ANSWER
Introduction
Rationale
According to the Australian National Health and Medical Research Council (2013) [1,] optimal nutrition is essential for children’s healthy growth and development. Healthy eating helps people achieve and maintain a healthy weight while protecting them from chronic disease and premature death. Conversely, unhealthy eating habits early in life, particularly excessive consumption of energy-dense, nutrient-poor foods and drinks, physical inactivity and a sedentary lifestyle, are risk factors for overweight and obesity [2,3]. Other noncommunicable diseases (such as diabetes, osteoporosis, and hypertension) are also linked to unhealthy eating habits and patterns formed during childhood [4]. As a result, it is critical to establish healthy eating habits early in life, as research shows that eating habits and patterns persist into adulthood [5,6]. As a result, education about healthy eating is critical during childhood to establish healthy eating habits in later years. Schools have been popular for implementing health promotion and prevention interventions because they provide continuous, intensive contact with children. Lifelong health and well-being begin with promoting healthy behaviors early in life [7]. School infrastructure, physical environment, policies, curricula, teaching and learning, and staff all have the potential to influence child health positively. While schools have remained a popular infrastructure for health promotion initiatives, teachers will continue to be the primary agents of promoting health and nutrition in schools after 2015 [8]. To date, no systematic review or meta-analysis has been conducted to determine the strategies teachers should employ to maximize the effectiveness of their teaching interventions on fostering healthy eating behaviors in primary school-aged children.

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Objectives
Our goal was to systematically review the evidence on interventions to improve primary school students’ healthy eating habits and patterns. Our goals were to 1) describe the nature of the interventions that had been conducted (i.e., theories and teaching strategies and approaches); and 2) conduct meta-analyses to determine the effectiveness of these interventions.

Methods
Design
This systematic review and meta-analyses report on data extracted and synthesized in 2014 as part of a review project for the New South Wales (NSW) Department of Education and Communities and the NSW Ministry of Health. The PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) Statement [9] was followed to ensure the study’s transparency.

Criteria for eligibility
Types of interventions
We included teaching and school-based elementary school interventions delivered by teachers or teacher substitutes that aimed to change elementary school children’s nutritional consumption, preferences, or knowledge. The following types of teaching and school-based interventions were used:

1.
Curriculum initiatives or evaluations

2.
School nutrition initiatives

3.
Community programs that are linked to curricula or are delivered by schools (e.g., community gardens)

4.
Health/nutrition education programs aimed at improving dietary habits

5.
Environmental school change strategies implemented by classroom teachers

6.
Environmental interventions/industry partnerships focused on point-of-purchase consumption linked through classroom-based education; this could include campaigns to draw attention to healthier products in school canteens or school lunch choices.

7.
Social marketing campaigns

8.
Policies aimed at improving the dietary habits of elementary school children (e.g., school board level, provincial/national level).

Good designs for this review included randomized, quasi-experimental, and cluster-controlled studies conducted in elementary schools (Grades K-6) where the primary change agent in the intervention was the classroom teacher (or their teaching substitute). Individual students, classrooms, schools, or communities were used as the unit of analysis in relevant clusters within studies.

Locations
Intervention sites had to include elementary schools and their immediate community settings. We excluded programs or strategies delivered solely through homes, religious institutions other than schools, non-governmental organizations, primary health care settings, universities, hospitals, outpatient clinics located within hospital settings, commercial programs, and metabolic or weight loss clinics.

Interested outcomes (Healthy eating behaviors)
Our primary outcomes included student consumption, preference, and knowledge of nutrient-dense foods. Individual, family, school, and community-level measures provided evidence of intervention effects. They also included measures of food consumption, preference, or knowledge, changes in food environments, food disappearance, and food sales (in school cafeterias). Diet and food intake records, self-reported and reported by parents, teachers, or both; food frequency questionnaires/balance sheets; food wastage and plate waste; and micronutrient measures were among the consumption measures used (i.e., biomarkers of exposure to food). Preference measures included questionnaires, surveys, or self-report instruments that included Likert scales, pairing activities, or self-reported preferences. Questionnaires or tests on food-related knowledge were used as measures of knowledge (i.e., Recommended Dietary intake, ingredients, and nutritional knowledge).

