title: Combating obesity through healthy eating behavior: a call for system dynamics optimization.
abstract: Poor eating behavior has been identified as one of the core contributory factors of the childhood obesity epidemic. The consequences of obesity on numerous aspects of life are thoroughly explored in the existing literature. For instance, evidence shows that obesity is linked to incidences of diseases such as heart disease, type-2 diabetes, and some cancers, as well as psychosocial problems. To respond to the increasing trends in the UK, in 2008 the government set a target to reverse the prevalence of obesity (POB) back to 2000 levels by 2020. This paper will outline the application of system dynamics (SD) optimization to simulate the effect of changes in the eating behavior of British children (aged 2 to 15 years) on weight and obesity. This study also will identify how long it will take to achieve the government's target. This paper proposed a simulation model called Intervention Childhood Obesity Dynamics (ICOD) by focusing the interrelations between various strands of knowledge in one complex human weight regulation system. The model offers distinct insights into the dynamics by capturing the complex interdependencies from the causal loop and feedback structure, with the intention to better understand how eating behaviors influence children's weight, body mass index (BMI), and POB measurement. This study proposed a set of equations that are revised from the original (baseline) equations. The new functions are constructed using a RAMP function of linear decrement in portion size and number of meal variables from 2013 until 2020 in order to achieve the 2020 desired target. Findings from the optimization analysis revealed that the 2020 target won't be achieved until 2026 at the earliest, six years late. Thus, the model suggested that a longer period may be needed to significantly reduce obesity in this population.
authors.affiliation: School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Sintok, Kedah, Malaysia.
authors.forename: Norhaslinda Zainal
authors.initials: NZ
authors.lastname: Abidin
authors.affiliation: Department of Mathematics, Faculty of Science and Technology, Universiti Malaysia Terengganu, Kuala Terengganu, Terengganu, Malaysia.
authors.forename: Mustafa
authors.initials: M
authors.lastname: Mamat
authors.affiliation: Department of Management, School of Economics, Finance and Management, University of Bristol, Bristol, United Kingdom.
authors.forename: Brian
authors.initials: B
authors.lastname: Dangerfield
authors.affiliation: School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Sintok, Kedah, Malaysia.
authors.forename: Jafri Haji
authors.initials: JH
authors.lastname: Zulkepli
authors.affiliation: School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Sintok, Kedah, Malaysia.
authors.forename: Md Azizul
authors.initials: MA
authors.lastname: Baten
authors.affiliation: School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, Sintok, Kedah, Malaysia.
authors.forename: Antoni
authors.initials: A
authors.lastname: Wibowo
mesh_terms: D000293:Adolescent; D015992:Body Mass Index; D001835:Body Weight; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D005247:Feeding Behavior; D006801:Humans; D008954:Models, Biological; D009765:Obesity / Q000453:epidemiology* / Q000473:pathology / Q000517:prevention & control*; D006113:United Kingdom / Q000453:epidemiology