Navigating Food Fraud: A Survey of Nigerian Consumer Knowledge and Attitudes
Abstract
:1. Introduction
2. Methods
2.1. Survey Questionnaire and Pilot Testing
- i.
- Socio-demographic characteristics including age, gender, marital status, educational level, income, and geopolitical zone.
- ii.
- Food fraud awareness, including knowledge of high-profile international and domestic cases of food fraud and relevant sources of information about food fraud.
- iii.
- Food fraud attitudes aimed at sampling the opinion of the respondents on the effects of food fraud, preventive measures, and rationale for food adulteration.
2.2. Sampling and Distribution of the Questionnaire
3. Statistical Analysis
4. Results
4.1. Sociodemographic Characteristics of Respondents
4.2. Consumer Awareness of Food Fraud
4.3. Consumer Attitudes towards Food Fraud
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- European-Commision. Food Fraud [Online]. 2020. Available online: https://knowledge4policy.ec.europa.eu/food-fraud-quality/topic/food-fraud_en (accessed on 10 July 2023).
- Hellberg, R.S.; Everstine, K.; Sklare, S.A. Food Fraud: A Global Threat with Public Health and Economic Consequences; Academic Press: Cambridge, MA, USA, 2020. [Google Scholar]
- Spink, J.; Moyer, D.C. Defining the public health threat of food fraud. J. Food Sci. 2011, 76, R157–R163. [Google Scholar] [CrossRef] [PubMed]
- GFSI Global Food Safety Initiative. Tackling Food Fraud through Food Safety Management Systems [Online]. 2018. Available online: https://mygfsi.com/wp-content/uploads/2019/09/Food-Fraud-GFSI-Technical-Document.pdf (accessed on 11 September 2023).
- Brooks, C.; Parr, L.; Smith, J.M.; Buchanan, D.; Snioch, D.; Hebishy, E. A review of food fraud and food authenticity across the food supply chain, with an examination of the impact of the COVID-19 pandemic and Brexit on food industry. Food Control 2021, 130, 108171. [Google Scholar] [CrossRef]
- Trienekens, J.H.; Wognum, P.M.; Beulens, A.J.; Van Der Vorst, J.G. Transparency in complex dynamic food supply chains. Adv. Eng. Inform. 2012, 26, 55–65. [Google Scholar] [CrossRef]
- Brooks, S.; Elliott, C.T.; Spence, M.; Walsh, C.; Dean, M. Four years post-horsegate: An update of measures and actions put in place following the horsemeat incident of 2013. NPJ Sci. Food 2017, 1, 5. [Google Scholar] [CrossRef]
- Wei, Y.; Liu, D. Review of melamine scandal: Still a long way ahead. Toxicol. Ind. Health 2012, 28, 579–582. [Google Scholar] [CrossRef]
- Andoh, S.S.; Nyave, K.; Asamoah, B.; Kanyathare, B.; Nuutinen, T.; Mingle, C.; Peiponen, K.-E.; Roussey, M. Optical screening for presence of banned Sudan III and Sudan IV dyes in edible palm oils. Food Addit. Contam. Part A 2020, 37, 1049–1060. [Google Scholar] [CrossRef]
- Spink, J.; Hegarty, P.V.; Fortin, N.D.; Elliott, C.T.; Moyer, D.C. The application of public policy theory to the emerging food fraud risk: Next steps. Trends Food Sci. Technol. 2019, 85, 116–128. [Google Scholar] [CrossRef]
- Spink, J.W. The current state of food fraud prevention: Overview and requirements to address ‘How to Start?’and ‘How Much is Enough?’. Curr. Opin. Food Sci. 2019, 27, 130–138. [Google Scholar] [CrossRef]
- National Agency for Food and Drug Administration and Control (NAFDAC). Recall, Disposal and Handling of Unwholesome and Adulterated Food and Food Products Regulations, 2019; NAFDAC: Abuja, Nigeria, 2019. Available online: https://www.nafdac.gov.ng/wp-content/uploads/Files/Resources/Regulations/New_Draft_Regulations/Recall-Disposal-and-Handling-of-Unwholesome-and-Adulterated-Food-Products-2019.pdf (accessed on 6 July 2024).
