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INTERVENTION STRATEGY FOR REDUCING ADOLESCENT SMOKING

  • BYUL NIM KIM (FINANCE.FISHERY.MANUFACTURE INDUSTRIAL MATHEMATICS CENTER ON BIG DATA, PUSAN NATIONAL UNIVERSITY) ;
  • CHUNYOUNG OH (DEPARTMENT OF MATHEMATICS EDUCATION, CHONNAM NATIONAL UNIVERSITY)
  • Received : 2023.10.10
  • Accepted : 2023.12.24
  • Published : 2023.12.25

Abstract

This study aims to establish and analyze a mathematical model for the transmission dynamics of male adolescent smoking and to determine an optimal control strategy to reduce male adolescent smoking. We consider three groups in the population: smokers, non-smokers, and temporary nonsmokers. In our model to which optimal control theory was applied, the number of smokers decreased sharply and the number of non-smokers increased significantly. Our simulation results under various control scenarios reveal that integrated control measures(such as prevention, education, and treatment) may be necessary to reduce the growth rate of adolescent smoking. Moreover, we concluded that efforts to encourage current smokers and temporary quitters to quit should be sustained longer than efforts to reduce the rate at which nonsmokers become smokers through smoking prevention education.

Keywords

Acknowledgement

C. Oh was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (2020R1I1A306562712).

References

  1. L Zhang 1, W Wang, Q Zhao, E Vartiainen, Psychosocial predictors of smoking among secondary school students in Henan, China, Health Educ Res, 15 (2000), 415-422. https://doi.org/10.1093/her/15.4.415
  2. K M Conrad 1, B R Flay, D Hill, Why children start smoking cigarettes: predictors of onset, Br J Addict. 87 (1992), 1711-1724. https://doi.org/10.1111/j.1360-0443.1992.tb02684.x
  3. JH Park, MJ Kim, HJ Lee, A Study on the Factors Influencing Smoking in Multicultural Youths in Korea, Healthcare, MDPI, 11 (2023)
  4. Yun-Hee Kwak, Tae-Joon Kim, A Study on Factors of Family and Friends Influencing on the youth smoking, Journal of Transactional Analysis & Counseling, 1 (2011), 47-71.
  5. H. Harrington, Smoking, Drinking at School May be Contagious for Teens, Health Behavior News Service,(2003), https://www.newswise.com/articles/smoking-drinking-at-school-may-be-contagious-for-teens
  6. KOSIS, Youth Health Behavior Survey, (2023), https://kosis.kr/.
  7. O. Sharomi, A.B. Gumel, Curtailing smoking dynamics: a mathematical modeling approach, Applied Mathematics and Computation, 195 (2008), 475-499. https://doi.org/10.1016/j.amc.2007.05.012
  8. Emmanuel Addai a b, Lingling Zhang b, Joshua K.K. Asamoah c, John Fiifi Essel, A fractional order agespecific smoke epidemic model, Applied Mathematical Modelling, Applied Mathematical Modelling, 119 (2023), 99-118.
  9. Ullah, Roman and Khan, Mehroz and Zaman, Gul and Islam, Saeed and Khan, M Altaf and Jan, Sakhi and Gul, Taza, Dynamical features of a mathematical model on smoking, Journal of Applied Environmental and Biological Sciences, 6 (2016), 92-96.
  10. Khan, Sajjad Ali and Shah, Kamal and Zaman, Gul and Jarad, Fahd, Existence theory and numerical solutions to smoking model under Caputo-Fabrizio fractional derivative, Chaos: An Interdisciplinary Journal of Nonlinear Science, AIP Publishing LLC, 29 (2019), doi: 10.1063/1.5079644.
  11. Gul Zaman, Optimal campaign in the smoking dynamics, Computational and Mathematical Methods in Medicine, 2011 2011, doi: 10.1155/2011/163834.
  12. kdca,Youth Health Behavior Survey 2023, https://www.kdca.go.kr/yhs/
  13. mohw, medifonews, 2017, https://www.medifonews.com/news/article.html?no=138794.
  14. Driessche, P. & Watmough, J., Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Mathematical Biosciences, 180 (2002), 29-48. https://doi.org/10.1016/S0025-5564(02)00108-6
  15. Diekmann, O. & Heesterbeek, J., Mathematical epidemiology of infectious diseases: model building, analysis, and interpretation, John Wiley & Sons, 2000.
  16. Pontryagin, Lev Semenovich, Mathematical theory of optimal processes, CRC press,1987.
  17. Lenhart, S. & Workman, J., Optimal control applied to biological models, Chapman, 2007.
  18. kess, Educational statistics, 2023, https://kess.kedi.re.kr/eng/stats/school.
  19. Kristin V Carson al.et., Mass media interventions for preventing smoking in young people, Cochrane Database of Systematic Reviews, Issue 6, 2017.
  20. M Siegel and L Biener, The impact of an antismoking media campaign on progression to established smoking: Results of a longitudinal youth study, Am J Public Health, 90 (2000), 380-386. https://doi.org/10.2105/AJPH.90.3.380
  21. Hwikon Lee, Hwansik Hwang, Hoonki Park and Jung Kwon Lee, Association between Adolescent Smoking and Family Function, Journal of the Korean Academy of Family Medicine, 26 (2005), 138-144.