These primary outcomes were then grouped into four dominant healthy eating outcomes that the authors determined aligned with the National Health and Medical Research Council (NHMRC) and their Healthy Eating for Children [10] Guidelines. As a result, our findings were as follows:

1.
Food Consumption and Energy Intake-NHMRC Guideline 1 (Limiting energy intake to meet energy needs)

2.
Fruit and vegetable (FV) consumption or preference-NHMRC Guideline 2 (Enjoy a wide variety of nutritious foods)

3.
Reduced Sugar Consumption or Preference (Not from Whole Fruit)-NHMRC Guideline 3 (Limit intake of foods containing added sugar)

4.
Nutritional Knowledge-NHMRC Guideline 5 (Care for food)

The instruments used and the number of studies included in the review and meta-analysis did not allow for the separation of consumption and preference for fruit and vegetables or sugar. We acknowledge that preferences for specific food types may have a greater impact on long-term consumption habits.

Interested outcomes (Teaching strategies)
The primary outcomes of interest included any recognized teaching strategy or articulated approach to teaching that has a known effect on student learning and behavior. These teaching strategies and approaches to curricula were largely derived from (but not limited to) those articulated in Hattie’s meta-analysis synthesis relating to teaching, learning, and student achievement [11].

Search
Our search strategy included electronic bibliographic databases, grey literature databases, reference lists of key articles, targeted internet searches via Google Scholar, and targeted internet searches of key organization websites.

We searched the following databases, adapting search terms to the requirements of individual databases in terms of subject heading terminology and syntax: PUBMED; MEDLINE; the Cochrane Central Register of Controlled Trials (CENTRAL); PsycINFO; ERIC; ScienceDirect; and A + Education. These search terms were based on the following:
Participants (e.g., child* OR young people OR youth OR pediatric OR pediatric OR primary school-age* OR elementary school-age* OR primary student* OR elementary student* OR primary school* OR elementary school*).
Delivery (e.g., teach* OR class*, OR health* ed* teach* OR learn* OR teach* polic* OR nutrition ed* OR health* to eat*).
Strategies (e.g., Phys* The search dates ranged from the database’s inception to May 31, 2014.

The search results were refined to include full-text copies retrieved from these databases and Google Scholar published after 1970. These citations were then electronically cross-referenced with 15 reference lists from scoping and systematic review papers published in the fields of nutrition, education, and health promotion between 1997 and 2012. A final database and internet search were then conducted to identify studies published between January 2010 (the year before the publication of the most recent systematic review) and May 2014.

Citation evaluation
Initially, the lead author removed duplicate citations from the search. Each citation’s abstract was then reviewed by a single researcher (DAD) to determine whether it would be included in the systematic review. The full-text articles of all potentially relevant citations were obtained and saved as Adobe PDF files. The full-text copy was obtained when it needed to be clarified whether a citation was appropriate. The lead author then reviewed the citation list. Citations deemed ineligible were reviewed by the remaining two authors (WGC, LRP) to see if any potentially relevant citations were missed, and full-text copies of these citations were obtained.

Study selection
Following the screening process, full-text articles were reviewed by the three researchers against the inclusion criteria; if the researchers were unsure whether or not to include an article, the article in question was reviewed again until a final decision was reached by majority consensus.

Data extraction
The lead researcher first extracted data from the included studies from full-text articles and tabulated it (see Table 1). This data set included:

Table 1: Studies on the teaching strategies/approaches used to promote healthy eating among primary school students.
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1.
Authors of research

2.
Year of publication;

3.
Country(s) of study;

4.
Study funding organization;

5.
Study layout;

6.
The Dominant Theoretical Framework was used to inform the study design.

7.
Study sample (size, grade, and average age of participants);

8.
Duration of intervention;

9.
Whether the intervention was combined with physical activity or a specially trained teacher;

10.
Relevant outcome categories

11.
Statistical significance (p-value/95% CI)

12.
The magnitude of the effect of various teaching strategies on each outcome (Cohen’s d). Note: If these were not reported in the study and Mean and Standard Deviations could be extracted directly or indirectly, Cohen’s d was calculated by the lead researcher and verified by the co-authors.

The lead author tabulated these data and distributed them to co-authors for feedback and review. All three researchers reached a unanimous decision on changes to these interpretations.

The three researchers then independently reviewed each of the articles and identified the teaching approaches used during the intervention phase of the studies. Researchers met and cross-referenced their identification of each teaching approach, deciding by consensus how each approach would be classified as a larger teaching strategy (if appropriate) to allow for comparison between studies.

