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A system dynamics model to simulate sustainable interventions on chronic disease outcomes in an urban community

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  • J Brittin
  • O M Araz
  • Y Nam
  • TT-K Huang

Abstract

Socio-demographics of urban US populations have been associated with poor health status and chronic disease. Patterns of rising chronic disease prevalence have persisted in populations with lower socio-economic status despite substantial and costly public health efforts to the contrary. In this paper, we used a system dynamics model to simulate chronic disease prevalence, along with potential interventions, for a low-income urban community in Chicago, Illinois. We hypothesized that the ‘triple bottom line’ of sustainability—addressing economic, social, and environmental issues—would be key to mitigation and reduction of chronic disease over time in such a community. The aim was to inform decision making about urban design and public health programme planning towards formulation of approaches—some beyond the traditional boundaries of health interventions—to improve community chronic disease outcomes over time. We found that single interventions on the constructs of Income and Employment, Neighbourhood Attractiveness, and Social Cohesion were most impactful in reducing or reversing the rise of chronic disease prevalence. Increasing Housing Capacity allowed the Neighbourhood Attractiveness intervention to have a greater impact. In addition, interventions in Neighbourhood Attractiveness and Chronic Disease Prevention produced a greater combined mitigating effect on chronic disease prevalence than the sum of the individual intervention effects. Findings suggest that socio-environmental conditions should be addressed, with consideration of population migration dynamics, in formulating viable and sustainable solutions to improve community-level health outcomes such as chronic disease prevalence.

Suggested Citation

  • J Brittin & O M Araz & Y Nam & TT-K Huang, 2015. "A system dynamics model to simulate sustainable interventions on chronic disease outcomes in an urban community," Journal of Simulation, Taylor & Francis Journals, vol. 9(2), pages 140-155, May.
  • Handle: RePEc:taf:tjsmxx:v:9:y:2015:i:2:p:140-155
    DOI: 10.1057/jos.2014.16
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    Cited by:

    1. Konrad, Renata A. & Saeed, Khalid & Kammer-Kerwick, Matt & Busaranuvong, Palawat & Khumwang, Wai, 2023. "“Fish-y” banks: Using system dynamics to evaluate policy interventions for reducing labor exploitation in the seafood industry," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    2. Li, Yina & Liang, Chenchen & Ye, Fei & Zhao, Xiande, 2023. "Designing government subsidy schemes to promote the electric vehicle industry: A system dynamics model perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).

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