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Food Security and Sustainability: Discussing the Four Pillars to Encompass Other Dimensions.

Raquel de Pinho Ferreira GuinéMaria Lúcia de Jesus PatoCristina Amaro da CostaDaniela de Vasconcelos Teixeira Aguiar da CostaPaulo Barracosa Correia da SilvaVítor João Pereira Domingues Martinho
Published in: Foods (Basel, Switzerland) (2021)
The unadjusted intake of food constitutes a real challenge for the several sustainability dimensions. In this perspective, the main objectives of this research are to characterise the current contexts of food security, its relationship with sustainability, and identify proposals and actions that may support the design of more adjusted policies in the future. In addition, it is intended to assess if the food security pillars properly address the sustainability goals and if the evolution of undernutrition is accompanied by sustainable frameworks. In this way, statistical information from the FAOSTAT database was considered for the several dimensions of food security over the period 2000-2020. These data were analysed through factor-cluster approaches and panel data methodologies, namely those related to quantile regressions. As main insights, we may refer that undernutrition is more impacted by the availability of food and nutrients and political stability than by the level of GDP-Gross Domestic Product (except for the extreme cases). This means that the level of development is not the primary explanation for the problems of nutrition. The main focus of the national and international policies must be to improve the agrifood supply chains and to support political stability, in order to mitigate undernutrition worldwide and ensure a global access to sustainable and healthy diets. In addition, it is suggested to rethink the four pillars of food security (availability, access, utilisation and stability), in order to encompass other dimensions, such as climate change.
Keyphrases
  • climate change
  • human health
  • global health
  • public health
  • mental health
  • physical activity
  • machine learning
  • big data
  • heavy metals
  • quality improvement
  • current status
  • body mass index