Methodological quality evaluation
The included articles were also evaluated for methodological quality using a 10-item quality assessment scale developed by van Sluijs and colleagues [12]. (see Table 2). Three reviewers independently assessed whether the assessed item was present or absent for each included article. When an item needed to be adequately described, it received an absent score. A priori, the agreement between reviewers for each article was set at 80% [12]. For each article, reviewers were required to agree on whether the items were present or absent for 8 of the ten items. In the case of less than 80% agreement, further discussion yielded consensus. Table 3 shows the results of the methodological quality assessment.

Table 2: Methodological quality assessment items (adapted from van Sluijs et al. 2007) [12].
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Table 3: Methodological quality and bias risk assessment
Full-size table
Synthesis of findings
Effect sizes are the preferred metric for estimating the magnitude of an intervention’s effect because they allow for comparisons between and within studies [13]. Cohen’s d, the effect-size metric at the heart of this meta-analysis, is one of the most widely used measures of the magnitude of effect and is frequently used in educational meta-analyses [11]. The formula for calculating Cohen’s d is:

d=(M1−M2)/SDp,
where M 1 is the mean of one group of study participants, M 2 is the mean of a second group of study participants, and SD P is the pooled standard deviation for both study participants.

In cases where the groups have received different learning experiences (e.g., an intervention), d is a measure of the magnitude of the effect of the experience on the group receiving the enhanced teaching and learning experience. In cases where SD was not reported, but SE (Standard Error) was, SE was converted to SD using the following formula:

SD=SE x N
Because Cohen’s d accounts for sample size, mean effect sizes for the meta-analysis were calculated as follows:

Md=∑d/Ns
where

M d is the mean Cohen’s d calculated by adding all d values and dividing by the number of studies (N s) from which a d value could be extracted for that outcome.

Data from each study were initially compiled and described in a narrative summary (see Table 1). Studies were divided into four categories to make it easier to compare the effects of different teaching strategies/approaches: decreased food consumption/energy intake, increased FV consumption/preference, decreased sugar consumption/preference, and increased nutritional knowledge. Meta-analyses were performed using the standardized mean difference approach (Cohen’s d) regardless of statistical significance, where at least two studies existed for a specific outcome measure, and sufficient statistical data was reported to allow such synthesis to occur.

The studies in the meta-analyses included a comparison of teaching strategies/approaches, reported post-test/follow-up values or change scores, and measures of distribution (i.e., mean and standard deviation). For studies that included post-test and follow-up assessments, the assessments completed at the end of the study period (i.e., follow-up) were included in the meta-analyses. The standardized effect sizes were classified as minimal (.02), small (0.2), medium (0.5), and large (0.8) [14]. Analyses also considered whether they represented an effective investment in education, given that the average effect size of most educational interventions is d = 0.4 [11].

Results
Study selection
Figure 1 depicts the study selection procedure. It initially returned over 200,000 possible citations. We refined our searches to include only full-text copies available online and published after 1970 in each database and Google Scholar, resulting in 18,100 possible citations. These citations were then electronically cross-referenced with reference lists from scoping and systematic review papers published in nutrition, education, and health promotion (n = 15) [15-29] between 1997 and 2012, yielding 454 likely studies. A final database and internet search were then conducted to identify studies published between January 2010 (the year before the publication of the most recent systematic review) and May 2014. This revealed 23 possible citations for a total of 487 publications considered for review.

Figure 1:
Figure 1
Flowchart of study selection.

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These 487 publications were then reviewed based on abstracts and excluded if they were conducted outside of primary schools or on primary school-aged children. This reduced the number of studies to 233. Studies were excluded if they were not: a) randomized controlled trials, b) quasi-experimental studies, or c) cluster-controlled trials. This left 55 studies. On review of the full-text paper, another six studies were excluded for failing to meet the inclusion criteria (i.e., conducted in a laboratory setting) or being a duplicate studies. The final 49 studies were all in the form of peer-reviewed journal publications.

To ensure a complete review of the relevant literature is given, all 49 of the included articles are presented in Table 1. Specifically, the table outlines the details of the studies, including author(s), title, year, location, design and stated dominant theoretical framework, target population, and types of outcomes measured. The year of publication for included articles ranged from 1973 to 2011.

