school feeding thesis

• Open access
• Published: 16 March 2020

Impacts of school feeding on educational and health outcomes of school-age children and adolescents in low- and middle-income countries: protocol for a systematic review and meta-analysis

• Dongqing Wang 1 &
• Wafaie W. Fawzi 1 , 2 , 3  

Systematic Reviews volume  9 , Article number:  55 ( 2020 ) Cite this article

138k Accesses

23 Citations

29 Altmetric

Metrics details

School feeding programs are beneficial for the physical, mental, and psychosocial development of school-age children and adolescents, particularly those in low- and middle-income countries (LMICs). While school feeding programs are ubiquitous in LMICs, the specific benefits of school feeding programs are unclear. The aim of this systematic review and meta-analysis is to evaluate the impacts of school feeding programs on the educational and health outcomes of children and adolescents in LMICs.

Rigorously designed interventional studies on the impacts of school feeding on nutritional and health outcomes of children and adolescents receiving primary or secondary education in LMICs will be included. The following information sources were used to identify relevant published or unpublished studies: MEDLINE, EMBASE, CINAHL, the Cochrane Library, and governmental or organizational websites. The risk of bias of randomized and non-randomized studies will be assessed using the Cochrane Risk of Bias tool and the ROBINS-I tool, respectively. Two reviewers will independently conduct the selection of studies, data extraction, and assessment of the risk of bias. A narrative synthesis of all the included studies will be provided. Meta-analyses will be performed whenever appropriate. Heterogeneity of effects will be assessed by I 2 , subgroup analyses, and meta-regression. The certainty of evidence for each outcome will be assessed using the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) approach.

The design and implementation of school feeding programs in LMICs should be based on the understanding of the benefits of such programs. This work will provide a crucial evidence base for the educational and health benefits of school feeding on children and adolescents in LMICs.

Systematic review registration

This protocol was submitted for registration with the International Prospective Register of Systematic Reviews (PROSPERO) on November 18, 2019 (registration number: pending).

Peer Review reports

Nutrition during the school years is crucial for the physical, mental, and psychosocial development of children and adolescents aged 6 to 19 years. It is estimated that, across the developing world, 66 million school-age children go to school every day hungry, with 23 million hungry children in Africa [ 1 ]. Attending classes hungry severely impacts children’s and adolescents’ abilities to learn, to thrive, and to realize their full potentials [ 2 ].

School feeding programs (sometimes referred to as school meal programs) are interventions that regularly provide nutritious foods to children and adolescents attending school [ 3 ]. Benefits of school feeding on children and adolescents include alleviating hunger, reducing micronutrient deficiency and anemia, preventing overweight and obesity, improving school enrollment and attendance, increasing cognitive and academic performance, and contributing to gender equity in access to education [ 4 , 5 , 6 , 7 , 8 ]. Most countries have some forms of school feeding programs in some way and at some scale [ 6 , 8 ]. School feeding programs are widely available in high-income countries but generally have incomplete coverages in low- and middle-income countries (LMICs), where the need is greatest in terms of hunger and poverty [ 5 ]. Most countries in sub-Saharan Africa only have school feeding interventions that are targeted toward the most food-insecure regions instead of being universally available [ 5 ]. It is imperative to expand the coverage of school feeding programs and to improve the quality of existing programs to maximize their benefits on children and adolescents.

Little is known about the impacts of school feeding programs on specific educational and health outcomes of school-age children and adolescents in LMICs. Previous reviews on the potential effects of school feeding are outdated, with the most recent Cochrane review published in 2007 [ 9 ], thus do not reflect all of the currently available evidence. Also, previous work has limited scopes in terms of the age range [ 10 ] or the outcomes examined (e.g., anthropometric and nutritional outcomes but not educational or psychosocial outcomes or vice versa) [ 11 ]. Further, prior reviews have focused on the provision of school meals and did not explicitly evaluate what specific content (types and amounts of foods and nutrients) of the school meals conferred the largest benefits on outcomes [ 9 ]. Therefore, an updated and refined synthesis of evidence on school feeding interventions and a wide range of educational and health outcomes of children and adolescents is warranted and will inform the design and implementation of future programs.

The aim of this systematic review and meta-analysis is to evaluate the impacts of school feeding programs on educational and health outcomes of children and adolescents aged 6 to 19 receiving primary or secondary education in LMICs. We will emphasize findings generated from randomized controlled trials (RCTs). RCTs better account for external factors that may confound the effect of school feeding programs, including background nutritional deficiency levels and inputs from schools and teachers [ 8 , 12 ]. We will also include other rigorously designed interventional studies, including controlled before-after studies (CBAs) and non-randomized controlled trials that were able to account for the baseline differences between intervention arms [ 9 ].

