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Modeling and Estimating Individual and Population Obesity Dynamics

  • Conference paper
Social Computing, Behavioral - Cultural Modeling and Prediction (SBP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7227))

Abstract

The obesity trend in the U.S. and many other countries has increased the need for models that can assess the potential impact of alternative interventions to reverse this trend. In this paper we report on building a generic dynamic model that can be used for obesity policy analysis at multiple levels. We build an individual level model for both childhood and adulthood to capture the energy balance and weight change throughout the life of individuals, and aggregate individual level models to create population level trends of obesity. Simulated method of moments is used to estimate uncertain parameters of this model from NHANES data. The resulting model enables community, state, or national policy analysis building on a calibrated model.

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Author information

Authors and Affiliations

  1. Grado Department of Industrial and Systems Engineering, Virginia Tech, Northern Virginia Center, Falls Church, VA, 22043, USA

    Hazhir Rahmandad & Nasim S. Sabounchi

Authors
  1. Hazhir Rahmandad
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  2. Nasim S. Sabounchi
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Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Rochester Institute of Technology, 14623, Rochester, New York, USA

    Shanchieh Jay Yang

  2. Applied Physics Laboratory, Research and Exploratory Development Department, Johns Hopkings University, 20723, Laurel, MD, USA

    Ariel M. Greenberg

  3. SA Technologies, 3750 Paladian Viillage Drive, Building 600, 30066, Marietta, GA, USA

    Mica Endsley

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© 2012 Springer-Verlag Berlin Heidelberg

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Rahmandad, H., Sabounchi, N.S. (2012). Modeling and Estimating Individual and Population Obesity Dynamics. In: Yang, S.J., Greenberg, A.M., Endsley, M. (eds) Social Computing, Behavioral - Cultural Modeling and Prediction. SBP 2012. Lecture Notes in Computer Science, vol 7227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29047-3_37

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  • DOI: https://doi.org/10.1007/978-3-642-29047-3_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29046-6

  • Online ISBN: 978-3-642-29047-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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