Study and intervention characteristics
The final 49 studies included one randomized controlled trial, 13 quasi-experiential studies and 35 cluster-controlled trials. These studies captured data from 38001 primary school children in 13 different countries. Data capable of inclusion in the meta-analyses came from 20234 (53%) participants. All but one country (Trinidad and Tobago) included in these studies were member nations of the Organization for Economic Co-operation and Development (OECD) (OECD). Only 27 of the 49 studies reported the theoretical frameworks used to inform their intervention design. While some studies reported multiple theoretical approaches (see Table 1), Social Cognitive Theory was the most frequently used theoretical framework and was reported in 16 of 27 studies.

Teaching strategies/approaches
There were eight dominant teaching strategies or approaches to teaching exhibited across the 49 studies that addressed the pre-determined areas of healthy eating for primary school students (i.e., food consumption/energy intake, fruit and vegetable consumption or preference, sugar consumption or preference, and nutritional knowledge). Some studies included more than one of these teaching strategies/approaches in their intervention group. The dominant teaching strategies/approaches were:
Enhanced curriculum approaches (i.e., specialty nutrition education programs beyond existing health curricula delivered by teachers or specialists) (n = 29).
Cross-curricular approaches (i.e., nutrition education programs delivered across two or more traditional primary school subjects) (n = 11).
Parental involvement (i.e., programs requiring active participation or assistance from a parent within or outside the school environment) (n = 10).
Experiential learning approaches (i.e., school/community garden, cooking and food preparation activities) (n = 10).
Contingent reinforcement approaches (i.e., rewards or incentives given to students in response to desired behaviors) (n = 7).
Literary abstraction approaches (i.e., literature read by/to children whereby a character promotes/exemplifies positive behaviors) (n = 3).
Games-based approaches (i.e., board/card games played by students at school designed to promote positive behavior and learning of new knowledge) (n = 2).
Web-based approaches (i.e., internet-based resources or feedback mechanisms that students at home or school could access) (n = 2).

The systematic review results indicate several dominant evidence-based approaches to teaching healthy eating in the randomized controlled trial, quasi-experimental and cluster-controlled trial literature. To determine the strength of the evidence for these approaches, they are analyzed against each of the major outcomes used to determine healthy eating and if the study achieved p-values of p < .05 for 50% of the studies, the magnitude of M d (i.e., minimal, small, medium, large) and if M d  > .40. The decision to use an effect size of M d  > .40 is based on Hattie’s Zone of Desired Effects reside above this hinge point [11] and therefore have the greatest influence and represent the best investment for improving educational outcomes.

