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Systems Analysis of the Complex Obesity Etiology and Trends
Author(s) -
Wang Youfa,
Xue Hong,
Chen Hsinjen,
Igusa Tak
Publication year - 2011
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.25.1_supplement.212.8
Subject(s) - obesity , psychological intervention , computer science , population , process (computing) , maximization , risk analysis (engineering) , psychology , econometrics , environmental health , social psychology , medicine , economics , psychiatry , operating system
The complex processes underlying obesity etiology are difficult to study because of the limitations of available data and traditional statistical methods. We applied innovative systems analysis approaches to study the dynamic process of the US obesity epidemic using agent‐based models and empirical data. Based on utility maximization assumption, heterogeneous individual food behaviors defined by distinct food environment and social networks are computationally simulated and quantitatively assessed. Our simulations show significant differences in eating behavior when the utility functions of the individuals are formulated with and without these network effects. While a propensity to conform to the social norm provides restraints to wide variations in food consumption, it does not provide restraints on a gradual progression towards obesity. Certain environmental factors, such as the availability of unhealthy food choices, will couple with the social norm effect, resulting in an increase in the population average body mass index. Our results provide insight into the interactive influences and relations of economic, social norm, and environmental factors on weight gain; also indicate how agent‐based simulation can serve as a valuable tool in identifying key factors that determine individual food behavior and guiding future interventions.