- Ochulor, C.E.; Onyeaka, H.; Njoagwuani, E.I.; Mazi, I.M.; Oladunjoye, I.O.; Akegbe, H.; Omotosho, A.D.; Odeyemi, O.A.; Nwaiwu, O.; Tamasiga, P. Improper food labeling and unverified food claims: Food safety implications. Am. J. Food Sci. Nutr. 2022, 4, 9–23. [Google Scholar] [CrossRef]
- Opia, J.E. Food Fraud in Nigeria: Challenges, Risks and Solutions. Master’s Thesis, Technological University Dublin, Dublin, Ireland, 2020. [Google Scholar]
- BBC-NEWS. ‘Plastic Rice’ Seized in Nigeria [Online]. 2016. Available online: https://www.bbc.co.uk/news/world-africa-38391998 (accessed on 9 February 2023).
- SAHARA-REPORTERS. NAFDAC Discovers Food Fraud in Tomato Paste Imports from China [Online]. 2016. Available online: https://saharareporters.com/2016/05/23/nafdac-discovers-%E2%80%98food-fraud%E2%80%99-tomato-paste-imports-china (accessed on 11 September 2023).
- BUSINESSDAY. NAFDAC Alerts on Expired Energy Drinks, Nabs Distributors [Online]. 2023. Available online: https://businessday.ng/news/article/nafdac-alerts-on-expired-energy-drinks-nabs-distributors/ (accessed on 2 August 2023).
- Akinwande, K.L.; Oladapo, A.J. Aberrant in physicochemical properties, functional health and medicinal grades of honeys from different sales outlets in Southwest Nigeria. Bull. Natl. Res. Cent. 2022, 46, 1–12. [Google Scholar] [CrossRef]
- Eagle, J. Dangote Salt Highlights Food Fraud in Nigeria [Online]. 2017. Available online: https://www.foodnavigator.com/Article/2017/03/15/Dangote-Salt-highlights-food-fraud-in-Nigeria (accessed on 10 July 2023).
- Nwaiwu, O.; Aduba, C.C.; Igbokwe, V.C.; Sam, C.E.; Ukwuru, M.U. Traditional and artisanal beverages in Nigeria: Microbial diversity and safety issues. Beverages 2020, 6, 53. [Google Scholar] [CrossRef]
- Foodwatch. New Revelations in the Mineral Water Scandal: Nestlé Has Apparently Been Using Illegal Filtering Methods for Decades. [Online]. 2024. Available online: https://www.foodwatch.org/en/new-revelations-in-the-mineral-water-scandal-nestle-has-apparently-been-using-illegal-filtering-methods-for-decades (accessed on 7 October 2024).
- Manning, L.; Kowalska, A. Illicit alcohol: Public health risk of methanol poisoning and policy mitigation strategies. Foods 2021, 10, 1625. [Google Scholar] [CrossRef] [PubMed]
- Rostrup, M.; Edwards, J.K.; Abukalish, M.; Ezzabi, M.; Some, D.; Ritter, H.; Menge, T.; Abdelrahman, A.; Rootwelt, R.; Janssens, B.; et al. The methanol poisoning outbreaks in Libya 2013 and Kenya 2014. PLoS ONE 2016, 11, e0152676. [Google Scholar] [CrossRef]
- Zhang, L.; Xu, Y.; Oosterveer, P.; Mol, A.P. Consumer trust in different food provisioning schemes: Evidence from Beijing, China. J. Clean. Prod. 2016, 134, 269–279. [Google Scholar] [CrossRef]
- Agnoli, L.; Capitello, R.; De Salvo, M.; Longo, A.; Boeri, M. Food fraud and consumers’ choices in the wake of the horsemeat scandal. Br. Food J. 2016, 118, 1898–1913. [Google Scholar] [CrossRef]
- Van Ruth, S.M.; Huisman, W.; Luning, P.A. Food fraud vulnerability and its key factors. Trends Food Sci. Technol. 2017, 67, 70–75. [Google Scholar] [CrossRef]
- Manning, L.; Soon, J.M. Developing systems to control food adulteration. Food Policy 2014, 49, 23–32. [Google Scholar] [CrossRef]
- Moyer, D.C.; DeVries, J.W.; Spink, J. The economics of a food fraud incident–Case studies and examples including Melamine in Wheat Gluten. Food Control 2017, 71, 358–364. [Google Scholar] [CrossRef]
