Next Article in Journal
Transcriptomics Integrated with Changes in Cell Wall Material of Chestnut (Castanea mollissima Blume) during Storage Provides a New Insight into the “Calcification” Process
Previous Article in Journal
Rapid Detection of Avocado Oil Adulteration Using Low-Field Nuclear Magnetic Resonance
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Foods
Volume 11
Issue 8
10.3390/foods11081135
foods-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Investigating the Effect of Consumers’ Knowledge on Their Acceptance of Functional Foods: A Systematic Review and Meta-Analysis

by
Mathew T. Baker
*,
Peng Lu
,
Jean A. Parrella
and
Holli R. Leggette
Department of Agricultural Leadership, Education and Communications, Texas A&M University, College Station, TX 77843, USA
*
Author to whom correspondence should be addressed.
Foods 2022, 11(8), 1135; https://doi.org/10.3390/foods11081135
Submission received: 21 March 2022 / Revised: 6 April 2022 / Accepted: 13 April 2022 / Published: 14 April 2022
(This article belongs to the Section Sensory and Consumer Sciences)
Browse Figures
Versions Notes

Abstract

:
Inconsistent results published in previous studies make it difficult to determine the precise effect of consumer knowledge on their acceptance of functional foods. We conducted a systematic review and meta-analysis by identifying and collecting relevant literature from three databases. Of the 1050 studies reviewed, we included 40 in the systematic review and 18 in the meta-analysis. Based on the focus of each included study, we operationally defined knowledge as knowledge of the functional food concept, nutritional-related knowledge, and knowledge of specific functional products. Results from the systematic review indicate that most participants from the included studies had low knowledge, especially nutrition-related knowledge associated with consuming functional foods, and were generally not familiar with the concept of functional foods. Results from the meta-analysis generated a summary effect size (r = 0.14, 95% CI [0.05; 0.23]), measured by the correlation coefficient r, which indicates a small positive relationship exists between consumers’ level of knowledge and their acceptance of functional foods. Results from our study demonstrate the importance of increasing consumers’ functional foods knowledge to improve their acceptance of such products. Agricultural and health communicators, educators, and functional foods industry professionals should prioritize increasing consumers’ knowledge through their communications, marketing, and programmatic efforts.

1. Introduction

Consumers’ modern rapid lifestyle, characterized by improper nutrition intake and low physical activity, has contributed to the spread of chronic diseases (e.g., obesity, diabetes, heart disease, cancer) [1], which are leading causes of US deaths [2]. In fact, the Centers for Disease Control and Prevention estimated that more than half of US adults have at least one chronic disease. As a result, US medical expenditure resulting from chronic disease is the highest health expenditure worldwide, reaching about $3.7 trillion per year [2]. Previous evidence suggests that adequate nutritional intake could sustain normal physiological function to prevent diet-related chronic diseases [3]. Therefore, to improve the health and well-being of consumers, decrease health expenditures, reduce the risk of chronic diseases, and support human health, functional foods were developed [4,5].
Many definitions of functional food have been offered. Diplock et al. [6] proposed the widely accepted definition of functional foods—“Food can be regarded as functional if it is satisfactorily demonstrated to affect beneficially one or more target functions in the body, beyond adequate nutritional effects, in a way that is relevant to either improved stage of health and well-being and/or reduction of risk of disease” (p. 6). Moreover, functional foods include a large variety of products, produced using novel technologies (e.g., enrichment, fortification, enhancement) to remove compounds that negatively impact human health and replace them with functional ingredients that provide health benefits [7].
In recent years, consumers have become increasingly aware of chronic diseases and are willing to modify their diet to ensure adequate nutritional intake [8]. As a result, the functional food industry has tried to expand functional attributes to diversify functional products [9]. In general, however, consumers are hesitant to accept novel food technologies [10], including those involved in the development of functional foods. The nutritional characteristics of functional foods, coupled with the novel technologies used in their development process, pose challenges for consumers who lack familiarity and nutritional knowledge.
Consumers’ knowledge has a significant effect on their food choice behavior [11]. Topolska et al. [12] identified knowledge as the most important factor influencing consumer preferences and acceptance of functional foods. Previous studies found that consumers are willing to accept functional foods if they have enough knowledge to understand the health benefits of consuming such foods [13,14,15]. Specifically, to accept functional foods, consumers need to link their knowledge about such foods to relevant health benefits associated with their consumption [16]. Consumers who have higher levels of knowledge can better understand the health benefits of consuming functional foods and, therefore, are motivated to purchase such products because they can connect the health information presented on products’ labels with their knowledge [16,17,18].
Consumer research has been identified as one of the most important research areas to evaluate consumers’ acceptance of functional foods [1,19,20]. Many studies have investigated the relationship between consumers’ level of knowledge and acceptance of functional foods. However, the strength and direction of this relationship reported in previous studies vary greatly. For example, some studies found consumers’ knowledge positively influenced their acceptance of functional foods [17,18,21], and others found no significant relationship [8] or a negative relationship [22]. Consequently, these inconsistent results posed problems in determining the precise effect consumers’ knowledge has on their acceptance.
To the best of our knowledge, no studies provide systematic evidence regarding the relationship between consumers’ knowledge and their acceptance of functional foods. Therefore, the purpose of our study was to provide a comprehensive overview of the peer-reviewed literature pertaining to consumers’ level of knowledge and determine the relationship between their level of knowledge and acceptance of functional foods. To achieve this purpose, three objectives guided the study: (1) Describe the included studies’ characteristics (e.g., country of origin, type of functional food, size and age range of the sample, type of knowledge, research design, outcome variable, key findings regarding consumers’ knowledge); (2) Qualitatively synthesize consumers’ level of knowledge as reported in the included studies; and (3) Identify the strength and direction of the relationship between consumers’ level of knowledge and their acceptance of functional foods.

2. Materials and Methods

2.1. Study Design

We conducted a systematic review (qualitative synthesis) and meta-analysis (quantitative synthesis) to achieve the study’s purpose. Using these methods, researchers seek to collect, combine, analyze, and present results from existing studies conducted on a specific topic using a predefined study protocol [23]. Together, a systematic review and meta-analysis can provide rigorous evidence and a comprehensive, unbiased overview of the body of knowledge on a specific topic [24]. Therefore, we chose to implement these methods because we sought to answer defined research questions through structured reviews of existing evidence [25]. We relied on the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement as a guide [26]. We also conducted a quality assessment of each included study to avoid potential reported biases or misleading results [23].

2.2. Database and Search Strategy

We systematically searched three databases—Web of Science (core collection), CAB abstracts (Ovid), and Food Science and Technology Abstracts (FSTA)—in July 2021. One author of this study and a subject librarian conducted the literature search. We selected relevant search terms related to functional food development technologies (e.g., enrichment, fortification, enhancement [7]) based on how they are described in previous research. We conducted a pilot test search to develop, test, and refine the search words. The combination of three sets of search strings included (functional food * or functional product * or enriched food * or enriched product * or fortified food * or fortified product * or enhanced food * or enhanced product *) and (accept * or behavior * or attitude * or perception * or pay or buy or purchase* or preference * or choice* or response *or reaction * or aware * or believe * or belief) and (knowledge). No limitation for the year of publication was applied (see the Supplementary Material Table S1 for the detailed search strings for the three databases). We also conducted a manual search through reference lists of included studies and similar published reviews to check for missing relevant studies.

2.3. Eligibility Criteria

We had five eligibility criteria for study inclusion. We included studies (records) that quantitatively investigated the relationship between consumers’ knowledge and acceptance of functional foods. We excluded qualitative studies to avoid researcher biases and, additionally, because qualitative methodologies do not allow for the extraction of effect sizes. Each study needed to include consumer knowledge as a primary variable of interest. In addition, we included studies focused on modified or altered functional foods, excluding studies focused on nutraceutical foods or unmodified whole functional foods because consumers tend to be less trusting of modified functional foods. We further excluded studies that focused on functional foods processes (e.g., product development process, functional ingredients evaluation, packing methods). Finally, we included only studies written in English and published in peer-reviewed journals.
The initial search of three databases generated 1050 studies, which were uploaded into Covidence, a citation management software for conducting systematic reviews. Two-hundred and forty-six (n = 246) duplicates were automatically removed from Covidence. Two authors individually conducted a title and abstract screening of the remaining 804 studies (n = 804) and excluded 715 (n = 715) because they did not qualify for our study based on the inclusion and exclusion criteria we established. Then, the same two authors conducted a full-text review of the remaining 89 studies (n = 89) and excluded an additional 49 (n = 49) that did not qualify. We addressed discrepancies through discussion. As a result, we included 40 studies (n = 40) in the systematic review, 18 (n = 18) of which provided sufficient quantitative data to be included in the meta-analysis. Figure 1 presents the flow chart of study selection and inclusion.