Methods/design

Research question.

We aim to evaluate the impacts of school feeding programs on educational and health outcomes of children and adolescents receiving primary or secondary education in LMICs. We also aim to assess the potentially different impacts of school feeding by characteristics of the program and by composition of the foods provided.

Eligibility criteria

Inclusion criteria.

We will include RCTs, with the intervention randomized individually or in clusters (classes or schools). We will also include CBAs as they are non-randomized studies with a relatively rigorous design and occupy a non-negligible proportion of the relevant literature [ 9 ]. Non-randomized controlled trials are also eligible for inclusion as long as the baseline differences between intervention arms were accounted for in the analysis.

We will include published articles as well as unpublished and grey literature and will include ongoing studies where preliminary findings are available to us.

Studies conducted in LMICs as defined by the World Bank 2020 fiscal year.

Studies involving children and adolescents (boys and girls) aged 6 to 19 who were receiving primary or secondary education (i.e., primary, middle, or high school).

Studies that examined the impacts of the provision of foods, including meals (breakfast, lunch, or dinner) or snacks consumed at school (in-school feeding), and foods distributed to the family and consumed outside of the school setting (take-home ration) [ 5 ]. We will consider the provision of solid foods or beverages (e.g., milk). We will also include studies that examined food stamps or food vouchers distributed at school for the participants to access foods (in the market or food banks).

The comparison (control) group in each included study can be participants who did not receive school feeding or any other interventions, or participants who received alternative interventions instead of school feeding. We will also consider the comparison of school feeding programs with different food compositions, such as the comparison between an updated program with an original one.

We will include educational, nutritional, anthropometric, cognitive, and morbidity outcomes of children and adolescents. Potential outcomes include height, weight, skinfold thickness, mid-upper arm circumference, micronutrient status, hemoglobin level, school enrollment, school attendance, dropout, school achievement (math, reading, spelling), on-task behavior, cognition, and morbidity (e.g., fever, cough, diarrhea, and vomiting). Studies with results for at least one outcome of interest will be included.

No restrictions will be placed on the year, language, sample size of the study, or the duration of the intervention.

Exclusion criteria

Non-randomized controlled trials that did not account for the baseline differences between intervention arms.

Interventional studies without a proper control group, such as uncontrolled before-after studies, uncontrolled interrupted time series studies, and uncontrolled difference-in-difference designs.

Observational studies (e.g., cohort, case-control, and cross-sectional studies).

Editorials, commentaries, opinions, and review articles (these will, however, be used to identify additional original studies).

Studies conducted among preschool children only. Feeding interventions among preschool children are important and of great interest but are beyond the scope of this work, which will focus on the school setting.

Studies that examined the impacts of micronutrient fortification, micronutrient supplementation, or nutrition education; however, if such interventions are complementary to otherwise eligible school feeding interventions, these studies will be included.

Clinical treatment programs targeted toward individuals with specific medical conditions, or programs toward underweight, overweight, or obese individuals.

Studies that only examined aggregate-level economical or agricultural outcomes.

Studies that described school feeding programs without linkage to specific outcomes.

Information sources

The following databases were searched for eligible studies, from the inception of each database through November 2019: MEDLINE (via PubMed), EMBASE, CINAHL, and the Cochrane Library. The selection of the four electronic databases was made in consultation with a health science librarian with expertise in systematic searching. Our search covered the three databases (i.e., MEDLINE, EMBASE, and the Cochrane Library) that are recommended by the Cochrane Handbook for Systematic Reviews of Interventions [ 13 ]. We also searched ClinicalTrials.gov and other governmental or organizational websites (World Food Programme (WFP), World Health Organization, Food and Agriculture Organization (FAO), and World Bank) for studies not identified from the database searching. We will conduct a manual search of references of retained articles and previous reviews. We will also consult with content experts on school feeding to identify any additional studies. Reports written in languages other than English will be translated by colleagues who are native speakers of the corresponding languages whenever possible. Studies that cannot be adequately translated will be excluded.

Search strategy

We consulted with a health science librarian to develop the PubMed search strategy, which is provided in Additional File 1 . The sensitivity of the search strategy was examined by confirming that several sentinel articles were identified. The PubMed strategy will be adapted to the syntax appropriate for other databases. The initial search took place in November 2019, and an updated search will be conducted in early April 2020.