- Essuman, E.K.; Teye, E.; Dadzie, R.G.; Sam-Amoah, L.K. Consumers’ knowledge of food adulteration and commonly used methods of detection. J. Food Qual. 2022, 2022, 2421050. [Google Scholar] [CrossRef]
- Onyeaka, H.; Ukwuru, M.; Anumudu, C.; Anyogu, A. Food fraud in insecure times: Challenges and opportunities for reducing food fraud in Africa. Trends Food Sci. Technol. 2022, 125, 26–32. [Google Scholar] [CrossRef]
- Kendall, H.; Clark, B.; Rhymer, C.; Kuznesof, S.; Hajslova, J.; Tomaniova, M.; Brereton, P.; Frewer, L. A systematic review of consumer perceptions of food fraud and authenticity: A European perspective. Trends Food Sci. Technol. 2019, 94, 79–90. [Google Scholar] [CrossRef]
- Gwenzi, W.; Makuvara, Z.; Marumure, J.; Simbanegavi, T.T.; Mukonza, S.S.; Chaukura, N. Chicanery in the food supply chain! Food fraud, mitigation, and research needs in low-income countries. Trends Food Sci. Technol. 2023, 136, 194–223. [Google Scholar] [CrossRef]
- Stratev, D.; Odeyemi, O.A.; Pavlov, A.; Kyuchukova, R.; Fatehi, F.; Bamidele, F.A. Food safety knowledge and hygiene practices among veterinary medicine students at Trakia University, Bulgaria. J. Infect. Public Health 2017, 10, 778–782. [Google Scholar] [CrossRef]
- Moreira, M.J.; García-Díez, J.; de Almeida, J.M.; Saraiva, C. Consumer Knowledge about Food Labeling and Fraud. Foods 2021, 10, 1095. [Google Scholar] [CrossRef]
- Charlebois, S.; Schwab, A.; Henn, R.; Huck, C.W. Food fraud: An exploratory study for measuring consumer perception towards mislabeled food products and influence on self-authentication intentions. Trends Food Sci. Technol. 2016, 50, 211–218. [Google Scholar] [CrossRef]
- Levy, I.; Kerschke-Risch, P. Attitudes toward food fraud, food safety concerns, national culture, and self-labeling as a victim. Isr. Aff. 2022, 28, 501–522. [Google Scholar] [CrossRef]
- Worldometer. Nigeria Population. 2024. Available online: https://www.worldometers.info/world-population/nigeria-population/#:~:text=The%20current%20population%20of%20Nigeria,latest%20United%20Nations%20data%201 (accessed on 9 July 2024).
- Akinyemi, A.I.; Mobolaji, J.W. Nigeria’s Large, Youthful Population Could Be an Asset or a Burden. 2022. Available online: https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://theconversation.com/nigerias-large-youthful-population-could-be-an-asset-or-a-burden-186574&ved=2ahUKEwin7IurrIWJAxXjgK8BHZ-VMdwQFnoECBIQAw&usg=AOvVaw15lArl4oMPeh-zfSpPgZNP (accessed on 25 February 2024).
- Kelfve, S.; Kivi, M.; Johansson, B.; Lindwall, M. Going web or staying paper? The use of web-surveys among older people. BMC Med. Res. Methodol. 2020, 20, 252. [Google Scholar] [CrossRef]
- Soon-Sinclair, J.M.; Imathiu, S.; Obadina, A.O.; Dongho Dongmo, F.F.; Kamgain, A.D.T.; Moholisa, E.; Saba, C.K.S.; Walekhwa, A.W.; Hunga, H.; Kussaga, J. How Worried Are You about Food Fraud? A Preliminary Multi-Country Study among Consumers in Selected Sub-Saharan African Countries. Foods 2023, 12, 3627. [Google Scholar] [CrossRef]
- UNDP. Valuable Insights and Findings of the 2023/2024 Human Development Report and Its Correlation to Nigeria’s Human Development Index [Internet]. 2023. Available online: https://www.undp.org/nigeria/news/valuable-insights-and-findings-2023/2024-human-development-report-and-its-correlation-nigerias-human-development-index (accessed on 6 July 2024).
- World Bank. Education Statistics (EdStats). Country at a Glance—Nigeria. 2024. Available online: https://datatopics.worldbank.org/education/country/nigeria (accessed on 6 July 2024).
