Food insecurity and healthy eating in Brazil: an agent-based model

• Grant number: 24/02600-0
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: September 02, 2024
• End date: March 01, 2025
• Field of knowledge: Health Sciences - Nutrition
• Principal Investigator: Dirce Maria Lobo Marchioni
• Grantee: Lucas de Almeida Moura
• Supervisor: Leandro Martin Totaro Garcia
• Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Institution abroad: Queen's University Belfast, Northern Ireland
• Associated to the scholarship: 22/13640-7 - Food insecurity and sustainable development in Brazil (2004-2023): spatial analysis, proposal of a multidimensional index and complex systems application, BP.DR

Abstract

The achievement of the Sustainable Development Goals of the 2030 Agenda aims primarily at eradicating poverty and the most severe form of food insecurity: hunger. For this to happen in a truly sustainable panorama, ensuring access to adequate and healthy nutrition is crucial. To this end, it's fundamental that public policies act to enhance food environments, integral parts of food systems. However, food insecurity is a complex, systemic, and multidimensional phenomenon, necessitating approaches that enable investigation of complex systems. This research aims to evaluate the influence of the food environment, price changes and sociodemographic factors on healthy food consumption behaviors and their impacts on groups at different levels of food insecurity. This is an agent-based model, implemented in NetLogo, which will be composed of two types of agents: individuals and food outlets, representing the food environment. Data on food consumption, food insecurity, and food sales locations will be used to inform the model. Four main steps will be carried out: elaboration and definition of the elements of a conceptual model; operationalization of the conceptual model in the computational model algorithm; parameterization and consistency and sensitivity analysis of the computational model; and execution and analysis of experiments. The model will be designed to represent a 4-year period, a period that represents the range from 2018 to 2022, years for which food insecurity and food consumption data are available, respectively.