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Complex Systems Approaches to Diet: A Systematic Review.

Brent A Langellier1, Usama Bilal2, Felipe Montes3

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Complex systems models offer insights into population diet patterns. This review examines agent-based and system dynamics models, highlighting opportunities for improved policy support and validation using real-world data.

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Area of Science:

  • Diet and nutrition modeling
  • Complex systems science
  • Public health interventions

Background:

  • Population-level diet patterns are shaped by intricate mechanisms.
  • Complex systems approaches provide a framework for understanding these dynamics.
  • Modeling diet is crucial for informing effective public health policies.

Purpose of the Study:

  • To conduct a structured review of complex systems models of diet.
  • To identify key design elements and methodologies in existing diet models.
  • To synthesize findings from agent-based and system dynamics models of diet.

Main Methods:

  • Systematic literature searches of PubMed, Web of Science, and LILACS databases.
  • Inclusion of peer-reviewed manuscripts utilizing agent-based or system dynamics models for diet exploration.
  • Data extraction on study outcomes, data usage for parameterization, calibration, validation, and generated insights, adhering to PRISMA guidelines.

Main Results:

  • Twenty-two agent-based and five system dynamics model studies met inclusion criteria.
  • Mechanistic studies investigated individual, interpersonal, and neighborhood-level influences on diet.
  • Policy-oriented studies examined interventions related to food pricing, environment, advertising, labels, and social norms.
  • Most models utilized empirical data for parameterization, with varied calibration and validation approaches.

Conclusions:

  • Opportunities exist to advance complex systems modeling in diet and nutrition science.
  • Enhanced model utilization for policy decision support is recommended.
  • Increased use of epidemiologic and policy evaluation data can improve model validation.