Skip to main content

ORIGINAL RESEARCH article

Front. Nutr., 22 March 2024
Sec. Food Policy and Economics
This article is part of the Research Topic Industry and Individuals: Branding, Labelling, and Marketing of Food Products View all 8 articles

Predicting willingness to consume healthy brand foods using the theory of planned behavior: the role of nutritional literacy

  • 1Unidad de Ciencias Empresariales, Escuela de Posgrado, Universidad Peruana Unión, Lima, Peru
  • 2Faculty Management Science, Universidad Autónoma del Perú, Lima, Peru
  • 3Departamento de Administración, Facultad de Administración y Economía, Universidad de Santiago de Chile, Santiago, Chile
  • 4Escuela Profesional de Administración, Facultad de Ciencias Empresariales, Universidad Peruana Unión, Lima, Peru
  • 5Escuela Profesional de Administración, Facultad de Ciencias Empresariales, Universidad Peruana Unión, Juliaca, Peru

Introduction: The willingness to consume healthy foods has highlighted the growing importance of health, even more so when it comes to food choice, and predicting the willingness to consume foods of a healthy brand represents an action that leads to the practice of conscious eating habits, but what is behind this willingness? To answer this question and based on previous studies such as the theory of planned behavior and nutritional literacy, this study aimed to build a predictive model through an empirical study to examine the influence of nutritional literacy (NL) on attitude (ATT), subjective norm (SN) and perceived behavioral control (PBC), as well as to determine the influence of the three variables of the theory of planned behavior (TPB) on the willingness to consume healthy brand foods (WCHBF) in the Peruvian market.

Methods: The research focused on the population that stated that they were consumers of the Unión brand (a brand whose value proposition is the sale of healthy foods), obtaining 482 consumers. The study was conducted under a quantitative, non-experimental, cross-sectional design approach.

Results: The results support the existence of a positive and significant effect of NL on ATT, SN, and PBC, finding the exact behavior of SN and PBC in WCHBF; however, in the proposed model, it is observed that ATT has no impact on WCHBF.

Conclusion: Applying strategies that lead to a change in consumer behavior towards healthy brands is a matter of time and will. In this context, the findings indicate that nutritional literacy plays an essential role in the willingness to consume healthy foods, which sheds more light on the design of educational interventions and awareness campaigns that independently inform about nutritional benefits and empower consumers, allowing them to make informed and healthy choices.

1 Introduction

Over time, there have been significant changes in food consumption patterns. Health has become one of the most critical factors influencing food choices (14). However, individuals have varying attitudes toward food and dietary behaviors, resulting in different food patterns and preferences (57).

People’s willingness to consume healthy brand-name foods can vary widely due to some factors, including personal preferences, purchasing power, health awareness, nutritional information and labeling, lifestyle, and dietary choices, price and availability, brand reputation, and cultural and social trends (8). Previous literature recognized a significant association between the willingness to consume foods from healthy brands with nutritional information and labeling since having clear and transparent information about the ingredients and nutrition of the product or food can influence purchasing decisions (9, 10). Brands that emphasize health attributes can attract health-conscious consumers (11, 12). In this sense, the intention to consume healthy branded products is a complex and multifaceted phenomenon involving personal and contextual factors. Food companies often adapt to these trends and adjust their marketing strategies to attract consumers looking for healthier options since studies ensure that social influence affects food intake and choice (13).

On the other hand, it is worth mentioning that nutritional literacy is considered one factor contributing to good practices in maintaining an adequate diet; that is, it provides the community with valuable information about the risks associated with malnutrition (14). Nutrition literacy is essential to promote health and well-being at individual and societal levels. Promotes disease prevention, weight control, healthy eating habits, and consumer empowerment, thus creating a healthier society that recognizes the importance of a balanced diet (15, 16).

Therefore, the willingness to consume foods from healthy brands and nutritional literacy are key aspects that are vital in promoting a balanced and healthy diet (11, 17, 18). Together, they are committed to building a healthier society where consumers can make informed decisions that benefit their well-being and society (8, 16).

Continuing education on healthy eating is critical to addressing nutrition-related public health issues and promoting healthier lifestyles. However, very little has been written about the willingness to consume foods from healthy brands (5, 1921). One of their studies refers to how emotional regulation influences food choice. When people reduce incidental negative emotions caused by reappraisal, they prefer foods from healthier brands more than when they let their feelings decide (21).

The theory of planned behavior (TPB) has been widely used to examine various aspects of people, such as to predict organic food adoption behavior (22), dietary behaviors (23), also to predict sugar intake (24), the intention to adopt a healthy diet (25) and fast food consumption (26); furthermore, its application has also been transferred to other contexts such as oral health behaviors (27), improving medication adherence (28), teaching complementary medicine (29), pro-environmental behavioral intention (30) and understanding Facebook user behavior (31). In this sense, the TPB is used to understand and predict human behavior, particularly in decision-making associated with planned actions or behaviors (22). TPB has been used in various fields, including health, psychology, marketing, and management. The application of the TPB is crucial because it provides a solid and practical theoretical framework for understanding, predicting, and changing people’s behavior (32). By understanding the motivations and perceptions of decisions, professionals can develop more effective strategies to encourage desired behaviors and increase the effectiveness of interventions in different fields of action (25).

After a diligent review of the background above, there has been a growing interest in continuing to study these topics for academics and professionals in the business and health sectors. Although scientific evidence validates that among the topics of study, the theory of planned behavior has caused the most significant interest. However, bibliometric indicators reveal the ten countries that most disclose their scientific results: the USA, China, United Kingdom, Australia, Iran, Malaysia, Canada, Taiwan, Indonesia, and South Korea. The same ones have applied their study to various areas, sectors, and populations, such as business, social sciences, medicine, psychology, environmental science, and engineering. When discerning the scientific dissemination by country, the studies carried out in the Peruvian population have been found to be very limited. That is, very little scientific literature can provide support and guidance for future studies in this context. Given the prevalence of diseases and poor eating practices related to nutrition, this research aims to fill the knowledge gap and provide a valuable contribution to the academic community and professionals of the sectors involved. In this sense, the purpose of the research is to build a predictive model through an empirical study to examine the influence of Nutritional Literacy (NL) on attitude (ATT), subjective norm (SN), and perceived behavioral control (PBC), as well as determine the influence of three variables of the theory of planned behavior (TPB) on the willingness to consume (WCHBF) for healthy products in the Peruvian market.

2 Theoretical background

2.1 Research variables

2.1.1 Nutritional literacy

Nutritional literacy was first established in 1995 to assess awareness of nutrition labels among healthy individuals in Canada (14, 33, 34). Nutrition literacy is an individual’s ability to understand, evaluate, and effectively use nutritional information (35, 36). It involves gaining knowledge about the principles of healthy eating, interpreting nutritional information in foods, and making informed decisions about diet and nutrition (37, 38). Nutritional literacy is crucial in promoting the health and well-being of consumers and can help prevent diet-related diseases such as obesity and diabetes. Furthermore, it can foster healthy eating habits and make informed dietary decisions (14, 37).

Critical nutrition literacy involves skillfully evaluating and scrutinizing nutrition information and guidance and being motivated to address nutritional obstacles from individual, societal, and global perspectives (17). In this context, there has been a noticeable increase in the interest and focus on nutritional literacy (33). Nutritional educational programs have been proven essential in formal and informal settings such as schools, universities, and communities. These programs aim to educate consumers about a balanced and healthy diet. The programs also teach them how to interpret nutritional information and make informed decisions about their diet and nutrition (34, 39, 40). Clear and understandable food labeling is essential. It helps consumers understand nutritional information and make better choices about their diet. Promoting healthy foods is also crucial (41, 42). Marketing campaigns, strategic discounts in stores and supermarkets, and offering nutritious options in restaurants and cafes all encourage healthier eating habits (43, 44). Quick access to healthy foods is also important. This strategy ensures that fruits, vegetables, whole grains, and lean proteins are available and accessible in stores and supermarkets (45, 46). It also encourages the creation of community gardens and farmers markets to promote a nutritious eating environment (47). Finally, collaboration with the food industry is essential. This cooperation seeks to develop and promote healthy foods, reduce the sugar, salt, and fat content in processed foods, and promote transparent and responsible food marketing (38, 48).

2.1.2 Willingness to consume healthy brand food

In today’s context, consumer behavior strongly favors foods that contribute to health and well-being, driven by consumers’ enhanced access to tools empowering informed decisions about their nutritional choices (49, 50). Consumers’ willingness to choose and consume healthy branded foods is related to their attitude toward foods perceived as healthy or beneficial to their health (5153). Numerous elements, including brand perception, nutritional information, cost, and personal preferences, can affect one’s attitude toward preferring this food (5457). According to previous studies, a brand’s perceived healthiness, product quality, and understandable nutritional information availability all impact consumers’ willingness to buy and consume healthy branded foods (42, 5860). Additionally, socio-economic factors like income level, education, and occupation can also impact the willingness to consume brand-name healthy foods (61, 62).

In addition, it is advisable to use nudge marketing tools to promote consumers’ willingness to choose and consume healthier brand foods (6365). Nudge marketing tools refer to marketing strategies influencing consumers’ readiness to select and consume more nutritious food products from specific brands. These tools may include visually appealing and informative nutritional labels, strategic product placement in retail environments, and promotional offers or discounts for healthier options (66, 67). The aim is to encourage consumers to make healthier food choices willingly, positively impacting their overall dietary habits (63, 68). This concept is particularly relevant in increasing awareness and concern about health and nutrition, where marketers seek effective and ethical ways to promote healthier brand foods without infringing upon consumers’ freedom of choice (65, 69).

2.1.3 Theory of planned behavior

The Theory of Planned Behavior (TPB) is a psychological framework that helps predict and understand human behavior (70). It is commonly used to predict purchasing and consumption behaviors (7073). TPB proposes three main factors influencing a person’s behavior: attitude toward the behavior, subjective norm, and perceived behavioral control (70, 74).

