Exploring tradeoffs among diet quality and environmental impacts in self-selected diets: a population-based study

Area of Science:

• Nutritional science
• Environmental science
• Data science

Background:

• Sustainable diets often require drastic dietary changes and focus narrowly on greenhouse gas emissions.
• Assessing environmental sustainability requires a multi-indicator approach beyond just carbon footprint.

Purpose of the Study:

• Identify existing, healthy diets with lower environmental impacts.
• Quantify potential reductions in multiple environmental impacts from dietary shifts.
• Explore trade-offs among various environmental indicators for diets.

Main Methods:

• Utilized energy-adjusted multiple factor analysis and hierarchical clustering on dietary data (National FinHealth 2017 Study).
• Integrated life cycle assessment data (Agribalyse 3.0, Agri-Footprint) for environmental impact assessment.
• Analyzed nutrient intake, global warming potential, land use, and eutrophication.

Main Results:

• Identified five diet clusters, with one 'best compromise' diet (20% of sample).
• This diet showed high quality and low environmental impacts (except freshwater eutrophication).
• It included more fruits, vegetables, and fish, and less of other animal products compared to the average diet.

Conclusions:

• Dietary shifts involve trade-offs among environmental impacts; multiple indicators are crucial.
• Cluster analysis aids in designing acceptable dietary transitions for improved health and sustainability.
• Tailored dietary paths can achieve high quality and reduced environmental footprint.