Research Article Consumer Knowledge and Attitudes Toward Nutritional Labels Komeela Cannoosamy, MSc1; Prity Pugo-Gunsam, PhD2; Rajesh Jeewon, PhD1 ABSTRACT Objective: To determine Mauritian consumers’ attitudes toward nutritional labels based on the Kano model and to identify determinants of the use and understanding of nutrition labels. Design: The researchers also used a Kano model questionnaire to determine consumers’ attitudes toward nutrition labeling. Setting: Four hundred consumers residing in Mauritius. Participants: Information was elicited via a questionnaire that assessed nutritional knowledge and information about the use and understanding of nutritional labels and demographic factors. Main Outcome Measures: Nutritional label use and understanding, nutrition knowledge, and association of demographic factors with label use. Analysis: Statistical tests performed included 1-way ANOVA and independent samples t tests. Results: Statistically significant relationships (P < .05) were found for nutritional knowledge and nutritional label usage with demographic factors. All demographic factors with the exception of gender were significantly associated (P < .05) with nutritional label understanding. Based on the outcome of the Kano survey, calorie content, trans fat content, protein content, and cholesterol content were found to be mustbe attributes: that is, attributes that, when not present, result in consumer dissatisfaction. Conclusions and Implications: Age, education, income, household size, and nutrition knowledge had an impact on nutritional label use. Health promoters should aim to increase the use of nutritional labels. Key Words: nutrition labels, nutrition knowledge, Kano survey, attitudes, socioeconomic status, education (J Nutr Educ Behav. 2014;-:1-7.) Accepted March 29, 2014.
INTRODUCTION A nutritional label is one of the most important instruments for promoting healthy eating habits. It aims to provide consumers with nutritional information about a food product at the moment of purchase.1 This information about the nutritional content may influence purchasing behavior by allowing consumers to judge the overall healthiness of the food and consequently enabling them to make informed food choices.2 Moreover, a nutritional label is an attractive tool because, while it supports the goal of healthy eating, consumers retain their freedom of choice.1
The success of a brand depends partly on its nutritional labeling. Nutritional labels are one of the main sources of information about the reliability of a food product. They attract consumers to the product. Nutritional and health claims have become a recognized way of communicating to the consumer the healthiness of foods that contain extra or reduced ingredients.3,4 The effectiveness of the nutritional labels remains to be discovered, because nutritional labeling cannot be fully successful until consumers are taught how to use them properly and regulations on nutritional claims are put into legislation.5,6
1
Department of Health Sciences, Faculty of Science, University of Mauritius, Reduit, Mauritius 2 Department of Biosciences, Faculty of Science, University of Mauritius, Reduit, Mauritius Address for correspondence: Rajesh Jeewon, PhD, Department of Health Sciences, Faculty of Science, University of Mauritius, Reduit, Mauritius; Phone: (þ230) 403 7498; Fax: (þ230) 465 6928; E-mail: [email protected] Ó2014 SOCIETY FOR NUTRITION EDUCATION AND BEHAVIOR http://dx.doi.org/10.1016/j.jneb.2014.03.010
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It is therefore crucial to establish a relationship between consumers' knowledge, attitudes, and use regarding nutritional labels to improve the type of information provided on labels and how consumers use them to make healthy dietary choices.7 A number of studies have targeted the determinants of nutritional label use and understanding. Among these, age, gender, level of education, health status, nutritional knowledge, household size, level of income, and occupation have a relationship with nutritional label usage and understanding.8-14 A lower frequency of nutritional label use has been determined among older people.15 Conversely, other studies9,10,16 reported that the use of nutritional labels is proportional to an increase in age. Gender is another factor determining nutritional label use and understanding. Women use labels more frequently than do men.9,11 However, Nayga17 reported no gender difference regarding the use of nutritional labeling. Similarly, a greater
1
2 Cannoosamy et al likelihood of nutritional label usage is associated with a higher level of education.5,6,18 Consumers with a low income usually give more importance to the price of products, but this is not always true, because irrespective of their household level of income, consumers concerned with proper dietary habits will use nutritional labels.19 A larger household size is also positively correlated with label usage, because the latter is perceived as more beneficial.20 It has also been shown that nutritional knowledge and its impact on label use is also well documented because it facilitates the understanding and consequently the use of nutritional labels.5,6,9 In Mauritius, according to Hawkes,21 nutritional labeling was introduced in the Food Regulations of 1999 (added to the Food Act of 1998). These regulations established the specific nutrients that must be labeled for a series of selected nutritional claims. The labeling of protein, fats, carbohydrates, vitamins, and mineral content on infant foods per 100 g of packaged food was also mandated. Assessing the relationship between product performance and consumer satisfaction has not always been easy and sometimes has been controversial. To overcome this, the Kano model was developed to enable the analysis of this nonlinear relationship.22 This model is an effective tool for categorizing product criteria and product requirements. The Kano model consists of 3 levels of consumer satisfaction: expected, desired, and excited qualities. In the same context, these quality attributes are classified into 5 categories; attractive, 1-dimensional, must-be, indifferent, and reverse.23 When fully achieved, the attractive quality provides satisfaction, but it does not cause dissatisfaction if not fulfilled. The 1-dimensional quality consists of articulated needs (ie, what customers express in terms of needs). The 1-dimensional quality results in satisfaction when fulfilled, but dissatisfaction when not fulfilled. When fulfilled, the must-be quality is taken for granted, but when it is not fulfilled, it results in dissatisfaction. The indifferent quality refers to aspects that are neither good nor bad, and consequently they result in neither
Journal of Nutrition Education and Behavior Volume -, Number -, 2014 customer satisfaction nor customer dissatisfaction. The reverse quality, when it is fulfilled, results in dissatisfaction, and vice versa.22 In 1 study, Chen and Chaang24 applied the Kano model to investigate consumer satisfaction; the authors demonstrated that the model was reliable because it presented advantages for better understanding consumer requirements. Likewise, Kim et al25 used Kano analysis to determine the role of nutritional labels and satisfaction or dissatisfaction with foods, in which 1 of the key findings was that sodium content was an indifferent attribute. However, research in the field of nutritional labeling with regard to the Kano model and the perception by consumers of nutritional labels has not been fully explored. In this context, this study was initiated with the following objectives: (1) to assess consumers' nutritional knowledge; (2) to determine the main factors associated with the use and understanding of nutritional labels; and (3) to assess consumers' attitudes toward nutritional labels, as well as the level of consumer satisfaction (using the Kano model).
