The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Can food be addictive? Public health and policy implications
Open accessAbstract
Aims Data suggest that hyperpalatable foods may be capable of triggering an addictive process. Although the addictive potential of foods continues to be debated, important lessons learned in reducing the health and economic consequences of drug addiction may be especially useful in combating food‐related problems. Methods In the current paper, we review the potential application of policy and public health approaches that have been effective in reducing the impact of addictive substances to food‐related problems. Results Corporate responsibility, public health approaches, environmental change and global efforts all warrant strong consideration in reducing obesity and diet‐related disease. Conclusions Although there exist important differences between foods and addictive drugs, ignoring analogous neural and behavioral effects of foods and drugs of abuse may result in increased food‐related disease and associated social and economic burdens. Public health interventions that have been effective in reducing the impact of addictive drugs may have a role in targeting obesity and related diseases.
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Cited by
Food cue reactivity and craving predict eating and weight gain: A meta-analytic review
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Self-citation
Metadata
- Authors
- Gearhardt, A. N., Grilo, C. M., DiLeone, R. J., Brownell, K. D., & Potenza, M. N.
- Venue
- Addiction
- Publisher
- Wiley
- Published
- 2011-02-14
- Volume
- 106
- Issue
- 7
- Pages
- 1208-1212
- ISSN
- 0965-2140 (ISSN-L)
- 1360-0443
- OpenAlex
- W2159166752
- Cited by
- 396
- References
- 69
- FWCI
- 60.57
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.