2.4. Data Extraction and Quality Assessment

The same two authors who conducted the title and abstract screenings and full-text reviews were also involved in data extraction, with one of us independently completing data extraction and the other thoroughly double-checking the work. We organized the extracted data into a Microsoft Excel spreadsheet and included authors’ names, the title of the article, publication year, country of origin, functional foods type, research method, sample size, participants’ age, the type of knowledge assessed, outcome variables, effect sizes, and key findings concerning consumers’ knowledge (see Table A1).
Additionally, the same two authors independently conducted a quality assessment of each included study. Due to the lack of standardized critical appraisal criteria for social science research, we developed the quality assessment instrument based on Petticrew and Robert’s [27] framework for appraising a survey and the Joanna Briggs Institute’s Critical Appraisal Checklist for Analytical Cross-Sectional Studies [28]. We used three categories to appraise the risk of bias: High (i.e., study reached “yes” scores of 49%); Moderate (i.e., study reached “yes” scores of 50% to 69%); and Low (i.e., study reached “yes” scores of more than 74%). We provide the quality assessment instrument and the risk of biases for each included study in Supplementary Material Table S2.

2.5. Data Synthesis

To complete the systematic review, we qualitatively synthesized the descriptive statistics and interpretations of inferential statistics reporting consumers’ knowledge of functional foods and the factors that influence their knowledge. We identified the type of consumer knowledge that each study investigated and used the constant comparative method to categorize knowledge types into distinct groups [29]. We extracted the percentages reporting consumers’ knowledge levels to determine the range of knowledge levels pertaining to each knowledge category. In addition, we identified and combined each of the factors reported that were found to influence consumers’ knowledge.

2.6. Data Analysis

We conducted a correlational meta-analysis and extracted correlation coefficient(s) (r) from each study to use as the estimated effect size. Eighteen studies (n = 18) provided sufficient quantitative data to be included in the meta-analysis. Of the 18 studies, five (n = 5) directly reported the correlation coefficient (r) [8,21,30,31,32]. Another nine studies (n = 9) reported regression coefficients that are appropriate for use in a meta-analysis, according to Peterson and Brown [5,22,33,34,35,36,37,38,39,40]. In addition, we calculated the correlation coefficients for two studies (n = 2) using the equations recommended by Borenstein et al. [41], which relied on means, standard deviations, and t-test results [20,42]. We also acquired correlation coefficients from two studies (n = 2) by connecting with the authors via email [17,43]. The authors of eight additional studies did not provide data for calculating effect sizes.
To complete the meta-analysis, we used R Studio software to conduct a random-effects model to analyze 18 studies (27 effect sizes) [44]. A random-effects model assumes all included studies are from different populations in which the average effect size varies randomly across studies [44,45]. Additionally, a random-effects model has unconditional inferences, allowing results obtained from the analysis to be generalized beyond the population of studies included in the meta-analysis [44]. We chose to use a random-effects model because the studies we included were conducted independently and their participants represented different populations. Therefore, through our study, we attempted to generalize results and conclusions. We also computed a funnel plot of effect sizes, in which standard error is plotted against the effect size measures, to visually examine the possibility of publication bias.
To interpret effect size homogeneity across studies, we relied on Cochran’s Q statistic and the I2 index [46]. Cochran’s Q statistic indicates the statistical significance of heterogeneity; however, when the number of included studies is small, its ability to detect true homogeneity is low [41,47]. Therefore, in addition to Cochran’s Q statistic, the I2 index was measured to report the extent of heterogeneity. The I2 index, which is not sensitive to the number of included studies, is reported as a percentage and represents the proportion of total variance across studies due to heterogeneity [46]. Generally, an I2 index of 75% or higher indicates high variation [46].

3. Results

3.1. Characteristics of Included Studies

The systematic review included 40 studies, 18 of which were included in the meta-analysis. Most of the reviewed studies were conducted in Europe (n = 23), six studies in Asia (n = 6), five studies in North America (n = 5), three studies in South America (n = 3), two studies in three different countries (i.e., Canada, U.S., France; n = 2), and one study in Africa (n = 1). All studies were conducted using survey methodology, including questionnaire surveys (n = 36) and survey-based economic evaluation techniques (i.e., experimental auctions (n = 2); choice experiments (n = 1)). One study used a mixed-method design (n = 1), part of which was also a questionnaire survey. The functional foods under investigation in the reviewed studies included functional meats, beverages, dairy products, and snacks (e.g., functional cookies, functional protein bars, functional cereal bars).

3.2. Qualitative Systematic Review Findings

We identified three categories of consumer knowledge based on the focus of each reviewed study: knowledge of the concept of functional foods (i.e., knowledge of functional food definition, knowledge of functional food description), knowledge about nutrition associated with consuming functional foods (i.e., knowledge about nutrition, knowledge about diet-related issues, knowledge about health claims), and knowledge of specific functional food products (i.e., knowledge about specific functional foods, knowledge about functional ingredients, knowledge about functional foods brands). It is important to note that some studies measured consumers’ perceived knowledge, and some studies measured consumers’ actual knowledge. For example, Verbeke et al. (2009) measured consumers’ perceived knowledge of the concept of functional foods. They included the question, “As compared to other people of your age with a similar background, how do you estimate your knowledge about functional foods?” with response options ranging from ‘very low’ to ‘very high’. Sääksjärvi et al. (2009), on the other hand, measured consumers’ actual knowledge of the concept of functional foods and included the question “What are functional foods?” with ‘gene manipulated foods’, ‘food with added beneficial ingredients’, ‘food in capsules or pills’, ‘ecological food’, and ‘I don’t know’ as response options. Some study authors, however, did not provide information about how they measured knowledge, preventing us from determining whether it was actual or perceived. Still, based on what we do know and for the purpose of our study, consumer knowledge included actual and perceived knowledge. Moreover, the outcome variable in each study was consumer acceptance of functional foods, which was defined and described using different concepts. These included general acceptance, willingness to pay or purchase, intent to purchase, likelihood to purchase, frequency of consumption, and frequency of purchase.

3.2.1. Consumers’ Knowledge of the Concept of Functional Foods

Consumers’ knowledge has been identified as an important predictor of their functional food acceptance. However, most studies indicated that participants had limited knowledge about or were not familiar with functional foods [48,49]. Five studies (n = 5) reported participants’ knowledge of the concept of functional foods. Specifically, the percentage of participants across studies knowledgeable about functional foods ranged from 21% to 52.3%. For example, Brečić et al. [17] found that only 21% of 424 Croatian participants believed they were ‘very well informed’ about functional foods, and Kolodinsky et al. [50] found that only 33.1% of 811 U.S., Canadian, and French participants had knowledge of functional foods. Similarly, 26.4% of 372 Chilean participants were knowledgeable about functional foods in Schnettler et al.’s study [51], and 40.6% of 251 Lebanese participants were knowledgeable about functional foods in Chammas et al.’s study [52]. Grochowska-Niedworok et al. [53] found that a higher percentage of 300 Polish participants (52.3%) were knowledgeable, and Stojanovic et al. [39] found more than half of Montenegrin participants (52% of 479) were moderately informed about functional foods.
Although most participants across studies were not knowledgeable about functional foods, they still showed interest in consuming functional foods [53]. Italian participants were more willing to accept functional foods if they were first exposed to the concept of functional foods [37]. In addition, providing appropriate health information about the health benefits of consuming functional foods could help consumers become more accepting [37]. For example, Dean et al. [34] found that consumers who were previously exposed to health information (i.e., how consuming functional foods could reduce disease risk) were more likely to accept functional foods.

3.2.2. Consumers’ Knowledge about Nutrition of Functional Foods

In addition to general knowledge of functional foods, several studies reported consumers’ level of nutritional knowledge. For example, O’Connor and Venter [54] found that only 17.3% of 139 South African participants believed they had a high level of nutritional knowledge. In two other studies investigating consumers in the Republic of Macedonia [55] and Canada [56], participants’ nutritional knowledge was moderate. Moreover, Barreiro-Hurlé et al. [30] found that 45% of 300 Spanish participants were familiar with fat and cholesterol content and daily caloric recommendations. Furthermore, Yalçın et al. [57] found that 65.7% of 293 Turkish participants were familiar with dietary fiber and foods, and 59.1% were knowledgeable concerning the health effects of consuming dietary fiber.

3.2.3. Consumers’ Knowledge of Specific Functional Foods

Five studies (n = 5) reported consumers’ level of knowledge regarding specific functional foods (e.g., iron-fortified soy sauce, functional eggs, functional meat, functional coffee). Generally, this type of knowledge was limited among global consumers. For example, Sun et al. [31] found that only 15% of 1090 Chinese participants in urban areas were familiar with iron-fortified soy sauce. In contrast, only 3% of Chinese participants in rural areas had heard about iron-fortified soy sauce. In addition, Hayat et al. [58] found that 24.3% of 262 Pakistani participants had heard about functional nutrient-enriched designer eggs, Sandmann et al. [8] found that 34% of 840 German participants were familiar with vitamin D fortified foods, and Corso et al. [21] found that only 3.7% of 270 Brazilian participants had heard of functional soluble coffee. Finally, a study conducted in four European countries—Belgium, Netherlands, Italy, and Germany—found that more than half of 2057 participants (54.9%) were unfamiliar with nitrite added to functional processed meats [59].

