| Literature DB >> 35601745 |
Luiz Torres Neto1,2,3, Maria Lúcia Guerra Monteiro1,2,3,4, Fernanda Medeiros Viana2, Carlos Adam Conte-Junior1,2,3,4,5.
Abstract
This study aimed to investigate through free word association the perception of Brazilian consumers regarding the possibility of infection with the SARS-CoV-2 virus through food. One thousand individuals answered the questionnaire via an online platform. Most cited terms (hygiene-8%, fear-8%, caution-5%) and categories (negative attitudes and feeling-72% and sanitization-60%) were related to overall COVID-19 infection rather than their specific infection through the food. The perception of the possibility of risk of this type of cross-contamination was greater for male participants, within the food field, with high income (>10 minimum wages), and from the midwest region. Nonetheless, there are still doubts regarding this possibility, especially for participants with low income (≤10 minimum wages), females, higher education (≥secondary school), who exercise professional activity outside the food sector and from most regions of Brazil. Practical applications: Although the SARS-CoV-2 virus was discovered 2 years ago, the emergence of new variants such as Omicron has increased infection and mortality rates worldwide. A possible way of COVID-19 infection is cross-contamination through food handling and contact surfaces if preventive measures are not applied. In this context, understanding the consumer perception from a continental-size country such as Brazil, with a wide variety of socioeconomic profiles, is crucial to minimize the severe impacts of the pandemic. Our study demonstrates the need to disseminate scientific information in different media to reduce misinformation, especially social media because most Brazilian consumers had doubts and uncertainties about the possibility of COVID-19 infection from cross-contamination through food.Entities:
Year: 2022 PMID: 35601745 PMCID: PMC9115115 DOI: 10.1111/joss.12748
Source DB: PubMed Journal: J Sens Stud ISSN: 0887-8250 Impact factor: 2.831
Socioeconomic and demographic information of the consumers (n = 1,000)
| Consumers (%) | |
|---|---|
| Gender | |
| Female | 70.8 |
| Male | 29.2 |
| Age (years old) | |
| 18–25 | 22.9 |
| 26–35 | 31.8 |
| 36–45 | 21.6 |
| 46–55 | 10.9 |
| 56–65 | 8.2 |
| >65 | 4.6 |
| Living region | |
| South | 22.5 |
| Southeast | 54.1 |
| Midwest | 5.0 |
| Northeast | 13.0 |
| North | 5.4 |
| Income—Brazilian minimum wage (R$ 1,045.00) | |
| 1–5 | 41.0 |
| >5–10 | 31.7 |
| >10–20 | 18.5 |
| >20–30 | 6.3 |
| >30 | 2.5 |
| Education | |
| Primary school | 0.7 |
| Secondary school | 4.1 |
| University and/or postgraduate | 95.2 |
| Education field | |
| Food field | 35.7 |
| Other fields | 64.3 |
In Brazilian currency (real).
Veterinary medicine, nutrition, pharmacy, food engineering, or food science and technology.
FIGURE 1Frequency of mention of the most frequently mentioned individual words or terms when participants were asked to write down the first four words, terms, or phrases that came to their minds when thinking about COVID‐19 contamination through food
Frequency of the dimensions, categories, and examples of individual associations identified when consumers were asked to write down the first four words, terms, or phrases that came to their minds when thinking about COVID‐19 contamination through food (in decreasing order of frequency)
| Dimensions | Categories (examples of the most relevant individual words/terms) | Percentage of mention (%) |
|---|---|---|
| Attitudes and feelings | 72 | |
| Negative (fear, worry, insecurity, sadness, anxiety, anguish) | 72 | |
| Sanitization | 70 | |
| Sanitization (hygiene, cleanliness, alcohol) | 60 | |
| Poor hygiene (lack of hygiene, dirt) | 10 | |
| Aspects of COVID‐19 | 67 | |
| Prevention measures (care, prevention, precaution) | 38 | |
| Symptoms and implications (dying, hospital, sneezing, tiredness, intensive care unit) | 12 | |
| Modes of transmission (cross‐contamination, contact, hand, saliva agglomeration) | 10 | |
