15‑35 years in Tehran. Med J 2008;32:315‑9.
    3. Jalilian F, Ataee M, Matin BK, Ahmadpanah M, Jouybari TA,
    Eslami AA, et al. Cognitive factors related to drug abuse among
    a sample of Iranian male medical college students. Glob J Health
    Sci 2015;7:143.
    4. Jackson CA, Henderson M, Frank JW, Haw SJ. An overview of
    prevention of multiple risk behaviour in adolescence and young
    adulthood. J Public Health (Bangkok) 2012;34 Suppl 1:i31‑40.
    5. Visser RO, Rissel CE, Smith AMA, Richters J. Sociodemographic
    correlates of selected health risk behaviors in a representative
    sample of Australian young people. Int J Behav Med 2006;13:153‑62.
    6. Daina L, Chereji A, Cioara F. Role of health education in
    prevention of dental disorders in school age. Heal Tolooh
    2010;8:20‑5.
    7. Paper O. Frequency of risky behaviours among students in Babol
    Universities (2009). J Gorgan Univ Med Sci 2011;13:53‑60.
    8. Changing the Population Structure of Iran from Youth to
    Old Age. ISNA; 2020. Available from: https://www.isna.ir/
    news/99023021943/. [Last updated on 2022 Jan 25; Last cited on
    2020 May 20].
    9. Abbasi Ghahramanloo A, Fotouhi A, Zeraati H ,
    Rahimi Movaghar A. Prescription drugs, alcohol, and illicit
    substance use and their correlations among medical sciences
    students in Iran. Int J High Risk Behav Addict 2015;4:e21945.
    10. Heydari ST, Izedi S, Sarikhani Y, Kalani N, Akbary A, Miri A,
    et al. The prevalence of substance abuse and associated risk factors
    among university students in the city of Jahrom, Southern Iran.
    Int J High Risk Behav Addict 2015;4:e22381.
    11. Maghsoudi A, Jalali M, Neydavoodi M, Rastad H, Hatami I,
    Dehghan A. Estimating the prevalence of high‑risk behaviors
    using network scale‑up method in university students of Larestan
    in 2014. J Subst Use 2017;22:145‑8.
    12. Ahmadi J, Benrazavi L, Ghanizadeh A. Substance abuse among
    contemporary Iranian medical students and medical patients.
    J Nerv Ment Dis 2001;189:860‑1.
    13. ShojaKazemi M. Elation between of Aknowledge to stimulent
    substance and consumption in students. Psychol Stud 2011;7:33‑48.
    14. Najafi K, Zarrabi H, Shirazi M, Fekri F, Mohseni R. Prevalence of
    substance use among Iranian high school students in 2005‑2006.
    Kuwait Med J 2009;41:20‑5.
    15. CenterRB. Institute of HIV/AIDS Disease Prevention and Control,
    Annual Report on HIV Care and Treatment. Unpubl Rep; 2012.
    16. Zamanian M, Zolala F, Haghdoost AA, Baneshi MR. Estimating
    the annual abortion rate in Kerman, Iran: Comparison of direct,
    network scale‑up, and single sample count methods. Int J Fertil
    Steril 2019;13:209‑14.
    17. HeydariZ, BaneshiMR, SharifiH, ZamanianM, Haji‑Maghsoudi S,
    Zolala F. Evaluation of the treatment failure ratio in individuals
    receiving methadone maintenance therapy via the network scale
    up method. Int J Drug Policy 2019;73:36‑41.
    18. Zamanian M, Zolala F, Haghdoost AA, Baneshi MR. Effect of
    estimation method, definition of ratio, and the plausible range
    in estimating social network size. Soc Netw Anal Min 2018;8:35.
    19. Zamanian M, Zolala F, Haghdoost AA, Haji‑Maghsoudi S,
    Heydari Z, Baneshi MR. Methodological considerations in using
    the Network Scale Up (NSU) for the estimation of risky behaviors
    of particular age‑gender groups: An example in the case of
    intentional abortion. PLoS One 2019;14:e0217481.
    20. Phosri A, Sihabut T, Jaikanlaya C. Short‑term effects of diurnal
    temperature range on hospital admission in Bangkok, Thailand.
    Sci Total Environ 2020;717:137202.
    21. Zahedi R, Noroozi A, Hajebi A, Haghdoost AA, Baneshi MR,
