There has been a global shift in food systems—whereas highly processed, low cost and convenient food items are more widely available in comparison to foods that are minimally processed and nutrient rich(Reference Steeves, Martins and Gittelsohn1). The availability of these highly processed foods, which are typically nutrient poor and energy dense, make it challenging to navigate the current food landscape to access and select nutritious foods.
Food literacy (FL) and nutrition literacy (NL) are concepts that may be important factors in supporting healthful dietary habits. While the literature includes a variety of definitions for FL and NL and their corresponding constructs(Reference Swinburn, Sacks and Hall2–Reference Truman, Lane and Elliott4), NL has been defined as ‘the degree to which individuals have the capacity to obtain, process, and understand nutrition information and skills needed in order to make appropriate nutrition decisions’(Reference Silk, Sherry and Winn5); where FL has been defined as ‘the scaffolding that empowers individuals, households, communities or nations to protect diet quality through change and strengthen dietary resilience over time. It is composed of a collection of inter-related knowledge, skills and behaviours required to plan, manage, select, prepare and eat food to meet needs and determine intake’(Reference Vidgen and Gallegos6). In this sense, being more food and nutrition literate provides one with the necessary aptitude and abilities to help navigate our current food environment. Indeed, FL and NL have been identified as key components in the promotion and maintenance of healthy dietary practices(Reference Cullen, Hatch and Martin7–Reference Velardo9). Both FL and NL are included in this review to provide a comprehensive assessment of existing tools(Reference Krause, Sommerhalder and Beer-Borst8).
Supporting children in developing FL and NL, starting as early as in preschool years, can shape their food choices—since building these aptitudes and capabilities at a young age may be important for skill retention(Reference Lavelle, Spence and Hollywood10), confidence in food practices(Reference Hersch, Perdue and Ambroz11) and supporting healthy eating habits later in life(Reference Utter, Larson and Laska12,Reference Laska, Larson and Neumark-Sztainer13) . A 10-year longitudinal study observed that those with higher cooking skills in emerging adulthood prepared meals with vegetables more frequently and consumed fast food less often as adults(Reference Utter, Larson and Laska12). Research has also shown that, among a sample University students, the strongest predictor of food skills was meal preparation as a teenager(Reference Seabrook, Dworatzek and Matthews14). While these studies underscore the importance of acquiring FL and NL early in life, there is currently no universally accepted tool to measure either FL or NL among children and adolescents.
NL and FL have been studied more extensively in the adult population, and a systematic review by Yuen, Thompson & Gardiner(Reference Yuen, Thomson and Gardiner15) identified 13 tools targeting adults. In addition, a scoping review by Amouzandeh and colleagues(Reference Amouzandeh, Fingland and Vidgen16) summarised the psychometric properties of 12 instruments that were used to assess FL among adults. While these reviews identified existing measures of FL and NL in adults, to our knowledge, no systematic review has been conducted to identify tools for children and adolescents. To ensure they are appropriate for use, NL and FL assessment tools must undergo validity testing, that is, to assess the extent to which the measure accurately reflects the intended variable, in addition to reliability testing, which refers to the consistency of a measure. Identifying valid and reliable tools that assess FL and NL in childhood can help facilitate research that examines the long-term impact of building these skills, abilities and aptitudes early in life.
The objectives of this systematic review were to: (i) identify existing tools that measure FL and NL among children and/or adolescents and (ii) describe the validity and reliability of these tools. Findings from this review will help to identify tools for use in FL and NL research with children as well as identify potential gaps in existing FL and NL measurement.
Methods
This systematic review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines(Reference Moher, Liberati and Tetzlaff17). This systemic review was registered with PROSPERO (CRD42021241819).