- Bärebring, L.; Palmqvist, M.; Winkvist, A.; Augustin, H. Gender differences in perceived food healthiness and food avoidance in a Swedish population-based survey: A cross sectional study. Nutr. J. 2020, 19, 140. [Google Scholar] [CrossRef]
- Grace, D. Food safety in low and middle income countries. Int. J. Environ. Res. Public Health 2015, 12, 10490–10507. [Google Scholar] [CrossRef]
- Udomkun, P.; Wiredu, A.N.; Nagle, M.; Müller, J.; Vanlauwe, B.; Bandyopadhyay, R. Innovative technologies to manage aflatoxins in foods and feeds and the profitability of application—A review. Food Control 2017, 76, 127–138. [Google Scholar] [CrossRef] [PubMed]
Question | % (n) | |
---|---|---|
Yes | No | |
Before reading the information provided about this study, were you aware of the term ‘food fraud’? | 64.1 (1384) | 35.9 (776) |
Are you aware of the milk adulteration with melamine scandal? | 33 (712) | 67 (1448) |
Are you aware of the sale of ‘plastic rice’? | 81.9 (1768) | 18.1 (392) |
Are you aware of the horsemeat scandal? | 44.4 (959) | 55.6 (1201) |
Which of the following practices are you aware of? | ||
a. Locally produced rice rebagged as imported rice brands. | 13.9 (301) | 77.5 (1674) |
b. Milk and yoghurt repackaged as popular brands. | 43.3 (936) | 50.5 (1090) |
c. Adulteration or counterfeiting of cooking oils, e.g., adding colour dye to palm oil. | 34.5 (746) | 59.3 (1280) |
d. Adulteration or counterfeiting of alcoholic drinks. | 25.2 (544) | 68.6 (1482) |
e. Adulteration of honey. | 15.5 (335) | 78.3 (1691) |
f. Addition of ground red kola nut or dyes to dry ground red pepper. | 21.1 (455) | 72.7 (1571) |
How likely are you to find out about a counterfeit or adulterated food product? Please select as many as apply. | ||
Through information from the place where the food was purchased. | 39.3 (848) | 54.5 (1178) |
Through information from the manufacturer (company or business) producing the food. | 19.1 (413) | 74.7 (1613) |
Through social media or news outlets. | 13.1 (283) | 80.6 (1741) |
Through communication from a regulatory agency, e.g., NAFDAC or Standards Organisation of Nigeria (SON) | 10.1 (218) | 83.7 (1807) |
Through your research or investigation. | 6.9 (149) | 86.9 (1876) |
Where do you think those food products are likely to be adulterated/counterfeited/mislabeled, etc.? Please select as many as apply | ||
Street vendors | 68.3 (1475) | 25.5 (551) |
Open market | 45.8 (990) | 48 (1036) |
Supermarket or store | 12.8 (277) | 81 (1749) |
Restaurant | 8 (172) | 85.8 (1854) |
Warehouse | 6.5 (140) | 87.3 (1886) |
Manufacturing facility | 5.4 (117) | 88.4 (1909) |
Are you aware of the recalls and safety alerts system from NAFDAC? | 50.8 (1098) | 49.2 (1062) |
(a). Awareness of food fraud and recall among respondents. | ||||||||||||
Variable | Statistic | Before Reading the Information Provided about this Study, Were You Aware of the Term ‘Food Fraud’ | Are You Aware of the Milk Adulteration with Melamine Scandal? | Are You Aware of the Sale of ‘Plastic Rice’? | Are You Aware of the Horsemeat Scandal? | Are You Aware of the Recalls & Safety Alerts System from NAFDAC? | ||||||
Age | ||||||||||||
Sum of Squares | 3.09 | 3.121 | 0.434 | 6.961 | 0.996 | |||||||
df | 5 | 5 | 5 | 5 | 5 | |||||||