METHODS Participants The study was based on a survey of 400 consumers. The researchers used stratified random sampling to obtain a sampling frame that reflected the Mauritian population. The sample consisted of males and females who were unemployed and employed (retired people, students, and housewives were classified as being unemployed). The University of Mauritius research ethics committee granted approval for the research and prior consent was obtained from all participants. The age group ranged from 19 to > 50 years and the household size ranged from 1 to 5. A larger number of female respondents were recruited, because often they were the main shopper in the household.26 Of the 400 respondents, 100 who had studied or were studying a nutrition-related subject were also included.
Questionnaire Design and Data Analysis The survey questionnaire consisted of different sections. The first section aimed to assess respondents' knowledge about nutrition. With reference to Grunert et al,11 respondents' nutritional knowledge was assessed with respect to their awareness of experts' dietary recommendations, knowledge of food sources of nutrients, and awareness of diet–disease associations. Questions developed by Parmenter and Wardle27 were used. The second section assessed respondents' use and understanding of nutritional labels and claims, and the type of information they look for in nutritional labels. The third section was composed of a demographic information assessment. The performancerating scale developed by Whati et al28 was used to interpret consumers' nutritional knowledge. Statistical tests included 1-way ANOVA and independent samples t tests with a 95% confidence level (SPSS version 16, Chicago, IL, 2007). A Kano questionnaire assessing consumer attribute classifications consisted of pairs of 1 functional and 1 dysfunctional question. Respondents were required to record their feelings and choose from 1 of the following responses: ‘‘like it,’’ ‘‘expect it,’’ ‘‘neutral,’’ ‘‘tolerate it,’’ and ‘‘dislike it.’’
RESULTS Nutritional Knowledge Most respondents correctly answered questions on expert recommendations about vegetables (97%), fruits (98.8%), and calcium (59.8%); 3% and 1.2% of the sample incorrectly answered questions about fruits and vegetables, respectively. Inversely, the majority of respondents incorrectly answered questions about expert dietary recommendations regarding sugary foods (65%) and calories from fats (78.8%). With the exception of packed soy products, respondents correctly classified other food items in the food groups. For the part on diet and disease awareness, 58.2% of the sample incorrectly answered the question about what reduces the risk of getting cancer.
Journal of Nutrition Education and Behavior Volume -, Number -, 2014 The total percentage score of each respondent was calculated and interpreted based on the performancerating scale developed by Whati et al.28 Nutritional knowledge of the sample population ranged from ‘‘very poor’’ to ‘‘excellent.’’ A total of 48% had ‘‘very good/above average’’ nutritional knowledge, whereas 23% obtained an ‘‘excellent’’ performance rating and 1% had a ‘‘very poor’’ rating. The researchers determined the correlation between nutritional knowledge and gender, age, and level of education. Table 1 shows that females had a higher nutrition knowledge score (72.2 16.2) compared with males (63.4 13.7). In addition, factors such as age (between 19 and 29 years of age), having a tertiary education, and studying a nutrition-related subject resulted in higher nutritional knowledge scores of 77.2 16.2, 77.1 13.4, and 80.6 14.1, respectively.
Use and Understanding of Nutritional Labels A total of 42.3% of consumers reported frequent use of nutritional labels when purchasing a product for the first time or when comparing 2 food products. However, only 22.2% claimed to always use nutritional labels, and 3.2% never used nutritional labels. The remaining 32% of the respondents reported occasional use. Of the respondents, 53.7% reported that it was ‘‘somewhat easy’’ to understand the nutritional information provided (Table 2). Similarly, when they were asked to what extent this information influenced their purchasing behavior, 30.5% reported a ‘‘fair’’ influence. Of the sample, 18.2% found that the content information was ‘‘very easy’’ to understand; a higher percentage of these respondents (11.5%) claimed that this information ‘‘greatly’’ affected their purchasing choices. However, some respondents (6.5%) claimed that the information was ‘‘very hard’’ to understand, and 4.2% reported ‘‘little’’ influence on their purchasing behavior. As Table 3 shows, statistical significance for gender, age group, education, occupation, household size and income, and nutritional knowledge was P < .05, which meant that younger females with a tertiary education and
Cannoosamy et al 3
Table 1. Relationship Between Demographic and Individual Factors and Nutritional Knowledge Score of Mauritian Consumers (n ¼ 400) Demographic and Individual Characteristics Gendera Male (n ¼ 184) Female (n ¼ 216)
Mean Nutritional Knowledge Score ± SD (%) 63.4 13.7 72.2 16.2
Age group, ya 19–29 (n ¼ 136) 30–39 (n ¼ 108) 40–49 (n ¼ 100) > 50 (n ¼ 56)
77.2 16.2 67.2 15.5 62.8 10.5 57.6 10.3
Level of educationa Primary (n ¼ 36) Secondary (n ¼ 215) Tertiary (n ¼ 149)
46 9.3 65.7 13.3 77.1 13.4
Studied nutrition-related subjectb Yes (n ¼100) No (n ¼300)
80.6 14.1 64.0 13.9
ANOVA test; bIndependent samples t test. Note: All comparisons were significant at P < .05. a
with a high income, household size, and nutritional knowledge were more likely to use nutritional labels. The understanding of a nutritional label was also investigated; Table 4 shows that the determinants of nutritional label understanding included age, education, occupation, household income and size, health status, and nutritional knowledge. The association between gender and label understanding was insignificant (P > .05).
did so for trans fat, 36% for cholesterol content, and 32% for protein content. The attractive attributes included serving size (35%), calcium content (36%), and iron content (35%). One-dimensional attributes included total fat content (48%) and sugar content (50%). Only sodium content was an indifferent attribute, categorized by 48% of respondents.