Search strategy
A systematic search of the literature was completed by 2 review authors (N.C. and M.P.). The search was last performed in May 2021. The following 6 databases were used: PubMed, Ovid MEDLINE, ScienceDirect, Web of Science, CINAHL plus and PsycInfo. Key words were identified through the expert guidance of a research librarian in addition to being based on previous literature reviews(Reference Yuen, Thomson and Gardiner15,Reference Amouzandeh, Fingland and Vidgen16,Reference Vaitkeviciute, Ball and Harris18) . The search terms included: preschool* OR child* OR adolescen* OR teen* AND ‘food literacy’ OR ‘food skills’ OR ‘nutrition literacy’. The complete search strategy for each database is provided on the Online Supplementary Table S1. Forward citation searching was also used on the articles included in the final review.
Eligibility criteria
Articles were included if they were primary research, described the development of a tool explicitly assessing FL or NL and assessed some form of validity (including content validity, face validity or structural/construct validity) or reliability (including internal consistency or test–retest reliability) testing. Only tools targeting children (2–12 years old) and/or adolescents (13–18 years old) were included. In the case that the ages extended beyond these ranges, if the mean age of the sample was ≥2 or ≤18 years, articles were included. Publications were excluded if an English language version was not available and if they were grey literature (e.g. theses, reports).
Study selection
A 4-phase screening process was applied to identify articles to be included in the review. After completing the search, articles were exported and saved into Mendeley (Version 1.19.4). Duplicates were removed. The titles and abstracts of the remaining articles were then screened by 2 reviewers (N.C. and M.P.), independently. After excluding articles based on the eligibility criteria in review of the titles and abstracts, the remaining studies were then further examined by a review of the full text. Any differences across reviewers (N.C. and M.P.) throughout the screening and selection process were discussed and resolved.
Data extraction and analysis
From each article that was included in the review, the following information was extracted into a table: (1) key characteristics of the identified tools (author, year of publication, country of origin, tool name, purpose, conceptual framework, number of items and constructs assessed, scoring details, method of development, method of administration, sample characteristics); and (2) psychometric properties (content validity, face validity, structural/construct validity, reliability). Missing or unclear information was also identified and reported. One review author (N.C.) extracted the data and another author (M.P.) reviewed the data. A narrative synthesis of the included studies was conducted to summarise and analyse findings.
Risk of bias assessment
Risk of bias was assessed using the COSMIN risk of bias checklist(Reference Mokkink, de Vet and Prinsen19). The assessment was completed independently by 2 reviewers (N.C. and M.P). Answers were compared and discussed to reach consensus. The COSMIN checklist consists of ten areas of consideration: outcome measure development, content validity, structural/construct validity, internal validity, cross-cultural validity, reliability, measurement error, criterion validity, hypothesis testing for construct validity and responsiveness(Reference Mokkink, de Vet and Prinsen19). Each area includes different items that are assessed using the following scoring: ‘Very Good’, ‘Adequate’, ‘Doubtful’, ‘Inadequate’ or ‘Not Applicable’(Reference Mokkink, de Vet and Prinsen19). The score ‘Not Reported’ was indicated when the details could not be found in the article. For each area of consideration, the lowest score across the area items was used to evaluate the overall quality of the measurement property(Reference Mokkink, de Vet and Prinsen19). Because the COSMIN checklist was developed for evaluating tools designed to measure symptom or functional health status, the detail and rigour described for the outcome measure development and content validity areas of the checklist exceeded what is typically presented for assessment of health behaviours, such as FL and NL. Thus, these areas of the checklist were not assessed, and were instead narratively summarized.
Results
After the 4-phase protocol, a total of 12 tools were included in this systematic review (Fig. 1). In the initial search, 1203 articles were identified, of which 747 remained once duplicates were removed. Upon screening the titles and abstracts, 716 were excluded and the remaining 31 were assessed for eligibility by reviewing the full text. After the full-text review, 19 articles were excluded. The reasons for exclusion included: the article was outside the scope of the review (n 445), not a primary research article (n 128), did not include children or adolescents as the study population (n 102), did not provide information on the development or validation of the FL or NL measure (n 45), or not in English (n 15). One article was retrieved in the forward citation step (n 1). Some studies appeared to meet the inclusion criteria, but were excluded, such as the study by Gartaula et al.(Reference Gartaula, Patel and Shukla20). While FL was evaluated among students, their definition only considered knowledge relating to cultivation practices and the processing of finger millet(Reference Gartaula, Patel and Shukla20). In addition, multiple publications(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi21–Reference Tabacchi, Battaglia and Alesi24) have been released using the Preschool-FLAT and the FNLIT; where, only the validation studies(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Tabacchi, Battaglia and Messina26) were included in this review.