Mean Square | 0.618 | 0.624 | 0.087 | 1.392 | 0.199 | |||||||
F | 2.694 | 2.836 | 0.584 | 5.698 | 0.797 | |||||||
Sig. | 0.02 * | 0.015 * | 0.713 | <0.001 * | 0.552 | |||||||
Gender | ||||||||||||
Sum of Squares | 0.098 | 0.133 | 2.405 | 1.87 | 1.385 | |||||||
df | 2 | 2 | 2 | 2 | 2 | |||||||
Mean Square | 0.049 | 0.066 | 1.203 | 0.935 | 0.693 | |||||||
F | 0.212 | 0.3 | 8.146 | 3.796 | 2.774 | |||||||
Sig. | 0.809 | 0.741 | <0.001 * | 0.023 * | 0.063 | |||||||
Education | ||||||||||||
Sum of Squares | 6.774 | 6.774 | 4.217 | 7.001 | 0.54 | |||||||
df | 4 | 4 | 4 | 4 | 4 | |||||||
Mean Square | 1.694 | 1.694 | 1.054 | 1.75 | 0.135 | |||||||
F | 7.441 | 7.757 | 7.174 | 7.168 | 0.54 | |||||||
Sig. | <0.001 * | <0.001 * | <0.001 * | <0.001 * | 0.707 | |||||||
Marital status | ||||||||||||
Sum of Squares | 0.231 | 0.786 | 1.03 | 7.354 | 0.876 | |||||||
df | 4 | 4 | 4 | 4 | 4 | |||||||
Mean Square | 0.058 | 0.197 | 0.258 | 1.839 | 0.219 | |||||||
F | 0.251 | 0.889 | 1.735 | 7.534 | 0.876 | |||||||
Sig. | 0.909 | 0.47 | 0.139 | <0.001 * | 0.477 | |||||||
Geo-political zone | ||||||||||||
Sum of Squares | 2.631 | 0.774 | 2.811 | 1.074 | 1.345 | |||||||
df | 5 | 5 | 5 | 5 | 5 | |||||||
Mean Square | 0.526 | 0.155 | 0.562 | 0.215 | 0.269 | |||||||
F | 2.292 | 0.699 | 3.808 | 0.87 | 1.076 | |||||||
Sig. | 0.043 * | 0.624 | 0.002 * | 0.501 | 0.372 | |||||||
Household income | ||||||||||||
Sum of Squares | 9.92 | 1.689 | 1.783 | 3.749 | 1.216 | |||||||
df | 4 | 4 | 4 | 4 | 4 | |||||||
Mean Square | 2.48 | 0.422 | 0.446 | 0.937 | 0.304 | |||||||
F | 10.967 | 1.913 | 3.011 | 3.815 | 1.216 | |||||||
Sig. | <0.001 * | 0.106 | 0.017 * | 0.004 * | 0.302 | |||||||
(b). Awareness of food fraud and recall among respondents. | ||||||||||||
Variables | ANOVA | Local Rice Rebagged as Imported Rice. | Milk and Yoghurt Repackaged as Popular Brands. | Adulteration or Counterfeiting of Cooking Oils, e.g., Adding Colour Dye to Palm Oil. | Adulteration or Counterfeiting of Alcoholic Drinks. | Adulteration of Honey. | Addition of Ground Red Kola Nut or Dyes to Dry Ground Red Pepper. | |||||
Age | ||||||||||||
Sum of Squares | 2.727 | 4.55 | 3.361 | 1.157 | 1.379 | 2.49 | ||||||
df | 3 | 1 | 1 | 1 | 1 | 1 | ||||||
Mean Square | 0.909 | 4.55 | 3.361 | 1.157 | 1.379 | 2.49 | ||||||
F | 0.846 | 4.242 | 3.131 | 1.077 | 1.284 | 2.319 | ||||||
Sig. | 0.469 | * 0.04 | 0.077 | 0.299 | 0.257 | 0.128 | ||||||
Gender | ||||||||||||
Sum of Squares | 1.066 | 0.001 | 0.038 | 0.002 | 0.151 | 0.103 | ||||||
df | 3 | 1 | 1 | 1 | 1 | 1 | ||||||
Mean Square | 0.355 | 0.001 | 0.038 | 0.002 | 0.151 | 0.103 | ||||||
F | 1.428 | 0.002 | 0.153 | 0.006 | 0.605 | 0.413 | ||||||
Sig. | 0.233 | 0.961 | 0.695 | 0.936 | 0.437 | 0.521 | ||||||
Education | ||||||||||||
Sum of Squares | 2.042 | 0.928 | 0.663 | 0.877 | 0.298 | 0.486 | ||||||
df | 3 | 1 | 1 | 1 | 1 | 1 | ||||||
Mean Square | 0.681 | 0.928 | 0.663 | 0.877 | 0.298 | 0.486 | ||||||
F | 1.189 | 1.621 | 1.158 | 1.532 | 0.519 | 0.848 | ||||||
Sig. | 0.313 | 0.203 | 0.282 | 0.216 | 0.471 | 0.357 | ||||||
Marital status | ||||||||||||
Sum of Squares | 0.723 | 1.817 | 3.39 | 2.032 | 1.691 | 3.624 | ||||||
df | 3 | 1 | 1 | 1 | 1 | 1 | ||||||
Mean Square | 0.241 | 1.817 | 3.39 | 2.032 | 1.691 | 3.624 | ||||||