Data management

EndNote X9 (Clarivate Analytics, PA, USA) will be used to store the records retrieved from searches of electronic databases. The records will also be imported into Covidence (Veritas Health Innovation, Melbourne, Australia), an internet-based program that facilitates the streamlined management of the systematic review. Duplicate records will be detected and removed first by EndNote and then by Covidence.

Selection of studies

The results of the searches will be independently assessed by two reviewers based on the inclusion and exclusion criteria. All titles and abstracts will be reviewed first to remove irrelevant studies. For potentially eligible studies and studies with unclear eligibility, the full texts will be obtained and reviewed to confirm eligibility using a form for full text screening, which will be pilot tested on five randomly selected full texts. Disagreements between reviewers will be resolved by discussion or by a third reviewer when necessary. Inter-rater agreement will be quantified by calculating the raw percentage of agreement and Cohen’s κ coefficient. Specific reasons for study exclusions will be documented and summarized using the flow diagram for the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [ 14 ]. Neither of the reviewers will be blind to journal titles or the names of the authors.

Data extraction

Data of the retained studies will be extracted by two reviewers independently and entered into a data extraction form, which will be pilot tested on five randomly selected studies. Disagreements in the extracted information between reviewers will be resolved by discussion or by a third reviewer. When necessary, the corresponding authors of the studies will be contacted to obtain relevant information. We will extract the following information: title, authors (first author and corresponding author), contact information of corresponding author, journal (or source for unpublished reports), calendar year of publication, calendar year of intervention, country, source of funding, study design, sample size (number of clusters for each group and number of participants in each group), sample characteristics (e.g., age, sex, and socioeconomic status), intervention (including timing, duration, food and nutritional content, and co-interventions), measure of adherence, comparator/control, outcomes assessed, main findings with point estimates and measures of variance (standard errors, 95% confidence intervals, or p values), theory to explain success (if available), and theory to explain failure (if available). Multiple reports of a single study will be collated as additional results may be provided in different reports. Whenever there are inconsistent results across reports of a single study, we will contact the corresponding author to obtain more accurate results. The data extraction form is provided in Additional File 2 .

Assessment of risk of bias

The risk of bias will be independently assessed by two reviewers. Any disagreement on the risk of bias between reviewers will be resolved by discussion and by a third reviewer when necessary. The risk of bias assessments will be conducted for each outcome reported in each trial, rather than for the whole study. For RCTs, we will use version 2 of the Cochrane Risk of Bias tool (RoB 2) [ 15 ], which considers the following five domains: bias arising from the randomization process, bias due to deviations from intended interventions, bias due to missing outcome data, bias in measurement of the outcome, and bias in selection of the reported results. For cluster-randomized trials, we will additionally consider bias from the timing of identification and recruitment of individual participants in relation to timing of randomization [ 16 ]. Each domain will be judged as “low risk of bias,” “high risk of bias,” or “some concerns.” We will consider an RCT to be of low risk of bias if it is judged to have low risk of bias for all domains; we will consider an RCT to be of high risk of bias if it is judged to have high risk of bias in at least one domain or have some concerns for multiple domains (≥ 3) in a way that substantially lowers confidence in the result; we will consider an RCT to have some concerns if it raises some concerns in at least one domain but not to be at high risk of bias for any domain [ 15 ]. For CBAs and non-randomized controlled trials, we will use the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) tool [ 17 ], which considers biases from confounding, bias in selection of participants into the study, bias in classification of interventions, bias due to deviations from intended interventions, bias due to missing data, bias in measurement of outcomes, and bias in selection of the reported results. Each domain will be judged as “low risk of bias,” “moderate risk of bias,” “serious risk of bias,” “critical risk of bias,” or “no information.” We will consider a non-randomized study to be of low risk of bias if it is judged to have low or moderate risk of bias for all domains; we will consider a non-randomized study to be of high risk of bias if it is judged to have serious or critical risk of bias in one or more domains; we will consider a non-randomized study to have some concerns if the assessment is unclear for one or more domains but low or moderate for all other domains. We will contact the corresponding authors of the reports to obtain more information when necessary. We will summarize the results of the assessment of the risk of bias in a table, in which the judgment for each domain will be presented with a justification [ 15 ].