First, consumer attitude towards the behavior refers to how a person evaluates the behavior they are considering (52, 75). According to Ajzen and Madden (76) “attitude” denotes the degree to which a person has a favorable or unfavorable opinion or evaluation of an action or behavior. People who hold a better attitude towards a particular behavior are more likely to have the intention to perform that action (77).

Subjective norms refer to a person’s social pressure to perform or not perform a behavior (70, 75, 78). According to Madden et al. (79), an individual’s close friends are the primary reference group influencing subjective norms. Subjective norms also refer to the positive or negative judgments and perceptions of individuals or groups that believe the individual should perform a particular action (78).

Lastly, perceived behavioral control is a term used to refer to the ease or difficulty with which an individual can carry out a behavior (74, 79). A combination of control beliefs and an individual’s perceived power significantly predict their intention (80). In other words, PBC refers to an individual’s ability to control and perform a specific action. This concept is crucial as it ensures that individuals can easily carry out their intended actions, leading to successful behavior change (74).

2.2 Conceptual model and research hypothesis

2.2.1 Influence of nutritional literacy on the theory of planned behavior

Previous studies have indicated that higher nutritional literacy influences consumers to have more positive attitudes towards healthy eating (49). According to Ramdam et al. (81) having more excellent nutrition knowledge is directly linked to more positive attitudes toward selecting healthy foods. Furthermore, Tian et al. (82) point out that labels such as educational materials and food promotions provide objective information to consumers when purchasing a healthy diet. This situation is attributed to the fact that individuals with better nutritional literacy tend to understand the benefits of a balanced diet, which positively influences their attitudes toward healthy eating and, therefore, towards healthy food brands. Similarly, Miller and Cassidy (83) understand nutritional information might be crucial in making dietary decisions through various means. This influence may extend beyond reliance on explicit food label details, encompassing direct impacts on food choices or shaping attitudes and beliefs. Considering these precedents, the hypothesis posits that:

H1: Nutritional Literacy (NL) positively influences consumer attitudes toward healthy brand food consumption.

According to previous research, people’s understanding of nutrition can affect their personal beliefs about eating habits (84, 85). Nutritional labels impact the consumer and the social environment, especially when consuming healthy products. For instance, when dining out, the people who matter to the consumer prefer to select a menu item that provides nutritional information (86). Similarly, Sousa et al. (87) found that customers’ intentions to purchase products with nutritional labels were significantly related to their subjective norms, indicating that consumers are influenced by their peers when using food labels to select healthy foods. Considering these antecedents arises the hypothesis that:

H2: Nutritional Literacy (NL) positively influences Subjective Norms (SN) for healthy brand food consumption.

Previous studies highlight the significant impact of food literacy on consumers’ perceived control and informed decision-making regarding their dietary choices. Sousa et al. (87) revealed a strong correlation between food literacy and perceived behavioral control, indicating that understanding nutrition information on food labels empowers individuals, amplifying their control over food choices. Similarly, Trieste et al. (88) observed that individuals knowledgeable about nutrition exhibit heightened attention toward nutritional aspects in products, facilitating informed decisions in food consumption. Begley et al. (89) further supported these findings, proposing that promoting food literacy programs can instigate positive shifts in eating behavior and facilitate well-informed decision-making in dietary choices. Taking into account these antecedents, the hypothesis proposes that:

H3: Nutritional Literacy (NL) positively influences Perceived Behavioral Control (PBC) for healthy brand food consumption.

2.2.2 Influence of the theory of planned behavior on willingness to consume healthy food

The theory of planned behavior has been fundamental in understanding consumer food decisions (9092). Based on the idea that attitudes, perceived social norms, and perceived behavioral control influence a person’s intentions and behaviors, this psychological theory has been successfully applied in numerous studies focused on consumers’ food choices (9197).

Previous studies have established a strong association between consumers’ attitudes and their intention to consume healthy food (9395, 98100). For instance, Roseman et al. (101) highlight the importance of the connection between consumers’ attitudes toward food and their intention to buy it. Creating a positive perception among consumers is crucial, as it can significantly affect their buying and consumption behavior (102104). Küster-Boluda and Vidal-Capilla (98) stated that consumers’ favorable attitudes toward functional foods significantly impact their likelihood of consuming them. Similarly, Khan et al. (105) emphasize that a positive consumer attitude toward an organic product can generate purchase intentions and result in an actual purchase. There is a correlation between consumer attitude and the intention to consume health-oriented products. Grounded in these precedents, the hypothesis posits that:

H4: Attitude (ATT) positively influences the consumers’ willingness to consume healthy brand food (WCHBF).

Prior research has established that consumers’ subjective perceptions of the social environment and expectations significantly impact their purchasing and consuming healthy brand foods (94, 96, 106108). This is mainly because societal trends toward healthier eating and increased individual responsibility for personal well-being have strongly impacted consumers’ choices to buy organic foods (90, 109). For example, Lim and Goh (93) emphasized how social norms and the reference opinions of other individuals positively impact the consumer’s inclination toward purchasing healthy drinks. This finding highlights the relevance of considering social influences in formulating effective strategies to encourage the acquisition of organic products. According to Teng and Wang (108) people who are significant in a consumer’s life can influence their intention to purchase organic products. If consumers perceive that those important to them have a favorable or unfavorable view of organic food, it can affect their purchase intentions towards organic food. Similarly, Agnoli et al. (97) affirmed a high association between wine consumption and social referents. They observed that close friends and partners considerably influenced subjective influence, implying that they are essential in controlling drink consumption. Based on these backgrounds, the hypothesis suggests that:

H5: Subjective Norms (SN) positively influence the consumers’ willingness to consume healthy brand food (WCHBF).

Previous research has shown that people are more likely to consume healthy brand foods when they control their behavior (53, 90, 92, 96). A study conducted by Ham et al. (96) found a significant correlation between an individual’s intention to purchase organic food products and their sense of control over their actions. This emphasizes the importance of an individual’s confidence in making informed choices regarding their food preferences. Another study by Giampietri et al. (110) revealed that consumers are more likely to buy their preferred food items when they feel they have greater control over their behavior. However, people’s perceptions of control over their actions may vary in different circumstances. This could be linked to how much power a consumer has over what they choose to purchase and consume. As a result, it can affect a consumer’s willingness to buy organic food (53). Based on these antecedents, the hypothesis suggests that:

H6: Perceived Behavioral Control (PBC) positively influences the consumers’ willingness to consume healthy brand food (WCHBF).

Considering the hypotheses mentioned above, the ensuing conceptual model of the study can be visualized, as depicted in Figure 1. Additionally, the advanced hypotheses and their associated constructs have been briefly outlined in tabular form and are available for reference in Appendix A.

Figure 1
www.frontiersin.org

Figure 1. Conceptual model.

3 Methods

3.1 Context and method

This article aimed to build a predictive model through an empirical study to examine the influence of Nutrition Literacy (NL) on attitude (ATT), subjective norm (SN), and perceived behavioral control (PBC), as well as determine the influence of the three variables of the theory of planned behavior (TPB) on the willingness to consume (WCHF) for healthy products in the Peruvian market. The study used a quantitative, non-experimental, and cross-sectional design approach, using a self-administered questionnaire (111).

3.2 Sample and procedure

Different authors recommend different sample sizes. The optimal sample size recommended by some authors should be more than 100 subjects, and the minimum acceptable is at least five times the number of items to be analyzed; however, they suggest that ten times the number of items to be interpreted would be more acceptable (112, 113). Considering these recommendations and given that the instrument of the present study is composed of 27 essential items and three socio-demographic items, a minimum sample of 300 subjects was established. In the end, a sample of 482 participants was obtained, which is above the minimum required sample.

Taking into account that, according to the last Peruvian census, the Lima population is made up of 9,485,405, where women predominate (114) and under the support established by the researchers by stating that young people (5, 115118) are the ones who tend to consume healthy products compared to adults, considered more traditional, the sample was based on university students. Non-probabilistic convenience sampling was applied to collect data for this research (119). It should be noted that this study was approved by the Ethics Committee of the EPG of the Universidad Peruana Unión (2023-CE-EPG-00043) and was conducted in accordance with the ethical standards of the Declaration of Helsinki. An online survey was carried out through the Google form, the link of which was shared through the official social networks of a private university, an institution where an adequate lifestyle is promoted through healthy eating and which also has the Unión industry within its facilities, applied during the period from July to December 2023 in the city of Lima, Peru. The investigation focused on consumers who stated they were consumers of the Unión brand (whose value proposition is the sale of healthy foods). Participants had to be of legal age, from 18 years onwards. Men and women were invited to participate in the survey; however, the response rate differed (see Table 1). To participate in the survey, each consumer must provide informed consent (Under the premise: ‘I acknowledge that by completing this questionnaire, I am giving my consent to participate in the study’). To do so, they were previously informed that their participation was voluntary, that the data collected would be analyzed anonymously, and that they would be used exclusively for academic and research purposes. Nearly 800 Peruvian consumers were invited to this survey, 482 correctly completed questionnaires were answered, and they were considered suitable to be considered in the analysis of this document. Of them, the most significant number of participants were between 18 and 24 years old (84%), were female (65.1%), and their civil status was single (95.2%) (see Table 1).

Table 1
www.frontiersin.org

Table 1. Socio-demographic data of the sample (n = 482).

3.3 Measures

To evaluate the Nutritional Literacy (NL) variable, this study applied the short 11-item scale developed by Vrinten et al. (120). To evaluate the variables of the theory of planned behavior, adaptation was proposed by Kumar et al. (121), where Attitude, Subjective Norm, and Perceived Behavioral Control have three items each, and the willingness to consume foods from healthy brands has seven items (Appendix B). All items are evaluated using a 5-point Likert-type scale, where “1” means “Strongly disagree” and “5” means “Strongly agree.” The digital questionnaire was divided into two sections. The first section presented the 27 items already mentioned, and the second section was composed of questions related to socio-demographic data such as age, sex, and civil status.

