Combining nutritional value with environmental impact: a novel approach to nutritional life cycle assessment

Purpose: In nutritional life cycle assessment (nLCA), nutrient provision is the key function of foods. This warrants replacing the traditional mass-based functional unit (FU) in LCA by a nutrient-based FU. However, such replacement causes several methodological issues and there is at present no uniform approach for integrating nutritional value into the FU of LCA. We therefore propose a novel approach where the mass-based FU is adjusted for nutritional value using a dimensionless Qualifying Index (QI). Methods: To demonstrate our approach, we calculated the nLCA for 164 food items from the environmental impact database of foods made by The Dutch National Institute for Public Health and the Environment. We used global warming potential (GWP, in kg CO₂ eq/kg) as indicator of environmental impact. As a measure of nutritional value, we used the QI, a dimensionless, numerical value expressing the relation between nutrient density and energy density of a food. To calculate the QI, we selected 21 qualifying nutrients, based on their contribution to the overall Dutch dietary intake. All QIs were calculated with and without capping to assess the influence of (excessively) high nutrient levels, and weighting was applied to calculate food-group-specific QIs. Results and discussion: For the majority of the 164 food items considered, the calculated QI was above 1, with higher values of QI representing higher nutrient density. The highest QI values were observed for vegetables and fish, whereas the lowest QI values were observed for fats, oils, and grain products. GWP values were highest for protein foods and lowest for fruits, vegetables, and grain products. For most foods, GWP decreased after nutritional adjustment, as their QI values were > 1. Food-group-specific weighting led to more distinctive GWP values. Additional analysis showed that the QI-nLCA methodology can be applied not only to compare individual food items, but also meals and diets. Conclusions: This study introduces a novel approach to nLCA, in which the original mass-based FU is corrected for by the QI, a numerical value expressing the relation between nutrient density and energy density of a food. This QI-nLCA enables a more comprehensive evaluation of foods, meals, and diets. It can be applied to different environmental indicators and, as such, could add to evidence-based decision-making by policy makers in the field of healthy and sustainable nutrition.