DISCUSSION
Analysis of Kano Model Consumer Survey Most attributes of the nutritional label were must-be attributes. A total of 47% respondents classified calorie content as a must-be attribute, 39%
The main findings of determinants of nutritional knowledge were gender, age, and education (especially prior nutritional knowledge). Nutritional label usage was associated with gender, age, education, occupation,
Table 2. How Mauritian Consumers Perceive Nutrition Information and Its Influence on Their Purchasing Behavior How Do You Find the Information Provided on the Nutritional Labels of Prepackaged Foods?
To What Degree Does the Content Information of the Prepackaged Food Product Affect Your Purchasing Behavior? Not at All Little Somewhat Fairly Greatly
Very hard to understand Somewhat hard to understand Somewhat easy to understand Very easy to understand
0.7 1 0.5 0
4.2 9.7 6.5 1
Note: Numbers represent percentage of consumers.
1.5 6.7 11.5 0.2
0 3 22 5.5
0 1 13.2 11.5
4 Cannoosamy et al
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Table 3. Relationship Between Use of Nutrition Labels and Demographic and Individual Factors of Mauritian Consumers (n ¼ 400) Demographic and Individual Characteristics Genderb Male (n ¼ 184) Female (n ¼ 216)
Mean Nutritional Label Use Score ± SD (%) 67.8 16.9 73.8 18.9
Age group, ya 19–29 (n ¼ 136) 30–39 (n ¼ 108) 40–49 (n ¼ 100) > 50 (n ¼ 56)
77.3 17.5 70.1 17.6 71.9 15.4 56 17.9
Level of educationa Primary (n ¼ 36) Secondary (n ¼ 215) Tertiary (n ¼ 149)
47.4 14.6 69.1 16.1 79.5 16.2
Occupationa Employed (n ¼ 177) Unemployed (n ¼ 90) Retired (n ¼ 36) Student (n ¼ 97)
73.0 17.2 68.9 17.3 53.8 18.6 75.7 17.2
Household income (Mauritian rupees)a < 10,000 (n ¼ 48) 10,000–20,000 (n ¼ 125) 20,000–30,000 (n ¼ 152) > 30,000 (n ¼ 75)
53.5 19.3 67.3 15.3 77.6 15.1 75.3 19.3
Household sizea 1 (n ¼ 12) 2 (n ¼ 43) 3 (n ¼ 101) 4 (n ¼ 174) > 5 (n ¼ 70)
62.2 25.3 59.0 18.4 70.1 15.2 74.3 18.6 73.0 16.9
Nutrition knowledgea Very poor (n ¼ 4) Fair/below average (n ¼ 59) Good/average (n ¼ 53) Very good/above average (n ¼ 191) Excellent (n ¼ 93)
30.8 0.0 57.5 13 59.5 18.4 74.7 15.8 80.5 15.9
ANOVA test; bIndependent samples t test. Note: All comparisons were significant at P < .05.
a
income, household size, and nutritional knowledge. However, an understanding of nutritional labels depended on the different demographic factors studied, with the exception of gender.
Consumers’ Nutritional Knowledge Based on the findings, Mauritians have a good knowledge of nutrition, because 48% had ‘‘very good/above average’’ nutritional knowledge and 23% had ‘‘excellent’’ nutritional knowledge. This high level of aware-
ness may be explained by the fact that the Ministry of Health and Quality of Life of Mauritius came up with a National Plan of Action for Nutrition in 2009 and 2010, whose aims were not only to emphasize public health promotional campaigns, but also to provide the population with nutritional information.29 The main determinants of nutritional knowledge, as obtained in this study, included gender (being female), knowledge about nutritional subjects, age (between 19 and 29 years), and having a tertiary education. Younger respondents had better nutritional knowl-
edge, because most aged between 19 and 29 years were university students; as such, they had a higher level of education and were more aware of nutritional issues, both of which justify their higher nutritional knowledge. A higher level of education has always been associated with higher nutritional knowledge30 and more highly educated individuals are more likely to be exposed to health or nutritionrelated news sources.20
Use and Understanding of Nutritional Labels Statistical evidence demonstrates a relationship between gender and nutritional label use. Women were more engaged in nutritional label use than were men. Females may use food labels more often than males simply because they are the primary food purchasers, and the greater social pressure that women experience to eat a healthy diet may further encourage them to take action toward achieving this objective.26 According to Nayga,31 men are less likely to accept that nutritional label information is useful; and contrary to women, men are generally less interested in nutrition and health. The current survey findings showed that younger respondents reported more frequent label use than older respondents, which is in accordance with the findings of Kim et al32,33 and Cole and Balasubramanian,34 who reported that as age increases, the probability of using nutritional labels also decreases. According to Ippolito and Mathios,35 individual characteristics affect the search for nutritional information, and age was one of the most common characteristics used in studies on nutritional labels.19 Burton and Andrews15 attributed this to the lower processing capacity of older people and the fact that older people tend to perceive labels as being difficult to understand. This lower use of labels may also be because, although older people have more interest in healthy eating, they have less nutritional knowledge, and higher nutritional knowledge leads to greater use and understanding of label information.11 However, studies by Coulson,10 Govindasamy and Italia,16 and Drichoutis et al19 found the
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Cannoosamy et al 5
Table 4. Effect of Demographic and Individual Factors on Mauritian Consumers’ Understanding of Nutrition Labels (n ¼ 400)
related news sources. Moreover, education may help them to interpret the information provided.37 The researchers investigated the link between occupational status and nutritional label use, and the outcome showed a positive association between them. Respondents who were working reported more frequent nutritional label use compared with those who were unemployed or retired. These results are in line with the findings of Drichoutis et al,9 who reported that working people were more likely to use nutritional labels. Furthermore, being employed is often associated with a higher household income, and the results of this study demonstrate that a higher income level is significantly associated with nutritional label use. This may be attributed to 2 main factors. First, a lower level of income limits the amount of choice consumers have regarding products; and second, consumers actively look for price information, which affects their use of nutritional information.19 The authors found a statistically significant association of nutritional label use with household size (nutritional label use was proportional to household size). A household size of more than 4 was associated with a higher mean nutritional label usage score. This result implies that the main meal planners of larger households were more likely to use information concerning the contents of food packages. A plausible explanation is that the use of nutritional information on food packages is viewed as beneficial by the main meal planners, especially where the eating habits of a larger number of persons are involved. Consequently, the relative value of time spent searching for information is higher for larger households than for smaller ones.20 The current study's findings demonstrated a statistically significant relationship between nutritional knowledge and nutritional label use. Respondents with ‘‘excellent’’ nutritional knowledge had a higher frequency of nutritional label usage compared with those with ’’fair’’ or ‘‘very poor’’ nutritional knowledge. According to Bender and Derby,18 nutritional knowledge may facilitate nutritional label use by increasing its perceived benefits and increasing the