3.4 Analysis of data

Two statistical software packages were used to analyze the data: IBM SPSS version 22 was used to analyze the respondents’ demographic data, shown in Table 1. Tests for discriminant validity, convergent validity, and reliability were carried out to assess the measurement model (122). Smart-PLS version 4.0 was used to test the conceptual model (see Figure 1) using a two-step approach involving measurement model evaluation and structural model evaluation (122). The PLS-SEM partial least squares method was used to test the hypotheses. PLS-SEM is a comprehensive multivariate statistical analysis approach that includes structural and measurement components to simultaneously examine the relationships between each of the variables in a conceptual model, which has the characteristic of multivariate analysis, i.e., it involves a number of variables equal to or greater than three (119). In addition, PLS-SEM was used in the present study because it facilitates the construction of theories (123).

The significance of the path coefficients (p-value and t-value) was sought to evaluate the structural model. The coefficient of determination (R2) was used to measure the predictive relevance of the structural model. Finally, the overall model fit was measured using the root mean square residual (SRMR). It is noteworthy that behavioral scholars have praised the application of PLS-SEM in interdisciplinary research (124).

4 Results

Before carrying out the model analyses, the exploratory data analysis was previously carried out with the SPSS-22 software and it was detected that there were no inconsistencies and no outliers, so there was no need to transform the data. Furthermore, according to the contributions of Professor Gaskin, since it is a Likert scale, there are no atypical values, since the participant responds at the extreme (1 or 5), which is why it does not represent a representative atypical component (125).

The application of the PLS-SEM software is carried out through two stages: (1) evaluation of the measurement model and (2) evaluation of the structural model. The first stage evaluates the validity and reliability of the measurement model, and the second evaluates the structural model, which addresses the relationships between the constructs (126, 127).

4.1 Evaluation of the structural model

To evaluate the internal consistency of the measurement model, it is necessary to evaluate the convergent validity and reliability of the construct. Convergent validity is acceptable if the loading of each indicator is greater than 0.7 (123). The composite reliability (CR) should be above 0.70, and the average variance extracted (AVE) should be above 0.5 (126, 127). Cronbach’s alpha coefficient should be greater than 0.7. The factor tends to be similar to CR values when factor-based algorithms are used (128). Table 2 shows that all the loadings of the 27 items of this construct had a value greater than 0.7 (except NL10 and NL11; however, together, they meet the reliability). Likewise, all the constructs’ Alpha and CR values were more significant than 0.80, and all the AVE values were more significant than 0.50. Therefore, the convergent validity of the measurement model was excellent. The skewness and kurtosis of the data distribution are also shown, and it is noted that all values are below +/−1.5, which indicates slight variations from the normal and, consequently, results suitable for carrying out factor analysis (129). Although the method used for statistical analysis in this study does not require compliance with normality, these data provide information about the distribution of the data.

Table 2
www.frontiersin.org

Table 2. Results of the measurement model.

The Fornell–Larker criterion was used to evaluate discriminant validity, so the square root of the AVE of each construct was calculated, which had to be greater than the highest correlation between the construct and other constructs in the model (126, 127). Table 3 shows that all bold diagonal values are more significant than the correlations. Therefore, the measurement model meets all the necessary assumptions to continue evaluating the structural model.

Table 3
www.frontiersin.org

Table 3. Discriminant validity (Fornell–Lacker criterion).

4.2 Evaluation of the structural model

After completing the discriminant, convergent, and reliability tests, the structural model was evaluated using the PLS bootstrapping algorithm with a complete result, a subsample of 5,000, and a one-tailed t-test at a significance level of 0.05%. The outcomes of the structural model with the path coefficient, which ought to be a value between −1 and +1 (111), are displayed in Figure 2.

Figure 2
www.frontiersin.org

Figure 2. Structural model. PBC, perceived behavioral control; NL, nutritional literacy; ATT, attitude; WCHBF, willingness to consume healthy brand food; SN, subjective norms.

Chin (130) suggests values of 0.67, 0.33, and 0.19 as substantial, moderate, and weak measures of R, respectively. In behavioral studies, a value of 0.2 for R2 is acceptable (127, 131). The present work’s R2 coefficients for ATT, SN, PBC, and WCHBF were 0.160, 0.200, 0.273, and 0.403, respectively. That is, the R2 values were acceptable, except for ATT, which is weak. Therefore, the values show that the variables in the present study explain an acceptable percentage of the variance of the WCHB. The overall model fit was measured by the root mean square residual (SRMR), resulting in a value of 0.054 for this indicator, which was below the recommended threshold value of 0.080 (126, 127), thus confirming the model fit.

The hypothesis tests and the evaluation of the path coefficients can be seen in Table 4. The results show that NL has a positive and significant effect on ATT, SN, and CBP, which supports hypotheses H1, H2, and H3. The results show that SN and PBC positively and significantly affect WCHBF, which supports hypotheses H5 and H6. This model indicates that ATT does not impact the WCHBF, so H4 is not accepted.

Table 4
www.frontiersin.org

Table 4. Hypothesis testing.

4.3 Invariance analysis and moderating effects: sex

To determine whether there is a difference in the willingness to consume healthy brand foods between male (34.9%, n = 168) and female (65.1%, n = 314) consumers, it is necessary first to perform the invariance analysis. In Table 5, the MICOM-STEP2 analysis is shown, which allows for the verification that there is no construct difference between men and women; that is, it allows for the verification of the construct invariance between both groups. In this sense, since the p-values are not significant (p > 0.5), it is concluded that there is invariance in the data collection of both groups, both men and women (132), so it is possible to continue with the analysis of the differences between both groups.

Table 5
www.frontiersin.org

Table 5. Invariance analysis.

Using the Multigroup Bootstrap Analysis (Bootstrap MGA), we proceeded to verify the difference in the results of the contrast of the hypotheses between men and women, after performing an analysis of 5,000 samples, the results show that none of the p values is less than 0.05, therefore (132), There is no significant difference between men and women in the contrasts of the hypotheses raised in this study (see Table 6).

Table 6
www.frontiersin.org

Table 6. Bootstrap MGA.

5 Discussions and conclusions

Nutritional literacy is a topic that has gained significant momentum within the scientific community, and research involving health care has aroused a high interest in contributing to a healthy lifestyle (133, 134). Although applying strategies that allow a change in consumer purchasing behavior toward healthy brands is a challenge, there is research that supports the findings of this study by supporting that there is a fundamental element that allows a positive change in consumer attitudes regarding the consumption of foods from healthy brands, this being nutritional literacy (135). Another study that defends the results of this research is based on the health behavior model, which states that human beings can change their habits that involve health as long as they are influenced by support for medical care. When people feel this support, they experience positive results that lead to maintaining good health behavior (135). However, the lack of nutritional information could generate severe health problems since consumers with this deficiency tend to minimize the value of healthy brands; therefore, it is necessary to use assertive measures so that consumers choose to purchase foods from healthy brands (136, 137). In general terms, antecedents that support this investigation have been found. Regardless of acquiring knowledge regarding a daily diet, nutritional literacy triggers an essential influence for a consumer to adopt healthy food consumption habits.

Furthermore, another result of this research proves that nutritional literacy exerts an essential influence on subjective norms for the consumption of healthy foods. Makiabadi (138) establishes that a person’s knowledge shapes the behavior of human life. That is to say, the greater the understanding of information, the more subjective norms point to a better decision when purchasing their food. Another antecedent that gives essential support to these findings is the theory of planned behavior. According to the research, this theory describes eating behavior, where subjective norms are influenced by nutritional literacy (139). Furthermore, it has been identified that the intention to change behaviors linked to nutrition is significantly influenced by subjective norms, with personal perceptions being a response to the consumer’s prior knowledge, translating this fact into further support that affirms that nutritional literacy influences subjective norms (140). In this context, the results of this study are reinforced, specifying that nutritional literacy influences subjective norms, constituting this fact as an opportunity to provide further strength to interventions aimed at promoting the consumption of healthy brand foods.

The third hypothesis that proposed investigating whether nutritional literacy positively influences the perceived behavioral control for consuming healthy brand foods has been rejected. To further support this finding, research has found that in the event of an inadequate state of health, nutritional literacy allows an individual to understand and raise awareness to follow nutritional advice, representing a change in perceived behavior (34, 141). A similar study addressed this behavior in adolescents, stating that this population has greater ease and access to nutritional information when required; thus, when an individual maintains a higher level of nutritional literacy, he or she maintains better control of perceived behavior (141). This means that every individual with a level of nutrition knowledge has a more fantastic option of making informed decisions and ratifying his or her decision, even when external pressures seek to be against healthy food choices. Furthermore, other research that supports this study indicates that nutritional literacy is an indicator that influences behavior and decisions regarding food consumption (142, 143).

Within the findings, it has been identified that attitude does not influence the willingness of consumers to consume healthy branded foods. It is that even though traditionally, it has been considered that attitude plays a determining role in the formation of individual behaviors and consumption decisions (144, 145). Within the study population, the choice of healthy foods is not a determinant in predicting the willingness to consume healthy branded foods, so it is claimed that other factors may have a more marked influence. While Renwick and Smith (146) refer that the attitudes of individuals can address a series of decisions, the same that with repetition becomes a habit, in the case of the Peruvian population, beyond the choice of a healthy brand, other factors intervene in the final decision. Under this context, Perry (147) states that beyond attitudes, knowledge, and skills can influence the final decision.

This study sheds light on the influence of subjective norms on consumers’ willingness to consume healthy branded foods. To better explain this finding, it is necessary to clarify that subjective norms involve “perceived social pressure to perform a particular behavior” (148). In this context, Oktavianus and Bautista (149) support the idea that subjective norms have a high potential to improve an individual’s behavioral intention. For its part, Chen and Fu (150) and Bautista et al. (151) declare that when people harbor bad practices due to some erroneous information, subjective norms are part of an ideal component to correct them. When an individual considers that his environment expects him to perform some specific behavior, the possibility of him opting increases. For addressing the expectations of others. Another result that coincides with the evidence established that the perception of a third person increases the intention for an individual to correct their actions, even more so if they are actions that can correct habits that damage health (152, 153). This means that subjective norms are a point of support since the participation of third parties and the social environment build positive attitudes regarding the consumption of healthy brand foods, which represents forming solid habits regarding a diet from healthy brands. Finally, the results suggest that the influence of nutritional literacy on attitude, subjective norm, and perceived behavioral control is similar between men and women. This indicates that both groups may similarly perceive the importance of nutritional literacy in their purchasing decisions for healthy products.