Data synthesis

A systematic and narrative synthesis of all included studies will be presented in the text and also as a table. School feeding will be treated as a dichotomous exposure (i.e., intervention vs. control). Effect estimates for continuous outcomes will be expressed as mean differences (with 95% confidence intervals) comparing the intervention group with the control group; effect estimates for dichotomous outcomes will be expressed as risk ratios, rate ratios, hazard ratios, or odds ratios (all with 95% confidence intervals), comparing the intervention group with the control group. For RCTs, we will extract the results based on intention-to-treat analyses. When more than two intervention groups are present in a study, they will be treated as separate arms. However, when the interventions of the additional arms are not relevant to school feeding, they will not be taken into account. Ideally, cluster-randomized studies should report results from analyses that appropriately account for the study design, such as mixed-effects models or generalized estimating equations. Studies that ignored clustering are overprecise and will receive unduly high weights in the meta-analysis. When cluster-based studies did not use the proper statistical methods to account for clustering, we will extract or apply an intraclass correlation coefficient to modify the standard errors based on the approach described in the Cochrane Handbook for Systematic Reviews of Interventions [ 13 ].

If studies for a given outcome are sufficiently consistent in terms of intervention, comparator, and outcome definition, we will conduct a random-effects, inverse-variance-weighted meta-analysis for the outcome. The random-effects method will be used as the effect of school feeding is presumed to be heterogeneous across time and populations. Heterogeneity of effects across studies will be assessed by computing the I 2 statistic, which represents the percentage of the total variation in the effect estimates that is due to true heterogeneity rather than chance; I 2 > 50% will be considered as substantial heterogeneity [ 18 ].

We will assess the sources of heterogeneity by conducting subgroup analyses with the following prespecified characteristics: unit of allocation (individual, class, or school), modality of intervention (in-school meal, in-school snacks, take-home ration, food stamps/food vouchers), presence of co-interventions (by itself or combined with complementary interventions), timing of intervention (breakfast, lunch, dinner, or snack), duration of intervention (defined as the interval between the initialization of the school feeding intervention, and when the outcomes were assessed), year of study, country or region, level of food insecurity of the region, age group of participants (primary or secondary education), sex of participants, type of report (published or unpublished), and risk of bias (low, high, or some concerns). To assess the potentially differential impacts by the specific content of the meal, we will conduct exploratory subgroup analyses by the type and amount of the foods or nutrients entailed in the program, such as the presence of fruits, vegetables, and animal source foods, or the adequacy of micronutrients and macronutrients (defined in relation to the Recommended Dietary Allowances). To further explain heterogeneity, we will perform meta-regression using the predictors mentioned above. We will use contour-enhanced funnel plots to detect publication bias if there are 10 or more studies available for an outcome [ 19 ]. We will assess the robustness of the results by excluding studies judged to have a high risk of bias, and by repeating the analyses using fixed-effects models. We will compute for each outcome a 95% prediction interval, which provides a predicted range of the effect of the intervention when applied in an individual setting [ 20 ]. Statistical analyses will be conducted using STATA 16 (StataCorp, College Station, Texas). For outcomes with insufficient data or extreme heterogeneity that cannot be assessed in subgroup analyses or meta-regression, we will provide a narrative synthesis without a meta-analysis.

Assessment of certainty of evidence

The overall certainty of evidence for each included outcome will be assessed using the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) approach, which considers risk of bias, publication bias, imprecision, inconsistency, and indirectness [ 21 , 22 , 23 , 24 , 25 , 26 ]. The strength of the overall evidence will be judged as high, moderate, low, or very low [ 21 ].

Registration and reporting

This protocol was submitted for registration with the International Prospective Register of Systematic Reviews (PROSPERO) on November 18, 2019. However, at the time of this proofing, the protocol has still not been reviewed or assigned a registration number. We reached out to PROSPERO for an update on the registration status and was told that the registration for non-U.K. studies would take a long time (4-5 months with a minimum of 140 days). In the event of protocol amendments, the date of each amendment will be accompanied by a description of each change and the rationale on PROSPERO. We prepared this protocol following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) [ 27 ]. The PRISMA-P checklist can be obtained from Additional File 3 . We will report this systematic review following the Cochrane Handbook for Systematic Reviews of Interventions [ 13 ] and the PRISMA guidelines [ 14 ].

School feeding programs have been and will continue to be essential for the provision of nutrients, improvement of academic performance, and the promotion of a healthy lifestyle in LMICs. Therefore, there is a strong political will to continue to fund new programs and to expand on existing programs [ 28 ]. The design and implementation of school feeding programs in LMICs should be based on the established benefits of such programs on specific educational and health outcomes of children and adolescents, for which an updated evidence base is needed.