Demographic and Individual Characteristics Gender*,b Male (n ¼ 184) Female (n ¼ 216) Age group, y**,a 19–29 (n ¼ 136) 30–39 (n ¼ 108) 40–49 (n ¼ 100) > 50 (n ¼ 56)
Mean Nutritional Label Understanding Score ± SD (%) 60.5 31.2 64.3 31.7 72.9 28.8 62 30.3 60.4 28.3 42.5 36
Level of education**,a Primary (n ¼ 36) Secondary (n ¼ 215) Tertiary (n ¼ 149) Occupation**,a
9.4 16.2 62.7 27.4 75.3 26.6
Employed (n ¼ 177) Unemployed (n ¼ 90) Retired (n ¼ 36) Student (n ¼ 97)
66.1 29.2 50 29.9 43.9 39.9 74.8 27
Household income (Mauritian rupees)**,a < 10,000 (n ¼ 48) 10,000–20,000 (n ¼ 125) 20,000–30,000 (n ¼ 152) > 30,000 (n ¼ 75) Household size**,a
31.6 38.2 62.6 31.9 68 23.8 71.5 28.9
1 (n ¼ 12) 2 (n ¼ 43) 3 (n ¼ 101) 4 (n ¼ 174) > 5 (n ¼ 70)
21.7 31.3 53.5 42.7 55.4 30.2 66.3 29.8 76.3 18.1
Have disease**,b No (n ¼ 276) Yes (n ¼ 124)
67.2 30.2 52.4 32.5
Nutrition knowledge**,a Very poor (n ¼ 4) Fair/below average (n ¼ 59) Good/average (n ¼ 53) Very good/above average (n ¼ 191) Excellent (n ¼ 93)
20 0.0 36.3 35.5 53.2 30.4 65.7 27.8 80 22.8
*P > .05; **P < .05; aANOVA test; bIndependent samples t test.
opposite, that nutritional label usage was proportional to an increase in age. The trend observed in these studies may be because older individuals might be more cautious about what they eat, for medical reasons (especially because the prevalence of noncommunicable diseases is high in Mauritius), contrary to their younger counterparts, which results in a higher likelihood of using nutritional labels. Many studies have demonstrated clear links between nutritional label
use and a high level of education level36 and occupation.9 Similarly, the results of this study showed that a higher mean score for nutritional label use was significantly associated with higher levels of education. A marked difference was observed in the mean score of respondents with a tertiary education and those with a primary education (Table 2). According to Nayga,20 more highly educated individuals were more likely to be exposed to health- or nutrition-
6 Cannoosamy et al efficiency of label use. Similarly, Moorman and Matulich38 showed that a higher level of health knowledge had a positive influence on receiving information from media sources, which include the use of nutritional labels. Drichoutis et al9 found that people with higher nutritional knowledge used nutritional labels more often, mainly because they were able to evaluate and understand the information on food labels; and furthermore, that consumers who were more able to derive information from nutritional labels were more likely to use them. The researchers also determined factors affecting the understanding of nutritional labels, and the main findings showed no significant association (P > .05) between gender and understanding labels. On the other hand, age had a significant association with nutritional label understanding. Similarly, the levels of household income and size, occupation, and nutritional knowledge were all significantly associated with better nutritional label understanding. Respondents with higher nutritional knowledge were more apt to further interpret and process the information on the label compared with those with lower nutritional knowledge. Grunert et al11 concluded that younger people had higher levels of understanding owing to their higher nutritional knowledge and intellectual ability. The influence of nutritional labels on purchasing behavior was greater when respondents could better understand the nutritional labels. This was attributed to the fact that as respondents were able to interpret the information provided, they could further process the information to decide which food products better suited their dietary needs. Fitzgerald et al39 reported that using food labels to choose high-fiber foods was associated with high consumption of fruits and vegetables, and using labels to choose foods low in sodium was associated with a lower intake of salty snacks. Furthermore, Ollberding et al40 observed a consistent relationship between the increased use of nutritional labels and improved nutrient intake. Although label use did not always lead to healthier consumption, it could change dietary patterns and contribute to better dietary intake or reduce the consumption of unhealthy foods.9
Journal of Nutrition Education and Behavior Volume -, Number -, 2014 The researchers investigated respondents' use of information on labels to perform certain tasks. Label information was nearly ‘‘always’’ used to compare food, check fat content, and get storage instructions. On the contrary, when deciding which brand to buy, this information was only ‘‘sometimes’’ used. This may be because consumers rely on nutritional information on food labels only when they have a specific reason to do so: for example, locating food products for specific dietary needs.41
Outcomes of Kano Study Based on the outcomes of the Kano survey, nutritional information on calories, trans fat, cholesterol, and protein was found to be a must-be attribute (an attribute that, when not present, results in consumer dissatisfaction). On the contrary, serving size, and calcium and iron content were attractive attributes, which means that these provide satisfaction when present and can be used to attract consumers to a product. Sugar and total fat content were 1-dimensional attributes, attributes that result in consumer satisfaction when present and dissatisfaction when absent. Sodium content was an indifferent attribute, which implies that whether sodium content is present or not, there is neither consumer satisfaction nor dissatisfaction. This agrees with the findings of Kim et al,25 in which the Kano analyses revealed that sodium content was an indifferent attribute. According to the prospect theory developed by Kahneman and Tversky (1979, cited by Hoefkens et al42), consumers tended to attach more importance to attributes (nutrients) that had potential losses rather than those having potential gains. The findings of the Kano survey support this theory, in which it was expected that more importance would be put on disqualifying nutrients (calories, trans fat, cholesterol, fat, and sugar content), that is, those that disqualify the food product when present. Furthermore, according to Russo et al,43 although consumers see both positive and negative nutrients as important, they emphasize the negative nutrients: those which they want to avoid or for which they want to
reduce their consumption. Negative nutrients include calories, cholesterol, sodium, and sugar. In fact, consumers used nutritional labels to avoid negative nutrients, and these effects might be even greater if labeling were combined with an information campaign to educate consumers.9
IMPLICATIONS FOR RESEARCH AND PRACTICE The results from this study may be used to shed light on current explanations regarding differences in the attributed importance of qualifying and disqualifying nutrients. The level of understanding nutritional labels among different population groups can be determined, thus providing a good starting point for addressing barriers to label usage. Moreover, these results can be used to design communication strategies and help health professionals to stress the importance of both qualifying and disqualifying nutrients. The Kano model can be used to classify information on nutritional panel labeling that may contribute to consumer satisfaction.