Flowchart of the literature search and review process
*The reasons for exclusion included: the article was outside the scope of the review (n 445), not a primary research article (n 128), did not include children or adolescents as the study population (n 102), did not provide information on the development or validation of the food literacy (FL) or nutrition literacy (NL) measure (n 45), or not in English (n 15).
**One tool was identified in the forward citation step.
Summary of existing tools
The 12 tools that assessed FL and NL among children and adolescents are summarized in Table 1. Three of the 12 tools measured FL(Reference Tabacchi, Battaglia and Messina26–Reference Amin, Lehnerd and Cash28), 4 tools measured both FL and NL(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Liu, Su and Li29–Reference Ashoori, Omidvar and Eini-Zinab31) , and the other 5 tools measured NL or subareas of NL(Reference Deesamer, Piaseu and Maneesriwongul32–Reference Guttersrud and Petterson35). More specifically, 2 of the NL tools assessed critical NL(Reference Naigaga, Pettersen and Henjum34,Reference Guttersrud and Petterson35) , 1 of the tools measured menu board literacy(Reference Williams, Quinn and Ramirez33) and the other tool assessed food label literacy(Reference Reynolds, Treu and Njike36). Critical NL focuses specifically on critically appraising and understanding nutrition information(Reference Naigaga, Pettersen and Henjum34), while menu board literacy targets understanding of menu board nutrition information(Reference Williams, Quinn and Ramirez33) and food label literacy measures one’s ability to interpret the information on food labels(Reference Reynolds, Treu and Njike36). The studies describing the 12 tools were published between 2012 and 2021 and were developed in 7 geographical regions: 2 from Norway(Reference Naigaga, Pettersen and Henjum34,Reference Guttersrud and Petterson35) , 3 from the USA(Reference Amin, Lehnerd and Cash28,Reference Williams, Quinn and Ramirez33) , 1 from Denmark(Reference Stjernqvist, Elsborg and Ljungmann27), 1 from Thailand(Reference Deesamer, Piaseu and Maneesriwongul32), 3 from Iran(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Khorramrouz, Doustmohammadian and Amini30,Reference Ashoori, Omidvar and Eini-Zinab31) , 1 from Italy(Reference Tabacchi, Battaglia and Messina26) and 1 from China(Reference Liu, Su and Li29). The purpose of most of the studies was to develop and test the validity and/or reliability of a tool that assesses either FL or NL. However, 2 of the studies(Reference Stjernqvist, Elsborg and Ljungmann27,Reference Guttersrud and Petterson35) tested the validity and reliability of a previously developed tool, while one study(Reference Khorramrouz, Doustmohammadian and Amini30) modified and updated a previously existing tool(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25). The tools were generally tailored to a specific population. For instance, the TFLAC(Reference Amin, Lehnerd and Cash28) was developed for low-to-middle income, ethnically and racially diverse school-aged children living in the USA (grades 4–5). One tool was intended for preschoolers (3–6 years of age)(Reference Tabacchi, Battaglia and Messina26), 5 tools were designed for school-aged children (7–12 years of age)(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Amin, Lehnerd and Cash28,Reference Khorramrouz, Doustmohammadian and Amini30,Reference Williams, Quinn and Ramirez33,Reference Reynolds, Treu and Njike36) , and 5 tools were aimed at adolescents (12–18 years of age)(Reference Stjernqvist, Elsborg and Ljungmann27,Reference Ashoori, Omidvar and Eini-Zinab31,Reference Deesamer, Piaseu and Maneesriwongul32,Reference Naigaga, Pettersen and Henjum34,Reference Guttersrud and Petterson35) . One tool was developed for school-aged children and adolescents (7–17 years of age) but was only validated among adolescents between ages 13–15 years(Reference Liu, Su and Li29).
