Within-food-group optimization improves nutritional adequacy, sustainability, and acceptability of modeled diets

Food production is a major contributor to global greenhouse gas emissions (GHGE). To mitigate this impact, researchers have developed methods for designing healthy and sustainable diets by modifying existing consumption patterns through dietary changes between food groups. However, the nutrient and emission profiles within these food groups can differ greatly. The aim of this study was to investigate the extent to which the nutritional adequacy, sustainability, and acceptability of diets can be improved through dietary changes within food groups.

To analyze the potential of within-food-group optimization, we investigated several diet modeling strategies and scenarios to optimize nutrient intake while minimizing GHGE and dietary change. The diets used as input for the diet model were derived from the U.S. National Health and Nutrition Examination Survey (NHANES) 2017-2018 consumption dataset.

By adjusting food quantities only within food groups, macro- and micronutrient recommendations could be met while achieving a 15 to 36% reduction in GHGE. When foods were optimized both within- and between food groups, only half the dietary change (23%) was required to achieve a 30% GHGE reduction, compared to optimizing between food groups alone (44%). This may improve consumer acceptance, assuming smaller dietary shifts are perceived as more acceptable.

Within-food-group optimization increases opportunities to improve the nutritional adequacy, sustainability, and acceptability of diets.