• Kim, Sehjeong (Department of Mathematical Sciences, United Arab Emirates University) ;
  • Kim, So-Yeun (Department of Finance and Insurance, Hongik University)
  • Received : 2018.05.04
  • Accepted : 2018.05.16
  • Published : 2018.05.31


We develop a mathematical model for the obesity dynamics to investigate the long term obesity trend with the consideration of psychological and social factors due to the increasing prevalence of obesity around the world. Many mathematical models for obesity dynamics adopted the modeling idea of infectious disease and treated overweight and obese people infectious and spreading obesity to normal weight. However, this modeling idea is not proper in obesity modeling because obesity is not an infectious disease. In fact, weight gain and loss are related to social interactions among different weight groups not only in the direction from overweight/obese to normal weight but also the other way around. Thus, we consider these aspects in our model and implement personal weight gain feature, a psychological factor such as body image dissatisfaction, and social interactions such as positive support on weight loss and negative criticism on weight status from various weight groups. We show that the equilibrium point with no normal weight population will be unstable and that an equilibrium point with positive normal weight population should have all other components positive. We conduct computer simulations on Korean demography data with our model and demonstrate the long term obesity trend of Korean male as an example of the use of our model.


Supported by : National Research Foundation of Korea


  1. T. Kelly, W. Yang, CS. Chen, K. Reynolds and J. He, Global burden of obesity in 2005 and projections to 2030, International Journal of Obesity. (2008), 1431-1437.
  2. T.Y. Mousa, R.H. Mashal, H.A. Al-Domi and M.A. Jibril, Body image dissatisfaction among adolescent schoolgirls in Jordan, Body Image. (2010), 46-50.
  3. D.K. Voelker, J.J. Reel and C. Greenleaf, Weight status and body image perceptions in adolescents: Current perspectives, Adolescent Health, Medicine and Therapeutics. (2015), 6, 149158.
  4. D.M. Thomas, D.A. Schoeller, L.A. Redman, C.K. Martin, J.A. Levine and S.B. Heyms-field, Dynamic Model Predicting Overweight, Obesity, and Extreme Obesity Prevalence Trends, Am J Clin Nutr. (2010), 6, 1326-1331.
  5. F. Santonja, A. Morales, R. Villanueva and J. Cortes, Analyzing the effect of public health campaigns on reducing excess weight: A modeling approach for the Spanish autonomous regions of the community of Valencia, Evaluation and Program Pl anning. (2012), 35, 34-39.
  6. K. Ejima, K. Aihara and H. Nishiura, Modeling the obesity epidemic: Social contagion and its implications for control, Theoretical Biology and Medical Modeling. (2013), 10(17).
  7. L. Frerichs, O. Araz and T. Huang, Modeling social transmission dynamics of unhealthy behaviors for evaluating prevention and treatment interventions on childhood obesity, PLOS ONE. (2013), 8(12):e82887.
  8. A.O. Musaiger, A.A. bin Zaal and R. DSouza, Body weight perception among adolescents in Dubai, United Arab Emirate, Nutr Hosp. (2012), 6, 1966-1972.
  9. V. Eapen, A. Mabrouk and S. Bin-Othman, Disordered eating attitudes and symptomatology among adolescent girls in the United Arab Emirates, Eating Behaviors. (2006), 1(1), 53-60.
  10. WHO, World Health Organization body mass index (BMI) classification, 2018.
  11. R.A. Horn and C.R. Johnson, Matrix analysis, Cambridge University Press, 2012
  12. Statistics Korea, Obesity Rate, 2018.
  13. Statistics Korea, 2016 Korea Birth Statistics, 2018.
  14. OECD, Health at a Glance 2015: OECD Indicators, 2015.
  15. Y. Kim, S. Choi, C. Chun, S. Park, Y. Khang and K. Oh, Data resource profile: The Korea Youth Risk Behavior Web-based Survey (KYRBS), International Journal of Epidemiology. (2016), 45(4), 1076-1076.
  16. Korea Food and Drug Administration, 2011 KFDA Report, 2011