3.2.4. Factors Influencing Consumers’ Knowledge of Functional Foods

Demographic characteristics (i.e., age, gender, educational level, marital status, nationality) influence consumers’ level of knowledge of functional foods. For example, Corso et al. [21] found that participants who were older and had higher education were more knowledgeable about the health benefits of consuming coffee enriched with antioxidants compared to participants who were younger and had less education. In addition, Cukelj et al. [7] found that female participants had higher nutritional knowledge than their male counterparts, and that female participants who had received a higher education had more nutritional knowledge when compared to females who had received less education. Although Cukelj et al. [7] found no association between participants’ knowledge and age, Chammas et al. [52] found that young people between the ages of 18 and 29, or single, had more knowledge of functional foods compared to people between the ages of 30 and 66 or married. Similarly, Hayat et al. [58] found that participants’ marital status significantly influenced their knowledge of specific functional foods, but their gender and educational level did not. Moreover, several studies found that consumers’ nationality influenced their knowledge. Specifically, Labrecque et al. [36] found that French participants had less knowledge about the term functional foods when compared to American and French-Canadian participants, and Kolodinsky et al. [50] found that American participants had more knowledge of functional foods when compared to French and Canadian participants.

3.2.5. Relationship between Consumers’ Knowledge and Their Acceptance of Functional Foods

Eighteen (n = 18) studies investigated the relationship between consumers’ level of knowledge and their acceptance of functional foods. Thirteen studies (n = 13) found positive correlations between participants’ knowledge (i.e., knowledge of functional foods, nutritional knowledge, knowledge of functional food brands) and their acceptance of functional foods, whereas two studies (n = 2) found significant negative correlations between participants’ health and/or nutritional knowledge and their functional foods purchasing frequency. In addition, three studies (n = 3) found that participants’ subjective nutritional knowledge was not significantly related to their acceptance of functional foods. Still, Sparke et al. [60] explained that even though a correlation did not exist between consumers’ knowledge of functional foods and their acceptance of such foods, knowledge is an important factor that could ultimately influence consumer acceptance.

3.3. Meta-Analysis Results

The 18 studies we included in the meta-analysis generated 27 effect sizes. These studies’ sample sizes ranged from 62 to 2385, and the total number of participants included in the meta-analysis was 13,736 (N = 13,736). We conducted a forest plot to view effect sizes across studies and determine their precision (see Figure 2). Results indicate that the pooled correlation effect size r between consumers’ level of knowledge and their acceptance of functional foods is 0.14 (r = 0.14, 95% CI = [0.05, 0.23], z = 3.05, p = 0.002), which represents a small effect, according to Funder and Ozer [61] and Gignac and Szodorai [62] who stated that 0.10 represents a small effect, 0.20 represents a medium effect, and 0.30 represents a large effect. Therefore, we found that a small, positive relationship exists between consumers’ knowledge and their acceptance of functional foods. In addition, results from Cochran’s Q test of effect size homogeneity (Q = 583.044, df = 26, p < 0.001) indicate that heterogeneity exists across studies. More specifically, results from the I2 index indicate that 95.5% [94.4%; 96.4%] of the variation across studies is due to heterogeneity. Results from the funnel plot show some asymmetry, which suggests publication bias may exist (see Figure 3).

4. Discussion

The first critical point of discussion for the study described herein is that promotion guided by the intent to build awareness is key to enhancing the conversation around and accepting functional foods. According to Wansink et al.’s [16] hierarchy of nutritional knowledge, consumers’ lack of knowledge could hinder their acceptance of functional foods. Urala and Lähteenmäki [15] found that consumers are more likely to accept functional foods if they understand the health benefits of consuming them. However, consumers need knowledge to evaluate and interpret information about health benefits adequately [63]. Therefore, helping consumers obtain knowledge is important because those who are more knowledgeable about functional foods and the health benefits associated with their consumption are significantly more likely to accept functional foods [5,17,34].
According to the studies included in this review, consumers’ knowledge of functional foods is limited. Most participants were not even aware of functional foods—they did not have adequate nutritional knowledge or understand the health benefits of consuming functional foods. Previous studies found consumers were unwilling to accept functional foods because they were uninformed about or found it difficult to understand nutritional information and health benefits [64,65]. In this regard, promoting the health benefits of, and nutritional information related to, functional foods is a key first step to increasing the public’s acceptance of such foods and, ultimately, their understanding of the relationship between diet and health.
Previous studies indicate that increasing consumers’ nutritional knowledge could change their nutritional behaviors. As a result, this change could improve the population’s health status [66] and simultaneously lead to a wider acceptance of functional foods. Thus, effective scientific communication efforts are critical to disseminating information about nutrition and, ultimately, the adoption of healthy eating habits across the nation’s varying demographics. Agricultural and health communicators and educators play an instrumental role in increasing consumers’ access to information about the concept of functional foods, the health benefits associated with consuming functional foods, and the health risk associated with nutrition deficiencies [63,67], and often with increased access comes increased knowledge and a higher potential for behavior change.
Because increased knowledge can lead to increased acceptance, we recommend the creation and implementation of a functional foods information campaign to increase consumers’ knowledge of functional foods and to educate consumers about the health benefits of consuming functional foods and the consequences of insufficient nutritional intake. This would likely be an effective approach because consumers are more willing to consume functional foods if they connect their knowledge to the health benefits of consuming them [16]. To reach broad audiences, including those more prone to accepting functional foods and those that would benefit most from consuming them, we recommend that social media, specifically Facebook, Twitter, and Instagram, be used as the primary platforms for dissemination. Because social media are an integral part of many people’s daily lives, they provide a low-cost way of reaching the masses with important health information [68,69]. As interactive spaces for scientific information dissemination, social media are effective modes for addressing public health nutrition issues and have the potential to influence healthy lifestyle behaviors [68].
Professionals in the functional foods industry should develop social media content that aims first to empathize with the group’s shared values to establish trust and then convey health information clearly and accurately [70,71]. The content should draw consumers’ attention to the connection between the health benefits of consuming functional foods and their personal health. Professionals should consider these specific strategies—use multimedia materials, include popular culture-inspired visual elements, and translate content into multiple languages—because these have been successful in other social media health promotion efforts [68]. Sufficient investment in educating consumers about comprehensive health information using social media could increase knowledge and lead to positives changes in nutritional behaviors [42,63,68].
Moreover, a cadre of school-based or secondary nutritional educators should provide curricula that include content about the health benefits of functional foods [72]. These curricula should help students better understand functional ingredients and products, provide adequate information about the consequences of insufficient nutritional intake, and increase their interest in consuming functional foods [73]. In addition, nutritional education programs should allow students to interact with industry scientists to learn how technology is used to develop functional foods. Better understanding will likely aid in counteracting consumer skepticism about such foods. Educators should also provide experiential learning opportunities for students to comprehend food science concepts [74], identify functional foods in grocery stores, and understand nutritional labels [75], ultimately helping students make healthy food choices.
The European Regulations on Food Information for Consumers recommend improving consumer knowledge of nutrition and labeling [76]. Providing explanatory health information (i.e., nutrient content, health benefits of essential nutrients) on food labels is the initial step in decreasing obesity [76,77]. Therefore, adults and educators should cooperate with dietitians and nutritionists to develop and deliver community-based nutrition education interventions [72]. These programs should include content about functional ingredients and products and explain the health benefits of consuming functional foods. For example, previous studies indicated that effective nutrition education inventions that include diet counseling, increasing access to health professionals, and distributing newsletters about healthy eating, can improve nutrition knowledge and result in positive behavior change across entire communities [72,78]. The benefits of school-based and adult consumer education programs should be evaluated holistically to document their impact [79].
A second important point of discussion is that the variation between effect sizes could be explained by the heterogeneity of the samples, the country of origin in which the studies were conducted, the types of functional foods used, and the unstandardized measurements of variables. Thus, we recommend that, when possible, future studies use nationally representative samples and standardized measurements to investigate the relationship between consumers’ knowledge and their acceptance of functional foods. In addition, using experimental research designs instead of survey methods can provide empirical causal evidence to explain the phenomenon using robust statistical methods. We also believe it would be valuable to include only studies in these meta-analyses that use specific populations, so we can begin to understand the differences in how these variables influence different consumer groups. Doing so would provide researchers with the data to segment audiences based on demographic and psychographic characteristics and, ultimately, develop audience-specific communications strategies, materials, and content.
These future research efforts should rely on existing theoretical models related to health and behavior change to transfer research into practice more effectively. For instance, the health belief model, originally developed in the 1950s to explain people’s participation in disease detection and prevention programs, is now widely used to study people’s health [80]. Examples of constructs included in the model are modifying factors (e.g., ethnicity, education, knowledge), individual perceptions (e.g., perceived benefits, perceived barriers, self-efficacy), and actions (e.g., behaviors). With this model in mind, researchers could investigate how consumers’ knowledge of functional foods influences their perceived barriers to adoption. Rogers [81] diffusion of innovation theory would also enable researchers to investigate consumers’ acceptance of functional foods through a novel lens. The theory, which explains how a product diffuses through a social system, is based on five adopter categories: innovators, early adopters, early majority, late majority, and laggards. It would be interesting for researchers to investigate types and levels of knowledge that influence consumers’ rate of adoption (acceptance) and their likelihood to adopt (to accept) functional foods earlier than other persons. Results from basic theoretical research would inform practitioners about the types of knowledge consumers need to overcome perceived barriers to adopting functional foods and, ultimately, increase the rate at which they accept these foods.
Because the current study has its limitations, we offer specific research recommendations to overcome them. Consumers’ acceptance of functional foods depends on a variety of interrelated factors, including consumers’ demographic characteristics (e.g., age, gender, educational level, marital status, nationality), affective domains (e.g., attitudes, perceptions), and situational domains (e.g., politics, economy) [82]. We focused only on consumers’ knowledge as a determinant of consumers’ acceptance. Other variables were beyond the scope of our research for the study described herein. Therefore, future systematic reviews and meta-analyses should focus on how other variables (e.g., attitudes, perceptions, motivations) influence consumers’ acceptance of functional foods so that the precise effect of these variables can be determined.
As stated in a previous section, consumers’ demographic characteristics can influence their knowledge of functional foods. We extracted participants’ age from the included studies and reported this information in the summary table to provide context to our results (see Table A1). However, some of the included studies did not provide adequate information about their participants’ demographic characteristics, which hindered us from conducting further analyses using these characteristics. Therefore, we believe results from the meta-analysis reported herein provide information regarding the influence of consumers’ knowledge on their acceptance of functional foods that represents the general population. We recommend future meta-analyses include meta-regressions to investigate how consumers’ acceptance of functional foods could be explained by their demographic characteristics.
In addition, the limited number of studies we included in the meta-analysis prevented us from conducting meta-regressions and moderator/mediator analyses. Therefore, future research should investigate potential moderators and mediators that might influence the relationship between consumers’ knowledge and their acceptance of functional foods. The more we know about this relationship, the more effectively we can communicate with specific audiences.
Findings from the systematic review and meta-analysis described herein provide novel and useful insight into the existing body of evidence regarding the effect of knowledge on consumers’ acceptance of functional foods. We independently analyzed the influence of knowledge types on consumer acceptance in the systematic review and collectively analyzed the influence of knowledge in the meta-analysis. As additional studies become published that investigate the relationship between consumers’ knowledge and their acceptance of functional foods, future meta-analyses should examine the effect of specific types of knowledge on consumer acceptance separately. However, for our meta-analysis, we chose to combine the three types of knowledge we identified in our literature review (i.e., knowledge of the concept of functional foods, knowledge about nutrition associated with consuming functional foods, knowledge of specific functional food products) seeking to generalize the meta-analysis results more broadly and because we were only able to include a small number of effect sizes. Qualitatively and quantitatively, we comprehensively synthesized the diverse findings from relevant studies. We added to the body of knowledge by providing practical recommendations for professionals in the functional foods industry and a clear trajectory for researchers to investigate varying dimensions of knowledge related to functional foods.