ACKNOWLEDGMENTS The authors appreciatively acknowledge the participants in the study.
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INTRODUCTION A nutritional label is one of the most important instruments for promoting healthy eating habits. It aims to provide consumers with nutritional information about a food product at the moment of purchase.1 This information about the nutritional content may influence purchasing behavior by allowing consumers to judge the overall healthiness of the food and consequently enabling them to make informed food choices.2 Moreover, a nutritional label is an attractive tool because, while it supports the goal of healthy eating, consumers retain their freedom of choice.1
The success of a brand depends partly on its nutritional labeling. Nutritional labels are one of the main sources of information about the reliability of a food product. They attract consumers to the product. Nutritional and health claims have become a recognized way of communicating to the consumer the healthiness of foods that contain extra or reduced ingredients.3,4 The effectiveness of the nutritional labels remains to be discovered, because nutritional labeling cannot be fully successful until consumers are taught how to use them properly and regulations on nutritional claims are put into legislation.5,6
1
Department of Health Sciences, Faculty of Science, University of Mauritius, Reduit, Mauritius 2 Department of Biosciences, Faculty of Science, University of Mauritius, Reduit, Mauritius Address for correspondence: Rajesh Jeewon, PhD, Department of Health Sciences, Faculty of Science, University of Mauritius, Reduit, Mauritius; Phone: (þ230) 403 7498; Fax: (þ230) 465 6928; E-mail: [email protected] Ó2014 SOCIETY FOR NUTRITION EDUCATION AND BEHAVIOR http://dx.doi.org/10.1016/j.jneb.2014.03.010
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It is therefore crucial to establish a relationship between consumers' knowledge, attitudes, and use regarding nutritional labels to improve the type of information provided on labels and how consumers use them to make healthy dietary choices.7 A number of studies have targeted the determinants of nutritional label use and understanding. Among these, age, gender, level of education, health status, nutritional knowledge, household size, level of income, and occupation have a relationship with nutritional label usage and understanding.8-14 A lower frequency of nutritional label use has been determined among older people.15 Conversely, other studies9,10,16 reported that the use of nutritional labels is proportional to an increase in age. Gender is another factor determining nutritional label use and understanding. Women use labels more frequently than do men.9,11 However, Nayga17 reported no gender difference regarding the use of nutritional labeling. Similarly, a greater
1
2 Cannoosamy et al likelihood of nutritional label usage is associated with a higher level of education.5,6,18 Consumers with a low income usually give more importance to the price of products, but this is not always true, because irrespective of their household level of income, consumers concerned with proper dietary habits will use nutritional labels.19 A larger household size is also positively correlated with label usage, because the latter is perceived as more beneficial.20 It has also been shown that nutritional knowledge and its impact on label use is also well documented because it facilitates the understanding and consequently the use of nutritional labels.5,6,9 In Mauritius, according to Hawkes,21 nutritional labeling was introduced in the Food Regulations of 1999 (added to the Food Act of 1998). These regulations established the specific nutrients that must be labeled for a series of selected nutritional claims. The labeling of protein, fats, carbohydrates, vitamins, and mineral content on infant foods per 100 g of packaged food was also mandated. Assessing the relationship between product performance and consumer satisfaction has not always been easy and sometimes has been controversial. To overcome this, the Kano model was developed to enable the analysis of this nonlinear relationship.22 This model is an effective tool for categorizing product criteria and product requirements. The Kano model consists of 3 levels of consumer satisfaction: expected, desired, and excited qualities. In the same context, these quality attributes are classified into 5 categories; attractive, 1-dimensional, must-be, indifferent, and reverse.23 When fully achieved, the attractive quality provides satisfaction, but it does not cause dissatisfaction if not fulfilled. The 1-dimensional quality consists of articulated needs (ie, what customers express in terms of needs). The 1-dimensional quality results in satisfaction when fulfilled, but dissatisfaction when not fulfilled. When fulfilled, the must-be quality is taken for granted, but when it is not fulfilled, it results in dissatisfaction. The indifferent quality refers to aspects that are neither good nor bad, and consequently they result in neither
Journal of Nutrition Education and Behavior Volume -, Number -, 2014 customer satisfaction nor customer dissatisfaction. The reverse quality, when it is fulfilled, results in dissatisfaction, and vice versa.22 In 1 study, Chen and Chaang24 applied the Kano model to investigate consumer satisfaction; the authors demonstrated that the model was reliable because it presented advantages for better understanding consumer requirements. Likewise, Kim et al25 used Kano analysis to determine the role of nutritional labels and satisfaction or dissatisfaction with foods, in which 1 of the key findings was that sodium content was an indifferent attribute. However, research in the field of nutritional labeling with regard to the Kano model and the perception by consumers of nutritional labels has not been fully explored. In this context, this study was initiated with the following objectives: (1) to assess consumers' nutritional knowledge; (2) to determine the main factors associated with the use and understanding of nutritional labels; and (3) to assess consumers' attitudes toward nutritional labels, as well as the level of consumer satisfaction (using the Kano model).
METHODS Participants The study was based on a survey of 400 consumers. The researchers used stratified random sampling to obtain a sampling frame that reflected the Mauritian population. The sample consisted of males and females who were unemployed and employed (retired people, students, and housewives were classified as being unemployed). The University of Mauritius research ethics committee granted approval for the research and prior consent was obtained from all participants. The age group ranged from 19 to > 50 years and the household size ranged from 1 to 5. A larger number of female respondents were recruited, because often they were the main shopper in the household.26 Of the 400 respondents, 100 who had studied or were studying a nutrition-related subject were also included.
