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Cited by 357

The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.

Meat Consumption and Sustainability

Open access
Parlasca, Martin C., Qaim, Matin·2022·Annual Review of Resource Economics

Abstract

Meat has become a controversial topic in public debates, as it involves multiple sustainability dimensions. Here, we review global meat consumption trends and the various sustainability dimensions involved, including economic, social, environmental, health, and animal welfare issues. Meat has much larger environmental and climate footprints than plant-based foods and can also be associated with negative health effects. Technological options can help to increase the sustainability of meat production, but changes in consumption are required as well. At least in high-income countries, where people consume a lot of meat on average, notable reductions will be important. However, vegetarian lifestyles for all would not necessarily be the best option. Especially in low-income countries, nutritious plant-based foods are not available or affordable year-round. Also, livestock production is an important source of income for many poor households. More research is needed on how to promote technological and behavioral changes while managing sustainability trade-offs.

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Crossref · 10.1146/annurev-resource-111820-032340

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Metadata

Authors
Parlasca, M. C., & Qaim, M.
Venue
Annual Review of Resource Economics
Published
2022-10-05
Volume
14
Issue
1
Pages
17-41
ISSN
  • 1941-1340 (ISSN-L)
  • 1941-1359
OpenAlex
W4226270155
Cited by
357
References
135
FWCI
6.58
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Meat Consumption and Sustainability. https://app.cochat.ai/papers/10.1146/annurev-resource-111820-032340
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Parlasca, M. C., & Qaim, M. (2022). Meat Consumption and Sustainability. Annual Review of Resource Economics. https://doi.org/10.1146/annurev-resource-111820-032340

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.