5. Conclusions

A systematic review and meta-analysis are effective research methods to synthesize existing data and explore systematic evidence relating to a specific research topic [45]. To our best knowledge, this study is the first of its kind to investigate the relationship between consumers’ knowledge and their acceptance of functional foods using these methods. We identified a small, positive relationship between consumers’ level of knowledge and their acceptance of functional foods. The positive relationship we identified emphasizes the important role of consumers’ knowledge in their acceptance of functional foods. We also found that, for the most part, global consumers have low levels of knowledge related to functional foods, which is problematic due to its positive influence. Therefore, agricultural and health communicators and functional foods industry professionals, who play an instrumental role in increasing consumers’ access to information about functional foods, should strategically promote the health benefits of and nutritional information related to functional foods to increase public acceptance. We recommend this be done by implementing a functional foods information campaign using social media as primary platforms for dissemination, curricula for school-based or secondary nutritional educators, and community-based nutrition education interventions. These efforts to increase consumers’ knowledge would likely lead to increased acceptance and increased consumption, leading to the improved health and well-being of consumers across the globe. Because our study was limited to investigating consumers’ knowledge as a determinant of their acceptance, future systematic reviews and meta-analyses should examine the precise effect of demographic, affective, and situational factors on the same outcome through the lens of theoretical models related to health and behavior change. As a result, we will improve our ability to develop strategic messages for specific audiences and circumstances that can effectively improve their acceptance of functional foods.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods11081135/s1. Table S1: Databases and search terms used to search articles. Table S2: Quality criteria of including studies for systematic review.

Author Contributions

Conceptualization and supervision, M.T.B.; Methodology, M.T.B. and P.L.; Data collection and analysis, P.L. and J.A.P.; Writing—review and editing, M.T.B., P.L., J.A.P. and H.R.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

