Nutrient-level analysis of the sustainability of food systems

Abstract

Healthy and sustainable dietary transformations offer significant potential to improve the health and sustainability of food systems. However, devising sustainable and healthy diets is challenging due to the lack of understanding of the relationship between nutrients and sustainability. The main aim of this thesis is to introduce a nutrient-level sustainability assessment approach to understand the win-win and trade-offs when developing healthy and sustainable diets. The novel approach for assessing sustainability in relation to macronutrients was introduced by integrating the input-output technique with nutritional geometry. Then, this approach was used to assess the sustainability of dietary patterns, macronutrient dietary recommendations, and ultra-processed food (UPF) consumption in Australia at the nutrient level. Next, global environmental and economic impacts of substituting nutrients lost from reduced consumption of livestock meat with soy-based meat substitutes were modeled to demonstrate the potential of plant-based foods to act as a nutrient replacement for livestock meat with added environmental benefits. The nutrient-level sustainability analysis showed that proteins play an important role in driving the adverse dietary environmental and economic impacts. Results also showed that to maximize the environmental benefits of reduced consumption of animal-based foods and avoid overconsumption, animal-based foods need to be replaced by plant-based foods rich in proteins, not by UPFs. Accordingly, the modeling study showed that soy-based meat substitutes, rich in plant proteins, can replace macronutrients lost from livestock meat with environmental benefits. The analysis concluded that for sustainability diets rich in plant proteins and low in ultra-processed foods are superior to diets rich in animal proteins and replacing animal-based foods with wholesome plant-based foods, not refined processed foods can improve both health and sustainability.