• Talia Masino, Patricia Eustachio Colombo, Kia Reis, Inge Tetens, and Alexandr Parlesak.
• Global Nutrition and Health, University College Copenhagen, Copenhagen, Denmark; Department of Nutrition, Exercise and Sports, Copenhagen, Denmark.
• Nutrition. 2023 May 1; 109: 111977111977.

ObjectivesA frequently suggested approach to reduce greenhouse gas emissions (GHGEs) caused by food production is to reduce the intake of animal products, which can create nutritional deficiencies. This study aimed to identify culturally acceptable nutritional solutions for German adults that are both climate friendly and health promoting.MethodsLinear programming was applied to optimize the food supply for omnivores, pescatarians, vegetarians, and vegans considering nutritional adequacy, health promotion, GHGEs, affordability, and cultural acceptability by approaching German national food consumption.ResultsImplementing dietary reference values and omitting meat (products) reduced the GHGEs by ≤52%. The vegan diet was alone in staying below the Intergovernmental Panel on Climate Change (IPCC) threshold of 1.6 kg carbon dioxide equivalents per person per day. The optimized omnivorous diet constrained to meet this goal maintained ≥50% of each baseline food and, on average, deviated from baseline by 36% for women and 64% for men. Butter, milk, meat products, and cheese were reduced by half for both sexes, whereas bread, bakery goods, milk, and meat were reduced mainly for men. The intake of vegetables, cereals, pulses, mushrooms, and fish increased by between 63% and 260% for the omnivores, compared with baseline. Besides the vegan dietary pattern, all optimized diets cost less than the baseline diet.ConclusionsA linear programming approach for optimizing the German habitual diet to be healthy, affordable, and meet the IPCC GHGE threshold was possible for several dietary patterns and appears to be a feasible way forward toward including climate goals into food-based dietary guidelines.Copyright © 2023 Elsevier Inc. All rights reserved.

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