Summary characteristics of the food literacy and nutrition literacy tools for children and adolescents
FL, food literacy; NL, nutrition literacy.
While 3 of the studies did not specify a conceptual framework or model on which the measure was based(Reference Amin, Lehnerd and Cash28,Reference Williams, Quinn and Ramirez33,Reference Reynolds, Treu and Njike36) , 7 of the tools assessing NL(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Liu, Su and Li29–Reference Deesamer, Piaseu and Maneesriwongul32,Reference Naigaga, Pettersen and Henjum34,Reference Guttersrud and Petterson35) were based on Nutbeam’s health literacy model(Reference Nutbeam37) and 2 were based on the models of FL(Reference Tabacchi, Battaglia and Messina26,Reference Stjernqvist, Elsborg and Ljungmann27) by Benn(Reference Benn38) and Vidgen and Gallegos(Reference Vidgen and Gallegos6), respectively. Among the 5 tools that focused on NL, the number of constructs assessed in the tools ranged from 2 to 5 and the number of items ranged from 5 to 61. The Thai–NLAT(Reference Deesamer, Piaseu and Maneesriwongul32) was the most comprehensive in assessing NL with 5 constructs: macronutrients–micronutrients and health, nutrition and energy balance, decision–making on nutrition information, food processing and food safety. The number of constructs assessed in the FL tools and the 4 FL and NL tools ranged from 5 to 6 and included from 20 to 60 items. Most of the tools included similar constructs including nutrition-related knowledge as well as functional skills, like cooking skills. An exception was the Preschool–FLAT(Reference Tabacchi, Battaglia and Messina26), which assessed concepts that are not covered in other measures, such as assessing the relationship of body weight and food and children’s ability to assemble traditional foods to create a meal.
Four tools(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Liu, Su and Li29,Reference Ashoori, Omidvar and Eini-Zinab31,Reference Deesamer, Piaseu and Maneesriwongul32) did not report the method of administration, 5 tools(Reference Tabacchi, Battaglia and Messina26,Reference Amin, Lehnerd and Cash28,Reference Khorramrouz, Doustmohammadian and Amini30,Reference Williams, Quinn and Ramirez33,Reference Reynolds, Treu and Njike36) used a paper and pen format, while 3 tools(Reference Stjernqvist, Elsborg and Ljungmann27,Reference Naigaga, Pettersen and Henjum34,Reference Guttersrud and Petterson35) were administered electronically. All tools were self-reported by the students except for the Preschool–FLAT(Reference Tabacchi, Battaglia and Messina26) which was interview led by the child’s educator.
Scoring differed across tools including a combination of either Likert-scaled or true or false, and correct or incorrect questions. Five out of 11 tools incorporated task-based items, e.g. creating a healthy meal using images(Reference Tabacchi, Battaglia and Messina26,Reference Stjernqvist, Elsborg and Ljungmann27,Reference Liu, Su and Li29,Reference Williams, Quinn and Ramirez33,Reference Reynolds, Treu and Njike36) . Some of the tools did not indicate how the score was interpreted(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Ashoori, Omidvar and Eini-Zinab31,Reference Williams, Quinn and Ramirez33,Reference Guttersrud and Petterson35) but for the most part, higher scores were indicative of higher FL or NL.