| General aspects (disease, virus, immunity, pandemic, bat) | 7 | |
| Risk perception | 38.5 | |
| Possibility of risk (likely, possibility) | 17 | |
| No risk (unlikely, fake, impossible) | 14 | |
| Low risk (difficult, rare) | 7.5 | |
| Productive chain | 37.5 | |
| Places of purchase and consumption (restaurants, supermarkets, fairs) | 17 | |
| Packing (packaging, contaminated packaging, plastic) | 8 | |
| Food handling (handling, improper handling) | 7 | |
| Food safety (security, quality) | 5.5 | |
| Other associations | 14 | |
| Others (family, transport, temperature, China, faith) | 9 | |
| Social and political matters (lack of information, information, research) | 5 | |
| Food | 12 | |
| Food type (fruits, raw foods, meat, vegetables) | 12 | |
| Unfamiliarity | 9 | |
| Doubt (doubt, uncertainty, “really?”) | 9 |
Frequency of mention of the categories identified in the free word association about COVID‐19 contamination through food by different participant groups considering their gender, age, living region, income, education, and education field
| Gender | Age (years old) | Living region | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dimensions | Categories | Female | Male | 18–25 | 26–35 | 36–45 | 46–55 | 56–65 | >65 | South | Southeast | Midwest | Northeast | North |
| Attitudes and feelings | ||||||||||||||
| Negative | 527 (+) | 186 (−) | 142 | 170 | 118 | 58 | 33 | 16 | 174 | 368 | 32 | 98 | 41 | |
| Sanitization | ||||||||||||||
| Sanitization | 444 | 168 | 48 | 67 | 48 | 17 | 16 | 12 | 137 | 357 (+) | 20 (−) | 73 | 25 | |
| Poor hygiene | 87 | 25 | 31 | 46 (+) | 21 | 9 | 5 | 0 (−) | 29 | 61 | 7 | 12 | 3 | |
| Aspects of COVID‐19 | ||||||||||||||
| Prevention measures | 267 | 112 | 24 | 33 | 22 | 11 | 7 | 6 | 84 | 191 | 23 | 60 | 21 | |
| Symptoms and implications | 82 | 37 | 136 (−) | 200 | 148 | 76 | 54 | 28 | 20 | 57 | 5 | 21 | 16 (+) | |
| Modes of transmission | 78 | 21 | 71 (+) | 64 | 40 | 19 | 21 | 9 | 30 | 46 | 4 | 14 | 5 | |
| General aspects | 48 | 22 | 20 (−) | 38 | 30 | 17 | 9 | 8 | 17 | 36 | 1 | 11 | 5 | |
| Risk perception | ||||||||||||||
| Possibility of risk | 124 | 42 | 31 | 34 | 27 | 15 | 5 | 4 | 51 (+) | 70 (−) | 17 (+) | 24 | 4 | |
| No risk | 93 | 44 | 31 | 32 | 19 | 11 | 11 | 6 | 22 (−) | 77 | 11 | 16 | 11 | |
| Low risk | 46 | 29 | 8 | 12 | 7 | 9 (+) | 4 | 0 | 19 | 43 | 2 | 8 | 3 | |
| Productive chain | ||||||||||||||
| Places of purchase and consumption | 107 (−) | 63 (+) | 27 | 44 | 28 | 14 | 6 | 6 | 42 | 92 | 2 (−) | 28 | 6 | |
| Packing | 42 (−) | 38 (+) | 13 (+) | 10 | 4 | 3 | 1 | 2 | 27 (+) | 41 | 3 | 8 | 1 | |
| Food handling | 51 | 19 | 7 | 12 | 10 | 2 | 1 | 3 | 13 | 41 | 7 (+) | 8 | 1 | |
| Food safety | 28 (−) | 27 (+) | 2 | 5 | 6 | 1 | 1 | 1 | 5 (−) | 33 | 4 | 10 | 3 | |
| Other associations | ||||||||||||||
| Others | 60 | 30 | 43 | 63 | 36 | 18 | 14 | 5 | 15 | 48 | 6 | 12 | 9 (+) | |
| Social and political matters | 32 | 18 | 22 | 39 | 25 | 10 | 9 | 5 | 11 | 23 | 4 | 8 | 4 | |
| Food | ||||||||||||||
| Food type | 84 | 34 | 19 | 33 | 14 | 13 | 8 | 2 | 26 | 79 (+) | 2 | 9 | 2 | |
| Unfamiliarity | ||||||||||||||
| Doubt | 26 | 10 | 5 | 6 | 5 | 3 | 4 | 1 | 10 | 20 | 0 | 3 | 3 | |
Note: (+) or (−) indicate that the observed value is higher or lower than the expected theoretical value.
University and postgraduate.
Veterinary medicine, nutrition, pharmacy, food engineering, or food science and technology.
p <.001.
p <.01.
p <.05, effect of the chi square per cell.
FIGURE 2Hierarchical cluster analysis (HCA) of the frequency of mention of the categories from free word association task about COVID‐19 contamination through food considering the different socioeconomic and demographic characteristics of the participants. BMW, Brazilian minimum wage
FIGURE 3Correspondence analysis (CA) of the participant characteristics (blue) and frequency of mention of the categories (red) from free word association task about COVID‐19 contamination through food. BMW, Brazilian minimum wage