We would like to thank librarian Carolyn Jackson for her assistance with designing and conducting literature searches.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Characteristics of the Included Studies.
Table A1. Characteristics of the Included Studies.
StudyCountryFunctional Foods TypeStudy
Design		Knowledge TypeOutcome VariableCorrelationSample Size Age of Participants Risk of BiasMain Findings about Knowledge
Arenna et al., 2019 [56]Canada Enhanced carnosine in porkSurveyed-based choice experiment Nutrition knowledge Willingness to pay Data was unusable99218+; Average age = 52.6 Low Participants’ average nutrition knowledge score was 15.8 (ranging from 5–25); Participants’ level of nutrition knowledge is significantly, positively associated with their willingness to pay for functional foods.
Ares et al., 2008 [66]Uruguay (South America)16 functional foods conceptsSurveyNutrition knowledge (nutrient content; antioxidants; connection between diet and diseases) Willingness to try Data was unusable10418–81; Average age = 34.3LowNutrition knowledge significantly affected participants’ willingness to try functional foods; Nutrition knowledge significantly affected participants’ perceived healthiness of functional foods; Participants who had a low level of nutrition knowledge were not interested in consuming functional foods; Participants with a high level of nutrition knowledge were interested in healthy foods enriched with fiber or antioxidants.
Barreiro-Hurlé et al., 2008 [30]SpainResveratrol-enriched red wineSurveyed-based choice experimentNutrition knowledge Willingness to pay r = −0.01 300Average age = 46.5Low45% of participants had nutrition knowledge regarding fat and cholesterol content and daily caloric recommendations; Participants who know the relationship between health and diet are more likely to buy functional wine.
Bimbo et al., 2018 [43]ItalianFunctional yogurtsPost-purchased survey Knowledge about leading functional yogurt brandsThe numbers of functional yogurt packages purchasedr = 0.201922918–60LowParticipants with more knowledge of leading functional yogurt brands purchased a higher number of functional yogurt packages; Regardless of participants’ level of knowledge of leading functional yogurt brands, those who did not like their own bodies were less likely to purchase functional yogurt packages.
Brečić et al., 2014 [17]CroatiaThe concept of functional foodsSelf-administered surveyKnowledge of functional foods Functional foods consumption frequency r = 0.12942418+; Average age = 47.6Low6% of participants reported themselves as “fully informed” about functional foods; 21% reported themselves as “very well informed” about functional foods; A significant, positive relationship existed between participants’ knowledge of functional foods and their consumption of functional foods.
Chammas et al., 2019 [52]Lebanon Prebiotic yogurt; Protein bars; Protein shakes; Cereal barsSurveyKnowledge of functional foods and functional ingredients Functional foods acceptanceData was unusable25134.5 ± 12.1 Low40.6% of participants were knowledgeable about functional foods; 32% of participants were knowledgeable about functional ingredients; Participants between the ages of 18 and 29 had a higher knowledge level of functional foods; Single participants had a higher knowledge level of functional foods; Participants who went to the gym had a higher knowledge of functional foods.
Clark et al., 2019 [48]EnglandVitamin D fortified foodsMixed methods (focus groups and survey)Knowledge of vitamin D Perceptions of fortified foodsData was unusable 10916+LowParticipants had basic knowledge of vitamin D; Participants lacked knowledge about the health benefits of vitamin D sufficiency.
Corso et al., 2018 [21]Brazil Coffee enriched with antioxidants Self-administered surveyKnowledge of functional foods Functional foods acceptance r = 0.168 (“if they taste good”); r = 0.137 (“if they taste
worse than their conventional counterpart foods”) (p. 5)
270Average age = 39.1LowParticipants’ knowledge of functional foods was significantly, positively associated with their acceptance of functional coffee; 49.6% of participants knew the benefits of coffee ingestion; 60.7% of participants knew the benefits of antioxidants ingestion; 5.6% of participants knew the benefits of consuming soluble coffee.
Cukelj et al., 2016 [7]CroatiaFlaxseed-enriched cookiesOnline surveyNutrition knowledge about lignans and omega-3 fatty acids (ingredients)Purchase interestsData was unusable103515–65 Moderate Female participants had a higher level of nutrition knowledge compared to male participants; Participants’ age was not associated with their knowledge level; Female participants’ educational level was significantly, positively associated with their level of nutrition knowledge; Participants with a higher level of nutrition knowledge consumed more functional cookies compared to those with a lower level of nutrition knowledge.
Dean et al., 2012 [34]Finland; the UK; Germany; ItalyBread, cake, and cereal-containing yogurt + benefit claim, risk reduction claim, and nutrition claimPaper and pencil survey Subjective knowledge Likelihood to buy r = 0.05 (nutrition claim); r = 0.04 (risk reduction claim)238535–95; Average age = 52.1LowParticipants’ subjective knowledge was a significant predictor of their likelihood to buy functional foods with a nutrition claim; Participants’ subjective knowledge did not increase their likelihood to buy functional foods with risk reduction claims.
Di Talia et al., 2018 [49]Italy; GermanyThe term functional foodsSurveyKnowledge of functional foods Attitudes toward functional foodsData was unusable230Data was not availableModerateParticipants’ level of knowledge of functional foods was low; 68% of participants were informed consumers who had knowledge of functional foods.
Grochowska-Niedworok et al., 2017 [53]PolandThe concept of functional foodsSurvey Knowledge of functional foodsFunctional foods consumption Data was unusable300Data was not availableModerateParticipants’ level of knowledge about functional foods was low; 83.3% of participants did not know the amount of functional foods available on the market; 43.1% of healthy participants and 53.97% of participants with diseases had no knowledge regarding their consumption of functional foods.
Hasnah 2011 [35]MalaysiaThe concept of functional foodsSelf-administered surveyKnowledge of functional foodsFunctional foods consumption r = 0.216 20018–54 LowParticipants’ knowledge of functional foods positively influenced their functional foods consumption; Participants were knowledgeable about functional foods.
Hayat et al., 2010 [58]Pakistan Nutrient enriched designer eggsSurveyKnowledge about designer eggs (type of functional food)Perception and willingness to buy Data was unusable26218+; Median age = 37Moderate14.2% of participants knew of nutrient-enriched designer eggs, and 85.7% did not; Male participants had slightly more knowledge than female participants; Participants’ marital status and occupation were significantly associated with their level of knowledge.
Henson et al., 2008 [22]Canada Tomato juice and a snack bar containing lycopene Self-administered surveyKnowledge of medicine, nutrition, or health carePurchase intentionr = −0.22 (tomato juice);
r = −0.26 (snack bar)		26818+LowParticipants’ knowledge of medicine, nutrition, or health care was significant, and negatively associated with their intent to buy functional foods.
Herath et al., 2008 [83]Canada Food/beverage containing desirable nutritional qualities (fiber, antioxidants, essential fatty acids)Survey Knowledge about food-health linkagesFunctional food receptivenessData was unusable 175318+LowParticipants who had a higher level of knowledge of age-related diseases had greater receptivity toward functional foods.
Hung et al., 2016 [59]Belgium; Netherlands; Italy; GermanyMeat products processed with natural compounds and a reduced level of nitriteSurveyObjective knowledge about the purpose of adding nitrite to meat Purchase intentionData was unusable205718–75; Average age = 45.5 Low54.9% of participants had no knowledge about nitrite added to processed meats product.
Kolodinsky et al., 2008 [50]Canada; United States; FranceEggs with omega-3; milk with calcium; orange juice with calcium Self-administered surveyKnowledge of functional foodsPurchase intentionData was unusable81122.4 ± 3.3Low33.1% of participants had good knowledge of functional foods; 28.1% had partial knowledge; 38.3% had no knowledge; Participants from the United States had greater knowledge about functional foods than French and Canadian participants.
Labrecque et al., 2006 [36]Canada; United States; FranceMilk with Omega-3; egg with Omega-3Self-administered surveyKnowledge of the term ‘functional foods’ Functional food acceptancer = 0.11 54518–25Low56.9% of American participants, 45.8% of Canadian participants, and 10.6% of French participants knew the term functional foods; Participants’ level of functional foods knowledge was significantly, positively associated with their acceptance of functional foods.