Food consumption and energy intake
Eleven studies reported on the outcomes of food consumption and the overall energy intake of primary school-aged children. Curriculum-based approaches were the most popular (seven studies) and reported achieving statistical significance of p < .05 or better across nine studies reducing food consumption or energy intake outcomes. However, researchers were able to calculate effect sizes across six of the reported outcomes and found that four showed minimal or no effect, one had a negative effect, and one reported small effect size. The mean effect size of curriculum-based approaches is minimal (M d  = 0.12). It would suggest that curriculum-based approaches alone are not the best influence on reducing food consumption or energy intake. Three studies utilizing experiential learning approaches (i.e., school/community gardens, cooking lessons and food preparation) reported outcomes associated with reducing food consumption and energy intake. Two of these studies reported achieving statistical significance of p < .05 or better for at least one food consumption or energy intake variable. Effect sizes could be calculated on three of the reported outcomes from two studies. Two large effect sizes were recorded, and the other showed no effect. While only a small number of effect sizes could be calculated based on the reporting method in these studies, the mean effect size was M d  = 1.31 and within the Zone of Desired Effects. These approaches warrant greater investigation to reduce the variance in the calculated effect but show promise in reducing food consumption and energy intake. Fruit and vegetable (FV) consumption or preference In terms of FV consumption or preference, curriculum-based approaches were again the most popular. 60% of curriculum-based approaches found statistically significant (p < .05) improvements in FV consumption or preference among primary school-aged children. However, it is important to note that many of the studies that used curriculum-based approaches (especially those with stronger p values) also coupled their interventions with secondary approaches (e.g., experiential learning, parental involvement) (e.g., experiential learning, parental-involvement). Given how data was reported in these studies, it is difficult to determine the degree to which curriculum-based approaches alone contributed to statistical significance. Of the 30 effect sizes calculated by the researchers, 33% had a medium to large effect, and 23% had a small effect size. The mean effect size for curriculum-based approaches was M d  = 0.45, indicating that having a nutrition curriculum delivered in primary schools makes an important investment in improving FV consumption or preference based on the educational hinge-point of effect sizes described by Hattie [11]. All but one study included in the analysis appeared to be based on behavioral, mastery, or didactic approaches and curricula models. The study, driven by a socio-cultural perspective of health [30], had only 33 participants and effect sizes ranging from 0.26 to 1.04 for different FV consumption or preference behaviors. Experiential-learning approaches were used in eight studies to improve FV consumption or preference in primary school children and proved to be very effective, with 75% of these studies yielding statistical significance at p < .05 or better. Of the 11 effect sizes calculated by the researchers, 45% had a large effect, and the remaining 55% had a minimal effect size. However, the mean effect size for experiential-learning approaches that included school/community gardens, cooking skills, or food preparation was M d  = 0.68, indicating experiential-learning approaches were within the Zone of Desired Effects [11] for improving FV consumption or preference in primary school children. Cross-curricular approaches (i.e., learning experiences taught across two or more learning areas/subjects) to improving FV consumption or preference in primary school children proved very effective. Of the ten studies using cross-curricular approaches, 90% of these yield statistical significance at p < .05 or better and of the six effect sizes calculated by the researchers, 50% had large effect sizes, and the remaining 50% had a small or medium effect size. While only a small number of effect sizes could be calculated based on the reporting method in these studies, the mean effect size was M d  = 0.63, which was within the Zone of Desired Effects. Four studies used a contingent reinforcement (i.e., a reward for behavior) approach in the promotion of FV consumption or preference among primary school children. All four (100%) of these studies reported achieving statistical significance of at least p < .05. There were six effect sizes reported across only two studies [31,32], and four of these effect sizes (67%) were considered large, and two (33%) were considered minimal. Based on these two studies, the average effect size for contingent reinforcement in promoting FV consumption or preference is M d  = 1.34. More studies are needed to ascertain an average effect size with less variance; however, based on available data, this approach is well above M d  = 0.4, with strong statistical significance in every study, indicating it is a profitable investment strategy in improving FV consumption or preference among primary school children. Parental involvement was incorporated into ten studies that reported against 23 FV consumption or preference outcomes in primary school children. 91% of the outcomes reported were statistically significant at the p < .05 level. The researchers were able to calculate 14 effect sizes in five of the studies. The results were varied, with three large, two medium, three small, two minimal and four negative effect sizes being calculated. The mean effect was M d   = 0.39, which was just below the Zone of Desired effects; however, it is worthwhile noting that no parent involvement approach was ever 'stand-alone.' They all included elements of the enhanced curriculum, cross-curricular, experiential learning or web-based support. Sugar consumption or preference (not from whole fruit) (not from whole fruit) Enhanced curriculum approaches (mainly based on behavioral or social cognitive theories) in primary schools provided ten studies for reducing sugar consumption or preference in students; however, only three yielded statistical significance of p < .05 or better for reducing any sugar-laden beverage (SLB), fruit juice or carbohydrate consumption. Six effect sizes were calculated from these studies that showed one large, one small and four minimal effect sizes. The mean effect size of curriculum approaches for reducing sugar consumption was only M d  = 0.28, suggesting that greater investment beyond the curriculum is required to make a substantial difference in reducing the sugar consumption of primary school children. Two studies [33,34] reported cross-curricular approaches in reducing SLB or fruit juice consumption. Both studies reported statistically significant reductions in both SLB and fruit juice consumption at p < .05 or better. Taylor et al. [34] reported two minimal effect sizes, while James et al. [35] reported a large effect size. The mean effect size for cross-curricular approaches at reducing SLB or fruit juice consumption was M d  = 0.42. This was within the Zone of Desired Effects [11], but more investigation may be required given the small number of studies included in the analysis. Nutritional knowledge Twelve studies adopted enhanced curricula approaches to improving the nutritional knowledge of primary school children. 13 nutritional knowledge outcomes achieved a statistically significant improvement of p < .05 or better. 8 of the 13 studies reported a statistical significance of p < .001. Researchers calculated seven effect sizes (3 × large, 1 × medium, 3 × minimal) with the mean effect size M d  = 0.75. This indicates that quality curriculum interventions (largely based on behavioral or social cognitive learning theory) are capable of achieving improvements in student nutritional knowledge with the Zone of Desired Effects [11]. Four studies adopted an experiential learning approach, and all reported achieving statistical significance of p < .05 across seven nutritional knowledge-related outcomes. The researchers calculated six effect sizes and found five large and one minimal effect size. The mean effect size for the experiential learning approaches to nutritional knowledge was M d  = 1.35, indicating this approach is a particularly strong evidence-based strategy for improving the nutritional knowledge of primary school-aged children. Discussion This meta-analysis of school-based teaching interventions that have focused on improving the eating habits of primary school children found that experiential learning approaches had the greatest effect on reducing the food consumption, energy intake and nutritional knowledge of primary school children and a smaller effect on primary school children's FV consumption or preference. The other strategies that had a smaller effect on improving primary school children's nutritional knowledge and reducing sugar consumption or preferences were cross-curricular approaches and quality curriculum interventions, respectively. Both cross-curricular and quality curriculum interventions were effective in improving primary school children's FV consumption or preferences. In light of these findings, it is important to note that the high heterogeneity among the included primary school healthy eating programs does not make it possible to make firm conclusions. However, the findings have been supported in other literature, with experiential learning strategies, such as garden-enhanced learning strategies, positively influencing vegetable preferences and consumption among primary school children, which is the strongest predictor of future consumption [36-39]. Like this review, Langellotto & Gupta [39], who used meta-analytic techniques, found that school gardens and associated teaching strategies increased vegetable consumption in children. In contrast, the impacts of nutrition education programs were marginal or non-significant. Two possible reasons for these findings are: 1) school gardens increase access to vegetables, and 2) gardening decreases children's reluctance to try new foods. Birch and colleagues [38] have also stated that to improve primary school children's healthy food preferences, experiences and strategies need to increase availability and accessibility to increase exposure to those foods that will affect their willingness to taste. While some studies report FV consumption or preference independently of each other, this tends to be the exception rather than the rule of reporting FV consumption or preference in primary school-based studies. Future studies should promote, analyze and report vegetable consumption independent of fruit consumption to ascertain what physiological and behavioral effects this may have on students and the study's findings. This is because excessive consumption of fruit-based sugars (i.e., consuming fructose >50 g/d) may be one of the underlying aetiologies of Metabolic Syndrome and Type 2 Diabetes [35].