Validity and reliability of existing tools
Nine(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25–Reference Williams, Quinn and Ramirez33) out of the 12 identified tools underwent content validity testing by a panel of experts including 5–29 experts (Table 2). Three tools(Reference Amin, Lehnerd and Cash28–Reference Ashoori, Omidvar and Eini-Zinab31) specifically assessed content validity using a modified Delphi approach with experts. Six(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Stjernqvist, Elsborg and Ljungmann27,Reference Khorramrouz, Doustmohammadian and Amini30–Reference Williams, Quinn and Ramirez33) out of the 12 tools assessed face validity, by either conducting interviews(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Khorramrouz, Doustmohammadian and Amini30–Reference Williams, Quinn and Ramirez33) or focus groups(Reference Stjernqvist, Elsborg and Ljungmann27) with their intended target population of the tool. Ten out of the 12 tools assessed structural/construct validity either using the Rasch model(Reference Naigaga, Pettersen and Henjum34,Reference Guttersrud and Petterson35) , confirmatory factory analysis(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Stjernqvist, Elsborg and Ljungmann27,Reference Liu, Su and Li29–Reference Ashoori, Omidvar and Eini-Zinab31) , the Known Group technique(Reference Deesamer, Piaseu and Maneesriwongul32), Structural Equation Modelling(Reference Tabacchi, Battaglia and Messina26) or between-group differences based on ONQI scores(Reference Reynolds, Treu and Njike36). Some tools also assessed convergent validity using a health literacy instrument(Reference Stjernqvist, Elsborg and Ljungmann27), using food intake as an outcome(Reference Stjernqvist, Elsborg and Ljungmann27) or using a Healthy Eating Index score(Reference Deesamer, Piaseu and Maneesriwongul32). One tool was assessed for its ability to detect change following a FL intervention(Reference Tabacchi, Battaglia and Messina26), while 2 tools measured change after a specific nutrition knowledge program(Reference Williams, Quinn and Ramirez33,Reference Reynolds, Treu and Njike36) .
Validity and reliability of the reviewed food and nutrition literacy tools for children and adolescents
CFA; confirmatory factor analyses; CVI, content validity index; CVR, content validity ratio; M-FNLIT, modified food and nutrition literacy; FNLQ-SC, food and nutrition literacy questionnaire for Chinese school-age children; FL, food literacy; THAI-NLAT, Thai-nutritional literacy assessment tool, preschool-FLAT, preschool-food literacy assessment tool; TFLAC, tool for food literacy assessment in children; CNL-E, Critical nutrition literacy-evaluation; MBL tool, menu board literacy tool; FLLANK, food label literacy for applied nutrition knowledge questionnaire; PCA, principal component analysis; SEM, structural equation model; EFA, explanatory factor analyses; ONQI, overall nutritional quality index; α, alpha; ICC, intraclass coefficient; KR-20, Kuder-Richardson-20; PSI, person separation index; ωt, McDonald’s omega; SE, self-efficacy; EDB, engagement in dietary behavior.
Seven tools reported overall internal consistency of their measure using Cronbach’s α (Reference Tabacchi, Battaglia and Messina26,Reference Stjernqvist, Elsborg and Ljungmann27,Reference Liu, Su and Li29–Reference Ashoori, Omidvar and Eini-Zinab31,Reference Naigaga, Pettersen and Henjum34,Reference Reynolds, Treu and Njike36) with internal consistency ranging from 0·77 to 0·90. Internal consistency across subscales was reported by 8 tools(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25–Reference Ashoori, Omidvar and Eini-Zinab31,Reference Guttersrud and Petterson35) , with internal consistency considered acceptable to high (Reference Taber42) for most tools’ subscales. The weakest internal consistency was observed in the subscale critical skill (α = 0·22) in the M-FNLIT tool(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Khorramrouz, Doustmohammadian and Amini30) and similarly, in the same critical skill subscale (α = 0·48) in the FNLIT tool(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25). The FNLQ-SC(Reference Liu, Su and Li29) had lower than acceptable scores across all subscales (α = 0·15–0·45). One tool(Reference Deesamer, Piaseu and Maneesriwongul32) reported overall internal consistency using Kuder-Richardson 20 test, with internal consistency of KR-20 = 0·83, and one tool(Reference Williams, Quinn and Ramirez33) using ordinal α for their 2 subscales, ranging from 0·78 to 0·90.