La Barbera et al., 2016 [5]ItalianCrushed tomatoes enriched with lycopeneSurveyed-based experimental auctionSubjective knowledge about lycopeneWillingness to payr = 0.1423100Average age = 23.06LowParticipants’ level of knowledge about lycopene was significantly, positively associated with their willingness to pay a higher premium price for functional foods.
Lu., 2015 [20]Canada 30 hypothetical functional foodsSurveyed-based experimental auctionNutrition knowledge Purchase intentionr = 0.18626218–55 LowParticipants’ level of nutrition knowledge was significantly, positively associated with their intent to purchase functional foods; Participants’ level of nutrition knowledge significantly moderated the relationship between their perceived carrier-ingredient fit of a functional food and their purchase intention.
Nguyen, 2020 [84]VietnamThe term functional foodsSurveyKnowledge of functional foods Functional food acceptanceData was unusable26020+ LowParticipants’ level of functional foods knowledge was significant, and positively associated with their acceptance of functional foods.
O’Connor & Venter, 2012 [54]South Africa Ten bioactive food ingredients (functional ingredients)SurveyHealth and wellness knowledge; Nutrition knowledge Perceived interest Data was unusable13925–65Low22.3% of participants perceived their level of health and wellness knowledge to be well informed; 66.9% of participants perceived their level of health and wellness knowledge to be moderately informed; 17.3% of participants perceived their level of nutrition knowledge to be well informed; 65.5% of participants perceived their level of nutrition knowledge to be moderately informed; Participants who had higher knowledge of Omega-3 fatty acids, probiotics, and soy protein tended to adopt functional foods.
Di Pasquale et al., 2011 [37]ItalyMilk, butter, and yogurt fortified with conjugated linoleic acidSelf-administered surveyKnowledge of the relationship between diet and health; Knowledge of functional foodsWillingness to pay r = 0.39 (milk);
r = 0.41; (yogurt);
r = 0.41 (butter)		16320–80; Average age = 43LowParticipants’ knowledge of functional foods significantly influenced their willingness to pay for functional foods; 29% of participants had no knowledge of functional foods or the relationship between diet and health; 29% of participants knew the major functional foods product categories and some knowledge of the relationship between diet and health; 28% of participants had some knowledge of functional foods that was greatly influenced by advertising and no knowledge of the relationship between diet and health; 14% of participants knew of (were familiar with) functional foods and knew (good awareness) of the relationship between diet and health.
Pounis et al., 2011 [38]GreeceIron-fortified foodsSurveyOverall nutrition knowledge; general nutrition knowledge; iron nutrition knowledge Iron fortified foods perception and consumptionr = 0.03 (overall nutrition); r = 0.05 (general nutrition);
r = 0.032 (iron deficiency)		50030 ± 12LowIncreasing participants’ overall nutrition knowledge improved their perception of iron-fortified foods; Participants’ overall nutrition knowledge, general nutrition knowledge, and iron nutrition knowledge were significantly, positively associated with their consumption of iron-fortified foods.
Sääksjärvi et al., 2009 [85]FinlandThe term functional foodsSurveyKnowledge of functional foods Purchase behavior Data was unusable40918+LowParticipants’ attitudes toward health mediated the effect between their knowledge of functional foods and purchase behavior; Female participants had more knowledge of functional foods than male participants; Participants aged 55 to 65 had the most knowledge of functional foods; Participants’ income was significantly, positively associated with their knowledge of functional foods; University-educated participants had more knowledge of functional foods than high school-educated participants.
Sandmann et al., 2015 [8]GermanyVitamin D-fortified foods (i.e., juice, cereals, butter, milk, yogurt)Online survey General knowledge of vitamin DAcceptance of vitamin D-fortified foods r = 0.07 84019+LowParticipants’ general knowledge about vitamin D was not significantly related to their acceptance of vitamin D-fortified foods; Most participants lacked general knowledge about vitamin D; 22% of participants reported that their vitamin D-related knowledge was good.
Schnettler et al., 2015 [86]Chile Functional foods with 18 health benefits SurveyKnowledge of functional foodWillingness to buyData was unusable 400<35 (34.5%); 35–54 (42.0%); 55 + (23.5%)LowParticipants’ level of functional foods knowledge positively influenced their willingness to buy.
Schnettler et al., 2016 [51]Chile Data was not availableSurveyKnowledge of functional foodAttitudeData was unusable 372Average age = 20.4 LowMost participants (83.6%) had no prior knowledge of functional foods.
Sparke et al., 2009 [60]Germany; Poland; Spain;
United Kingdom 		Orange juice enriched with functional ingredients recombined with different health claimsSurvey Knowledge of functional foodFunctional food purchase frequencyData was unusable590Data was not availableLowThere was no correlation between participants’ knowledge of functional foods and their purchase frequency.
Spiroski et al., 2013 [55]Republic of Macedonia Data was not availableSurveyNutrition knowledge AttitudeData was unusable51818+LowParticipants’ nutrition knowledge was at a moderate level.
Stojanovic et al., 2013 [39]Montenegro Products with health claims (e.g., the benefits of high calcium)Self-administered surveyKnowledge of foods with health claims Consumption frequency r = −0.35 47918+Low52% of participants were moderately informed about foods with health claims; 1.9% of participants were fully informed; 8.6% of participants were not informed at all; Participants’ level of knowledge of foods with health claims is a predictor of their functional food consumption.
Sun et al., 2006 [31]ChinaIron-fortified soy sauceSurveyKnowledge of iron-fortified soy sauce Purchase intentionr = 0.2451090Average age = 37.33LowParticipants had limited knowledge of iron-fortified soy sauce; 3% of participants from rural areas and 15% of participants from urban areas had heard of iron-fortified soy sauce; Participants’ knowledge of iron-fortified soy sauce was significant, and positively associated with their intention to purchase.
Szakály et al., 2019 [40]HungaryDairy-based probiotic products (e.g., yogurt, cheese, muesli)Self-administered survey Knowledge of functional foods Willingness to payr = 0.550018–69 LowParticipants’ subjective knowledge of functional foods was significant, and positively associated with their purchase patterns of functional dairy products.
Verbeke et al., 2009 [42]BelgiumCalcium-enriched fruit juice; Omega-3 enriched spread; fiber-enriched cerealSelf-administered survey Knowledge of functional foods Intention to buy product r = 0.15341Average age = 37.4LowThere was no significant relationship between participants’ knowledge of functional foods and their acceptance.
Verbeke, 2005 [18]BelgiumThe concept of functional foodsSelf-administered survey Knowledge of functional foods Functional foods acceptance Data was unusable215Average age = 39.1LowThere was no significant relationship between participants’ knowledge of functional foods and their acceptance.
Verneau et al., 2019 [87]ItalyCanned crushed tomatoes enriched with lycopeneExperimental auctionKnowledge about lycopene (ingredients)Willingness to payData was unusable100Average age = 23.88LowParticipants with low knowledge of lycopene increased their willingness to pay after receiving information about the product.
Wansink et al., 2005 [16] Canada; United States The term functional foodsMail surveyKnowledge of soy (attribute-related knowledge; consumption consequence-related knowledge)Functional foods consumptionData was unusable 606Data was not availableLow74.4% of participants had attribute-related knowledge, consumption consequence-related knowledge, or both; participants with attribute-related knowledge and consequence-related knowledge were more likely to consume soy products.
Xin & Seo, 2019 [32]ChinaKorean functional foods (e.g., red ginseng, ginseng, vitamin, tonic, calcium, fish oil)Online surveySubjective knowledge of Korean functional foodsPurchase intentionr = 0.6836120–60LowParticipants’ subjective knowledge about Korean functional foods was significant, and positively associated with their purchase intention.
Yalçın et al., 2020 [57]Turkey Foods with dietary fibersSurveyKnowledge of dietary fibers and foods; knowledge of dietary fibers and health effects AttitudeData was unusable29318–71; Average age = 34.8Low65.7% of participants had a high level of knowledge about dietary fibers and foods; 59.1% of participants had a high level of knowledge about dietary fibers and health effects.