F | 0.608 | 4.592 | 8.584 | 5.136 | 4.273 | 9.178 | ||||||
Sig. | 0.61 | * 0.032 | * 0.003 | * 0.024 | * 0.039 | * 0.002 | ||||||
Geopolitical zone | ||||||||||||
Sum of Squares | 9.83 | 2.366 | 2.656 | 0.182 | 0.031 | 0.438 | ||||||
df | 3 | 1 | 1 | 1 | 1 | 1 | ||||||
Mean Square | 3.277 | 2.366 | 2.656 | 0.182 | 0.031 | 0.438 | ||||||
F | 1.331 | 0.96 | 1.078 | 0.074 | 0.013 | 0.178 | ||||||
Sig. | 0.263 | 0.327 | 0.299 | 0.786 | 0.911 | 0.674 | ||||||
Household income | ||||||||||||
Sum of Squares | 6.722 | 2.487 | 1.542 | 1.504 | 2.11 | 4.532 | ||||||
df | 3 | 1 | 1 | 1 | 1 | 1 | ||||||
Mean Square | 2.241 | 2.487 | 1.542 | 1.504 | 2.11 | 4.532 | ||||||
F | 1.688 | 1.873 | 1.161 | 1.132 | 1.589 | 3.415 | ||||||
Sig. | 0.167 | 0.171 | 0.281 | 0.287 | 0.208 | 0.065 | ||||||
(c). Awareness of food fraud and recall among respondents. | ||||||||||||
Variables | ANOVA | Through Information from the Place Where the Food Was Purchased. | Through Information from the Manufacturer (Company or Business) Producing the Food. | Through Social Media or News Outlets. | Through Communication from a Regulatory Agency, e.g., NAFDAC or Standards Organisation of Nigeria (SON) | Through your Research or Investigation. | Street Vendors | Open Market | Supermarket or Store | Restaurant | Warehouse | Manufacturing Facility |
Age | ||||||||||||
Sum of Squares | 0.7 | 1.171 | 0.257 | 0.736 | 0.2 | 0 | 0.824 | 3.454 | 2.253 | 0.8 | 0.001 | |
df | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
Mean Square | 0.7 | 1.171 | 0.257 | 0.736 | 0.2 | 0 | 0.824 | 3.454 | 2.253 | 0.8 | 0.001 | |
F | 0.651 | 1.09 | 0.239 | 0.684 | 0.186 | 0 | 0.767 | 3.219 | 2.099 | 0.745 | 0.001 | |
Sig. | 0.42 | 0.297 | 0.625 | 0.408 | 0.666 | 0.992 | 0.381 | 0.073 | 0.148 | 0.388 | 0.974 | |
Gender | ||||||||||||
Sum of Squares | 0.133 | 1.014 | 0.331 | 0.073 | 0.078 | 0.474 | 0.079 | 0.238 | 0.367 | 0.268 | 0.233 | |
df | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
Mean Square | 0.133 | 1.014 | 0.331 | 0.073 | 0.078 | 0.474 | 0.079 | 0.238 | 0.367 | 0.268 | 0.233 | |
F | 0.536 | 4.082 | 1.33 | 0.294 | 0.313 | 1.906 | 0.319 | 0.955 | 1.477 | 1.077 | 0.936 | |
Sig. | 0.464 | * 0.043 | 0.249 | 0.588 | 0.576 | 0.168 | 0.572 | 0.329 | 0.224 | 0.299 | 0.333 | |
Education | ||||||||||||
Sum of Squares | 0.531 | 0.883 | 1.243 | 0.085 | 0.162 | 0.469 | 1.912 | 1.3 | 0.655 | 0.142 | 0.002 | |
df | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
Mean Square | 0.531 | 0.883 | 1.243 | 0.085 | 0.162 | 0.469 | 1.912 | 1.3 | 0.655 | 0.142 | 0.002 | |
F | 0.928 | 1.542 | 2.171 | 0.149 | 0.283 | 0.819 | 3.342 | 2.271 | 1.143 | 0.249 | 0.003 | |
Sig. | 0.336 | 0.214 | 0.141 | 0.7 | 0.595 | 0.366 | 0.068 | 0.132 | 0.285 | 0.618 | 0.958 | |
Marital status | ||||||||||||
Sum of Squares | 0.153 | 0.686 | 0.207 | 0.06 | 0.04 | 0.225 | 0.002 | 0.131 | 0.135 | 0.014 | 0.098 | |
df | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
Mean Square | 0.153 | 0.686 | 0.207 | 0.06 | 0.04 | 0.225 | 0.002 | 0.131 | 0.135 | 0.014 | 0.098 | |
F | 0.385 | 1.731 | 0.522 | 0.15 | 0.1 | 0.567 | 0.006 | 0.33 | 0.341 | 0.036 | 0.246 | |
Sig. | 0.535 | 0.188 | 0.47 | 0.699 | 0.752 | 0.452 | 0.939 | 0.566 | 0.559 | 0.85 | 0.62 | |
Geopolical zone | ||||||||||||