Questionnaire Design and Data Analysis The survey questionnaire consisted of different sections. The first section aimed to assess respondents' knowledge about nutrition. With reference to Grunert et al,11 respondents' nutritional knowledge was assessed with respect to their awareness of experts' dietary recommendations, knowledge of food sources of nutrients, and awareness of diet–disease associations. Questions developed by Parmenter and Wardle27 were used. The second section assessed respondents' use and understanding of nutritional labels and claims, and the type of information they look for in nutritional labels. The third section was composed of a demographic information assessment. The performancerating scale developed by Whati et al28 was used to interpret consumers' nutritional knowledge. Statistical tests included 1-way ANOVA and independent samples t tests with a 95% confidence level (SPSS version 16, Chicago, IL, 2007). A Kano questionnaire assessing consumer attribute classifications consisted of pairs of 1 functional and 1 dysfunctional question. Respondents were required to record their feelings and choose from 1 of the following responses: ‘‘like it,’’ ‘‘expect it,’’ ‘‘neutral,’’ ‘‘tolerate it,’’ and ‘‘dislike it.’’
RESULTS Nutritional Knowledge Most respondents correctly answered questions on expert recommendations about vegetables (97%), fruits (98.8%), and calcium (59.8%); 3% and 1.2% of the sample incorrectly answered questions about fruits and vegetables, respectively. Inversely, the majority of respondents incorrectly answered questions about expert dietary recommendations regarding sugary foods (65%) and calories from fats (78.8%). With the exception of packed soy products, respondents correctly classified other food items in the food groups. For the part on diet and disease awareness, 58.2% of the sample incorrectly answered the question about what reduces the risk of getting cancer.
Journal of Nutrition Education and Behavior Volume -, Number -, 2014 The total percentage score of each respondent was calculated and interpreted based on the performancerating scale developed by Whati et al.28 Nutritional knowledge of the sample population ranged from ‘‘very poor’’ to ‘‘excellent.’’ A total of 48% had ‘‘very good/above average’’ nutritional knowledge, whereas 23% obtained an ‘‘excellent’’ performance rating and 1% had a ‘‘very poor’’ rating. The researchers determined the correlation between nutritional knowledge and gender, age, and level of education. Table 1 shows that females had a higher nutrition knowledge score (72.2 16.2) compared with males (63.4 13.7). In addition, factors such as age (between 19 and 29 years of age), having a tertiary education, and studying a nutrition-related subject resulted in higher nutritional knowledge scores of 77.2 16.2, 77.1 13.4, and 80.6 14.1, respectively.
Use and Understanding of Nutritional Labels A total of 42.3% of consumers reported frequent use of nutritional labels when purchasing a product for the first time or when comparing 2 food products. However, only 22.2% claimed to always use nutritional labels, and 3.2% never used nutritional labels. The remaining 32% of the respondents reported occasional use. Of the respondents, 53.7% reported that it was ‘‘somewhat easy’’ to understand the nutritional information provided (Table 2). Similarly, when they were asked to what extent this information influenced their purchasing behavior, 30.5% reported a ‘‘fair’’ influence. Of the sample, 18.2% found that the content information was ‘‘very easy’’ to understand; a higher percentage of these respondents (11.5%) claimed that this information ‘‘greatly’’ affected their purchasing choices. However, some respondents (6.5%) claimed that the information was ‘‘very hard’’ to understand, and 4.2% reported ‘‘little’’ influence on their purchasing behavior. As Table 3 shows, statistical significance for gender, age group, education, occupation, household size and income, and nutritional knowledge was P < .05, which meant that younger females with a tertiary education and
Cannoosamy et al 3
Table 1. Relationship Between Demographic and Individual Factors and Nutritional Knowledge Score of Mauritian Consumers (n ¼ 400) Demographic and Individual Characteristics Gendera Male (n ¼ 184) Female (n ¼ 216)
Mean Nutritional Knowledge Score ± SD (%) 63.4 13.7 72.2 16.2
Age group, ya 19–29 (n ¼ 136) 30–39 (n ¼ 108) 40–49 (n ¼ 100) > 50 (n ¼ 56)
77.2 16.2 67.2 15.5 62.8 10.5 57.6 10.3
Level of educationa Primary (n ¼ 36) Secondary (n ¼ 215) Tertiary (n ¼ 149)
46 9.3 65.7 13.3 77.1 13.4
Studied nutrition-related subjectb Yes (n ¼100) No (n ¼300)
80.6 14.1 64.0 13.9
ANOVA test; bIndependent samples t test. Note: All comparisons were significant at P < .05. a
with a high income, household size, and nutritional knowledge were more likely to use nutritional labels. The understanding of a nutritional label was also investigated; Table 4 shows that the determinants of nutritional label understanding included age, education, occupation, household income and size, health status, and nutritional knowledge. The association between gender and label understanding was insignificant (P > .05).
did so for trans fat, 36% for cholesterol content, and 32% for protein content. The attractive attributes included serving size (35%), calcium content (36%), and iron content (35%). One-dimensional attributes included total fat content (48%) and sugar content (50%). Only sodium content was an indifferent attribute, categorized by 48% of respondents.
DISCUSSION
Analysis of Kano Model Consumer Survey Most attributes of the nutritional label were must-be attributes. A total of 47% respondents classified calorie content as a must-be attribute, 39%
The main findings of determinants of nutritional knowledge were gender, age, and education (especially prior nutritional knowledge). Nutritional label usage was associated with gender, age, education, occupation,
Table 2. How Mauritian Consumers Perceive Nutrition Information and Its Influence on Their Purchasing Behavior How Do You Find the Information Provided on the Nutritional Labels of Prepackaged Foods?
To What Degree Does the Content Information of the Prepackaged Food Product Affect Your Purchasing Behavior? Not at All Little Somewhat Fairly Greatly
Very hard to understand Somewhat hard to understand Somewhat easy to understand Very easy to understand
0.7 1 0.5 0
4.2 9.7 6.5 1
Note: Numbers represent percentage of consumers.