Six tools(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Stjernqvist, Elsborg and Ljungmann27,Reference Amin, Lehnerd and Cash28,Reference Khorramrouz, Doustmohammadian and Amini30,Reference Ashoori, Omidvar and Eini-Zinab31,Reference Reynolds, Treu and Njike36) reported test–retest reliability using Intraclass Correlation Coefficients (ICC) ranging from 0·64 to 0·93, suggesting moderate to excellent reliability (Reference Koo and Li43). Two tools(Reference Naigaga, Pettersen and Henjum34,Reference Guttersrud and Petterson35) reported on test–retest reliability using Person Separation Index (PSI), with values ranging from 0·79 to 0·90, and one tool(Reference Williams, Quinn and Ramirez33) reported on McDonald’s omega on their 2 scales ranging from 0·78 to 0·91.
Ratings for the risk of bias assessment are presented in Supplemental Table S2. Most of the included studies showed a ‘Very Good’ methodological quality for the psychometric properties which were tested, including all 12 studies sufficiently evaluating internal consistency and 8 studies assessing structural/construct validity(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25–Reference Stjernqvist, Elsborg and Ljungmann27,Reference Liu, Su and Li29–Reference Ashoori, Omidvar and Eini-Zinab31,Reference Naigaga, Pettersen and Henjum34,Reference Guttersrud and Petterson35) . Moreover, 7 studies(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Stjernqvist, Elsborg and Ljungmann27,Reference Amin, Lehnerd and Cash28,Reference Khorramrouz, Doustmohammadian and Amini30,Reference Ashoori, Omidvar and Eini-Zinab31,Reference Williams, Quinn and Ramirez33,Reference Reynolds, Treu and Njike36) tested reliability; however, 3 articles(Reference Stjernqvist, Elsborg and Ljungmann27,Reference Amin, Lehnerd and Cash28,Reference Williams, Quinn and Ramirez33) had a narrow time window between test and retest (e.g. 1 week), where a ‘Doubtful’ score was subsequently given. Furthermore, Preschool–FLAT(Reference Tabacchi, Battaglia and Messina26) received an ‘Inadequate’ score for responsiveness, since there was insufficient information about the intervention. No studies reported cross-cultural validity, measurement error or criterion validity. Overall, all 12 studies generally showed low risk of bias.
Discussion
This systematic review provides a comprehensive overview of published tools designed to measure FL and NL among children and adolescents. Twelve tools assessed some components of validity and/or reliability for specific target populations. The majority of tools targeted older children and adolescents (9–18 years of age), and one tool targeted preschoolers (3–6 years of age). FL and NL have primarily been studied among adults(Reference Yuen, Thomson and Gardiner15,Reference Amouzandeh, Fingland and Vidgen16) and research examining the use and applicability of these concepts among children and adolescents is still emerging. To our knowledge, this review is the first to systematically assess what FL and NL tools have been developed among children and adolescents.
All the tools underwent some testing of validity. Five tools were validated for most types of validity, including content, face and construct(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Stjernqvist, Elsborg and Ljungmann27,Reference Khorramrouz, Doustmohammadian and Amini30–Reference Deesamer, Piaseu and Maneesriwongul32) , showing a rigorous process in designing and testing these tools. Most of the tools demonstrated acceptable to good internal consistency(Reference Tavakol and Dennick44). However, 6 tools(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Stjernqvist, Elsborg and Ljungmann27–Reference Liu, Su and Li29,Reference Ashoori, Omidvar and Eini-Zinab31,Reference Deesamer, Piaseu and Maneesriwongul32) had subscales with either poor or questionable internal consistency scores. This suggests that further adaptions may be needed to improve consistency among these subscales. Six out of 12 tools assessed test–rest reliability(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Stjernqvist, Elsborg and Ljungmann27,Reference Amin, Lehnerd and Cash28,Reference Khorramrouz, Doustmohammadian and Amini30,Reference Ashoori, Omidvar and Eini-Zinab31,Reference Reynolds, Treu and Njike36) and were able to show that these tools could sufficiently replicate a similar result over time. Only 3 tools assessed whether they could detect change after an intervention or a nutrition education program(Reference Tabacchi, Battaglia and Messina26,Reference Williams, Quinn and Ramirez33,Reference Reynolds, Treu and Njike36) and 2 of these tools focused specifically on sub-areas of NL. The Thai-NLAT(Reference Deesamer, Piaseu and Maneesriwongul32), the FNLAT(Reference Ashoori, Omidvar and Eini-Zinab31), the FNLIT(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25) and its adaptions(Reference Khorramrouz, Doustmohammadian and Amini30) have been shown to have the strongest psychometric properties. However, important factors need to be considered when using these tools, such as the context and culture within which these tools were developed and tested.
FL and NL are highly contextual(Reference Perry, Thomas and Samra3), influenced by the geography and its food system as well as the cultural and social context. The current tools have been developed for specific populations from countries around the world. For instance, the TFLAC(Reference Amin, Lehnerd and Cash28) has one item that focuses on food groups specific to their national food guidelines, whereas the FNLIT(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25) includes foods that are contextually and culturally appropriate such as Tafi, which is a type of chocolate. As suggested by Beaton et al. (Reference Beaton, Bombardier and Guillemin45), a cross-cultural adaptation and validation of these existing tools is needed to ensure tools are appropriate for specific populations who might differ in language, cultural background as well as public health messaging.
In addition, FL and NL need to be conceptualised in an age-dependent manner, where younger children are not expected to develop the same level of complex skills as older teens or adults given their stages of cognitive development and reduced level of independence to make nutrition decisions. As mentioned, most of the existing tools targeted older children (9–18 years old), while only one tool targeted the preschoolers (3–6 years old). Tools developed for younger children such as the Preschool-FLAT(Reference Tabacchi, Battaglia and Messina26) are centered around general concepts like recognizing foods and building balanced plates. Using task-based approaches, specific questions that address these general concepts include: ‘Paint the foods suitable for lunch/dinner’, and ‘Compose a typical Sicilian meal by choosing foods among those shown’. On the other hand, tools developed for older teenagers such as the FNLAT(Reference Ashoori, Omidvar and Eini-Zinab31) focus on more complex nutrition knowledge and food choices that are more appropriate for this age group. Examples of questions include: ‘Which of the following foods are good sources of Calcium?’, and ‘If I go to grocery stores independently, I can easily ask the seller for the information I need.’ Given the small number of current tools available and the increase in FL and NL programs focusing on children and adolescents in recent years(Reference Brooks and Begley46), research should focus on developing and validating tools assessing FL and NL among children and/or adolescents, especially in younger children.
While FL and NL are related, there are important distinctions between their respective definitions. NL focuses largely on the knowledge and aptitude to obtain, interpret and use nutrition information whereas, FL is more comprehensive and encompasses a collection of inter-related knowledge, skills and behaviours, and extends to other determinants that may influence food decisions, like social and cultural factors(Reference Truman, Lane and Elliott4). This is reflected in the type of items and constructs included in the FL and NL tools. For example, 4 of the 12 tools included in this review measured both FL and NL(Reference Doustmohammadian, Omidvar and Keshavarz-Mohammadi25,Reference Liu, Su and Li29–Reference Ashoori, Omidvar and Eini-Zinab31) , their constructs assessed 2 universal domains, including both knowledge and skills. In comparison, the tools that only measured NL(Reference Deesamer, Piaseu and Maneesriwongul32–Reference Reynolds, Treu and Njike36), focused on cognitive competencies – for instance, Thai-NLAT(Reference Deesamer, Piaseu and Maneesriwongul32) included knowledge-based questions evaluating one’s understanding of nutrition information, food safety and energy balance.