The State of School Feeding Worldwide , published by the WFP, summarized the status of school feeding across the world and reported that school feeding programs are ubiquitously present. However, the quality of school feeding programs varies greatly across countries and with national income [ 6 ]. The report also highlighted a need to strengthen the evidence base on the potential benefits of school feeding. Drake et al. reviewed the design and implementation of 14 school feeding programs in LMICs [ 28 ]. They concluded that there is no one-size-fits-all model for school feeding programs, given that different countries approach school feeding programs with different objectives. However, they did identify some good practices that are likely applicable across countries, such as the inclusion of fruits and vegetables, the collaboration with local smallholder farmers, and the incorporation of school feeding programs as the component of a much broader curriculum of nutrition and health education. They noted that there was a lack of quantitative data on the impacts of school feeding, especially those from randomized controlled trials. A recently published report by the FAO-reviewed nutrition guidelines and standards for school meals from 33 LMICs through surveys targeted toward relevant stakeholders and found considerable variation between and within countries in terms of coordination, management, funding, objectives, and modalities of school feeding programs [ 3 ]. For example, the objectives of the identified school feeding programs include addressing short-term hunger, reducing nutrient deficiency, improving attendance and school performance, encouraging healthy eating habits, and supporting local agriculture and economy. Lunch is the most common timing for the identified programs, and the majority of the school lunch programs offer cooked meals that range from single dishes based on staples with added vegetables, legumes, and animal-source foods to menus with a main dish and a side dish; fruits are provided as part of the meal in some programs. Nutrition education and school gardens (often also for educational purposes) are the most common complementary interventions to the feeding programs. However, this report focused on government-owned programs and excluded any pilot projects or scalable programs coordinated by non-governmental entities. None of the reports mentioned above quantitatively linked school feeding programs to specific outcomes of children and adolescents.

Numerous systematic reviews have synthesized the impacts of school-based dietary interventions on various outcomes of children and adolescents [ 9 , 10 , 11 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. However, most of the reviews consist primarily of nutrition education programs that did not provide actual foods. To date, only a few reviews focused on or were able to draw conclusions regarding school feeding programs [ 9 , 10 , 11 , 44 , 45 ]. Kristjansson et al. conducted the first systematic review on this topic with 18 studies (nine from lower-income countries) among socio-economically disadvantaged children and adolescents across the world [ 9 ]. It was reported that, in RCTs from lower-income countries, participants who were fed at school gained an average of 0.39 kg more weight over 19 months and attended school more frequently (4 to 6 more days per year per participant) than those in control groups; school-fed participants in lower-income countries also had better performances in math and short-term cognitive tasks compared to controls. However, results for height and results from higher-income countries are mixed, suggesting that the benefit of school feeding varies by outcome and by socioeconomic status, with disadvantaged participants from lower-income countries likely to benefit more from school feeding. While comprehensive at the time, this first systematic review only included seven RCTs, five of which were conducted in lower-income countries. Jomaa et al. reviewed the impacts of school feeding programs on educational and health outcomes of primary-school-age children in developing countries. They reported relatively consistent positive associations between school feeding and energy intake, micronutrient status, school enrollment, and school attendance, but reported inconclusive results on growth, cognition, and academic achievement [ 10 ]. However, this review did not include children and adolescents at the secondary school level or studies conducted prior to 1990. Krishnaratne et al. reviewed rigorously designed studies among children and adolescents in LMICs. They found significant associations between school feeding and enrollment, dropout, progression, and nonsignificant associations with attendance and learning [ 44 ]. Snilstveit et al. systematically reviewed interventions for improving learning outcomes and access to education for children and adolescents in LMICs and reported positive associations between school feeding and enrollment, attendance, and various learning outcomes [ 45 ]. The reviews by Krishnaratne [ 44 ] and Snilstveit [ 45 ], however, did not specifically focus on school feeding, nor did they consider non-educational endpoints such as nutrition and health. Watkins et al. reviewed the impacts of school feeding on the nutritional status of primary-school-age children and preschool and adolescent girls in LMICs; they reported small and significant effects on weight gain and small and nonsignificant effects on height gain among school-age children [ 11 ]. Nevertheless, this review focused on anthropometric outcomes and nutritional status and had limited coverage on educational or psychosocial outcomes. None of the previous reviews examined in detail whether different content (e.g., types and amounts of foods and nutrients) of the provided meals had differential impacts on children and adolescents, which is crucial information for the design and improvement of future programs.

School years represent a critical period not only for physical and mental development but also for the formation of long-term dietary and lifestyle habits. This systematic review and meta-analysis will provide a comprehensive evidence base for the development and refinement of future school feeding programs targeted toward children and adolescents in LMICs.

Availability of data and materials

All data that will be generated and analyzed during this study will be included in the published article or its supplementary information files.

