Modeling the diet dynamics of children

Muntaser Safan
Simon A. Levin Mathematical, Computational and Modeling Sciences Center, Arizona State University, Tempe, AZ, USA; Faculty of Science, Mathematics Department, Mansoura University, Mansoura, Egypt; Faculty of Applied Science, Department of Mathematical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia

Anarina L. Murillo
Simon A. Levin Mathematical, Computational and Modeling Sciences Center, Arizona State University, Tempe, AZ, USA; Conditioned Feeding Lab, Behavioral Neuroscience, Department of Psychology, Arizona State University, Tempe, AZ, USA; Department of Biostatistics, School of Public Health, University of Alabama, Birmingham, AL, USA

Devina Wadhera
Conditioned Feeding Lab, Behavioral Neuroscience, Department of Psychology, Arizona State University, Tempe, AZ, USA

Carlos Castillo-Chavez
Simon A. Levin Mathematical, Computational and Modeling Sciences Center, Arizona State University, Tempe, AZ, USA

Abstract

Childhood obesity is a health emergency in many parts of the world including the U.S. and, consequently, identifying local, regional or national intervention models capable, of altering the dynamics of obesity at scales that make a difference remains a challenge. The fact that consumption of healthful foods among most youth has yet to meet recommended nutritional standards highlights a lack of effective policies aimed at addressing the epidemic of obesity. Mathematical models are used to evaluate the roles of socialisation and school environment on the diet dynamics of children. Data suggest that standard nutrition education programmes may have, at best, minimal impact in altering diet dynamics at the population-level. Inclusion of peer influence (model as contagion) reinforced by the use of culturally-sensitive school menus (environmental disruption) may prove capable of modifying obesity enhancing diet dynamics; altering the diets of a significant (critical) proportion of youngsters. A framework is introduced to explore the value of behaviour-based interventions and policies that account for the sociocultural environments of at risk communities. These models capture carefully choreographed scenarios to account for the fact that when dealing with diet-dynamics systems, thinking additively is not enough as it cannot account for the power of nonlinear effects.

Keywords: Socioepidemiology ,nutrition ,Contagion ,Differential equations ,Ecological modelling ,Population dynamics

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