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REVIEW ARTICLE
Year : 2018  |  Volume : 3  |  Issue : 1  |  Page : 3-8

Noncommunicable disease modeling and simulation as means of understanding childhood obesity and intervention effectiveness


1 Program Evaluation and Research Unit (PERU), Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, USA
2 Department of Biostatistics, Public Health Dynamics Laboratory, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, USA; ICMR National Institute of Medical Statistics, New Delhi, India

Correspondence Address:
Prof. Saumyadipta Pyne
Department of Biostatistics, Public Health Dynamics Laboratory, Graduate School of Public Health, University of Pittsburgh, Pittsburgh

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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/bjhs.bjhs_8_18

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Lifestyle and dietary changes have led to rise in noncommunicable diseases such as diabetes, obesity, and cardiovascular disorders, accounting for increased mortality and morbidity in many parts of the world including developing countries. Obesity has doubled since 1980s and continues to be a growing problem of our times. Public health policies to address obesity are evolving in connection with dynamically changing human behaviors and complex interactions with the environment. However, designing and testing of new interventions are expensive and time-consuming. Computational simulations to model interventions offer useful tools to compare the effectiveness of potential interventions. In this article, we discuss a popular computational approach, agent-based modeling (ABM), to address the global challenge of childhood obesity through modeling of different interventions as described in the literature.


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