Abbreviations

Controlled before-after study

Food and Agriculture Organization

Grading of Recommendation, Assessment, Development, and Evaluation

Low- and middle-income country

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols

International Prospective Register of Systematic Reviews

Randomized controlled trial

Risk of Bias in Non-randomized Studies of Interventions

World Food Programme

Bundy D, Silva Nd, Horton S, Jamison DT, Patton GC, Schultz L, et al. Re-imagining school feeding: a high-return investment in human capital and local economies. 2018.

Plaut D, Thomas M, Hill T, Worthington J, Fernandes M, Burnett N. Getting to education outcomes: reviewing evidence from health and education interventions. Child and Adolescent Health and Development 3rd edition: The International Bank for Reconstruction and Development/The World Bank; 2017.

Food and Agriculture Organization (FAO). Nutrition guidelines and standards for school meals: a report from 33 low and middle-income countries. Rome: FAO; 2019.

Adelman S, Gilligan D, Lehrer K. How effective are food for education programs?: a critical assessment of the evidence from developing countries: Intl Food Policy Res Inst; 2008.

Bundy D, Burbano C, Grosh ME, Gelli A, Juke M, Drake L. Rethinking school feeding: social safety nets, child development, and the education sector: The World Bank; 2009.

WFP (World Food Programme). State of school feeding worldwide. Rome, Italy: WFP; 2013.

Google Scholar  

Aliyar R, Gelli A, Hamdani SH. A review of nutritional guidelines and menu compositions for school feeding programs in 12 countries. Front Public Health. 2015;3:148.

Article   Google Scholar  

Drake L, Fernandes M, Aurino E, Kiamba J, Giyose B, Burbano C, et al. School feeding programs in middle childhood and adolescence. Child and Adolescent Health and Development 3rd edition: The International Bank for Reconstruction and Development/The World Bank; 2017.

Kristjansson B, Petticrew M, MacDonald B, Krasevec J, Janzen L, Greenhalgh T, et al. School feeding for improving the physical and psychosocial health of disadvantaged students. Cochrane Database Syst Rev. 2007;1.

Jomaa LH, McDonnell E, Probart C. School feeding programs in developing countries: impacts on children's health and educational outcomes. Nutr Rev. 2011;69(2):83–98.

Watkins K, Gelli A, Hamdani S, Masset E, Mersch C, Nadazdin N, et al. Sensitive to nutrition? A literature review of school feeding effects in the child development lifecycle. Working Paper Series; 2015.

Greenhalgh T, Kristjansson E, Robinson V. Realist review to understand the efficacy of school feeding programmes. Bmj. 2007;335(7625):858–61.

Chandler J, Cumpston M, Li T, Page MJ, Welch VA. Cochrane handbook for systematic reviews of interventions: John Wiley & Sons; 2019.

Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals Int Med. 2009;151(4):264–9.

Sterne JA, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. bmj. 2019;366:l4898.

Eldridge S, Campbell M, Campbell M, Dahota A, Giraudeau B, Higgins J, et al. Revised Cochrane risk of bias tool for randomized trials (RoB 2.0): additional considerations for cluster-randomized trials. Cochrane Methods Cochrane Database Syst Rev. 2016:10.

Sterne JA, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. bmj. 2016;355:i4919.

Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. Bmj. 2003;327(7414):557–60.

Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L. Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J Clin Epidemiol. 2008;61(10):991–6.

Riley RD, Higgins JP, Deeks JJ. Interpretation of random effects meta-analyses. Bmj. 2011;342:d549.

Balshem H, Helfand M, Schünemann HJ, Oxman AD, Kunz R, Brozek J, et al. GRADE guidelines: 3. Rating the quality of evidence. J Clin Epidemiol. 2011;64(4):401–6.

Guyatt GH, Oxman AD, Vist G, Kunz R, Brozek J, Alonso-Coello P, et al. GRADE guidelines: 4. Rating the quality of evidence—study limitations (risk of bias). J Clin Epidemiol. 2011;64(4):407–15.

Guyatt GH, Oxman AD, Montori V, Vist G, Kunz R, Brozek J, et al. GRADE guidelines: 5. Rating the quality of evidence—publication bias. J Clin Epidemiol. 2011;64(12):1277–82.

Guyatt GH, Oxman AD, Kunz R, Brozek J, Alonso-Coello P, Rind D, et al. GRADE guidelines 6. Rating the quality of evidence—imprecision. J Clin Epidemiol. 2011;64(12):1283–93.

Guyatt GH, Oxman AD, Kunz R, Woodcock J, Brozek J, Helfand M, et al. GRADE guidelines: 7. Rating the quality of evidence—inconsistency. J Clin Epidemiol. 2011;64(12):1294–302.