References

  1. Plasek, B.; Lakner, Z.; Kasza, G.; Temesi, Á. Consumer evaluation of the role of functional food products in disease prevention and the characteristics of target groups. Nutrients 2020, 12, 69. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Centers for Disease Control and Prevention. Chronic Disease Prevention and Health Promotion, Chronic Disease Overview. 2020. Available online: https://www.cdc.gov/chronicdisease/about/index.htm (accessed on 1 September 2021).
  3. Stover, P.J.; Garza, C.; Durga, J.; Field, M.S. Emerging concepts in nutrient needs. J. Nutr. 2020, 150 (Suppl. S1), 2593S–2601S. [Google Scholar] [CrossRef] [PubMed]
  4. Hasler, C.M. Functional foods: Benefits, concerns and challenges—A position paper from the American Council on Science and Health. J. Nutr. 2002, 132, 3772–3781. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. La Barbera, F.; Amato, M.; Sannino, G. Understanding consumers’ intention and behavior towards functionalized food. Br. Food J. 2016, 118, 885–895. [Google Scholar] [CrossRef]
  6. Diplock, A.T.; Aggett, P.J.; Ashwell, M.; Bornet, F.; Fern, E.B.; Roberfroid, M.B. Scientific concepts in functional foods in Europe: Consensus document. Br. J. Nutr. 1999, 81, 1–27. [Google Scholar] [CrossRef]
  7. Cukelj, N.; Putnik, P.; Novotni, D.; Ajredini, S.; Voŭcko, B.; Duška, C. Market potential of lignans and omega-3 functional cookies. Br. Food J. 2016, 118, 2420–2433. [Google Scholar] [CrossRef]
  8. Sandmann, A.; Brown, J.; Mau, G.; Saur, M.; Amling, M.; Barvencik, F. Acceptance of vitamin D-fortified products in Germany—A representative consumer survey. Food Qual. Prefer. 2015, 43, 53–62. [Google Scholar] [CrossRef]
  9. Granato, D.; Barba, F.J.; Bursać Kovačević, D.; Lorenzo, J.M.; Cruz, A.G.; Putnik, P. Functional foods: Product development, technological trends, efficacy testing, and safety. Annu. Rev. Food Sci. Technol. 2020, 11, 93–118. [Google Scholar] [CrossRef] [Green Version]
  10. Siegrist, M.; Hartmann, C. Consumer acceptance of novel food technologies. Nat. Food 2020, 1, 343–350. [Google Scholar] [CrossRef]
  11. Wardle, J.; Parmenter, K.; Waller, J. Nutrition knowledge and food intake. Appetite 2000, 111, 1713–1726. [Google Scholar] [CrossRef] [PubMed]
  12. Topolska, K.; Florkiewicz, A.; Filipiak-Florkiewicz, A. Functional food—Consumer motivations and expectations. Int. J. Environ. Res. Public Health 2021, 18, 5327. [Google Scholar] [CrossRef] [PubMed]
  13. Annunziata, A.; Vecchio, R. Functional foods development in the European market: A consumer perspective. J. Funct. Food 2011, 3, 223–228. [Google Scholar] [CrossRef]
  14. Peng, Y.; West, G.E.; Wang, C. Consumer attitudes and acceptance of CLA-enriched dairy products. Can. J. Agric. Econ. 2006, 54, 663–684. [Google Scholar] [CrossRef]
  15. Urala, N.; Lähteenmäki, L. Attitudes behind consumers’ willingness to use functional foods. Food Qual. Prefer. 2004, 15, 793–803. [Google Scholar] [CrossRef]
  16. Wansink, B.; Westgren, R.E.; Cheney, M.M. Hierarchy of nutritional knowledge that relates to the consumption of a functional food. Nutrition 2005, 21, 264–268. [Google Scholar] [CrossRef] [PubMed]
  17. Brečić, R.; Gorton, M.; Barjolle, D. Understanding variations in the consumption of functional foods–evidence from Croatia. Br. Food J. 2014, 116, 662–675. [Google Scholar] [CrossRef]
  18. Verbeke, W. Consumer acceptance of functional foods: Socio-demographic, cognitive and attitudinal determinants. Food Qual. Prefer. 2005, 16, 45–57. [Google Scholar] [CrossRef]
  19. Guiné, R.P.F.; Florença, S.G.; Barroca, M.J.; Anjos, O. The link between the consumer and the innovations in food product development. Foods 2020, 9, 1317. [Google Scholar] [CrossRef]
  20. Lu, J. The effect of perceived carrier-ingredient fit on purchase intention of functional food moderated by nutrition knowledge and health claim. Br. Food J. 2015, 117, 1872–1885. [Google Scholar] [CrossRef]
  21. Corso, M.P.; Kalschne, D.L.; Benassi, M.D.T. Consumer’s attitude regarding soluble coffee enriched with antioxidants. Beverages 2018, 4, 72. [Google Scholar] [CrossRef] [Green Version]
  22. Henson, S.; Masakure, O.; Cranfield, J. The propensity for consumers to offset health risks through the use of functional foods and nutraceuticals: The case of lycopene. Food Qual. Prefer. 2008, 19, 395–406. [Google Scholar] [CrossRef]
  23. Ahn, E.; Kang, H. Introduction to systematic review and meta-analysis. Korean J. Anesth. 2018, 71, 103–112. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Impellizzeri, F.M.; Bizzini, M. Systematic review and meta-analysis: A primer. Int. J. Sports Phys. Ther. 2012, 7, 493–503. Available online: https://pubmed.ncbi.nlm.nih.gov/23091781/ (accessed on 12 April 2022). [PubMed]
  25. Paul, M.; Leibovici, L. Systematic review or meta-analysis? Their place in the evidence hierarchy. Clin. Microbiol. Infect. 2014, 20, 97–100. [Google Scholar] [CrossRef] [Green Version]
  26. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Ann. Intern. Med. 2009, 151, 264–269. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Petticrew, M.; Roberts, H. Systematic Reviews in the Social Sciences; Blackwell Publishing: Malden, MA, USA, 2006. [Google Scholar]
  28. Moola, S.; Munn, Z.; Tufanaru, C.; Aromataris, E.; Sears, K.; Sfetcu, R.; Currie, M.; Qureshi, R.; Mattis, P.; Lisy, K.; et al. Systematic Reviews of Etiology and Risk. In Joanna Briggs Institute Reviewer’s Manual; Aromataris, E., Munn, Z., Eds.; Joanna Briggs Institute: Adelaide, Australia, 2017; Chapter 7. [Google Scholar]
  29. Glaser, B.G. The constant comparative method of qualitative analysis. Soc. Probl. 1965, 12, 436–445. [Google Scholar] [CrossRef]
  30. Barreiro-Hurlé, J.; Colombo, S.; Cantos-Villar, E. Is there a market for functional wines? Consumer preferences and willingness to pay for resveratrol-enriched red wine. Food Qual. Prefer. 2008, 19, 360–371. [Google Scholar] [CrossRef]
  31. Sun, X.; Guo, Y.; Wang, S.; Sun, J. Predicting iron-fortified soy sauce consumption Intention: Application of the theory of planned behavior and health belief model. J. Nutr. Educ. Behav. 2006, 38, 276–285. [Google Scholar] [CrossRef]
  32. Xin, L.; Seo, S.S. The role of consumer ethnocentrism, country image, and subjective knowledge in predicting intention to purchase imported functional foods. Br. Food J. 2019, 122, 448–464. [Google Scholar] [CrossRef]
  33. Peterson, R.A.; Brown, S.P. On the use of beta coefficients in meta-analysis. J. Appl. Psychol. 2005, 90, 175–181. [Google Scholar] [CrossRef] [Green Version]
  34. Dean, M.; Lampila, P.; Shepherd, R.; Arvola, A.; Saba, A.; Vassallo, M.; Claupein, E.; Winkelmann, M.; Lähteenmäki, L. Perceived relevance and foods with health-related claims. Food Qual. Prefer. 2012, 24, 129–135. [Google Scholar] [CrossRef]
  35. Hasnah Hassan, S. Consumption of functional food model for Malay Muslims in Malaysia. J. Islam. Mark. 2011, 2, 104–124. [Google Scholar] [CrossRef]
  36. Labrecque, J.; Doyon, M.; Bellavance, F.; Kolodinsky, J. Acceptance of functional foods: A comparison of French, American, and French Canadian consumers. Can. J. Agric. Econ. 2006, 54, 647–661. [Google Scholar] [CrossRef]
  37. Di Pasquale, J.; Adinolfi, F.; Capitanio, F. Analysis of consumer attitudes and consumers’ willingness to pay for functional foods. Int. J. Food Syst. Dyn. 2011, 2, 181–193. [Google Scholar] [CrossRef]
  38. Pounis, G.D.; Makri, S.; Gougias, L.; Makris, H.; Papakonstantinou, M.; Panagiotakos, D.B.; Kapsokefalou, M. Consumer perception and use of iron fortified foods is associated with their knowledge and understanding of nutritional issues. Food Qual. Prefer. 2011, 22, 683–688. [Google Scholar] [CrossRef]
  39. Stojanovic, Z.; Filipovic, J.; Mugosa, B. Consumer acceptance of functional foods in Montenegro. Montenegrin J. Econ. 2013, 9, 65–74. [Google Scholar]
  40. Szakály, Z.; Kovács, S.; Pető, K.; Huszka, P.; Kiss, M. A modified model of the willingness to pay for functional foods. Appetite 2019, 138, 94–101. [Google Scholar] [CrossRef]
  41. Borenstein, M.; Hedges, L.; Higgins, J.; Rothstein, H. Introduction to Meta-Analysis; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2009. [Google Scholar]
  42. Verbeke, W.; Scholderer, J.; Lähteenmäki, L. Consumer appeal of nutrition and health claims in three existing product concepts. Appetite 2009, 52, 684–692. [Google Scholar] [CrossRef]
  43. Bimbo, F.; Bonanno, A.; Van Trijp, H.; Viscecchia, R. Body image dissatisfaction and health-enhancing food choices: A pilot study from a sample of Italian yogurt consumers. Br. Food J. 2018, 120, 2778–2792. [Google Scholar] [CrossRef]
  44. Field, A.P.; Gillett, R. How to do a meta-analysis. Br. J. Math. Stat. Psychol. 2010, 63, 665–694. [Google Scholar] [CrossRef]
  45. Quintana, D.S. From pre-registration to publication: A non-technical primer for conducting a meta-analysis to synthesize correlational data. Front. Psychol. 2015, 6, 1549. [Google Scholar] [CrossRef] [Green Version]
  46. Higgins, J.P.; Thompson, S.G.; Deeks, J.J.; Altman, D.G. Measuring inconsistency in meta-analyses. BMJ 2003, 327, 557–560. [Google Scholar] [CrossRef] [Green Version]
  47. Ioannidis, J.P.; Patsopoulos, N.A.; Evangelou, E. Uncertainty in heterogeneity estimates in meta-analyses. BMJ 2007, 335, 914–916. [Google Scholar] [CrossRef] [Green Version]
  48. Clark, B.; Hill, T.; Hubbard, C. Consumers’ perception of vitamin D and fortified foods. Br. Food J. 2019, 121, 2205–2218. [Google Scholar] [CrossRef]
  49. Di Talia, E.; Simeone, M.; Scarpato, D. Consumer acceptance and consumption of functional foods. An attempt of comparison between Italy and Germany. Qual. Access Success 2018, 19, 125–132. [Google Scholar]
  50. Kolodinsky, J.; Labrecque, J.; Doyon, M.; Reynolds, T.; Oble, F.; Bellavance, F.; Marquis, M. Sex and cultural differences in the acceptance of functional foods: A comparison of American, Canadian, and French college students. J. Am. Coll. Health 2008, 57, 143–149. [Google Scholar] [CrossRef]