5.1 Implications

This study has addressed consumer behavior from the planned behavior perspective within the theoretical implications. Thus, the proposed theoretical model is part of a robust conceptual structure that allows a clear understanding of the factors involved in decision shopping. Based on the theory, specific strategies that aim to correct consumer behavior regarding the consumption of healthy foods can be addressed. Statistics make an essential contribution to the literature on these topics. Therefore, more research is needed to evaluate the data obtained in this study more broadly.

Now, the results lead to discovering specific practical implications that have to do with technology. In a digitalized world, allowing consumers to be well-informed and achieve nutritional literacy is not an impossible task. Still, it does require that the media disseminate information about it. On the other hand, it is necessary to increase nutritional literacy to ensure a healthier diet in the population; therefore, new government policies on health must be developed to achieve these standards. When analyzing projects and programs related to nutrition in underdeveloped countries, some of these successful programs include multiple behavioral development initiatives that could last over time but require a progressive lifestyle change. In this sense, the results of this study can be translated into recommendations to improve nutritional literacy, nutrition, and the development of good eating habits to avoid health risks and complications (poor quality of life, malnutrition, dietary intake, diabetes, among others).

On the other hand, the Ministries of Health and Education should show a more significant commitment to cooperating for this national purpose. Some practical courses, such as healthy eating and lifestyle programs, are necessary to educate a new generation with a broader vision. Currently, some private educational institutions, in their attempt to join this movement, could be spreading less-than-appropriate eating practices. For this reason, these issues should be addressed with permanent guidance from experts in the field.

This study deepens knowledge about nutritional literacy and the consumption of foods from healthy brands, which would allow the senior management of any organization, the academic community, those responsible for the Ministry of Health, and other public and private organizations to consider reforming food policies and designing strategies to improve the health of more citizens.

Finally, given that there are no significant differences between men and women, marketing strategies related to promoting healthy products could be designed more unisex. Campaigns that highlight the importance of nutritional literacy could effectively target both sexes.

5.2 Limitations and future research

The size of the sample and the type of sampling (non-probability by convenience) used in the study do not allow the results to be projected onto the composition of the base population. The study sample was observed to have a significant disproportion in terms of civil status, sex, and age range. Due to this, the study’s findings may not be applicable to other populations or contexts since the sample was biased toward specific socio-demographic characteristics. It is suggested that future studies should attempt to obtain more homogeneous samples to avoid this issue.

On the other hand, the study did not consider some essential socio-economic determinants to describe the profile of the participants, such as educational level, health conditions, occupation, and economic income. This fact is part of one of the limitations of this study, so this research could not be generalized. In this way, it is proposed that future research address the differences in perception of the study variables in a different cultural context to measure the gaps. The study was also limited by the time it took to complete the survey, making some prone to abandoning the questionnaire. Furthermore, another limitation of this research is that it has not been considered whether the sample has received or possesses any level of nutritional literacy since the difference between them may be a research bias, so future research should address the level of nutritional literacy to carry out an analysis that measures the strength of influence of one variable on another.

Finally, although there are no significant differences between men and women in the results of this study, it could be beneficial to explore external factors such as culture, advertising, or social events that may influence men and women differently in relation to eating and health. These factors must be considered for future research, in this way to understand the context fully.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Universidad Peruana Unión Ethics Committee. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

RC-T: Conceptualization, Data curation, Funding acquisition, Investigation, Resources, Validation, Visualization, Writing – original draft. EG-S: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. ME-F: Conceptualization, Funding acquisition, Resources, Visualization, Writing – original draft, Writing – review & editing. DM-L: Conceptualization, Funding acquisition, Investigation, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. MV-G: Conceptualization, Funding acquisition, Investigation, Resources, Visualization, Writing – original draft, Writing – review & editing.

Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnut.2024.1353569/full#supplementary-material

References

1. Ruiz, AMP, de Assumpção, D, Malta, DC, and Francisco, PMSB. Consumption of healthy food and ultra-processed products: comparison between pregnant and non-pregnant women, vigitel 2018. Revista Brasileira de Saude Materno Infantil. (2021) 21:511–9. doi: 10.1590/1806-93042021000200009

Crossref Full Text | Google Scholar

2. Rafacz, SD. Healthy eating: approaching the selection, preparation, and consumption of healthy food as choice behavior. Perspect Behav Sci. (2019) 42:647–74. doi: 10.1007/s40614-018-00190-y

PubMed Abstract | Crossref Full Text | Google Scholar

3. Formoso, G, Pipino, C, Antonia Baldassarre, MP, Del Boccio, P, Zucchelli, M, D’Alessandro, N, et al. An Italian innovative small-scale approach to promote the conscious consumption of healthy food. Appl Sci. (2020) 10:1–14. doi: 10.3390/app10165678

Crossref Full Text | Google Scholar

4. Nguyen, T, de Brauw, A, van den Berg, M, and Do, HTP. Testing methods to increase consumption of healthy foods evidence from a school-based field experiment in Viet Nam. Food Policy. (2021) 101:102047–37. doi: 10.1016/j.foodpol.2021.102047

Crossref Full Text | Google Scholar

5. Savelli, E, and Murmura, F. The intention to consume healthy food among older gen-Z: examining antecedents and mediators. Food Qual Prefer. (2023) 105:104788–17. doi: 10.1016/j.foodqual.2022.104788

Crossref Full Text | Google Scholar

6. Hopwood, CJ, Bleidorn, W, Schwaba, T, and Chen, S. Health, environmental, and animal rights motives for vegetarian eating. PLoS One. (2020) 15:e0230609–20. doi: 10.1371/journal.pone.0230609

PubMed Abstract | Crossref Full Text | Google Scholar

7. Sorić, T, Brodić, I, Mertens, E, Sagastume, D, Dolanc, I, Jonjić, A, et al. Evaluation of the food choice motives before and during the COVID-19 pandemic: a cross-sectional study of 1232 adults from Croatia. Nutrients. (2021) 13:1–18. doi: 10.3390/nu13093165

PubMed Abstract | Crossref Full Text | Google Scholar

8. Zhang, R, Yu, X, Yu, Y, Guo, D, He, H, Zhao, Y, et al. Family food environments and their association with primary and secondary students’ food consumption in Beijing, China: a cross-sectional study. Nutrients. (2022) 14:1–16. doi: 10.3390/nu14091970

PubMed Abstract | Crossref Full Text | Google Scholar

9. Dube, S, Tsvakirai, CZ, Mabuza, LM, and Makgopa, T. The influence of cognitive bias on the use of menu nutritional information among consumers in Mahikeng city. South Africa Appl Food Res. (2023) 3:100348–6. doi: 10.1016/j.afres.2023.100348

Crossref Full Text | Google Scholar

10. Wanselius, J, Larsson, C, Berg, C, Öhrvik, V, Lindroos, AK, and Lissner, L. Consumption of foods with the keyhole front-of-pack nutrition label: potential impact on energy and nutrient intakes of Swedish adolescents. Public Health Nutr. (2022) 25:3279–90. doi: 10.1017/S1368980022002178

PubMed Abstract | Crossref Full Text | Google Scholar

11. Foxall, G, and Bhate, S. Cognitive style and personal involvement as explicators of innovative purchasing of healthy food brands. Eur J Mark. (1993) 27:5–16. doi: 10.1108/03090569310026376

Crossref Full Text | Google Scholar

12. Folkvord, F, Roes, E, and Bevelander, K. Promoting healthy foods in the new digital era on Instagram: an experimental study on the effect of a popular real versus fictitious fit influencer on brand attitude and purchase intentions. BMC Public Health. (2020) 20:1677–8. doi: 10.1186/s12889-020-09779-y

PubMed Abstract | Crossref Full Text | Google Scholar

13. Cruwys, T, Bevelander, KE, and Hermans, RCJ. Social modeling of eating: a review of when and why social influence affects food intake and choice. Appetite. (2015) 86:3–18. doi: 10.1016/j.appet.2014.08.035

PubMed Abstract | Crossref Full Text | Google Scholar

14. Zanella, CP, Sampaio Ha De, C, JWO, DL, and TMM, M. Cultural adaptation and content validity evidence of the nutritional literacy scale Brazilian version. Rev Bras Enferm. (2022) 75:1:e20210657. doi: 10.1590/0034-7167-2021-0657

PubMed Abstract | Crossref Full Text | Google Scholar

15. Diamond, JJ. Development of a reliable and construct valid measure of nutritional literacy in adults. Nutr J. (2007) 6:1–4. doi: 10.1186/1475-2891-6-5

PubMed Abstract | Crossref Full Text | Google Scholar

16. Maleki, M, Payandeh, A, Seraji, M, Taherkhani, M, and Bolouri, A. Nutritional knowledge, family income, and blood sugar level among diabetic patients. Int J Publ Health Sci. (2023) 12:1064–9. doi: 10.11591/ijphs.v12i3.22234

Crossref Full Text | Google Scholar

17. Guttersrud, O, Dalane, JO, and Pettersen, S. Improving measurement in nutrition literacy research using Rasch modelling: examining construct validity of stage-specific critical nutrition literacy scales. Public Health Nutr. (2014) 17:877–83. doi: 10.1017/S1368980013000530

PubMed Abstract | Crossref Full Text | Google Scholar

18. McNamara, J, Kunicki, ZJ, Neptune, L, Parsons, K, and Byrd-Bredbenner, C. Development and validation of the young adult nutrition literacy tool. J Nutr Educ Behav. (2022) 54:691–701. doi: 10.1016/j.jneb.2022.01.011

PubMed Abstract | Crossref Full Text | Google Scholar

19. Tudoran, AA, Scholderer, J, and Brunsø, K. Regulatory focus, self-efficacy and outcome expectations as drivers of motivation to consume healthy food products. Appetite. (2012) 59:243–51. doi: 10.1016/j.appet.2012.05.002

PubMed Abstract | Crossref Full Text | Google Scholar

20. Salleh, HS, and Noor, NAM. Moderating effect of self-efficacy on the relationship between consumer attitude and willingness to consume healthy food. J Sustain Sci Manag. (2018) 75:33–50.