This study has some important considerations with regard to its generalizability. The target population was the students attending primary schools from any country around the world, but all the studies bar one [40] were conducted in nations of the OECD. As such, they represent some of the most developed and advanced economies on the planet and should be considered seriously when seeking to generalize these findings. More than half of the 49 studies analyzed (n = 28) were conducted in the United States, followed by the United Kingdom (n = 7). This may be attributed to the growing percentage of children in the USA and UK with non-communicable diseases attributed to diet-related factors [4,41]. It may also indicate the capacity of advanced economies, such as the USA and the UK, to conduct empirically robust studies in primary school settings [42].

Strengths and limitations
There are several strengths of this systematic review and meta-analysis. First, this is the first known paper to systematically extract specific teaching strategies and approaches that facilitate the healthy eating of primary school children. As such, we conducted a systematic review using broad search terms to increase the probability of identifying all eligible publications, which yielded a well-sized (k = 49) evidence base. Second, the meta-analysis method allowed these strategies to be considered against other nutritional and educational meta-analytic literature. Third, teaching strategies and approaches were reliably coded using a schema of existing evidence of ‘what works’ in educational settings [11].

There were a few limitations associated with this review. The heterogeneity of primary school healthy eating interventions is large. This fact alone limited our ability to measure the effectiveness of each teaching strategy in the multi-faceted nutrition education programs. Moreover, some strategies may be commonly clustered with others. Thus our findings should be considered carefully in terms of these strategies having similar effects when implemented independently.
Given that all the articles were identified from the peer-reviewed literature, there is a possibility of publication bias on the nature of the evidence available to inform the review. Publication bias by particular journals, or the inability and discouragement of publishing articles that report negative results, may distort conclusions reached. Further, due to all but one study being conducted in OECD countries, findings from this systematic review and meta-analyses should be limited to informing the decision making of stakeholders in those of similar nations.

Conclusion
Most teaching strategies from intervention studies lead to positive changes in primary school children’s nutritional knowledge and behaviors. However, the most effective strategies for facilitating healthy eating in primary school children are enhanced curricula, cross-curricula and experiential learning approaches. Other strategies that showed some good effect but needed further investigation include contingent reinforcement and parental involvement approaches.
QUESTION
Nutritional teaching plan for a diabetic patient