    Sharifi H, et al. Self‑reported and network scale‑up estimates of
    substance use prevalence among university students in Kerman,
    Iran. J Res Health Sci 2018;18:e00413.
    22. Sheikhzadeh K, Baneshi MR, Afshari M, Haghdoost AA.
    Comparing direct, network scale‑up, and proxy respondent
    methods in estimating risky behaviors among collegians. J Subst
    Use 2016;21:9‑13.
    23. Shekari F, HabibiP, Nadrian H, MohammadpooraslA. Health‑risk
    behaviors among Iranian university students, 2019: A web‑based
    survey. Arch Public Heal 2020;78:131.
    24. Kazemzadeh Y, Shokoohi M, Baneshi MR, Haghdoost AA. The
    frequency of high‑risk behaviors among Iranian college students
    using indirect methods: Network scale‑up and crosswise model.
    Int J High Risk Behav Addict 2016;5:e25130.
    25. Amare T, Yeneabat T, Amare Y. Systematic review and
    meta‑analysis of epidemiology of risky sexual behaviors in college
    and university students in Ethiopia, 2018. Environ Public Health
    2019;2019:1‑8.
    26. Evans‑Polce R, Lanza S, Maggs J. Heterogeneity of alcohol,
    tobacco, and other substance use behaviors in U.S. college
    students: A latent class analysis. Addict Behav 2016;53:80‑5.
    27. Kwan MY, Arbour‑Nicitopoulos KP, Duku E, Faulkner G. Patterns
    of multiple health risk‑behaviours in university students and
    their association with mental health: Application of latent class
    analysis. Heal Promot Chronic Dis Prev Canada Res Policy Pract
    2016;36:163‑70.
    28. Thomas D. Smoking and cardiovascular diseases. Rev Prat
    2012;62:339‑43.
    29. Deressa W, Azazh A. Substance use and its predictors among
    undergraduate medical students of Addis Ababa University in
    Ethiopia. BMC Public Health 2011;11:660.
    30. Velazquez EA. Generational status, sexual behavior, and alcohol
    use among college students. McNair Sch Res J 2012;8:13.
    31. Hedayati‑Moghaddam MR, Eftekharzadeh‑Mashhadi I,
    Fathimoghadam F, Pourafzali SJ. Sexual and reproductive
    behaviors among undergraduate university students in Mashhad,
    a city in northeast of Iran. Reprod Infertil 2015;16:43‑8.
    32. Primack BA, Sidani J, Agarwal AA, Shadel WG, Donny EC,
    Eissenberg TE. Prevalence of and associations with waterpipe
    tobacco smoking among U.S. university students. Ann Behav
    Med 2008;36:81‑6.
    33. Primack BA, Land SR, Fan J, Kim KH, Rosen D. Associations
    of mental health problems with waterpipe tobacco and
    cigarette smoking among college students. Subst Use Misuse
    2013;48:211‑9.
    34. Sajjadi H, Jorjoran Shushtari Z, Shati M, Salimi Y, Dejman M,
    Vameghi M, et al. An indirect estimation of the population
    size of students with high‑risk behaviors in select universities
    of medical sciences: A network scale‑up study. PLoS One
    2018;13:e0195364.
  2. 35. Ji Y, Xu H, Zhang Y, Liu Q. Heterogeneity of adolescent health
    risk behaviors in rural western China: A latent class analysis.
    PLoS One 2018;13:e0199286.
    36. Van Etten ML, Anthony JC. Male‑female differences in transitions
    from first drug opportunity to first use: Searching for subgroup
    variation by age, race, region, and Urban status. J Womens Health
    Gend Based Med 2001;10:797‑804.
    37. Roncero C, Egido A, Rodríguez‑Cintas L, Pérez‑Pazos J,
    Collazos F, Casas M. Substance use among medical students:
    A literature review 1988‑ 2013. Actas Esp Psiquiatr 2015;43:109‑21.
    38. Webb E, Ashton C, Kelly P, Kamali F. Alcohol and drug use in
    UK university students. Lancet 1996;348:922‑5.
Journal of Education and Health Promotion
Volume 12, Issue 10
November 2022
Pages 1-6

Home

Guide for Authors

Submit Manuscript

Reviewers

Contact Us