Optimised diets for achieving One Health: A pilot study in the Rhine-Ruhr Metropolis in Germany

Minetto Gellert Paris, J., Escobar Lanzuela, N. ORCID: https://orcid.org/0000-0001-7644-8790, Falkenberg, T., Gupta, S., Heinzel, C., Verly Junior, E., Jolliet, O., Borgemeister, C., et al. (2024). Optimised diets for achieving One Health: A pilot study in the Rhine-Ruhr Metropolis in Germany. Environmental Impact Assessment Review 106 e107529. 10.1016/j.eiar.2024.107529.

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Abstract

Dietary changes are needed to align the global food systems with the planetary boundaries and contribute to Sustainable Development Goals. We employed a Life Cycle Assessment (LCA) framework, extended with indicators on human health and animal welfare, to assess 2020 food consumption data of a pilot sample collected through an online survey in the Rhine-Ruhr Metropolis (Germany). Feasible optimisation scenarios representing alternative sustainable choices towards overarching environmental, societal and policy goals were explored. Meat and meat products contributed most to overall environmental impacts (e.g., climate change, terrestrial acidification), and fish and seafood to animal welfare loss (e.g., animal lives lost, animal life years suffered). Sodium intake was the most contributing risk factor for life minutes lost. The combined optimisation scenario reduces 55% of greenhouse gas emissions, improves human health indicators by 25% and reduces animal welfare loss substantially (by 52-97%). This is possible with a shift towards flexitarian and vegetarian dietary scenarios. These optimisations deliver improvements across One Health dimensions with marginal changes in dietary scenarios and align with the sustainability goals of the EU Green Deal. Working with regional data can offer advantages in obtaining more realistic baseline dietary information to promote localised dietary shifts. While this research has limitations regarding sample representativeness, it can serve as a case study to encourage sustainable consumption in the Rhine-Ruhr region.

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