  51. Schnettler, B.; Adasme-Berríos, C.; Grunert, K.G.; Márquez, M.P.; Lobos, G.; Salinas-Onate, N.; Orellana, L.; Sepulveda, J. The relation between attitudes toward functional foods and satisfaction with food-related life. Br. Food J. 2016, 118, 2234–2250. [Google Scholar] [CrossRef]
  52. Chammas, R.; El-Hayek, J.; Fatayri, M.; Makdissi, R.; Bou-Mitri, C. Consumer knowledge and attitudes toward functional foods in Lebanon. Nutr. Food Sci. 2019, 49, 762–776. [Google Scholar] [CrossRef]
  53. Grochowska-Niedworok, E.; Brukało, K.; Kardas, M. Consumer choice determinants in context of functional food. Int. J. Nutr. Food Eng. 2017, 11, 605–608. [Google Scholar] [CrossRef]
  54. O’Connor, K.; Venter, I. Awareness, knowledge, understanding and readiness to adopt bioactive food ingredients as part of functional food consumption by health-conscious consumers of the City of Cape Town. J. Consum. Sci. 2012, 40, 59–73. [Google Scholar]
  55. Spiroski, I.; Gjorgjev, D.; Milosevic, J.; Kendrovski, V.; Naunova-Spiroska, D.; Barjolle, D. Functional Foods in Macedonia: Consumers Perspective and Public Health Policy. Open Access Maced. J. Med. Sci. 2013, 1, 102–107. [Google Scholar] [CrossRef] [Green Version]
  56. Arenna; Goddard, E.; Muringai, V. Consumer purchase intentions for pork with enhanced carnosine-A functional food. Can. J. Agr. Econ. Rev. Can. Agroecon. 2019, 67, 151–169. [Google Scholar] [CrossRef]
  57. Yalçln, E.; Kösemeci, C.; Correia, P.; Karademir, E.; Ferreira, M.; Florenca, S.G.; Guiné, R.P.F. Evaluation of consumer habits and knowledge about dietary fibre and fibre-rich products in Turkish population. Open Agric. 2020, 5, 375–385. [Google Scholar] [CrossRef]
  58. Hayat, Z.; Pasha, T.N.; Khattak, F.M.; Jabbar, M.A.; Nasir, Z.; Samiullah, S. Consumer’s perception and willingness to buy nutrient enriched designer eggs in Pakistan. Archiv. Fur Geflugelkunde 2010, 74, 145–150. [Google Scholar]
  59. Hung, Y.; de Kok, T.M.; Verbeke, W. Consumer attitude and purchase intention towards processed meat products with natural compounds and a reduced level of nitrite. Meat Sci. 2016, 121, 119–126. [Google Scholar] [CrossRef]
  60. Sparke, K.; Menrad, K. Cross-European and Functional Food related consumer segmentation for new product development. J. Food Prod. Mark. 2009, 15, 213–220. [Google Scholar] [CrossRef] [Green Version]
  61. Funder, D.C.; Ozer, D.J. Evaluating effect size in psychological research: Sense and nonsense. Adv. Methods Pract. Psychol. Sci. 2019, 2, 156–168. [Google Scholar] [CrossRef]
  62. Gignac, G.E.; Szodorai, E.T. Effect size guidelines for individual differences researchers. Pers. Individ. Dif. 2016, 102, 74–78. [Google Scholar] [CrossRef]
  63. Vella, M.N.; Stratton, L.M.; Sheeshka, J.; Duncan, A.M. Functional food awareness and perceptions in relation to information sources in older adults. Nutr. J. 2014, 13, 44. [Google Scholar] [CrossRef] [Green Version]
  64. Braun, M.; Venter, I. Awareness and knowledge of phytonutrient food sources and health benefits for functional food application among health food store customers in the Cape Town city bowl. J. Consum. Sci. 2008, 36, 30–39. [Google Scholar] [CrossRef]
  65. Mollet, B.; Rowland, I. Functional foods: At the frontier between food and pharma. Curr. Opin. Biotechnol. 2002, 13, 483–485. [Google Scholar] [CrossRef]
  66. Ares, G.; Giménez, A.; Gámbaro, A. Influence of nutritional knowledge on perceived healthiness and willingness to try functional foods. Appetite 2008, 51, 663–668. [Google Scholar] [CrossRef] [PubMed]
  67. Siro, I.; Kápolna, E.; Kápolna, B.; Lugasi, A. Functional food. Product development, marketing and consumer acceptance—A review. Appetite 2008, 51, 456–467. [Google Scholar] [CrossRef] [PubMed]
  68. Mendoza-Herrera, K.; Morales, I.V.; Ocampo-Granados, M.E.; Reyes-Morales, H.; Arce-Amaré, F.; Barquera, S. An overview of social media use in the field of public health nutrition: Benefits, scope, limitations, and a Latin American experience. Prev. Chronic Dis. 2020, 17, E76. [Google Scholar] [CrossRef]
  69. Stellefson, M.; Paige, S.R.; Chaney, B.H.; Chaney, J.D. Evolving role of social media in health promotion: Updated responsibilities for health education specialists. Int. J. Environ. Res. Public Health 2020, 17, 1153. [Google Scholar] [CrossRef] [Green Version]
  70. Foodintegrity.org. A Dangerous Food Disconnect When Consumers Hold You Responsible but Don’t Trust You; Technical Report; The Center for Food Integrity: Gladstone, MO, USA, 2018. [Google Scholar]
  71. Palmieri, N.; Stefanoni, W.; Latterini, F.; Pari, L. Factors influencing Italian consumers’ willingness to pay for eggs enriched with omega-3-fatty acids. Foods 2022, 11, 545. [Google Scholar] [CrossRef]
  72. Moore, S.G.; Donnelly, J.K.; Jones, S.; Cade, J.E. Effect of educational interventions on understanding and use of nutrition labels: A systematic review. Nutrients 2018, 10, 1432. [Google Scholar] [CrossRef] [Green Version]
  73. Katz, D.L.; Treu, J.A.; Ayettey, R.G.; Kavak, Y.; Katz, C.S.; Njike, V. Testing the effectiveness of an abbreviated version of the nutrition detectives program. Prev. Chronic Dis. 2014, 11, E57. [Google Scholar] [CrossRef] [Green Version]
  74. Lu, P.; Schroeder, S.; Burris, S.; Rayfield, J.; Baker., M. The effectiveness of a metacognitive strategy during the reading process on cognitive allocation and subject matter retention. J. Agric. Educ. 2022. In press. [Google Scholar]
  75. Carrillo, E.; Varela, P.; Fiszman, S. Influence of nutritional knowledge on the use and interpretation of Spanish nutritional food labels. J. Food Sci. 2012, 77, H1–H8. [Google Scholar] [CrossRef]
  76. European Union. Regulation (EU) No 1169/2011 of the European Parliament and of the Council of 25 October 2011 on the Provision of Food Information to Consumers. Available online: https://eurlex.europa.eu/legal-content/en/ALL/?uri=CELEX%3A32011R1169 (accessed on 15 March 2022).
  77. Sassi, F.; Cecchini, M.; Lauer, J.; Chisholm, D. Improving Lifestyles, Tackling Obesity: The Health and Economic Impact of Prevention Strategies; OECD Health Working Papers, No. 48; OECD Publishing: Paris, France, 2009. [Google Scholar] [CrossRef]
  78. Sahyoun, N.R.; Pratt, C.A.; Anderson, A. Evaluation of nutrition education interventions for older adults: A proposed framework. J. Am. Diet. Assoc. 2004, 104, 58–69. [Google Scholar] [CrossRef] [PubMed]
  79. Strong, R.; Dooley, K.; Murphrey, T.; Strong, J.; Elbert, C.; Baker, M. The EVAL framework: Developing impact evaluation scholars. Adv. Agric. Dev. 2021, 2, 1–13. [Google Scholar] [CrossRef]
  80. Janz, N.K.; Becker, M.H. The health belief model: A decade later. Health Educ. Q. 1984, 11, 1–47. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  81. Rogers, E.M. Diffusion of Innovations, 5th ed.; Free Press: New York, NY, USA, 2003. [Google Scholar]
  82. Baker, M.T.; Lu, P.; Parrella, J.A.; Leggette, H.R. Consumer acceptance toward functional foods: A scoping review. Int. J. Environ. Res. Public Health 2022, 19, 1217. [Google Scholar] [CrossRef] [PubMed]
  83. Herath, D.; Cranfield, J.; Henson, S. Who consumes functional foods and nutraceuticals in Canada? Results of cluster analysis of the 2006 survey of Canadians’ demand for food products supporting health and wellness. Appetite 2008, 51, 256–265. [Google Scholar] [CrossRef] [PubMed]
  84. Nguyen, N.T. Attitudes and repurchase intention of consumers towards functional foods in Ho Chi Minh city, Vietnam. Int. J. Anal. Appl. 2020, 18, 212–242. [Google Scholar]
  85. Sääksjärvi, M.; Holmlund, M.; Tanskanen, N. Consumer knowledge of functional foods. Int. Rev. Retail. Distrib. Consum. Res. 2009, 19, 135–156. [Google Scholar] [CrossRef]
  86. Schnettler, B.; Miranda, H.; Lobos, G.; Sepúlveda, J.; Orellana, L.; Mora, M.; Grunert, K. Willingness to purchase functional foods according to their benefits. Br. Food J. 2015, 117, 1453–1473. [Google Scholar] [CrossRef]
  87. Verneau, F.; La Barbera, F.; Furno, M. The role of health information in consumers’ willingness to pay for canned crushed tomatoes enriched with Lycopene. Nutrients 2019, 11, 2173. [Google Scholar] [CrossRef] [Green Version]
Foods 11 01135 g001 550
Figure 1. The PRISMA flow chart of study selection and screening.
Figure 1. The PRISMA flow chart of study selection and screening.
Foods 11 01135 g001
Foods 11 01135 g002 550
Figure 2. Forest plot of the 27 effect sizes (correlation coefficients (r)) with corresponding 95% confidence intervals [5,8,17,18,20,21,22,30,31,32,34,35,36,37,38,39,40,42,43].
Figure 2. Forest plot of the 27 effect sizes (correlation coefficients (r)) with corresponding 95% confidence intervals [5,8,17,18,20,21,22,30,31,32,34,35,36,37,38,39,40,42,43].
Foods 11 01135 g002
Foods 11 01135 g003 550
Figure 3. Funnel plot of the 27 effect sizes in which standard error is plotted against the effect size measures.
Figure 3. Funnel plot of the 27 effect sizes in which standard error is plotted against the effect size measures.
Foods 11 01135 g003
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Baker, M.T.; Lu, P.; Parrella, J.A.; Leggette, H.R. Investigating the Effect of Consumers’ Knowledge on Their Acceptance of Functional Foods: A Systematic Review and Meta-Analysis. Foods 2022, 11, 1135. https://doi.org/10.3390/foods11081135

AMA Style

Baker MT, Lu P, Parrella JA, Leggette HR. Investigating the Effect of Consumers’ Knowledge on Their Acceptance of Functional Foods: A Systematic Review and Meta-Analysis. Foods. 2022; 11(8):1135. https://doi.org/10.3390/foods11081135

Chicago/Turabian Style

Baker, Mathew T., Peng Lu, Jean A. Parrella, and Holli R. Leggette. 2022. "Investigating the Effect of Consumers’ Knowledge on Their Acceptance of Functional Foods: A Systematic Review and Meta-Analysis" Foods 11, no. 8: 1135. https://doi.org/10.3390/foods11081135

APA Style

Baker, M. T., Lu, P., Parrella, J. A., & Leggette, H. R. (2022). Investigating the Effect of Consumers’ Knowledge on Their Acceptance of Functional Foods: A Systematic Review and Meta-Analysis. Foods, 11(8), 1135. https://doi.org/10.3390/foods11081135

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop