Exploring the relationship between food literacy and food insecurity: a systematic review

Abstract

BACKGROUND/OBJECTIVES

Interest in food insecurity (FI) has intensified amid global efforts to address dietary and nutritional issues. Food literacy (FL) has emerged as a key competency for promoting healthy eating behaviors and potentially mitigating FI. This systematic review synthesized evidence on the relationship between FL and FI by summarizing their definitions and components, comparing measurement tools, and examining overall trends and characteristics of their association.

MATERIALS/METHODS

This review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines and the Joanna Briggs Institute (JBI) framework. Studies examining FL and FI as primary variables were identified from PubMed, Web of Science, and Google Scholar. Nine studies published between 2019 and 2025 were included. Methodological quality was assessed using JBI checklists, and findings were synthesized narratively due to study heterogeneity.

RESULTS

The included studies employed cross-sectional, quasi-experimental (pre–post), mixed-methods, and cluster randomized controlled designs. FI was primarily assessed using definitions proposed by the Food and Agriculture Organization or the United States Department of Agriculture. FL was commonly measured using frameworks based on Vidgen and Gallegos (2014). Most cross-sectional studies reported an inverse relationship between FI and FL. However, one cross-sectional study found no significant relationship, suggesting that sociocultural and economic factors may influence this association. Intervention studies generally showed improvements in FL and reductions in FI or related behaviors.

CONCLUSION

Most studies indicated that individual FL levels were associated with FI status. In some studies, this relationship appeared to be influenced by sociodemographic, economic, and cultural factors, although these findings were not consistently reported. The findings suggested that combining FL education with structural strategies may more effectively alleviate FI. Future research should use standardized measurement tools and longitudinal or randomized controlled designs to clarify the observed associations and potential mechanisms underlying the relationship between FL and FI.

INTRODUCTION

As global mortality from chronic diseases such as obesity and diabetes continues to rise, the importance of dietary management for disease prevention is being increasingly emphasized [1,2]. However, modern dietary patterns are characterized by a higher consumption of calorie-dense yet nutrient-poor foods, the normalization of processed foods and eating out, and a general decline in the overall dietary quality [3,4]. While the intake of fruits, vegetables, and whole grains has decreased, the consumption of sodium and saturated fat has increased [5,6]. Nutritional imbalances resulting from these dietary changes reportedly account for over 50% of diet-related deaths and approximately 66% of disability-adjusted life years [5]. According to the World Health Organization (WHO), major chronic diseases such as cardiovascular disease, hypertension, and diabetes are closely associated with dietary intake, and dietary improvement can prevent approximately 20% of deaths worldwide [7].

Among the various approaches to addressing modern dietary challenges, growing global attention has been directed toward food security (FS) [8,9]. FS refers to “a state in which all people, at all times, have physical, social, and economic access to sufficient, safe, and nutritious food to meet their dietary needs for an active and healthy life” [10]. The Committee on World Food Security emphasizes that achieving FS requires adequate sanitation, health services, and social infrastructure [11]. However, when individuals face barriers, such as low income, limited transportation, or insufficient social support, the stable access to desired food becomes difficult, consequently leading to food insecurity (FI) [12]. The United States Department of Agriculture (USDA) defines FI as “the limited or uncertain availability of nutritionally adequate and safe foods, or the inability to acquire such foods in socially acceptable ways” [13]. FI decreases access to nutritious foods, reduces dietary quality, and contributes to nutritional imbalance. It also serves as a socioeconomic inequality and health status indicator beyond mere income deprivation [14,15]. Through the Sustainable Development Goals, the United Nations designated the elimination of FI and the achievement of FS as global priorities [16]. According to the State of Food Security and Nutrition in the World 2023, jointly published by the Food and Agriculture Organization (FAO), International Fund for Agricultural Development, United Nations Children's Fund, World Food Programme, and WHO [17], approximately 30.4% of the global population experiences severe FI [18]. This finding highlights that FI remains a critical global issue despite international efforts.

In this context, food literacy (FL) has gained attention as a core competency for alleviating FI and promoting healthy eating behaviors [19,20,21]. Numerous studies have reported a close association between these 2 concepts [2,22,23]. FL is derived from the concept of health literacy which refers to the ability to access, understand, evaluate, and apply health-related information for the maintenance and promotion of health, disease prevention, and healthcare utilization [24,25]. Health literacy encompasses the subdomains of nutrition literacy and FL. While nutrition literacy primarily focuses on knowledge acquisition and information interpretation, FL emphasizes behavior-oriented competencies, including food preparation, cooking, and consumption [26,27]. Higher levels of FL are associated with greater consumption of fruits and vegetables, reduced intake of processed foods, improved dietary quality, and better overall nutritional and health outcomes [20,28,29]. FL, thus, contributes to enabling individuals, households, and communities to sustain and strengthen healthy eating practices, thereby could play a important role in mitigating the experience of FI [22,30].

Previous studies have suggested that FL and FI interrelated. One study found that individuals experiencing higher FI levels were more likely to engage in less healthy dietary behaviors, such as consuming energy-dense, nutrient-poor foods; irregular eating patterns; or binge eating [31]. Lower levels of FL have also been observed alongside poorer dietary behaviors and nutritional status, particularly among socioeconomically vulnerable populations such as young adults and older adults [22,31]. FL is recognized as a modifiable competency that can be improved through education and may be conceptually related to the relationship between FI and dietary behaviors. However, inconsistencies in the measurement tools, conceptual definitions, and study designs across existing research make it difficult to establish coherence in interpretation. Moreover, findings have been accumulated in fragmented forms under different contexts and study frameworks, consequently limiting the comprehensive understanding of the overall relationship between the 2 variables. Therefore, this systematic review aimed:

• 1) to review previous studies on FL and FI and summarize the definitions and key components of both concepts, and

• 2) to compare and analyze the major measurement tools and findings used in the existing studies and examine the trends and characteristics of the relationship between FL and FI.

MATERIALS AND METHODS

This study was conducted as a systematic review to synthesize evidence on the association between FL and FI, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines [32]. The research question guiding this review was: “How is food literacy associated with food insecurity across diverse population groups?” Given the substantial heterogeneity in study designs, populations, measurement tools, and outcome measures among the included studies, findings were synthesized using a narrative synthesis approach rather than statistical meta-analysis [33].

Information sources and search strategy

A comprehensive literature search was conducted between July and September 2025 using the PubMed, Web of Science, and Google Scholar databases. The following search strategy was applied: “food literacy” AND (“food insecurity” OR “food security”). As studies jointly examining FL and FI have emerged relatively recently, no restrictions on publication year were applied to minimize the risk of omitting relevant evidence.

Eligibility criteria

Studies were eligible for inclusion if they were original research articles that assessed both FL and FI as primary variables and reported their relationship using quantitative and/or qualitative methods. No restrictions were placed on participants’ age or country of origin. Studies were excluded if they assessed only 1 of the 2 variables, focused solely on related concepts such as nutrition literacy or health literacy, or were not original research (e.g., reviews, editorials, or commentaries). In addition, theoretical papers or exploratory studies that were not directly aligned with the research question were excluded.

Study selection process

The initial database search identified 191 records. After removing duplicates, titles and abstracts were screened, and 151 studies were excluded because they measured only 1 of the 2 variables or focused on related concepts. During full-text review, an additional 24 studies were excluded for not being original research or for not addressing both variables as primary outcomes, and 7 studies were excluded for not aligning with the study objectives. Ultimately, 9 studies were included in the final analysis. The study selection process is illustrated in the PRISMA flow diagram (Fig. 1).

Fig. 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart of search.

FL, food literacy; FI, food insecurity.

Quality appraisal

The methodological quality of the included studies was assessed using the Joanna Briggs Institute Critical Appraisal Checklists [34], with tools selected according to study design. Specifically, the checklist for analytical cross-sectional studies (8 items), quasi-experimental studies (9 items), and randomized controlled trials (RCTs; 13 items) were applied as appropriate. Each item was rated as Yes, No, Unclear, or Not applicable. Quality appraisal was conducted independently by 2 reviewers. To ensure consistency, assessment criteria were agreed upon in advance. Unclear was assigned when an item may have been addressed but was insufficiently reported, whereas No was used only when the item was clearly absent or structurally not feasible given the study design. Discrepancies between reviewers were resolved through discussion and re-examination of the original articles, with consultation from a third reviewer when necessary. Overall methodological quality was categorized as High, Moderate, or Low based on the extent to which key methodological criteria were met.

Data extraction and synthesis

Data were extracted using a standardized form and included information on authors, year of publication, country of study, study objectives, definitions and measurement tools for FL and FI, and key findings. Data extraction was performed by one reviewer and cross-checked by a second reviewer to ensure accuracy. Due to heterogeneity in study designs, measurement instruments, and outcome measures, a meta-analysis was not conducted. Instead, results were synthesized narratively. Studies were first grouped by study design and then compared according to conceptual definitions and components of FL and FI, characteristics of measurement tools, the direction and consistency of associations or intervention effects, and study populations and contexts. Common patterns, differences, and contextual factors across studies were identified and integrated narratively. Key findings are summarized in tables, with similarities and differences across studies described in the text.

RESULTS

Summary of the included studies

Table 1 summarizes the main characteristics of the 9 studies meeting the inclusion criteria. These studies published between 2019 and 2025 were conducted across diverse cultural and regional contexts, including Australia, the United States, Iran, Lebanon, Saudi Arabia, and South Korea. All studies examined the relationship between FL and FI. The study designs varied and comprised cross-sectional design (n = 5), mixed-methods design incorporating surveys and interviews (n = 1), quasi-experimental analysis with pre–post designs (n = 2), and cluster RCT design (n = 1). Five studies analyzed the correlations between the FL and FI; 3 assessed the effects of FL interventions by examining the pre–post changes; and 1 explored the relationship between FL and food consumption behaviors. The samples were recruited through community organizations (n = 5), schools (n = 2), and nationally stratified sampling (n = 2). The study durations ranged from 4 to 6 weeks (n = 3) to over 2 yrs (n = 1), with one program interrupted by coronavirus disease 2019 and resumed after approximately 3 yrs. The participant groups included low-income adults, elementary school students, university students, older adults, youth–parent dyads, and household food purchasers, with sample sizes ranging from 38 to 3,321. The primary variables measured were FL and FI, along with the subcomponents such as eating behaviors, cooking confidence, nutrition knowledge, and food consumption frequency.

Table 1. Summary of included studies.

No.	Studies	Country	Research design	Study purpose	Target population	Sampling methods	Sample size (n)	Study duration	Key measures
1	Begley et al. [22]	Australia	Cross-sectional survey	To investigate the relationship between FL behaviors and FI among participants enrolling in a state-wide FL program.	Low- to middle-income adults attending a FL program (aged ≥ 18)	Recruitment through community groups and open public programs for low- to middle-income adults	1,433	2 yrs (May 2016–April 2018)	FL behaviors, dietary behaviors, demographics, FI
2	Khorramrouz et al. [35]	Iran		To assess the association between household FI and FNLIT among children.	Primary school children (aged 9–12)	Multi-stage cluster random sampling from schools in Mashhad	315	4 mon (December 2018–March 2019)	FNLIT, HFIAS, BMI, demographics
3	Hoteit et al. [38]	Lebanon		To assess parents FL and adolescents nutrition literacy and their impact on household FS, adolescent FS, malnutrition, and anemia.	Lebanese parents (aged 18–64) + children (aged 10–19)	Stratified cluster sampling from 8 Lebanese governorates	450	4 mon (mid-March to mid-July 2022)	FL, nutrition literacy, household FS, adolescent FS, malnutrition, anemia
4	Nam et al. [41]	South Korea		To examine how FL affects healthy food consumption behaviors and willingness to pay for healthier foods among food secure and insecure households.	Adults (aged 19–75)	Stratified probability sampling; data from the 2022 CBSF, KREI	3,321	2 mon (June 10–August 21 2022)	FL (knowledge, attitude, behavior), intention to pay for healthier food, FS status, demographics
5	Hanbazaza et al. [36]	Saudi Arabia		To assess the prevalence of FI, evaluate the level of FL, and examine food intake among low-income households in Saudi Arabia, as well as to determine the associations among these variables.	Low-income adults (aged ≥ 18)	Recruitment through community groups and open public programs for low- middle-income adults in Jeddah, Saudi Arabia	483	June 2024	FL, FI, food intake
6	West et al. [2]	Australia	Mixed-methods (pre–post survey + interviews)	To evaluate the impact of the NEST program on FS and FL.	Low socioeconomic status adults	Convenience sampling via community organizations	Pre–post: 21; Interviews: 17	6 weeks	FS, cooking confidence, nutrition knowledge, dietary intake
7	Morgan et al. [40]	USA	Pre–post survey	To evaluate whether a FL-focused laboratory class improves FL-based skills, behaviors, and self-efficacy and reduces FI among undergraduate students.	Nutrition, dietetics, fermentation science majors undergraduate students	Convenience sampling (basic food science lab at appalachian state university)	Pre-test: 51; Post-test: 39	11 weeks (1 academic semester)	FL behaviors, self-efficacy, and FS indicators
8	Kearsey et al. [37]	Australia	Quasi-experimental (pre–post survey + 6-mon follow-up)	To evaluate the short- and longer-term impacts (6-mon follow-up) of the NEST program on FS, FL and dietary intake in vulnerable adults.	Vulnerable adults at high risk of FI, across 6 major Australian cities (aged ≥ 18)	Recruited via community organizations	Pre-survey: 636; Pre–post: 258; 6-mon follow-up: 20	June 2019–July 2022 *COVID-19 suspension (Mar 2020–late 2021)	FL (nutrition knowledge, cooking confidence, food preparation), FS, dietary behaviors (intake)
9	Royer et al. [39]	USA	12-mon cluster randomized controlled trial	To examine whether the FLAN intervention improves FS and fruit and vegetable intake compared to a nutrition information-only control.	Physically inactive, Spanish/English-speaking older adults (aged ≥ 50)	Recruited through local community centers in San Francisco bay area	Total: 39; FLAN: 13; Intervention: 26	12 mon	FI, daily
									FV intake

FL, food literacy; FI, food insecurity; FNLIT, Food and Nutrition Literacy; HFIAS, Household Food Insecurity Access Scale; BMI, body mass index; FS, food security; CBSF, consumer behavior survey for food; KREI, Korea Rural Economic Institute; NEST, nutrition education and skills training; FLAN, food literacy and nutrition; FV, fruit and vegetable.

Definitions of FI and FL

Table 2 presents the FI and FL definitions used in the 9 studies included in this systematic review. Most studies based their conceptualization of FI on the definitions proposed by the FAO or the USDA. Some adapted these definitions to fit their specific research purposes. Studies following the FAO definition [2,22,35,36,37] described FI as a condition in which one’s physical, social, or economic access to adequate and safe food is limited or uncertain. Those adopting the USDA definition [38,39] conceptualized FI as an economic and social condition that is characterized by a limited or uncertain access to sufficient quantities and quality of food. Morgan et al. [40] emphasized the lack of “sufficient quantity of food” whereas Nam et al. [41] highlighted “limited access to and instability of nutritionally adequate food” succinctly capturing the essential elements of the existing definitions.

Table 2. Definitions of FI and FL in the included studies.

No.	Studies	Country	FI	FL
1	Begley et al. [22]	Australia	Uncertain or limited physical, social and economic access of individuals and households to sufficient, safe, nutritious, and culturally relevant food (FAO, 2008).	Practical food knowledge and skills encompassing the planning, management, selection, preparation and eating of food [30].
2	Khorramrouz et al. [35]	Iran	Limited or uncertain access to nutritionally adequate and safe food or inability to acquire acceptable foods in socially acceptable ways (FAO, 2008).	Relatively new term that reflects the technical, cultural and ethical aspects of the foods beyond just a source of satisfying the caloric requirements.
3	Hoteit et al. [38]	Lebanon	State of being unable to access a sufficient quantity and quality of food (USDA, 2006).	Collection of inter-related knowledge, skills and behaviors required to plan, manage, select, prepare and eat food to meet needs and determine intake [30].
4	Nam et al. [41]	South Korea	Inadequate and unstable access to nutritious food.	Practical aspects of maintaining a healthy diet and encompasses skills such as planning, managing, selecting, preparing and consuming food [30].
5	Hanbazaza et al. [36]	Saudi Arabia	Lack sufficient socioeconomic or physical access to adequate, nutritious, and safe food that meets their dietary needs and preferences for a healthy, active life (FAO, 2021).	Skills, behaviors, and knowledge needed to organize, manage, choose, prepare, and consume food in ways that meet dietary needs and support informed choices [30].
6	West et al. [2]	Australia	Limited or uncertain access to nutritionally adequate and safe food or inability to acquire acceptable foods in socially acceptable ways (FAO, 2008).	Collection of inter-related knowledge, skills and behaviors required to plan, manage, select, prepare and eat food to meet needs and determine intake [30].
7	Morgan et al. [40]	USA	Lack of access to enough to food.	Ability to plan, select, prepare and eat food [30].
8	Kearsey et al. [37]	Australia	Limited physical, social, and economic access to sufficient, safe and nutritious food to meet dietary needs and food preferences (FAO, 2021).	Skills and behaviours, health and food choices, nutrition knowledge and the ability to prepare and consume food required for optimal health [30].
9	Royer et al. [39]	USA	Economic and social condition involving limited or uncertain access to adequate food (USDA, 2023).	Proficiency in food related skills and knowledge.

FI, food insecurity; FL, food literacy; FAO, Food and Agriculture Organization; USDA, United States Department of Agriculture.

Regarding FL, most studies adopted the definition proposed by Vidgen and Gallegos [30]. Based on this framework, studies [2,22,36,38,40,41] consistently defined FL as a set of knowledge, skills, and behaviors required for food planning, managing, selecting, preparing, and eating. The 4 domains outlined by Vidgen and Gallegos [30], namely, planning and management, selection, preparation, and eating, refer to efficient resource and time management, the ability to interpret food information and make appropriate choices, the use of safe and effective cooking techniques, and the maintenance of healthy eating practices, respectively. Kearsey et al. [37] extended this definition by emphasizing the practical competencies necessary for optimal health. In contrast, Khorramrouz et al. [35] used the term “Food and Nutrition Literacy (FNLIT)” framing it as a comprehensive concept encompassing not only caloric adequacy but also the technical, cultural, and ethical dimensions of food. Royer et al. [39] provided a more concise definition, describing FL as food-related knowledge and skill proficiency.

Measurement of FI and FL

Table 3 summarizes the measurement tools, items, and main findings concerning the associations between FI and FL in each work. FI was assessed using diverse approaches. Some studies employed single-item questions to directly assess whether individuals or households were able to purchase sufficient food during a recent period [22,41]. The structured scales included the Household Food Insecurity Access Scale, Arab Family Food Security Scale, Arabic version of the Food Insecurity Experience Scale, and self-reported adolescent scales capturing financial constraints, food depletion, deficiencies in meal quantity and quality, and experiences of hunger [35,38]. Other studies used the USDA 6-item short form to measure FI at the individual level [2,37,39,40]. FL was also assessed using various instruments depending on the study objectives and populations. Begley et al. [22] employed an FL behavior checklist, while Khorramrouz et al. [35] utilized the FNLIT tool encompassing the cognitive and skill domains. Hoteit et al. [38] and Hanbazaza et al. [36] employed the Short Food Literacy Questionnaire to evaluate the information use, dietary guideline awareness, daily application, and critical appraisal. Nam et al. [41] used a Korean version encompassing knowledge, attitudes, and behaviors, including willingness to pay more for healthy foods. West et al. [2] and Kearsey et al. [37] applied survey instruments that focus on cooking confidence, food-related behaviors, and nutrition knowledge to assess the pre–post changes following interventions. Morgan et al. [40] measured skills and self-efficacy to evaluate the intervention effects, while Royer et al. [39] utilized fruit and vegetable intake frequency as an indirect indicator of changes in FL.

Table 3. Measurement of FI and FL in the included studies.

No.	Studies	Country	Research design	Measurement tools/key concepts measured
				FI/FS	FL
1	Begley et al. [22]	Australia	Cross-sectional survey	Single item on financial access	14-item FL behaviors checklist
				- Ran out of money for food in the past month?	- FL behaviors (15 items)
					- Dietary behaviors (4 items)
					- FL-related practices (3 items)
2	Khorramrouz et al. [35]	Iran		HFIAS	40-item validated questionnaire measuring FNLIT
				- Household FI due to financial limits	- Cognition domain, Skills domain
3	Hoteit et al. [38]	Lebanon		1. AFFSS	SFLQ
				- Household food insufficiency	- Information, Guideline knowledge, Daily application, Critical evaluation
				2. Self-reported adolescent-level FS scale
				- Adolescent household FI
4	Nam et al. [41]	South Korea		Self-reported adequacy of financial resources (adapted from validated Korean tools)	Adapted from prior validated Korean tools
				- “Did you have sufficient economic resources to purchase an adequate quantity and variety of food for your family in the last 12 mon?”	- Knowledge (10 items)
					- Attitude (4 items)
					- Behavior (1 item)
5	Hanbazaza et al. [36]	Saudi Arabia		Arabic version of the FIES	SFLQ
				- Conditions and behaviors experienced in the previous 12 mon	- Functional, interactive, and critical skills
6	West et al. [2]	Australia	Mixed-methods (pre–post survey + interviews)	USDA 6-item short form (modified for 6 weeks)	Tools adapted from existing validated surveys
				- Individual-level FI (food depletion, inability to afford healthy meals, meal skipping due to financial reasons, and hunger without eating)	- Cooking confidence (6 items)
					- Food behaviors (8 items)
					- Nutrition knowledge (4 items)
7	Morgan et al. [40]	USA	Pre–post survey	Modified USDA 6-item short form (3 questions)	Adapted from validated tools (Likert scale: confidence, behavior frequency)
				- Food affordability, portion reduction sizes or skipping meals, eating less due to lack of money	- FL-based skills (4 items)
					- FL-based self-efficacy (9 items)
8	Kearsey et al. [37]	Australia	Quasi-experimental (pre–post survey + 6-mon follow-up)	USDA 6-item short form	Custom 36-item questionnaire
				- Individual-level FI (running out of food, inability to afford healthy meals, reduced meal size/frequency, eating less than needed, skipping meals)	- Nutrition knowledge (5 items)
					- Cooking confidence (3 items)
					- Food preparation behaviors (4 items)
					- Dietary intake (4 items)
9	Royer et al. [39]	USA	12-mon cluster randomized controlled trial		Intervention content aligned with practical FL skills; FV intake measured via adapted NHANES FFQ
					- FV intake (60 items)
					Frequency of FV consumption over the past 12

FI, food insecurity; FL, food literacy; FS, food security; HFIAS, Household Food Insecurity Access Scale; FNLIT, Food and Nutrition Literacy; AFFSS, Arab Family Food Security Scale; SFLQ, Short Food Literacy Questionnaire; FIES, Food Insecurity Experience Scale; USDA, United States Department of Agriculture; FV, fruit and vegetable; NHANES, National Health and Nutrition Examination Survey; FFQ, food frequency questionnaire.

Key findings on FL and FI

Table 4 summarizes the key findings on the association between FL and FI across studies. To further examine these findings from a domain-specific perspective, additional results are presented in Supplementary Table 1. Begley et al. [22] identified low confidence in the budgeting and cooking skills as the key predictors of FI, whereas the price comparison behavior served as a protective factor. In addition, financial management capacity related to food purchasing was reported as an important factor in differentiating FI status. Khorramrouz et al. [35] and Hoteit et al. [38] found that children and adolescents from food-insecure households were significantly more likely to exhibit lower FL scores. Hoteit et al. [38] further reported that lower parental education levels, lower household income, and larger household size were significantly associated with household FI. Nam et al. [41] reported that food-insecure households scored lower in terms of knowledge, attitudes, behaviors, and willingness to pay for healthy food. Economic status was identified as an important factor influencing willingness to pay for healthier food across groups. The path from attitude to behavior was significant, but direct paths among knowledge, attitude, behavior, and willingness to pay were not. Conversely, Hanbazaza et al. [36] found no significant difference between FL and FI levels despite a high FI prevalence among participants who generally demonstrated adequate FL. Higher FI was also associated with a lower consumption of the key food groups.

Table 4. Key findings on FL and FI in the included studies.

No.	Studies	Country	Research design	Key findings on the association between FL and FI
1	Begley et al. [22]	Australia	Cross-sectional survey	- The FI group had lower proportions of participants demonstrating confidence in managing money to buy healthy food, confidence in cooking, and the use of healthy ingredients.
				- Low confidence in managing money to buy healthy food and lack of cooking skills were identified as strong predictors of FI, whereas comparing food prices was identified as a protective factor.
				- FL behavior variables provided acceptable discriminatory power.
2	Khorramrouz et al. [35]	Iran		- Children from FI households showed lower total FNLIT scores, with differences observed in cognitive domains and in skill domains.
				- Children with low FNLIT were nearly 3 times more likely to live in FI households, after adjusting for sociodemographic variables.
3	Hoteit et al. [38]	Lebanon		- The 68.2% of the households and 54.0% of the adolescents were FI.
				- Households with low-educated parents, crowded households, and 78.1% of parents with low FL were classified as FI.
				- Parental with low FL was associated with a 2.7-fold increase in the odds of household FI and having more than one child and a monthly income of ≤ 1.5 million LBP were also significant predictors of FI.
4	Nam et al. [41]	South Korea		- FI households showed lower scores in knowledge, attitude, behavior, and intention to pay a higher price for healthier food.
				- Knowledge, attitude, and behavior were associated with intention to pay a higher price for healthier food, with the pathway from knowledge to behavior significant in all groups.
				- FI group, the pathway from attitude to behavior was also significant, whereas knowledge, attitude, and behavior all showed no significant pathways to the intention to pay for healthier food.
				- Economic status and knowledge were important factors influencing willingness to pay across all groups.
5	Hanbazaza et al. [36]	Saudi Arabia		- Most participants demonstrated adequate FL, although the prevalence of FI was also high.
				- No significant difference was found between the levels of FL and FI.
				- Higher levels of FI were associated with lower intake of major food groups.
6	West et al. [2]	Australia	Mixed-methods (pre–post survey + interviews)	- After intervention FI decreased and FL (cooking confidence, food behaviors, nutrition knowledge) increased.
				- In the interviews, participants reported improvements in cooking confidence, food choices, and eating habits, but noted that actual practice could be constrained by practical budget limitations.
7	Morgan et al. [40]	USA	Pre–post survey	- FS status did not change significantly.
				- FL-related skills and self-efficacy measures improved.
8	Kearsey et al. [37]	Australia	Quasi-experimental (pre–post survey + 6-mon follow-up)	- After intervention FS improved, with corresponding reductions in both low and very low FS.
				- Nutrition knowledge, cooking confidence, food preparation behaviors, and the intake of vegetables, fruits, and water increased.
				- In a 6-mon follow-up subgroup, cooking confidence continued to improve, alongside sustained increases in vegetables and fruit intake.
9	Royer et al. [39]	USA	12-mon cluster randomized controlled trial	- Compared to the control group, the intervention group had lower odds of FI at 12 mon.
				- Increases in fruit and vegetable servings at 6 mon were correlated with reductions in FI at 12 mon.

FL, food literacy; FI, food insecurity; FNLIT, Food and Nutrition Literacy; LBP, Lebanese pound; FS, food security.

Intervention studies generally showed that the FL improvements were linked to FI reductions. West et al. [2] found that after an educational program, the FI levels decreased, while all FL domains significantly improved, although the participants noted that budget constraints limited practical application. Participants reported that economic and budgetary constraints remained barriers to implementing newly acquired food-related skills. Kearsey et al. [37] reported increased FS and decreased FI following intervention, along with improvements in nutrition knowledge, cooking confidence, food preparation behaviors, and vegetable, fruit, and water intake. Cooking confidence and vegetable and fruit consumption remained higher at the 6-mon follow-up. Morgan et al. [40] observed no significant changes in FI but found enhanced FL skills and self-efficacy. This result suggests a potential indirect effect. Meanwhile, in a 12-mon RCT, Royer et al. [39] reported that intervention group participants showed significantly lower odds of FI, with the increased fruit and vegetable intake negatively correlated with FI.

DISCUSSION

This review synthesized studies conducted across various countries and population groups to examine the relationship between FL and FI. Multiple cross-sectional studies [22,35,38,41] reported that lower levels of FL were associated with a higher likelihood of FI, with key risk factors including lack of cooking confidence, difficulties in budget management, and inadequate food selection behaviors. Hoteit et al. [38] further identified associations between parental education, income, FL levels, and children’s FI. Previous research has also reported that sociodemographic and economic characteristics are significantly associated with both FL and FI, suggesting that these factors should be considered as potential confounders in the observed association between the 2 variables. Single-parent and large-family households were particularly vulnerable to FI compared with other groups, and family eating culture and parental eating habits were found to shape adolescents’ food choice behaviors [42]. In low-income households, higher levels of FI were associated with lower dietary quality and more frequent consumption of processed or energy-dense, nutrient-poor foods. Moreover, low-income areas are often categorized as “food deserts,” where limited access to supermarkets or fresh food markets constrains food choices, even among individuals with high FL [43,44]. Older adults, those with low educational attainment, and rural residents were also identified as having lower FL levels [45].

However, Hanbazaza et al. [36] found no significant relationship between the 2 variables. The authors attributed this finding to the sociocultural context of Saudi Arabia, including patriarchal family structures, women’s economic dependency, and unstable income among younger adults, which collectively influence food access and dietary practices. Cultural background has thus been identified as another important factor shaping the relationship between FL and FI [46]. In immigrant households, language barriers and dietary acculturation challenges tend to lower FL and increase vulnerability to FI [47], Similarly, in multicultural families, parental cultural background and eating habits directly affect children’s FL, while conflicts arising during cultural adaptation may exacerbate FI [48]. The effectiveness of FL education also varies depending on social networks and community culture, suggesting that FL is not solely determined by individual knowledge or skills but is moderated by broader social and cultural contexts [22]. These findings collectively indicate that FL extends beyond the individual level and is influenced by socioeconomic structures and cultural environments, which are also closely associated with the risk of FI.

Intervention studies [37,39,40] reported improvements in FL and reductions in FI and suggested that long-term interventions may contribute to the alleviation of FI. Educational programs strengthened practical food-related competencies such as budgeting, meal planning, cooking, and storage skills, while encouraging participants to apply these skills through community engagement. As a result, participants not only improved their eating behaviors but also enhanced their food utilization and budgeting abilities, contributing to the dissemination of healthier dietary practices within their communities. These findings may suggest that integrating skill-based education and community participation into FL programs can be a potential strategy for reducing FI.

Nevertheless, economic constraints continued to act as barriers to behavioral implementation. In West et al. [2], although FI improved following FL intervention, food costs and household income remained limiting factors. This highlights the vulnerability of low-income populations to FI due to insufficient income, unemployment, and limited resources. Therefore, mitigating FI among socioeconomically disadvantaged groups requires not only FL education but also broader improvements in social determinants such as economic stability, educational attainment, and local environments [45,49]. In particular, given the strong association between economic factors and FI, the importance of direct food assistance and price subsidy policies should not be overlooked alongside FL enhancement [50,51].

Encouragingly, various programs and policies that address these factors have shown positive results in alleviating FI. For example, community-based garden programs have been reported to improve both social connectedness and food access, thereby reducing FI [52]. Nutrition education initiatives such as the Supplemental Nutrition Assistance Program Education and the Expanded Food and Nutrition Education Program for low-income households have improved budgeting and cooking skills and contributed to long-term reductions in FI [53,54]. In Bangladesh, the “Graduation” program provided asset transfers, skills training, and education for ultra-poor households, demonstrating sustainable improvements in FS in follow-up assessments [55]. These cases illustrate that strategies to enhance FL can be most effective when combined with structural interventions that address socioeconomic inequalities.

The studies included in this review employed diverse statistical techniques—such as ROC analysis, structural equation modeling, and multigroup analysis—to more precisely examine the relationship between the 2 variables. They also identified major risk factors by categorizing FL into specific domains including knowledge, skills, attitudes, and behaviors. Cross-sectional studies frequently identified associations between FI and FL domains related to budgeting and financial management, with lower scores observed food-insecure groups. In contrast, intervention studies more commonly reported improvements in cooking confidence and food preparation behaviors alongside changes in FI indicators. Together, these findings demonstrate that different study designs can illuminate distinct domain-level aspects of FL associated with FI, highlighting the analytical value of examining FL beyond composite scores. Furthermore, the inclusion of cross-sectional, intervention, and longitudinal designs, the reviewed studies provided multidimensional insights into the association between FL and FI, offering both theoretical and practical implications. Consequently, this review underscores the need for FL education and policy-based interventions, providing an evidence base for future public health strategies and community practices.

However, several limitations should be noted. First, the included studies employed diverse instruments to assess FL and FI, which limited direct comparisons and hindered consistent interpretation across studies. Although many studies referred to the FL framework proposed by Vidgen and Gallegos [30], substantial heterogeneity existed in operational definitions and domain composition. Variations in included domains—such as budgeting, cooking confidence, and knowledge-based components— as well as the indirect assessment of FL through dietary indicators (e.g., fruit and vegetable intake in Royer et al. [39]) may have influenced interpretation of the reported associations between FL and FI. Second, the predominance of cross-sectional designs (n = 5) constrained causal inference, and in some intervention studies, relatively small sample sizes or the absence of randomization may have limited internal validity. Third, the small number of studies incorporating follow-up assessments (n = 1) restricted evaluation of the long-term sustainability of intervention effects, and the frequent reliance on self-reported questionnaires may have introduced subjective bias. In addition, heterogeneity in study designs, populations, and outcome measures precluded quantitative synthesis, necessitating a narrative synthesis approach. Although methodological quality was systematically appraised using standardized criteria, some studies exhibited insufficient reporting of key methodological elements, which was considered during interpretation rather than used as a basis for study exclusion.

Future research should include adequately powered intervention and longitudinal studies to further examine the relationship between FL and FI [28]. Community-based controlled trials are also needed to rigorously evaluate the intervention effects of FL education. As discussed above, improving FI among vulnerable populations cannot be achieved solely through educational approaches; rather, combining educational strategies with structural interventions—such as food assistance and price subsidies—while employing standardized measurement tools will enhance cross-study comparability. Such efforts will help clarify the directionality and mechanisms underlying the observed association between FL and FI.

In conclusion, the available evidence indicates a consistent association between FL and FI across diverse populations and contexts. However, due to the predominance of cross-sectional designs and methodological variability, causal direction and potential pathways remain uncertain. Clarifying these relationships through rigorous future research will be essential for informing effective and sustainable public health strategies. Within broader efforts to address the structural determinants of FI, strengthening FL may serve as a complementary and potentially sustainable component rather than a standalone solution.

SUPPLEMENTARY MATERIAL

Supplementary Table 1

Domain-specific findings on FL