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Public awareness of seafood mislabeling

Ryburn, Savannah J., Ballantine, Wilker M., Loncan, Florencia M., Manning, Olivia G., Alston, Meggan A., Steinwand, Blaire, Bruno, John F.·2022·PeerJ
DOI 10.7717/peerj.13486PMC PMC9248779
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Abstract

A substantial portion of seafood is mislabeled, causing significant impacts to human health, the environment, the economy, and society. Despite the large scientific literature documenting seafood mislabeling the public’s awareness of seafood mislabeling is unknown. We conducted an online survey to assess the public’s awareness and perceptions of seafood mislabeling. Of the 1,216 respondents, 38% had never heard of seafood mislabeling and 49% were only ‘vaguely familiar’ with it. After being provided the definition of seafood mislabeling 95% had some degree of concern. Respondents were the most concerned about environmental impacts caused by seafood mislabeling and the least concerned about the social justice implications. Respondents who were also more concerned and familiar with seafood mislabeling stated that they would be more likely to purchase seafood from a vendor where the labeling was independently verified.

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Figures

Figure 1 How often respondents consume seafood. Figure includes all responses (n = 1,216).
Figure 1 How often respondents consume seafood. Figure includes all responses (n = 1,216).CC BY · PubMed Central
Figure 2 Where the respondents typically purchase seafood. Respondents were told to check all that apply. Figure includes all responses (n = 1,216).
Figure 2 Where the respondents typically purchase seafood. Respondents were told to check all that apply. Figure includes all responses (n = 1,216).CC BY · PubMed Central
Figure 3 The public’s response to the questions: “How concerned are you about seafood mislabeling?” (i.e., general concern) and “Which issues related to mislabeling concern you?”. The percentages on the left side of the figure include responses for both “Not at all concerned” and “Slightly concerned” while the percentages on the right include responses for “Very concerned” and “Extremely concerned”. The percentages in the middle include responses for “Moderately concerned”. Figure includes all responses (n = 1,216).
Figure 3 The public’s response to the questions: “How concerned are you about seafood mislabeling?” (i.e., general concern) and “Which issues related to mislabeling concern you?”. The percentages on the left side of the figure include responses for both “Not at all concerned” and “Slightly concerned” while the percentages on the right include responses for “Very concerned” and “Extremely concerned”. The percentages in the middle include responses for “Moderately concerned”. Figure includes all responses (n = 1,216).CC BY · PubMed Central
Figure 4 Distribution of survey respondents based on their familiarity with seafood mislabeling in relation to how concerned they were with seafood mislabeling. Numbers overlayed on the figure represent the number of respondents within each category. Figure includes all responses (n = 1,216).
Figure 4 Distribution of survey respondents based on their familiarity with seafood mislabeling in relation to how concerned they were with seafood mislabeling. Numbers overlayed on the figure represent the number of respondents within each category. Figure includes all responses (n = 1,216).CC BY · PubMed Central
Figure 5 Distribution of survey respondents based on their likelihood of preferentially purchasing seafood from a restaurant or retailer where the labeling is independently verified in relation to (A) how concerned they were with seafood mislabeling or (B) how familiar they were with seafood mislabeling. Numbers overlayed on the figures represent the number of respondents within each category. Each figure includes all responses (n = 1,216).
Figure 5 Distribution of survey respondents based on their likelihood of preferentially purchasing seafood from a restaurant or retailer where the labeling is independently verified in relation to (A) how concerned they were with seafood mislabeling or (B) how familiar they were with seafood mislabeling. Numbers overlayed on the figures represent the number of respondents within each category. Each figure includes all responses (n = 1,216).CC BY · PubMed Central