Sum of Squares | 11.881 | 19.841 | 18.597 | 9.737 | 13.3 | 0.038 | 0.01 | 5.387 | 2.07 | 0.735 | 5.474 | |
df | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
Mean Square | 11.881 | 19.841 | 18.597 | 9.737 | 13.3 | 0.038 | 0.01 | 5.387 | 2.07 | 0.735 | 5.474 | |
F | 4.831 | 8.081 | 7.568 | 3.955 | 5.407 | 0.015 | 0.004 | 2.188 | 0.84 | 0.298 | 2.223 | |
Sig. | * 0.028 | * 0.005 | * 0.006 | * 0.047 | * 0.02 | 0.901 | 0.95 | 0.139 | 0.359 | 0.585 | 0.136 | |
Household income | ||||||||||||
Sum of Squares | 0.001 | 0.307 | 0.003 | 0.08 | 0.003 | 0.117 | 0.404 | 0.039 | 0.011 | 0.093 | 0.292 | |
Df | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | |
Mean Square | 0.001 | 0.307 | 0.003 | 0.08 | 0.003 | 0.117 | 0.404 | 0.039 | 0.011 | 0.093 | 0.292 | |
F | 0 | 0.231 | 0.002 | 0.06 | 0.002 | 0.088 | 0.304 | 0.03 | 0.008 | 0.07 | 0.22 | |
Sig. | 0.983 | 0.631 | 0.962 | 0.807 | 0.963 | 0.767 | 0.581 | 0.863 | 0.927 | 0.792 | 0.639 |
Statement | Responses % (n) | ||||
---|---|---|---|---|---|
Strongly Disagree | Disagree | Neither Agree Nor Disagree | Agree | Strongly Agree | |
I am generally concerned about counterfeit, adulterated, or mislabelled food items. | 5.9 (127) | 2.2 (48) | 6.3 (136) | 26.5 (572) | 59.1 (1277) |
I am generally concerned about counterfeit, adulterated, or mislabelled food items that are made in Nigeria. | 4.2 (90) | 3.5 (76) | 7.2 (155) | 27 (584) | 58.1 (1255) |
I am generally concerned about counterfeit, adulterated, or mislabelled food items that are imported. | 4.2 (91) | 4 (87) | 12.4 (268) | 26.9 (582) | 52.4 (1132) |
I believe that regulatory agencies, i.e., government agencies like NAFDAC and SON, are the most competent to protect Nigerians from counterfeit, adulterated or mislabelled foods. | 8.9 (192) | 8.8 (191) | 18.1 (392) | 28 (605) | 36.1 (780) |
I believe food producers, manufacturers, and sellers are the most competent to protect Nigerians from counterfeit, adulterated or mislabelled foods. | 10.6 (229) | 12.9 (279) | 20.9 (451) | 27.3 (589) | 28.3 (612) |
I believe it is up to consumers to protect themselves from counterfeit, adulterated, or mislabelled foods when shopping or eating at a restaurant. | 9.6 (208) | 9.4 (203) | 13.4 (289) | 18.7 (403) | 48.9 (1057) |
Food fraud can cause serious health challenges, including death. | 9.3 (201) | 8.4 (182) | 12.8 (277) | 20.3 (439) | 49.1 (1061) |
I believe the government is creating enough awareness about counterfeit, adulterated or mislabelled foods. | 24.4 (527) | 28.3 (612) | 21.3 (460) | 16.3 (353) | 9.6 (208) |
A food product with a NAFDAC number is not counterfeit, adulterated, or mislabeled | 21.5 (464) | 22.2 (479) | 27.5 (593) | 17.1 (370) | 11.8 (254) |
If I suspect a food product is counterfeit, mislabelled, or adulterated, it is easy to report this to regulatory agencies like NAFDAC or SON. | 17.6 (380) | 25.4 (548) | 23.4 (505) | 20 (432) | 13.7 (295) |
During challenging economic times, it is acceptable for food sellers to sell counterfeit or adulterated food items as long as these foods do not cause harm. | 52.3 (1129) | 16.9 (366) | 9.7 (210) | 9.8 (212) | 11.3 (243) |
Gender | Age | Education | Marital Status | Geo-Political Zone | Household Income | Awareness | Attitude | ||
---|---|---|---|---|---|---|---|---|---|
