Hanna Lee1, Eun Suk Park1, Jae Kook Yu2, Eun Kyoung Yun3. 1. College of Nursing Science, Kyung Hee University, Seoul, Korea. 2. National Assembly Research Service, Seoul, Korea. 3. College of Nursing Science · East-West Nursing Research Institute, Kyung Hee University, Seoul, Korea. ekyun@khu.ac.kr.
Abstract
PURPOSE: The purpose of this study was to develop a system dynamics model for adolescent obesity in Korea that could be used for obesity policy analysis. METHODS: On the basis of the casual loop diagram, a model was developed by converting to stock and flow diagram. The Vensim DSS 5.0 program was used in the model development. We simulated method of moments to the calibration of this model with data from The Korea Youth Risk Behavior Web-based Survey 2005 to 2013. We ran the scenario simulation. RESULTS: This model can be used to understand the current adolescent obesity rate, predict the future obesity rate, and be utilized as a tool for controlling the risk factors. The results of the model simulation match well with the data. It was identified that a proper model, able to predict obesity probability, was established. CONCLUSION: These results of stock and flow diagram modeling in adolescent obesity can be helpful in development of obesity by policy planners and other stakeholders to better anticipate the multiple effects of interventions in both the short and the long term. In the future we suggest the development of an expanded model based on this adolescent obesity model.
PURPOSE: The purpose of this study was to develop a system dynamics model for adolescent obesity in Korea that could be used for obesity policy analysis. METHODS: On the basis of the casual loop diagram, a model was developed by converting to stock and flow diagram. The Vensim DSS 5.0 program was used in the model development. We simulated method of moments to the calibration of this model with data from The Korea Youth Risk Behavior Web-based Survey 2005 to 2013. We ran the scenario simulation. RESULTS: This model can be used to understand the current adolescent obesity rate, predict the future obesity rate, and be utilized as a tool for controlling the risk factors. The results of the model simulation match well with the data. It was identified that a proper model, able to predict obesity probability, was established. CONCLUSION: These results of stock and flow diagram modeling in adolescent obesity can be helpful in development of obesity by policy planners and other stakeholders to better anticipate the multiple effects of interventions in both the short and the long term. In the future we suggest the development of an expanded model based on this adolescent obesity model.