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Citations

Cites

Research works printed but not linked: 22

  1. Barendse, 2019, DNA barcoding validates species labelling of certified seafood, Current Biology, 29, R198, 10.1016/j.cub.2019.02.014 · DOI
  2. Béné, 2015, Feeding 9 billion by 2050–putting fish back on the menu, Food Security, 7, 261, 10.1007/s12571-015-0427-z · DOI
  3. Cline, 2012, Marketplace substitution of Atlantic salmon for Pacific salmon in Washington State detected by DNA barcoding, Food Research International, 45, 388, 10.1016/j.foodres.2011.10.043 · DOI
  4. FAO, 2016, Contributing to food security and nutrition for all, the state of world fisheries and aquaculture
  5. FAO, 2018, Meeting the sustainable development goals, the state of world fisheries and aquaculture
  6. Figgener, 2018, What I learnt pulling a straw out of a turtle’s nose, Nature, 563, 157, 10.1038/d41586-018-07287-z · DOI
  7. Golden, 2014, The global reach of seafood fraud: a current review of the literature 11
  8. Gutiérrez, 2012, Eco-label conveys reliable information on fish stock health to seafood consumers, PLOS ONE, 7, e43765, 10.1371/journal.pone.0043765 · DOI
  9. Jacquet, 2007, The rise of seafood awareness campaigns in an era of collapsing fisheries, Marine Policy, 31, 308, 10.1016/j.marpol.2006.09.003 · DOI
  10. Luque, 2019, The characterization of seafood mislabeling: a global meta-analysis, Biological Conservation, 236, 556, 10.1016/j.biocon.2019.04.006 · DOI
  11. Mariani, 2015, Low mislabeling rates indicate marked improvements in European seafood market operations, Frontiers in Ecology and the Environment, 13, 536, 10.1890/150119 · DOI
  12. Marko, 2014, Seafood substitutions obscure patterns of mercury contamination in patagonian toothfish (Dissostichus eleginoides) or chilean sea bass, PLOS ONE, 9, e104140, 10.1371/journal.pone.0104140 · DOI
  13. Matta, 1999, Heavy metals, lipid peroxidation, and ciguatera toxicity in the liver of the caribbean barracuda (Sphyraena barracuda), Biological Trace Element Research, 70, 69, 10.1007/BF02783850 · DOI
  14. Melo Palmeira, 2013, Commercialization of a critically endangered species (largetooth sawfish, Pristis perotteti) in fish markets of northern Brazil: authenticity by DNA analysis, Food Control, 34, 249, 10.1016/j.foodcont.2013.04.017 · DOI
  15. Naaum, 2016, Chapter 1 - seafood mislabeling incidence and impacts, 3, 10.1016/B978-0-12-801592-6.00001-2 · DOI
  16. Nakamura, 2018, Seeing slavery in seafood supply chains, Science Advances, 4, e1701833, 10.1126/sciadv.1701833 · DOI
  17. Sicherer, 2004, Prevalence of seafood allergy in the United States determined by a random telephone survey, Journal of Allergy and Clinical Immunology, 114, 159, 10.1016/j.jaci.2004.04.018 · DOI
  18. Spencer, 2019, Fishy business: red snapper mislabeling along the coastline of the Southeastern United States, Frontiers in Marine Science, 6, 97, 10.3389/fmars.2019.00513 · DOI
  19. Spencer, 2020, A high proportion of red snapper sold in North Carolina is mislabeled, PeerJ, 8, e9218, 10.7717/peerj.9218 · DOI
  20. Teh, 2013, Contribution of marine fisheries to worldwide employment: global marine fisheries employment, Fish and Fisheries, 14, 77, 10.1111/j.1467-2979.2011.00450.x · DOI
  21. Tveterås, 2012, Fish is food-the FAO’s fish price index, PLOS ONE, 7, e36731, 10.1371/journal.pone.0036731 · DOI
  22. Zabkar, 2013, Willingness to act and environmentally conscious consumer behaviour: can prosocial status perceptions help overcome the gap?, International Journal of Consumer Studies, 37, 257, 10.1111/j.1470-6431.2012.01134.x · DOI

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Metadata

Authors
Ryburn, S. J., Ballantine, W. M., Loncan, F. M., Manning, O. G., Alston, M. A., Steinwand, B., & Bruno, J. F.
Affiliations
  • Environment, Ecology and Energy Program, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
  • The Department of Biology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
ORCID
Alston, Meggan A.
Venue
PeerJ
Publisher
PeerJ
Published
2022-06-28
Volume
10
Pages
e13486
ISSN
2167-8359
DOI
10.7717/peerj.13486
PMC
PMC9248779
Cited by
24
References
1
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (unspecified)
Funders
  • Department of Biology at UNC-CH
  • QEP (Quality Enhancement Plan) CURE (Course-based Undergraduate Research Experience) initiative
  • National Science Foundation (OCE #1737071)

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