Gender | Pearson Correlation | 1 | 0.068 ** | 0.025 | −0.049 * | −0.161 ** | 0.062 ** | 0.027 | −0.001 |
Sig. (2-tailed) | 0.002 | 0.25 | 0.022 | <0.001 | 0.004 | 0.215 | 0.963 | ||
N | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | |
Age | Pearson Correlation | 0.068 ** | 1 | 0.557 ** | 0.585 ** | 0.042 | 0.445 ** | −0.023 | −0.026 |
Sig. (2-tailed) | 0.002 | <0.001 | <0.001 | 0.054 | <0.001 | 0.295 | 0.234 | ||
N | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | |
Education | Pearson Correlation | 0.025 | 0.557 ** | 1 | 0.334 ** | 0.036 | 0.382 ** | 0.011 | 0.037 |
Sig. (2-tailed) | 0.25 | <0.001 | <0.001 | 0.091 | <0.001 | 0.596 | 0.089 | ||
N | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | |
Marital status | Pearson Correlation | −0.049 * | 0.585 ** | 0.334 ** | 1 | 0.021 | 0.312 ** | −0.023 | −0.027 |
Sig. (2-tailed) | 0.022 | <0.001 | <0.001 | 0.324 | <0.001 | 0.276 | 0.214 | ||
N | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | |
Geo-political zone | Pearson Correlation | −0.161 ** | 0.042 | 0.036 | 0.021 | 1 | 0.029 | −0.037 | 0.03 |
Sig. (2-tailed) | <0.001 | 0.054 | 0.091 | 0.324 | 0.177 | 0.086 | 0.168 | ||
N | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | |
Household income | Pearson Correlation | 0.062 ** | 0.445 ** | 0.382 ** | 0.312 ** | 0.029 | 1 | 0.024 | −0.054 * |
Sig. (2-tailed) | 0.004 | <0.001 | <0.001 | <0.001 | 0.177 | 0.259 | 0.012 | ||
N | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | |
Awareness | Pearson Correlation | 0.027 | −0.023 | 0.011 | −0.023 | −0.037 | 0.024 | 1 | 0.024 |
Sig. (2-tailed) | 0.215 | 0.295 | 0.596 | 0.276 | 0.086 | 0.259 | 0.267 | ||
N | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | |
Attitude | Pearson Correlation | −0.001 | −0.026 | 0.037 | −0.027 | 0.03 | −0.054 * | 0.024 | 1 |
Sig. (2-tailed) | 0.963 | 0.234 | 0.089 | 0.214 | 0.168 | 0.012 | 0.267 | ||
N | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 | 2160 |
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Onyeaka, H.; Anyogu, A.; Odeyemi, O.A.; Ukwuru, M.U.; Eze, U.; Isaac-Bamgboye, F.J.; Anumudu, C.K.; Akinwunmi, O.O.; Sotayo, O.P.; Jeff-Agboola, Y.A. Navigating Food Fraud: A Survey of Nigerian Consumer Knowledge and Attitudes. Foods 2024, 13, 3270. https://doi.org/10.3390/foods13203270
Onyeaka H, Anyogu A, Odeyemi OA, Ukwuru MU, Eze U, Isaac-Bamgboye FJ, Anumudu CK, Akinwunmi OO, Sotayo OP, Jeff-Agboola YA. Navigating Food Fraud: A Survey of Nigerian Consumer Knowledge and Attitudes. Foods. 2024; 13(20):3270. https://doi.org/10.3390/foods13203270
Chicago/Turabian StyleOnyeaka, Helen, Amarachukwu Anyogu, Olumide A. Odeyemi, Michael Ukwuru Ukwuru, Ukpai Eze, Folayemi J. Isaac-Bamgboye, Christian K. Anumudu, Oluwabunmi O. Akinwunmi, Olufemi Peter Sotayo, and Yemisi A. Jeff-Agboola. 2024. "Navigating Food Fraud: A Survey of Nigerian Consumer Knowledge and Attitudes" Foods 13, no. 20: 3270. https://doi.org/10.3390/foods13203270
APA StyleOnyeaka, H., Anyogu, A., Odeyemi, O. A., Ukwuru, M. U., Eze, U., Isaac-Bamgboye, F. J., Anumudu, C. K., Akinwunmi, O. O., Sotayo, O. P., & Jeff-Agboola, Y. A. (2024). Navigating Food Fraud: A Survey of Nigerian Consumer Knowledge and Attitudes. Foods, 13(20), 3270. https://doi.org/10.3390/foods13203270