Complex Systems Approaches to Diet:A Systematic Review

Brent A Langellier, Usama Bilal, Felipe Montes, Jose D Meisel, Letícia de Oliveira Cardoso, Ross A Hammond

Resultado de la investigación: Contribución a una revistaArtículo de revisión

Resumen

CONTEXT: Complex systems approaches can help to elucidate mechanisms that shape population-level patterns in diet and inform policy approaches. This study reports results of a structured review of key design elements and methods used by existing complex systems models of diet.

EVIDENCE ACQUISITION: The authors conducted systematic searches of the PubMed, Web of Science, and LILACS databases between May and September 2018 to identify peer-reviewed manuscripts that used agent-based models or system dynamics models to explore diet. Searches occurred between November 2017 and May 2018. The authors extracted relevant data regarding each study's diet and nutrition outcomes; use of data for parameterization, calibration, and validation; results; and generated insights. The literature search adhered to PRISMA guidelines.

EVIDENCE SYNTHESIS: Twenty-two agent-based model studies and five system dynamics model studies met the inclusion criteria. Mechanistic studies explored neighborhood- (e.g., residential segregation), interpersonal- (e.g., social influence) and individual-level (e.g., heuristics that guide food purchasing decisions) mechanisms that influence diet. Policy-oriented studies examined policies related to food pricing, the food environment, advertising, nutrition labels, and social norms. Most studies used empirical data to inform values of key parameters; studies varied in their approaches to calibration and validation.

CONCLUSIONS: Opportunities remain to advance the state of the science of complex systems approaches to diet and nutrition. These include using models to better understand mechanisms driving population-level diet, increasing use of models for policy decision support, and leveraging the wide availability of epidemiologic and policy evaluation data to improve model validation.

Idioma originalInglés
Páginas (desde-hasta)273-281
Número de páginas9
PublicaciónAmerican Journal of Preventive Medicine
Volumen57
N.º2
DOI
EstadoPublicada - 1 ago 2019

Huella dactilar

Diet
Food
Calibration
Decision Support Techniques
Manuscripts
PubMed
Population
Databases
Guidelines
Costs and Cost Analysis

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Langellier, B. A., Bilal, U., Montes, F., Meisel, J. D., Cardoso, L. D. O., & Hammond, R. A. (2019). Complex Systems Approaches to Diet:A Systematic Review. American Journal of Preventive Medicine, 57(2), 273-281. https://doi.org/10.1016/j.amepre.2019.03.017
Langellier, Brent A ; Bilal, Usama ; Montes, Felipe ; Meisel, Jose D ; Cardoso, Letícia de Oliveira ; Hammond, Ross A. / Complex Systems Approaches to Diet:A Systematic Review. En: American Journal of Preventive Medicine. 2019 ; Vol. 57, N.º 2. pp. 273-281.
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Langellier, BA, Bilal, U, Montes, F, Meisel, JD, Cardoso, LDO & Hammond, RA 2019, 'Complex Systems Approaches to Diet:A Systematic Review', American Journal of Preventive Medicine, vol. 57, n.º 2, pp. 273-281. https://doi.org/10.1016/j.amepre.2019.03.017

Complex Systems Approaches to Diet:A Systematic Review. / Langellier, Brent A; Bilal, Usama; Montes, Felipe; Meisel, Jose D; Cardoso, Letícia de Oliveira; Hammond, Ross A.

En: American Journal of Preventive Medicine, Vol. 57, N.º 2, 01.08.2019, p. 273-281.

Resultado de la investigación: Contribución a una revistaArtículo de revisión

TY - JOUR

T1 - Complex Systems Approaches to Diet:A Systematic Review

AU - Langellier, Brent A

AU - Bilal, Usama

AU - Montes, Felipe

AU - Meisel, Jose D

AU - Cardoso, Letícia de Oliveira

AU - Hammond, Ross A

N1 - Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

PY - 2019/8/1

Y1 - 2019/8/1

N2 - CONTEXT: Complex systems approaches can help to elucidate mechanisms that shape population-level patterns in diet and inform policy approaches. This study reports results of a structured review of key design elements and methods used by existing complex systems models of diet.EVIDENCE ACQUISITION: The authors conducted systematic searches of the PubMed, Web of Science, and LILACS databases between May and September 2018 to identify peer-reviewed manuscripts that used agent-based models or system dynamics models to explore diet. Searches occurred between November 2017 and May 2018. The authors extracted relevant data regarding each study's diet and nutrition outcomes; use of data for parameterization, calibration, and validation; results; and generated insights. The literature search adhered to PRISMA guidelines.EVIDENCE SYNTHESIS: Twenty-two agent-based model studies and five system dynamics model studies met the inclusion criteria. Mechanistic studies explored neighborhood- (e.g., residential segregation), interpersonal- (e.g., social influence) and individual-level (e.g., heuristics that guide food purchasing decisions) mechanisms that influence diet. Policy-oriented studies examined policies related to food pricing, the food environment, advertising, nutrition labels, and social norms. Most studies used empirical data to inform values of key parameters; studies varied in their approaches to calibration and validation.CONCLUSIONS: Opportunities remain to advance the state of the science of complex systems approaches to diet and nutrition. These include using models to better understand mechanisms driving population-level diet, increasing use of models for policy decision support, and leveraging the wide availability of epidemiologic and policy evaluation data to improve model validation.

AB - CONTEXT: Complex systems approaches can help to elucidate mechanisms that shape population-level patterns in diet and inform policy approaches. This study reports results of a structured review of key design elements and methods used by existing complex systems models of diet.EVIDENCE ACQUISITION: The authors conducted systematic searches of the PubMed, Web of Science, and LILACS databases between May and September 2018 to identify peer-reviewed manuscripts that used agent-based models or system dynamics models to explore diet. Searches occurred between November 2017 and May 2018. The authors extracted relevant data regarding each study's diet and nutrition outcomes; use of data for parameterization, calibration, and validation; results; and generated insights. The literature search adhered to PRISMA guidelines.EVIDENCE SYNTHESIS: Twenty-two agent-based model studies and five system dynamics model studies met the inclusion criteria. Mechanistic studies explored neighborhood- (e.g., residential segregation), interpersonal- (e.g., social influence) and individual-level (e.g., heuristics that guide food purchasing decisions) mechanisms that influence diet. Policy-oriented studies examined policies related to food pricing, the food environment, advertising, nutrition labels, and social norms. Most studies used empirical data to inform values of key parameters; studies varied in their approaches to calibration and validation.CONCLUSIONS: Opportunities remain to advance the state of the science of complex systems approaches to diet and nutrition. These include using models to better understand mechanisms driving population-level diet, increasing use of models for policy decision support, and leveraging the wide availability of epidemiologic and policy evaluation data to improve model validation.

U2 - 10.1016/j.amepre.2019.03.017

DO - 10.1016/j.amepre.2019.03.017

M3 - Artículo de revisión

C2 - 31326011

VL - 57

SP - 273

EP - 281

JO - American Journal of Preventive Medicine

JF - American Journal of Preventive Medicine

SN - 0749-3797

IS - 2

ER -