Modelling the drivers of a widespread shift to sustainable diets

Abstract

A reduction in global meat consumption can significantly reduce the adverse environmental effects of the food system, but it would require widespread dietary changes. Such shifts to sustainable diets depend on several behavioural factors that have not yet been addressed in relation to the food system. This study links a behavioural diet shift model to an integrated assessment model to identify the main drivers of global diet change and its implications for the food system. The results show that the social norm effect (for instance, the extent of vegetarianism in the population that accelerates a further switch to a vegetarian diet) and self-efficacy are the main drivers of widespread dietary changes. These findings stress the importance of value-driven actions motivated either by intrinsic identity or by group dynamics over health and climate risk perceptions in steering diet change dynamics.

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Fig. 1: Conceptual framework of the diet change model.
Fig. 2: Dynamic simulation results.
Fig. 3: Environmental impact of diet change scenarios in 2050.
Fig. 4: Sobol sensitivity indices for the percentage of vegetarians in 2050 and 2100 for the reference diet composition scenario.
Fig. 5: Scenario discovery results for percentage of vegetarians.

Data availability

The input data of the model presented in this study may be seen in Supplementary Table 3. The input data are obtained from calibration according to historical data of agro-economic variables as described in Methods. The historical data used in calibration are obtained from the statistics of the United Nations Food and Agriculture Organization, available at http://www.fao.org/faostat/en/#data. This study also made use of online Global Burden of Disease datasets (http://ghdx.healthdata.org) provided by the Institute for Health Metrics and Evaluation, University of Washington.

Code availability

The model used in this study (the FeliX) and its input data are available at https://github.com/iiasa/Felix-Model/tree/master/Current%20Version. The custom computer code written in Python (IPython Notebooks) and used to analyze simulation results may be accessed on https://github.com/sibeleker/FeliX_DietChange.

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Acknowledgements

This research was supported by the International Institute for Applied Systems Analysis (IIASA) and by the European Research Council Synergy grant ERC-2013-SyG. 610028-IMBALANCE-P. We thank Hugo Valin for his suggestion to use the Global Burden of Disease datasets for modelling the health risk of red meat consumption. We thank Ansa Heyl for a language check.

Author information

S.E. designed the research. S.E., G.R. and M.O. conceptualized the model. S.E. developed the model, conducted the analysis and wrote the manuscript with contributions from G.R. and M.O. All authors contributed to the discussion and interpretation of the results.

Correspondence to Sibel Eker.

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Supplementary Methods, Supplementary Figs. 1–18, Supplementary Tables 1–3, Supplementary References 1–11

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