1.5 6.7 11.5 0.2
0 3 22 5.5
0 1 13.2 11.5
4 Cannoosamy et al
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Table 3. Relationship Between Use of Nutrition Labels and Demographic and Individual Factors of Mauritian Consumers (n ¼ 400) Demographic and Individual Characteristics Genderb Male (n ¼ 184) Female (n ¼ 216)
Mean Nutritional Label Use Score ± SD (%) 67.8 16.9 73.8 18.9
Age group, ya 19–29 (n ¼ 136) 30–39 (n ¼ 108) 40–49 (n ¼ 100) > 50 (n ¼ 56)
77.3 17.5 70.1 17.6 71.9 15.4 56 17.9
Level of educationa Primary (n ¼ 36) Secondary (n ¼ 215) Tertiary (n ¼ 149)
47.4 14.6 69.1 16.1 79.5 16.2
Occupationa Employed (n ¼ 177) Unemployed (n ¼ 90) Retired (n ¼ 36) Student (n ¼ 97)
73.0 17.2 68.9 17.3 53.8 18.6 75.7 17.2
Household income (Mauritian rupees)a < 10,000 (n ¼ 48) 10,000–20,000 (n ¼ 125) 20,000–30,000 (n ¼ 152) > 30,000 (n ¼ 75)
53.5 19.3 67.3 15.3 77.6 15.1 75.3 19.3
Household sizea 1 (n ¼ 12) 2 (n ¼ 43) 3 (n ¼ 101) 4 (n ¼ 174) > 5 (n ¼ 70)
62.2 25.3 59.0 18.4 70.1 15.2 74.3 18.6 73.0 16.9
Nutrition knowledgea Very poor (n ¼ 4) Fair/below average (n ¼ 59) Good/average (n ¼ 53) Very good/above average (n ¼ 191) Excellent (n ¼ 93)
30.8 0.0 57.5 13 59.5 18.4 74.7 15.8 80.5 15.9
ANOVA test; bIndependent samples t test. Note: All comparisons were significant at P < .05.
a
income, household size, and nutritional knowledge. However, an understanding of nutritional labels depended on the different demographic factors studied, with the exception of gender.
Consumers’ Nutritional Knowledge Based on the findings, Mauritians have a good knowledge of nutrition, because 48% had ‘‘very good/above average’’ nutritional knowledge and 23% had ‘‘excellent’’ nutritional knowledge. This high level of aware-
ness may be explained by the fact that the Ministry of Health and Quality of Life of Mauritius came up with a National Plan of Action for Nutrition in 2009 and 2010, whose aims were not only to emphasize public health promotional campaigns, but also to provide the population with nutritional information.29 The main determinants of nutritional knowledge, as obtained in this study, included gender (being female), knowledge about nutritional subjects, age (between 19 and 29 years), and having a tertiary education. Younger respondents had better nutritional knowl-
edge, because most aged between 19 and 29 years were university students; as such, they had a higher level of education and were more aware of nutritional issues, both of which justify their higher nutritional knowledge. A higher level of education has always been associated with higher nutritional knowledge30 and more highly educated individuals are more likely to be exposed to health or nutritionrelated news sources.20
Use and Understanding of Nutritional Labels Statistical evidence demonstrates a relationship between gender and nutritional label use. Women were more engaged in nutritional label use than were men. Females may use food labels more often than males simply because they are the primary food purchasers, and the greater social pressure that women experience to eat a healthy diet may further encourage them to take action toward achieving this objective.26 According to Nayga,31 men are less likely to accept that nutritional label information is useful; and contrary to women, men are generally less interested in nutrition and health. The current survey findings showed that younger respondents reported more frequent label use than older respondents, which is in accordance with the findings of Kim et al32,33 and Cole and Balasubramanian,34 who reported that as age increases, the probability of using nutritional labels also decreases. According to Ippolito and Mathios,35 individual characteristics affect the search for nutritional information, and age was one of the most common characteristics used in studies on nutritional labels.19 Burton and Andrews15 attributed this to the lower processing capacity of older people and the fact that older people tend to perceive labels as being difficult to understand. This lower use of labels may also be because, although older people have more interest in healthy eating, they have less nutritional knowledge, and higher nutritional knowledge leads to greater use and understanding of label information.11 However, studies by Coulson,10 Govindasamy and Italia,16 and Drichoutis et al19 found the
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Cannoosamy et al 5
Table 4. Effect of Demographic and Individual Factors on Mauritian Consumers’ Understanding of Nutrition Labels (n ¼ 400)
related news sources. Moreover, education may help them to interpret the information provided.37 The researchers investigated the link between occupational status and nutritional label use, and the outcome showed a positive association between them. Respondents who were working reported more frequent nutritional label use compared with those who were unemployed or retired. These results are in line with the findings of Drichoutis et al,9 who reported that working people were more likely to use nutritional labels. Furthermore, being employed is often associated with a higher household income, and the results of this study demonstrate that a higher income level is significantly associated with nutritional label use. This may be attributed to 2 main factors. First, a lower level of income limits the amount of choice consumers have regarding products; and second, consumers actively look for price information, which affects their use of nutritional information.19 The authors found a statistically significant association of nutritional label use with household size (nutritional label use was proportional to household size). A household size of more than 4 was associated with a higher mean nutritional label usage score. This result implies that the main meal planners of larger households were more likely to use information concerning the contents of food packages. A plausible explanation is that the use of nutritional information on food packages is viewed as beneficial by the main meal planners, especially where the eating habits of a larger number of persons are involved. Consequently, the relative value of time spent searching for information is higher for larger households than for smaller ones.20 The current study's findings demonstrated a statistically significant relationship between nutritional knowledge and nutritional label use. Respondents with ‘‘excellent’’ nutritional knowledge had a higher frequency of nutritional label usage compared with those with ’’fair’’ or ‘‘very poor’’ nutritional knowledge. According to Bender and Derby,18 nutritional knowledge may facilitate nutritional label use by increasing its perceived benefits and increasing the
Demographic and Individual Characteristics Gender*,b Male (n ¼ 184) Female (n ¼ 216) Age group, y**,a 19–29 (n ¼ 136) 30–39 (n ¼ 108) 40–49 (n ¼ 100) > 50 (n ¼ 56)
Mean Nutritional Label Understanding Score ± SD (%) 60.5 31.2 64.3 31.7 72.9 28.8 62 30.3 60.4 28.3 42.5 36
Level of education**,a Primary (n ¼ 36) Secondary (n ¼ 215) Tertiary (n ¼ 149) Occupation**,a
9.4 16.2 62.7 27.4 75.3 26.6
Employed (n ¼ 177) Unemployed (n ¼ 90) Retired (n ¼ 36) Student (n ¼ 97)
66.1 29.2 50 29.9 43.9 39.9 74.8 27
Household income (Mauritian rupees)**,a < 10,000 (n ¼ 48) 10,000–20,000 (n ¼ 125) 20,000–30,000 (n ¼ 152) > 30,000 (n ¼ 75) Household size**,a
31.6 38.2 62.6 31.9 68 23.8 71.5 28.9
1 (n ¼ 12) 2 (n ¼ 43) 3 (n ¼ 101) 4 (n ¼ 174) > 5 (n ¼ 70)
21.7 31.3 53.5 42.7 55.4 30.2 66.3 29.8 76.3 18.1
Have disease**,b No (n ¼ 276) Yes (n ¼ 124)
67.2 30.2 52.4 32.5
Nutrition knowledge**,a Very poor (n ¼ 4) Fair/below average (n ¼ 59) Good/average (n ¼ 53) Very good/above average (n ¼ 191) Excellent (n ¼ 93)
20 0.0 36.3 35.5 53.2 30.4 65.7 27.8 80 22.8
*P > .05; **P < .05; aANOVA test; bIndependent samples t test.
opposite, that nutritional label usage was proportional to an increase in age. The trend observed in these studies may be because older individuals might be more cautious about what they eat, for medical reasons (especially because the prevalence of noncommunicable diseases is high in Mauritius), contrary to their younger counterparts, which results in a higher likelihood of using nutritional labels. Many studies have demonstrated clear links between nutritional label
use and a high level of education level36 and occupation.9 Similarly, the results of this study showed that a higher mean score for nutritional label use was significantly associated with higher levels of education. A marked difference was observed in the mean score of respondents with a tertiary education and those with a primary education (Table 2). According to Nayga,20 more highly educated individuals were more likely to be exposed to health- or nutrition-
6 Cannoosamy et al efficiency of label use. Similarly, Moorman and Matulich38 showed that a higher level of health knowledge had a positive influence on receiving information from media sources, which include the use of nutritional labels. Drichoutis et al9 found that people with higher nutritional knowledge used nutritional labels more often, mainly because they were able to evaluate and understand the information on food labels; and furthermore, that consumers who were more able to derive information from nutritional labels were more likely to use them. The researchers also determined factors affecting the understanding of nutritional labels, and the main findings showed no significant association (P > .05) between gender and understanding labels. On the other hand, age had a significant association with nutritional label understanding. Similarly, the levels of household income and size, occupation, and nutritional knowledge were all significantly associated with better nutritional label understanding. Respondents with higher nutritional knowledge were more apt to further interpret and process the information on the label compared with those with lower nutritional knowledge. Grunert et al11 concluded that younger people had higher levels of understanding owing to their higher nutritional knowledge and intellectual ability. The influence of nutritional labels on purchasing behavior was greater when respondents could better understand the nutritional labels. This was attributed to the fact that as respondents were able to interpret the information provided, they could further process the information to decide which food products better suited their dietary needs. Fitzgerald et al39 reported that using food labels to choose high-fiber foods was associated with high consumption of fruits and vegetables, and using labels to choose foods low in sodium was associated with a lower intake of salty snacks. Furthermore, Ollberding et al40 observed a consistent relationship between the increased use of nutritional labels and improved nutrient intake. Although label use did not always lead to healthier consumption, it could change dietary patterns and contribute to better dietary intake or reduce the consumption of unhealthy foods.9
Journal of Nutrition Education and Behavior Volume -, Number -, 2014 The researchers investigated respondents' use of information on labels to perform certain tasks. Label information was nearly ‘‘always’’ used to compare food, check fat content, and get storage instructions. On the contrary, when deciding which brand to buy, this information was only ‘‘sometimes’’ used. This may be because consumers rely on nutritional information on food labels only when they have a specific reason to do so: for example, locating food products for specific dietary needs.41
Outcomes of Kano Study Based on the outcomes of the Kano survey, nutritional information on calories, trans fat, cholesterol, and protein was found to be a must-be attribute (an attribute that, when not present, results in consumer dissatisfaction). On the contrary, serving size, and calcium and iron content were attractive attributes, which means that these provide satisfaction when present and can be used to attract consumers to a product. Sugar and total fat content were 1-dimensional attributes, attributes that result in consumer satisfaction when present and dissatisfaction when absent. Sodium content was an indifferent attribute, which implies that whether sodium content is present or not, there is neither consumer satisfaction nor dissatisfaction. This agrees with the findings of Kim et al,25 in which the Kano analyses revealed that sodium content was an indifferent attribute. According to the prospect theory developed by Kahneman and Tversky (1979, cited by Hoefkens et al42), consumers tended to attach more importance to attributes (nutrients) that had potential losses rather than those having potential gains. The findings of the Kano survey support this theory, in which it was expected that more importance would be put on disqualifying nutrients (calories, trans fat, cholesterol, fat, and sugar content), that is, those that disqualify the food product when present. Furthermore, according to Russo et al,43 although consumers see both positive and negative nutrients as important, they emphasize the negative nutrients: those which they want to avoid or for which they want to
reduce their consumption. Negative nutrients include calories, cholesterol, sodium, and sugar. In fact, consumers used nutritional labels to avoid negative nutrients, and these effects might be even greater if labeling were combined with an information campaign to educate consumers.9
IMPLICATIONS FOR RESEARCH AND PRACTICE The results from this study may be used to shed light on current explanations regarding differences in the attributed importance of qualifying and disqualifying nutrients. The level of understanding nutritional labels among different population groups can be determined, thus providing a good starting point for addressing barriers to label usage. Moreover, these results can be used to design communication strategies and help health professionals to stress the importance of both qualifying and disqualifying nutrients. The Kano model can be used to classify information on nutritional panel labeling that may contribute to consumer satisfaction.
ACKNOWLEDGMENTS The authors appreciatively acknowledge the participants in the study.
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