Google Scholar

21. Schubert, E, and Bode, S. Positive emotions and their upregulation increase willingness to consume healthy foods. Appetite. (2023) 181:106420–16. doi: 10.1016/j.appet.2022.106420

PubMed Abstract | Crossref Full Text | Google Scholar

22. Dangaiso, P. Extending the theory of planned behavior to predict organic food adoption behavior and perceived consumer longevity in subsistence markets: a post-peak COVID-19 perspective. Cogent Psychol. (2023) 10:1–18. doi: 10.1080/23311908.2023.2258677

Crossref Full Text | Google Scholar

23. Haubenstricker, JE, Lee, JW, Segovia-Siapco, G, and Medina, E. The theory of planned behavior and dietary behaviors in competitive women bodybuilders. BMC Public Health. (2023) 23:1716–4. doi: 10.1186/s12889-023-16568-w

PubMed Abstract | Crossref Full Text | Google Scholar

24. Phipps, DJ, Hagger, MS, and Hamilton, K. Predicting sugar intake using an extended theory of planned behavior in a sample of adolescents: the role of habit and self-control. Brain Behav. (2023) 13:1–8. doi: 10.1002/brb3.3200

PubMed Abstract | Crossref Full Text | Google Scholar

25. Bélanger, M, Dugas, C, Perron, J, St-Yves, A, Rancourt-Bouchard, M, John Weisnagel, S, et al. Intention to adopt a healthy diet among women with and without a history of gestational diabetes: constructs and beliefs from the theory of planned behavior. Prev Med Rep. (2023) 35:102328. doi: 10.1016/j.pmedr.2023.102328

PubMed Abstract | Crossref Full Text | Google Scholar

26. Sajjad, M, Bhatti, A, Hill, B, and Al-Omari, B. Using the theory of planned behavior to predict factors influencing fast-food consumption among college students. BMC Public Health. (2023) 23:987–13. doi: 10.1186/s12889-023-15923-1

PubMed Abstract | Crossref Full Text | Google Scholar

27. Mohammadkhah, F, Amirhajelu, RM, Bakhtiar, M, Salemi, SA, Kevenjan, M, and Jeihooni, AK. The effect of training intervention based on the theory of planned behavior on oral and dental health behaviors in pregnant women. BMC Oral Health. (2023) 23:521–9. doi: 10.1186/s12903-023-03239-w

PubMed Abstract | Crossref Full Text | Google Scholar

28. Hamtaeigashti, S, Shamsi, M, Sahraian, MA, Soltani, R, and Almasi-Hashiani, A. Effect of an educational intervention based on the theory of planned behavior on improving medication adherence in patients with multiple sclerosis treated with injectable disease-modifying drugs: randomized controlled trial. BMC Public Health. (2023) 23:999–13. doi: 10.1186/s12889-023-15910-6

PubMed Abstract | Crossref Full Text | Google Scholar

29. Mahmoodi, MR, Shafian, S, and Alinaghizade, MS. The effectiveness of teaching complementary and alternative medicine based on the components of theory of planned behavior on nutrition students: multicenter research study. BMC Med Educ. (2023) 23:253–9. doi: 10.1186/s12909-023-04239-8

PubMed Abstract | Crossref Full Text | Google Scholar

30. Savari, M, Damaneh, HE, Damaneh, HE, and Cotton, M. Integrating the norm activation model and theory of planned behaviour to investigate farmer pro-environmental behavioural intention. Sci Rep. (2023) 13:5584–14. doi: 10.1038/s41598-023-32831-x

PubMed Abstract | Crossref Full Text | Google Scholar

31. Malik, A, Mahmood, K, and Islam, T. Understanding the Facebook users’ behavior towards COVID-19 information sharing by integrating the theory of planned behavior and gratifications. Inf Dev. (2023) 39:750–63. doi: 10.1177/02666669211049383

Crossref Full Text | Google Scholar

32. McDermott, MS, Oliver, M, Simnadis, T, Beck, EJ, Coltman, T, Iverson, D, et al. The theory of planned behaviour and dietary patterns: a systematic review and meta-analysis. Prev Med (Baltim). (2015) 81:150–6. doi: 10.1016/j.ypmed.2015.08.020

PubMed Abstract | Crossref Full Text | Google Scholar

33. Silva, P, Araújo, R, Lopes, F, and Ray, S. Nutrition and food literacy: framing the challenges to health communication. Nutrients. (2023) 15:4708. doi: 10.3390/nu15224708

PubMed Abstract | Crossref Full Text | Google Scholar

34. Ayer, Ç, and Ergin, A. Status of nutritional literacy in adolescents in the semi-rural area in Turkey and related factors. Public Health Nutr. (2021) 24:3870–8. doi: 10.1017/S1368980021002366

PubMed Abstract | Crossref Full Text | Google Scholar

35. Truman, E, Bischoff, M, and Elliott, C. Which literacy for health promotion: health, food, nutrition or media? Health Promot Int. (2020) 35:432–44. doi: 10.1093/heapro/daz007

Crossref Full Text | Google Scholar

36. Fordyce-Voorham, S. Identification of essential food skills for skill-based healthful eating programs in secondary schools. J Nutr Educ Behav. (2011) 43:116–22. doi: 10.1016/j.jneb.2009.12.002

PubMed Abstract | Crossref Full Text | Google Scholar

37. Liao, L-L, and Lai, I-J. Construction of nutrition literacy indicators for college students in Taiwan: a Delphi consensus study. J Nutr Educ Behav. (2017) 49:734–742.e1. doi: 10.1016/j.jneb.2017.05.351

PubMed Abstract | Crossref Full Text | Google Scholar

38. Vettori, V, Lorini, C, Milani, C, and Bonaccorsi, G. Towards the implementation of a conceptual framework of food and nutrition literacy: providing healthy eating for the population. Int J Environ Res Public Health. (2019) 16:5041. doi: 10.3390/ijerph16245041

PubMed Abstract | Crossref Full Text | Google Scholar

39. Sarkis Lb Da, S, Teruel-Camargo, J, Gibbs, HD, Nakano, EY, Ginani, VC, and De Aguiar, AS. The nutrition literacy assessment instrument for Brazilians, NLit-Br: an exploratory cross-cultural validity study. Nutrients. (2022) 14:4914. doi: 10.3390/nu14224914

PubMed Abstract | Crossref Full Text | Google Scholar

40. CDS, C, Camargo, JT, Zandonadi, RP, Nakano, EY, and Ginani, VC. Nutrition literacy level in Bank employees: the case of a large Brazilian company. Nutrients. (2023) 15:2360. doi: 10.3390/nu15102360

PubMed Abstract | Crossref Full Text | Google Scholar

41. Grunert, KG, Wills, JM, and Fernández-Celemín, L. Nutrition knowledge, and use and understanding of nutrition information on food labels among consumers in the UK. Appetite. (2010) 55:177–89. doi: 10.1016/j.appet.2010.05.045

PubMed Abstract | Crossref Full Text | Google Scholar

42. Schnettler, B, Miranda, H, Lobos, G, Sepulveda, J, Orellana, L, Mora, M, et al. Willingness to purchase functional foods according to their benefits. Br Food J. (2015) 117:1453–73. doi: 10.1108/BFJ-07-2014-0273

Crossref Full Text | Google Scholar

43. Malloy-Weir, L, and Cooper, M. Health literacy, literacy, numeracy and nutrition label understanding and use: a scoping review of the literature. J Hum Nutr Diet. (2017) 30:309–25. doi: 10.1111/jhn.12428

PubMed Abstract | Crossref Full Text | Google Scholar

44. Cummings, CA, and Obel-Omia, C. Healthy reading: teaching strategies for integrating health and literacy education. Child Educ. (2016) 92:455–64. doi: 10.1080/00094056.2016.1251794

Crossref Full Text | Google Scholar

45. Larson, N, and Story, M. A review of environmental influences on food choices. Ann Behav Med. (2009) 38:56–73. doi: 10.1007/s12160-009-9120-9

Crossref Full Text | Google Scholar

46. Ko, LK, Enzler, C, Perry, CK, Rodriguez, E, Mariscal, N, Linde, S, et al. Food availability and food access in rural agricultural communities: use of mixed methods. BMC Public Health. (2018) 18:634. doi: 10.1186/s12889-018-5547-x

PubMed Abstract | Crossref Full Text | Google Scholar

47. Hieke, S, and Taylor, C. A critical review of the literature on nutritional labeling. J Consum Aff. (2012) 46:120–56. doi: 10.1111/j.1745-6606.2011.01219.x

Crossref Full Text | Google Scholar

48. Barreiro-Hurlé, J, Gracia, A, and de-Magistris, T. Does nutrition information on food products lead to healthier food choices? Food Policy. (2010) 35:221–9. doi: 10.1016/j.foodpol.2009.12.006

Crossref Full Text | Google Scholar

49. Priya, KM, and Alur, S. Analyzing consumer behaviour towards food and nutrition labeling: a comprehensive review. Heliyon. (2023) 9:e19401. doi: 10.1016/j.heliyon.2023.e19401

PubMed Abstract | Crossref Full Text | Google Scholar

50. La Vieille, S, Hourihane, JO, and Baumert, JL. Precautionary allergen labeling: what advice is available for health care professionals, allergists, and allergic consumers? J Allergy Clin Immunol Pract. (2023) 11:977–85. doi: 10.1016/j.jaip.2022.12.042