Most definitions of FL and NL do not acknowledge life-stage specific criterion. The widely used definition of FL, conceptualised by Vidgen and Gallegos(Reference Vidgen and Gallegos6), consists of 4 domains, some of which might not be applicable for children and adolescents. For instance, the plan and manage domain assesses one’s ability to make feasible food decisions in balancing personal needs, like nutrition, taste and hunger, with available resources(Reference Vidgen and Gallegos6). This domain may not be appropriate for young children who have minimal independence over their food decisions. The Preschool–FLAT was informed by FL definition described by Vidgen and Gallegos(Reference Vidgen and Gallegos6) and the authors stated they modified this definition to incorporate knowledge and skills suitable for preschoolers but provided limited detail on how those concepts were derived. While the emerging framework developed by Slater et al. (Reference Slater, Falkenberg and Rutherford47) identified FL dimensions suitable for youth, none of the identified tools used this youth-focused framework. Continued efforts are needed to develop a comprehensive definition and framework of FL and NL appropriate for children. These efforts will help facilitate and inform developmentally appropriate assessment tools in the future.
An important limitation in the current tools assessing FL and NL among adults(Reference Yuen, Thomson and Gardiner15,Reference Amouzandeh, Fingland and Vidgen16) is the lack of objective, i.e. task-based, assessment of FL or NL. Five of the tools included in this current review used task-based assessment approach. The Preschool–FLAT(Reference Tabacchi, Battaglia and Messina26) incorporated visuals to assess certain FL constructs – for instance, one item asks the respondents to select which picture of food is the healthier option or which portion size is either small, medium or big. Similarly, the FLLANK assesses one’s ability to choose healthier food options given information from a nutrition facts label or an ingredients list(Reference Reynolds, Treu and Njike36). The respondent is given 2 choices and is asked to determine which option is more nutritious. Incorporating task-based items can help reduce reporting and social desirability bias(Reference Garcia, Reardon and McDonald48) and, thus, future FL and NL measures for children should include both subjective, i.e. self or proxy reports and objective, i.e. task-based activities.
Findings from this review should be interpreted with some limitations. First, only articles that explicitly developed FL or NL assessment tools were included. It is possible that relevant articles may have been missed if they did not directly mention assessing literacy. However, our search strategy did include the term ‘food skills’ to help further yield an extensive pool of studies. Due to the variability and specificity across target audiences and the various frameworks used to inform their development, comparability across tools was limited. Despite these limitations, this review provides a current snapshot of existing tools assessing FL and NL among children and adolescents.
Conclusion
Our systematic review identified 12 tools that measure FL or NL among children and adolescents in which 4 of these tools assess specific subareas of NL. The majority of tools targeted older children and adolescents (9–18 years of age) and only one tool targeted preschoolers (3–6 years of age). Most of the tools assessed validity or reliability within a specific target population. In addition, most FL and NL frameworks have been contextualised among adults. Considering cognitive development as well as constraints on children’s food decisions due to their limited independence, a comprehensive and developmentally appropriate definition and framework of FL and NL is needed for children. These efforts will help inform FL and NL assessment tools in the future(Reference Velardo9,Reference Schwarzer, Fuchs, Conner and Norman39–Reference Nutbeam41) .
Acknowledgements
Acknowledgements: We would like to thank our research librarian, Karen Nicholson, for her expertise and guidance in developing key search terms and choosing appropriate databases. Financial support: This research was supported by the Helderleigh Foundation. The Helderleigh Foundation had no role in the design, analysis or writing of this article. Conflict of interest: The authors declare no conflict of interest. Authorship: N.C. and J.H. formulated the research question. N.C. and M.P. conducted the systematic search, screened titles, abstracts, and full-text articles, independently. N.C. extracted information from the final articles into the tables, while M.P. ensured the information was extracted appropriately by double-checking. Any differences throughout the review process were discussed and resolved. Both N.C. and M.P. wrote the manuscript with critical revision and input provided by J.H. and D.W.L.M. Ethics of human subject participation: Not applicable.
Supplementary material
For supplementary material accompanying this paper visit https://doi.org/10.1017/S1368980021004389
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