PubMed Abstract | Crossref Full Text | Google Scholar

51. Predanócyová, K, Šedík, P, and Horská, E. Exploring consumer behavior and attitudes toward healthy food in Slovakia. Br Food J. (2023) 125:2053–69. doi: 10.1108/BFJ-06-2022-0517

Crossref Full Text | Google Scholar

52. Ajzen, I. The theory of planned behaviour is alive and well, and not ready to retire: a commentary on Sniehotta, Presseau, and Araújo-Soares. Health Psychol Rev. (2015) 9:131–7. doi: 10.1080/17437199.2014.883474

PubMed Abstract | Crossref Full Text | Google Scholar

53. Eyinade, GA, Mushunje, A, and Yusuf, SFG. The willingness to consume organic food: a review. Food Agric Immunol. (2021) 32:78–104. doi: 10.1080/09540105.2021.1874885

Crossref Full Text | Google Scholar

54. Mancini, P, Marchini, A, and Simeone, M. Which are the sustainable attributes affecting the real consumption behaviour? Consumer understanding and choices. Br Food J. (2017) 119:1839–53. doi: 10.1108/BFJ-11-2016-0574

Crossref Full Text | Google Scholar

55. Tan, BC, Lau, TC, Sarwar, A, and Khan, N. The effects of consumer consciousness, food safety concern and healthy lifestyle on attitudes toward eating green. Br Food J. (2022) 124:1187–203. doi: 10.1108/BFJ-01-2021-0005

Crossref Full Text | Google Scholar

56. Ayanwale, AB, Alimi, T, and Ayanbimipe, MA. The influence of advertising on consumer brand preference. J Soc Sci. (2005) 10:9–16. doi: 10.1080/09718923.2005.11892453

Crossref Full Text | Google Scholar

57. Feldmann, C, and Hamm, U. Consumers’ perceptions and preferences for local food: a review. Food Qual Prefer. (2015) 40:152–64. doi: 10.1016/j.foodqual.2014.09.014

Crossref Full Text | Google Scholar

58. Plasek, B, Lakner, Z, and Temesi, Á. Factors that influence the perceived healthiness of food—review. Nutrients. (2020) 12:1881. doi: 10.3390/nu12061881

PubMed Abstract | Crossref Full Text | Google Scholar

59. Krystallis, A, and Chryssohoidis, G. Consumers’ willingness to pay for organic food. Br Food J. (2005) 107:320–43. doi: 10.1108/00070700510596901

Crossref Full Text | Google Scholar

60. Kozup, JC, Creyer, EH, and Burton, S. Making healthful food choices: the influence of health claims and nutrition information on consumers’ evaluations of packaged food products and restaurant menu items. J Mark. (2003) 67:19–34. doi: 10.1509/jmkg.67.2.19.18608

Crossref Full Text | Google Scholar

61. Barbu, A, Ion, VA, Frîncu, M, Defta, N, Lagunovschi-Luchian, V, and Bădulescu, LA. Organic vegetable chips: exploring Romanian consumers’ preferences in relation to socio-demographic factors. Food Secur. (2023) 12:3374. doi: 10.3390/foods12183374

PubMed Abstract | Crossref Full Text | Google Scholar

62. Akter, S, Ali, S, Fekete-Farkas, M, Fogarassy, C, and Lakner, Z. Why organic food? Factors influence the organic food purchase intension in an emerging country (study from northern part of Bangladesh). Resources. (2023) 12:e5. doi: 10.3390/resources12010005

Crossref Full Text | Google Scholar

63. Guthrie, J, Mancino, L, and Lin, CTJ. Nudging consumers toward better food choices: policy approaches to changing food consumption behaviors. Psychol Mark. (2015) 32:501–11. doi: 10.1002/mar.20795

Crossref Full Text | Google Scholar

64. Velema, E, Vyth, EL, Hoekstra, T, and Steenhuis, IHM. Nudging and social marketing techniques encourage employees to make healthier food choices: a randomized controlled trial in 30 worksite cafeterias in the Netherlands. Am J Clin Nutr. (2018) 107:236–46. doi: 10.1093/ajcn/nqx045

PubMed Abstract | Crossref Full Text | Google Scholar

65. Gonçalves, D, Coelho, P, Martinez, LF, and Monteiro, P. Nudging consumers toward healthier food choices: a field study on the effect of social norms. Sustainability. (2021) 13:1–14. doi: 10.3390/su13041660

Crossref Full Text | Google Scholar

66. Houghtaling, B, Serrano, EL, Kraak, VI, Harden, SM, Davis, GC, and Misyak, SA. A systematic review of factors that influence food store owner and manager decision making and ability or willingness to use choice architecture and marketing mix strategies to encourage healthy consumer purchases in the United States, 2005–2017. Int J Behav Nutr Phys Act. (2019) 16:1–14. doi: 10.1186/s12966-019-0767-8

PubMed Abstract | Crossref Full Text | Google Scholar

67. Wansink, B. Change their choice! Changing behavior using the CAN approach and activism research. Psychol Mark. (2015) 32:486–500. doi: 10.1002/mar.20794

Crossref Full Text | Google Scholar

68. Wilson, AL, Buckley, E, Buckley, JD, and Bogomolova, S. Nudging healthier food and beverage choices through salience and priming. Evidence from a systematic review. Food Qual Prefer. (2016) 51:47–64. doi: 10.1016/j.foodqual.2016.02.009

Crossref Full Text | Google Scholar

69. Ryan, M. The ethics of dietary apps: technology, health, and the capability approach. Technol Soc. (2022) 68:101873–12. doi: 10.1016/j.techsoc.2022.101873

Crossref Full Text | Google Scholar

70. Ajzen, I. The theory of planned behavior: frequently asked questions. Hum Behav Emerg Technol. (2020) 2:314–24. doi: 10.1002/hbe2.195

Crossref Full Text | Google Scholar

71. Greaves, M, Zibarras, LD, and Stride, C. Using the theory of planned behavior to explore environmental behavioral intentions in the workplace. J Environ Psychol. (2013) 34:109–20. doi: 10.1016/j.jenvp.2013.02.003

Crossref Full Text | Google Scholar

72. McEachan, RRC, Conner, M, Taylor, NJ, and Lawton, RJ. Prospective prediction of health-related behaviours with the theory of planned behaviour: a meta-analysis. Health Psychol Rev. (2011) 5:97–144. doi: 10.1080/17437199.2010.521684

Crossref Full Text | Google Scholar

73. Valenzuela-Fernández, L, Escobar-Farfán, M, Guerra-Velásquez, M, and García-Salirrosas, EE. COVID-19 effects on environmentally responsible behavior: a social impact perspective from Latin American countries. Int J Environ Res Public Health. (2023) 20:3330. doi: 10.3390/ijerph20043330

PubMed Abstract | Crossref Full Text | Google Scholar

74. Ajzen, I. The theory of planned behavior. Organ Behav Hum Decis Process. (1991) 50:179–211. doi: 10.1016/0749-5978(91)90020-T

Crossref Full Text | Google Scholar

75. Ajzen, I. Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior 1. J Appl Soc Psychol. (2002) 32:665–83. doi: 10.1111/j.1559-1816.2002.tb00236.x

Crossref Full Text | Google Scholar

76. Ajzen, I, and Madden, TJ. Prediction of goal-directed behavior: attitudes, intentions, and perceived behavioral control. J Exp Soc Psychol. (1986) 22:453–74. doi: 10.1016/0022-1031(86)90045-4

Crossref Full Text | Google Scholar

77. Bong Ko, S, and Jin, B. Predictors of purchase intention toward green apparel products. J Fashion Marketing Manag. (2017) 21:70–87. doi: 10.1108/JFMM-07-2014-0057

Crossref Full Text | Google Scholar

78. Finlay, NC, Peacock, CL, Hudson-Edwards, KA, and Johnson, KL. Characteristics and mechanisms of Pb(II) sorption onto Fe-rich waste water treatment residue (WTR): a potential sustainable Pb immobilisation technology for soils. J Hazard Mater. (2021) 402:123433. doi: 10.1016/j.jhazmat.2020.123433

PubMed Abstract | Crossref Full Text | Google Scholar

79. Madden, TJ, Ellen, PS, and Ajzen, I. A comparison of the theory of planned behavior and the theory of reasoned action. Personal Soc Psychol Bull. (1992) 18:3–9. doi: 10.1177/0146167292181001

Crossref Full Text | Google Scholar

80. Shin, YH, and Hancer, M. The role of attitude, subjective norm, perceived behavioral control, and moral norm in the intention to purchase local food products. J Foodserv Bus Res. (2016) 19:338–51. doi: 10.1080/15378020.2016.1181506

Crossref Full Text | Google Scholar

81. Ramdan, MR, Zainol, Z, Yahaya, R, Habidin, NF, and Osman, J. The effect of nutrition label literacy and attitude towards nutrition label on healthy food choice among consumer in Malaysia. Int J Acad Res Business Soc Sci. (2018) 8:e3976. doi: 10.6007/IJARBSS/v8-i2/3976

Crossref Full Text | Google Scholar

82. Tian, Y, Yoo, JH, and Zhou, H. To read or not to read: an extension of the theory of planned behaviour to food label use. Int J Consum Stud. (2022) 46:984–93. doi: 10.1111/ijcs.12741

Crossref Full Text | Google Scholar

83. Miller, LMS, and Cassady, DL. The effects of nutrition knowledge on food label use. A review of the literature. Appetite. (2015) 92:207–16. doi: 10.1016/j.appet.2015.05.029

PubMed Abstract | Crossref Full Text | Google Scholar

84. Worsley, A. Nutrition knowledge and food consumption: can nutrition knowledge change food behaviour? Asia Pac J Clin Nutr. (2002) 11:e7. doi: 10.1046/j.1440-6047.11.supp3.7.x

Crossref Full Text | Google Scholar

85. Chen, P-J, and Antonelli, M. Conceptual models of food choice: influential factors related to foods, individual differences, and society. Food Secur. (2020) 9:1898. doi: 10.3390/foods9121898

PubMed Abstract | Crossref Full Text | Google Scholar

86. Sobaih, AEE, and Abdelaziz, AS. The impact of nutrition labelling on customer buying intention and behaviours in fast food operations: some implications for public health. Int J Environ Res Public Health. (2022) 19:7122. doi: 10.3390/ijerph19127122

PubMed Abstract | Crossref Full Text | Google Scholar

87. Sousa, IC, Mucinhato, RMD, Prates, CB, Zanin, LM, da Cunha, DT, Capriles, VD, et al. Do Brazilian consumers intend to use food labels to make healthy food choices? An assessment before the front-of-package labelling policy. Food Res Int. (2023) 172:113107. doi: 10.1016/j.foodres.2023.113107

PubMed Abstract | Crossref Full Text | Google Scholar

88. Trieste, L, Bazzani, A, Amato, A, Faraguna, U, and Turchetti, G. Food literacy and food choice—a survey-based psychometric profiling of consumer behaviour. Br Food J. (2021) 123:124–41. doi: 10.1108/BFJ-09-2020-0845

Crossref Full Text | Google Scholar

89. Begley, A, Paynter, E, Butcher, L, Bobongie, V, and Dhaliwal, SS. Identifying who improves or maintains their food literacy behaviours after completing an adult program. Int J Environ Res Public Health. (2020) 17:4462. doi: 10.3390/ijerph17124462

PubMed Abstract | Crossref Full Text | Google Scholar

90. Aliaga-Ortega, L, Adasme-Berríos, C, Méndez, C, Soto, C, and Schnettler, B. Processed food choice based on the theory of planned behavior in the context of nutritional warning labels. Br Food J. (2019) 121:3266–80. doi: 10.1108/BFJ-10-2018-0695

Crossref Full Text | Google Scholar

91. Scalco, A, Noventa, S, Sartori, R, and Ceschi, A. Predicting organic food consumption: a meta-analytic structural equation model based on the theory of planned behavior. Appetite. (2017) 112:235–48. doi: 10.1016/j.appet.2017.02.007

PubMed Abstract | Crossref Full Text | Google Scholar

92. Ahmed, N, Li, C, Khan, A, Qalati, SA, Naz, S, and Rana, F. Purchase intention toward organic food among young consumers using theory of planned behavior: role of environmental concerns and environmental awareness. J Environ Plan Manag. (2021) 64:796–822. doi: 10.1080/09640568.2020.1785404

Crossref Full Text | Google Scholar

93. Lim, C-C, and Goh, Y-N. Investigating the purchase intention toward healthy drinks among urban consumers in Malaysia. J Foodserv Bus Res. (2019) 22:286–302. doi: 10.1080/15378020.2019.1603043

Crossref Full Text | Google Scholar

94. Canova, L, Bobbio, A, and Manganelli, AM. Buying organic food products: the role of trust in the theory of planned behavior. Front Psychol. (2020) 11:575820. doi: 10.3389/fpsyg.2020.575820

PubMed Abstract | Crossref Full Text | Google Scholar

95. Sparks, P, and Shepherd, R. Self-identity and the theory of planned behavior: assessing the role of identification with green consumerism. Soc Psychol Q. (1992) 55:388. doi: 10.2307/2786955

Crossref Full Text | Google Scholar

96. Ham, M, Jeger, M, and Frajman, IA. The role of subjective norms in forming the intention to purchase green food. Econ Res Ekonomska Istraživanja. (2015) 28:738–48. doi: 10.1080/1331677X.2015.1083875

Crossref Full Text | Google Scholar

97. Agnoli, L, Capitello, R, and Begalli, D. Behind intention and behaviour: factors influencing wine consumption in a novice market. Br Food J. (2016) 118:660–78. doi: 10.1108/BFJ-05-2015-0181

Crossref Full Text | Google Scholar

98. Küster-Boluda, I, and Vidal-Capilla, I. Consumer attitudes in the election of functional foods. Spanish J Marketing. (2017) 21:65–79. doi: 10.1016/j.sjme.2017.05.002

Crossref Full Text | Google Scholar

99. Vermeir, I, and Verbeke, W. Sustainable food consumption among young adults in Belgium: theory of planned behaviour and the role of confidence and values. Ecol Econ. (2008) 64:542–53. doi: 10.1016/j.ecolecon.2007.03.007

Crossref Full Text | Google Scholar

100. Quevedo-Silva, F, Freire, O, Lima-Filho, DO, Brandão, MM, Isabella, G, and Moreira, LB. Intentions to purchase food through the internet: developing and testing a model. Br Food J. (2016) 118:572–87. doi: 10.1108/BFJ-09-2015-0305

Crossref Full Text | Google Scholar

101. Roseman, MG, Hoon Kim, Y, and Zhang, Y. A study of consumers’ intention to purchase ethnic food when eating at restaurants. J Foodserv Bus Res. (2013) 16:298–312. doi: 10.1080/15378020.2013.810529

Crossref Full Text | Google Scholar

102. García-Salirrosas, EE, Niño-de-Guzmán, JC, Gómez-Bayona, L, and Escobar-Farfán, M. Environmentally responsible purchase intention in Pacific Alliance countries: geographic and gender evidence in the context of the COVID-19 pandemic. Behav Sci. (2023) 13:221. doi: 10.3390/bs13030221

PubMed Abstract | Crossref Full Text | Google Scholar

103. García-Salirrosas, EE, Escobar-Farfán, M, Gómez-Bayona, L, Moreno-López, G, Valencia-Arias, A, and Gallardo-Canales, R. Influence of environmental awareness on the willingness to pay for green products: an analysis under the application of the theory of planned behavior in the Peruvian market. Front Psychol. (2024) 14:282383. doi: 10.3389/fpsyg.2023.1282383

PubMed Abstract | Crossref Full Text | Google Scholar

104. Valenzuela-Fernández, L, Guerra-Velásquez, M, Escobar-Farfán, M, and García-Salirrosas, EE. Influence of COVID-19 on environmental awareness, sustainable consumption, and social responsibility in Latin American countries. Sustain For. (2022) 14:12754. doi: 10.3390/su141912754

Crossref Full Text | Google Scholar

105. Khan, Y, Hameed, I, and Akram, U. What drives attitude, purchase intention and consumer buying behavior toward organic food? A self-determination theory and theory of planned behavior perspective. Br Food J. (2023) 125:2572–87. doi: 10.1108/BFJ-07-2022-0564

Crossref Full Text | Google Scholar

106. Chen, M-F. Consumer attitudes and purchase intentions in relation to organic foods in Taiwan: moderating effects of food-related personality traits. Food Qual Prefer. (2007) 18:1008–21. doi: 10.1016/j.foodqual.2007.04.004

Crossref Full Text | Google Scholar

107. Dean, M, Raats, MM, and Shepherd, R. Moral concerns and consumer choice of fresh and processed organic foods 1. J Appl Soc Psychol. (2008) 38:2088–107. doi: 10.1111/j.1559-1816.2008.00382.x

Crossref Full Text | Google Scholar

108. Teng, C-C, and Wang, Y-M. Decisional factors driving organic food consumption. Br Food J. (2015) 117:1066–81. doi: 10.1108/BFJ-12-2013-0361

Crossref Full Text | Google Scholar

109. Hill, H, and Lynchehaun, F. Organic milk: attitudes and consumption patterns. Br Food J. (2002) 104:526–42. doi: 10.1108/00070700210434570

Crossref Full Text | Google Scholar

110. Giampietri, E, Finco, A, and Del Giudice, T. Exploring consumers’ behaviour towards short food supply chains. Br Food J. (2016) 118:618–31. doi: 10.1108/BFJ-04-2015-0168

Crossref Full Text | Google Scholar

111. Hair, J, Page, M, and Brunsveld, N. Essentials of business research methods. 4th edn, New York, (2019), 1–507

Google Scholar

112. Frías-Navarro, D, and Soler, MP. Prácticas del Análisis Factorial Exploratorio (AFE) en la investigación sobre conducta del consumidor y marketing. Suma Psicológica. (2012) 19:47–58.

Google Scholar

113. Hair, JF, Anderson, RE, Tatham, RL, and Black, WC. Multivariate data analysis. 5th ed. Hoboken, NJ, USA: Prentice Hall (1998).

Google Scholar

114. INEI, Instituto Nacional de Estadística e Informática, (2018). Available at: https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1544/00TOMO_01.pdf

Google Scholar

115. Orea-Giner, A, and Fusté-Forné, F. The way we live, the way we travel: generation Z and sustainable consumption in food tourism experiences. Br Food J. (2023) 125:330–51. doi: 10.1108/BFJ-11-2022-0962

Crossref Full Text | Google Scholar

116. Kamenidou, IC, Mamalis, SA, Pavlidis, S, and Bara, EZG. Segmenting the generation Z cohort university students based on sustainable food consumption behavior: a preliminary study. Sustainability. (2019) 11:1–22. doi: 10.3390/su11030837

Crossref Full Text | Google Scholar

117. Su, CH, Tsai, CH, Chen, MH, and Lv, WQ. U.S. sustainable food market generation Z consumer segments. Sustainability. (2019) 11:1–14. doi: 10.3390/su11133607

Crossref Full Text | Google Scholar

118. Predanócyová, K, Árvay, J, and Šnirc, M. Exploring consumer behavior and preferences towards edible mushrooms in Slovakia. Food Secur. (2023) 12:1–18. doi: 10.3390/foods12030657

PubMed Abstract | Crossref Full Text | Google Scholar

119. Hair, J, Black, W, Babin, B, and Anderson, R. Multivariate data analysis. 7th Edn. Pearson Prentice Hall (2013). 758 p.

Google Scholar

120. Vrinten, J, Van Royen, K, Pabian, S, De Backer, C, and Matthys, C. Development and validation of a short nutrition literacy scale for young adults. Front Nutr. (2023) 10:1–10. doi: 10.3389/fnut.2023.1008971

PubMed Abstract | Crossref Full Text | Google Scholar

121. Kumar, A, Prakash, G, and Kumar, G. Does environmentally responsible purchase intention matter for consumers? A predictive sustainable model developed through an empirical study. J Retail Consum Serv. (2021) 58:102270–9. doi: 10.1016/j.jretconser.2020.102270

Crossref Full Text | Google Scholar

122. Hair, JF, Hult, GTM, Ringle, CM, Sarstedt, M, Castillo Apraiz, J, Cepeda Carrión, GA, et al. Manual de partial least squares structural equation modeling (PLS-SEM). Terrassa, Barcelona: OmniaScience Scholar (2019).

Google Scholar

123. Hair, JF, Ringle, CM, and Sarstedt, M. PLS-SEM: indeed a silver bullet. J Mark Theory Pract. (2011) 19:139–52. doi: 10.2753/MTP1069-6679190202

Crossref Full Text | Google Scholar

124. Bhutto, MH, Tariq, B, Azhar, S, Ahmed, K, Khuwaja, FM, and Han, H. Predicting consumer purchase intention toward hybrid vehicles: testing the moderating role of price sensitivity. Eur Bus Rev. (2022) 34:62–84. doi: 10.1108/EBR-10-2019-0274

Crossref Full Text | Google Scholar

125. Gaskin, J., Data prep, Gaskination’s StatWiki. (2021), Available at: http://statwiki.gaskination.com, (Accessed February 29, 2024)

Google Scholar

126. Chin, WW. How to write up and report PLS analyses, Handbook of partial least squares. (2010). 655–690

Google Scholar

127. Hair, F, Sarstedt, M, Hopkins, LG, and Kuppelwieser, V. Partial least squares structural equation modeling (PLS-SEM). Eur Bus Rev. (2014) 26:106–21. doi: 10.1108/EBR-10-2013-0128

Crossref Full Text | Google Scholar

128. Kock, N. A note on how to conduct a factor-based PLS-SEM analysis. Int J e-Collaboration. (2015) 11:1–9. doi: 10.4018/ijec.2015070101

Crossref Full Text | Google Scholar

129. Pérez, E, and Medrano, L. Análisis Factorial Exploratorio: bases Conceptuales y Metodológicas Artículo de Revisión. Rev Argent Cienc Comport. (2010) 2:58–66.

Google Scholar

130. Chin, MG. The partial least squares approach to structural formula modeling. Adv Hosp Leisure. (1998) 8:295–336.

Google Scholar

131. Kock, N. WarpPLS 4.0 user manual. Laredo, TX: ScriptWarp Systems (2013). 94 p.

Google Scholar

132. Meredith, W. Measurement invariance, factor analysis and factorial invariance. Psychometrika. (1993) 58:525–43. doi: 10.1007/BF02294825

Crossref Full Text | Google Scholar

133. Gibbs, H, and Chapman-Novakofski, K. A review of health literacy and its relationship to nutrition education. Top Clin Nutr. (2012) 27:325–33. doi: 10.1097/TIN.0b013e31826f8dc5

Crossref Full Text | Google Scholar

134. Zwierczyk, U, Sowada, C, and Duplaga, M. Eating choices—the roles of motivation and health literacy: a cross-sectional study. Nutrients. (2022) 14:194026. doi: 10.3390/nu14194026

PubMed Abstract | Crossref Full Text | Google Scholar

135. Patrick, H, and Williams, GC. Self-determination theory: its application to health behavior and complementarity with motivational interviewing. Int J Behav Nutr Phys Act. (2012) 9:18. doi: 10.1186/1479-5868-9-18

Crossref Full Text | Google Scholar

136. Tavousi, M, Mohammadi, S, Sadighi, J, Zarei, F, Kermani, RM, Rostami, R, et al. Measuring health literacy: a systematic review and bibliometric analysis of instruments from 1993 to 2021. PLoS One. (2022) 17:e0271524. doi: 10.1371/journal.pone.0271524

PubMed Abstract | Crossref Full Text | Google Scholar

137. García-Salirrosas, E, Millones-liza, D, Esponda-Pérez, J, Acevedo-duque, Á, Müller-Pérez, J, and Sanchez, DL. Factors influencing loyalty to health food brands: an analysis from the value perceived by the Peruvian consumer. Sustain For. (2022) 14:1–16. doi: 10.3390/su141710529

Crossref Full Text | Google Scholar

138. Makiabadi, E, Kaveh, MH, Asadollahi, A, and Ostovarfar, J. Development and validating of a quest for predicting nutrition literacy promoting behavior based on the theory of planned behavior in southern Iran, 2017. J Nutr Food Security. (2020) 5:1–11. doi: 10.18502/JNFS.V5I1.2312

Crossref Full Text | Google Scholar

139. Kassem, N. Understanding soft drink consumption among female adolescents using the theory of planned behavior. Health Educ Res. (2003) 18:278–91. doi: 10.1093/her/cyf017

PubMed Abstract | Crossref Full Text | Google Scholar

140. Kohlenberg-Müller, K, Ramminger, S, Kolm, A, Barkmeijer, A, Gast, C, Adam, M, et al. Nutrition assessment in process-driven, personalized dietetic intervention—the potential importance of assessing behavioural components to improve behavioural change: results of the EU-funded IMPECD project. Clin Nutr ESPEN. (2019) 32:125–34. doi: 10.1016/j.clnesp.2019.03.017

PubMed Abstract | Crossref Full Text | Google Scholar

141. Yıldırım, S, Uskun, E, and Kurnaz, M. Eating attitudes of students in high schools in a province center, and related factors. J Pediatr Res. (2017) 4:149–55. doi: 10.4274/jpr.97659

Crossref Full Text | Google Scholar

142. Mortaş, H, Navruz-Varlı, S, Çıtar-Dazıroğlu, M, and Bilici, S. Can unveiling the relationship between nutritional literacy and sustainable eating behaviors survive our future? Sustainability. (2023) 15:1–12. doi: 10.3390/su151813925

Crossref Full Text | Google Scholar

143. Teng, C, and Chih, C. Sustainable food literacy: a measure to promote sustainable diet practices. Sustain Prod Consum. (2022) 30:776–86. doi: 10.1016/j.spc.2022.01.008

Crossref Full Text | Google Scholar

144. Palumbo, R, Adinolfi, P, Annarumma, C, Catinello, G, Tonelli, M, Troiano, E, et al. Unravelling the food literacy puzzle: evidence from Italy. Food Policy. (2019) 83:104–15. doi: 10.1016/j.foodpol.2018.12.004

Crossref Full Text | Google Scholar

145. Palumbo, R. Sustainability of well-being through literacy. The effects of food literacy on sustainability of well-being. Agric Agric Sci Proc. (2016) 8:99–106. doi: 10.1016/j.aaspro.2016.02.013

Crossref Full Text | Google Scholar

146. Renwick, K, and Smith, M. The political action of food literacy: a scoping review. J Fam Consum Sci. (2020) 112:14–22. doi: 10.14307/JFCS112.1.14

Crossref Full Text | Google Scholar

147. Perry, E, Thomas, H, Samra, HR, Edmonstone, S, Davidson, L, Faulkner, A, et al. Identifying attributes of food literacy: a scoping review. Public Health Nutr. (2017) 20:2406–15. doi: 10.1017/S1368980017001276

PubMed Abstract | Crossref Full Text | Google Scholar

148. Fishbein, M, and Ajzen, I. Predicting and changing behavior: the reasoned action approach. (2011). doi: 10.4324/9780203838020

Crossref Full Text | Google Scholar

149. Oktavianus, J, and Bautista, JR. Motivating healthcare professionals to correct online health misinformation: the roles of subjective norm, third-person perception, and channel differences. Comput Human Behav. (2023) 147:107839. doi: 10.1016/j.chb.2023.107839

Crossref Full Text | Google Scholar

150. Chen, L, and Fu, L. Let’s fight the infodemic: the third-person effect process of misinformation during public health emergencies. Internet Res. (2022) 32:1357–77. doi: 10.1108/INTR-03-2021-0194

Crossref Full Text | Google Scholar

151. Bautista, J, Zhang, Y, and Gwizdka, J. Healthcare professionals’ acts of correcting health misinformation on social media. Int J Med Inform. (2021) 148:104375. doi: 10.1016/j.ijmedinf.2021.104375

PubMed Abstract | Crossref Full Text | Google Scholar

152. Koo, A, Su, M, Lee, S, Ahn, S, and Rojas, H. What motivates people to correct misinformation? Examining the effects of third-person perceptions and perceived norms. J Broadcast Electron Media. (2021) 65:111–34. doi: 10.1080/08838151.2021.1903896

Crossref Full Text | Google Scholar

153. Sui, Y, and Zhang, CB. Determinants of the perceived credibility of rebuttals concerning health misinformation. Int J Environ Res Public Health. (2021) 18:1345. doi: 10.3390/ijerph

Crossref Full Text | Google Scholar

Keywords: nutrition literacy, attitude, subjective norm, perceived behavioral control, planned behavior, willingness to consume, healthy brand foods

Citation: Chilón-Troncos RF, García-Salirrosas EE, Escobar-Farfán M, Millones-Liza DY and Villar-Guevara M (2024) Predicting willingness to consume healthy brand foods using the theory of planned behavior: the role of nutritional literacy. Front. Nutr. 11:1353569. doi: 10.3389/fnut.2024.1353569

Received: 10 December 2023; Accepted: 11 March 2024;
Published: 22 March 2024.

Edited by:

Iuliana Petronela Gardan, Spiru Haret University, Romania

Reviewed by:

Zoltán Szakály, University of Debrecen, Hungary
Azam Doustmohammadian, Iran University of Medical Sciences, Iran

Copyright © 2024 Chilón-Troncos, García-Salirrosas, Escobar-Farfán, Millones-Liza and Villar-Guevara. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Elizabeth Emperatriz García-Salirrosas, egarciasa@autonoma.edu.pe

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.