Guyatt GH, Oxman AD, Kunz R, Woodcock J, Brozek J, Helfand M, et al. GRADE guidelines: 8. Rating the quality of evidence—indirectness. J Clin Epidemiol. 2011;64(12):1303–10.

Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. 2015;4(1):1.

Drake L, Woolnough A, Burbano C, Bundy D. Global school feeding sourcebook: lessons from 14 countries: World Scientific; 2016.

Story M. School-based approaches for preventing and treating obesity. Int J Obesity. 1999;23(S2):S43.

Summerbell CD, Waters E, Edmunds L, Kelly SA, Brown T, Campbell KJ. Interventions for preventing obesity in children. Cochrane database of systematic reviews. 2005(3).

Katz DL, O’Connell M, Yeh M-C, Nawaz H, Njike V, Anderson LM, et al. Public health strategies for preventing and controlling overweight and obesity in school and worksite settings: a report on recommendations of the Task Force on Community Preventive Services. MMWR Recomm Rep. 2005;54(10):1–12.

PubMed   Google Scholar  

Doak C, Visscher T, Renders C, Seidell J. The prevention of overweight and obesity in children and adolescents: a review of interventions and programmes. Obesity Rev. 2006;7(1):111–36.

Article   CAS   Google Scholar  

Flynn M, McNeil D, Maloff B, Mutasingwa D, Wu M, Ford C, et al. Reducing obesity and related chronic disease risk in children and youth: a synthesis of evidence with ‘best practice’recommendations. Obesity Rev. 2006;7:7–66.

Sharma M. School-based interventions for childhood and adolescent obesity. Obesity Rev. 2006;7(3):261–9.

Cole K, Waldrop J, D’Auria J, Garner H. An integrative research review: effective school-based childhood overweight interventions. J Specialists Pediatr Nurs. 2006;11(3):166–77.

Budd GM, Volpe SL. School-based obesity prevention: research, challenges, and recommendations. J School Health. 2006;76(10):485–95.

Katz DL, O'Connell M, Njike VY, Yeh M-C, Nawaz H. Strategies for the prevention and control of obesity in the school setting: systematic review and meta-analysis. Int J Obesity. 2008;32(12):1780.

Li M, Li S, Baur LA, Huxley RR. A systematic review of school-based intervention studies for the prevention or reduction of excess weight among Chinese children and adolescents. Obesity Rev. 2008;9(6):548–59.

Brown T, Summerbell C. Systematic review of school-based interventions that focus on changing dietary intake and physical activity levels to prevent childhood obesity: an update to the obesity guidance produced by the National Institute for Health and Clinical Excellence. Obesity Rev. 2009;10(1):110–41.

De Bourdeaudhuij I, Van Cauwenberghe E, Spittaels H, Oppert JM, Rostami C, Brug J, et al. School-based interventions promoting both physical activity and healthy eating in Europe: a systematic review within the HOPE project. Obesity Rev. 2011;12(3):205–16.

Khambalia A, Dickinson S, Hardy L. Gill Ta, Baur L. A synthesis of existing systematic reviews and meta-analyses of school-based behavioural interventions for controlling and preventing obesity. Obesity Rev. 2012;13(3):214–33.

Verstraeten R, Roberfroid D, Lachat C, Leroy JL, Holdsworth M, Maes L, et al. Effectiveness of preventive school-based obesity interventions in low-and middle-income countries: a systematic review. Am J Clin Nutr. 2012;96(2):415–38.

Petrosino A, Morgan C, Fronius TA, Tanner-Smith EE, Boruch RF. Interventions in developing nations for improving primary and secondary school enrollment of children: a systematic review. Campbell Syst Rev. 2012;8(1):i–192.

Krishnaratne S, White H, Carpenter E. Quality education for all children? What works in education in developing countries, vol. 20. New Delhi: International Initiative for Impact Evaluation (3ie), Working Paper; 2013. p. 155.

Snilstveit B, Stevenson J, Phillips D, Vojtkova M, Gallagher E, Schmidt T, et al. Interventions for improving learning outcomes and access to education in low-and middle-income countries: a systematic review. Campbell Collaboration. 2015.

Download references

Acknowledgements

We thank Jacqueline Cellini at Francis A. Countway Library of Medicine at Harvard University for conceptual consultation and assistance with developing the search strategy.

This work will not receive financial support.

Author information

Authors and affiliations.

Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, 90 Smith Street, 310 WS-5, Boston, MA, 02120, USA

Dongqing Wang & Wafaie W. Fawzi

Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA

Wafaie W. Fawzi

Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA

You can also search for this author in PubMed   Google Scholar

Contributions

DW is the guarantor. DW and WWF contributed to the development of the selection criteria, the search strategy, the risk of bias assessment strategy, and the data extraction form. DW drafted the manuscript. Both authors read, provided feedback, and approved the final manuscript.

Corresponding author

Correspondence to Dongqing Wang .

Ethics declarations

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Additional file 1..

PubMed search strategy.

Additional File 2.

Data extraction form.

Additional File 3.

PRISMA-P 2015 Checklist.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Wang, D., Fawzi, W.W. Impacts of school feeding on educational and health outcomes of school-age children and adolescents in low- and middle-income countries: protocol for a systematic review and meta-analysis. Syst Rev 9 , 55 (2020). https://doi.org/10.1186/s13643-020-01317-6

Download citation

Received : 19 November 2019

Accepted : 01 March 2020

Published : 16 March 2020

DOI : https://doi.org/10.1186/s13643-020-01317-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• School feeding
• School meal
• Low- and middle-income countries
• Adolescents
• Systematic review
• Meta-analysis
• Randomized controlled trials
• Controlled before-after studies

Systematic Reviews

ISSN: 2046-4053

• Submission enquiries: Access here and click Contact Us
• General enquiries: [email protected]

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Cochrane Database Syst Rev

School feeding programs for improving the physical and psychological health of school children experiencing socioeconomic disadvantage

This is a protocol for a Cochrane Review (intervention). The objectives are as follows:

• To assess the effectiveness of school feeding programs for improving the physical and psychological health of children experiencing socioeconomic disadvantage across the world.
• To compare the effectiveness of school feeding programs for children experiencing socioeconomic disadvantage and those experiencing socioeconomic advantage. This includes subgroups by income and gender.
• To understand the process by which school feeding programs achieve (or fail to achieve) an impact on growth, cognitive development, and school performance.
• To gather data that are useful for cost‐benefit analysis.

Description of the condition

Although the world has made great advances in improved access to food and health care, good health is still unevenly and unfairly distributed according to socioeconomic position. Health and longevity are highest for the richest and decrease steadily with decreasing income ( Baretto 2017 ;  Wilkins 1983 ;  Wilkinson 1996 ). These inequities are evident both within and between countries ( Baretto 2017 ). Social gradients in health, or socioeconomic inequalities in health, are pervasive in all countries of the world ( Diderichsen 2001 ) and are evident in most diseases, injuries, and health behaviours ( Marchand 1998 ). Health inequalities have been defined as "the virtually universal phenomenon of variation in health indicators ... associated with socioeconomic status" ( Last 1995 ). Inequalities may also be seen between different sexes or geographic groups. Health inequities "are unfair and remediable inequalities" ( Peter 2001 ;  Tan‐Torres Edejer 2001 ).

Socioeconomic differences in nutrition may be one of the most important factors causing disparities in health and mortality ( Gwatkin 2007 ). In 2018, over 678 million people across the world were undernourished; many were children, and most lived in low‐ and middle‐income countries (LMIC;  FAO/IFAD/UNICEF/WFP/WHO 2020 ). For example, over 250 million people in Africa were chronically undernourished in 2019 ( World Vision 2021 ). Even in the USA, more than 2.7 million households with children experienced food insecurity in 2017 ( USDA 2019 ). Overall, the incidence of malnutrition or micronutrient deficiencies (or both) is a health concern especially impacting LMIC. 

Undernutrition and micronutrient deficiencies can adversely affect physical, mental, and social aspects of child health and development ( Drake 2020 ;  Kristjansson 2007 ). Effects on physical health may include being underweight, stunted growth, lowered immunity, and mortality. Early malnutrition or micronutrient deficiencies (or both) have been linked to poorer cognitive functioning ( DiGirolamo, 2020 ;  Mattei 2019 ). Overnight and morning fasting (e.g. skipping breakfast) can adversely affect performance on cognitive tasks, particularly for children who are nutritionally at risk ( Pollitt 1995 ). Short‐term hunger also impacts classroom behaviour, as malnutrition can affect attention and interest, thus impairing knowledge retention ( Afridi 2019 ;  Levinger 1996 ;  Read 1973 ). Moreover, extreme poverty and hunger often keep children, especially girls, out of school. "One of the reasons for this lag in progress towards universal primary education is the persistence of poverty, hunger, and malnutrition" ( Jomaa 2011 ). Because these factors impair physical and cognitive development, food insecurity threatens the adequate development of children and youth who experience socioeconomic disadvantage around the world. 

Description of the intervention

 School feeding programs have been a longstanding global public health standard, focused on improving health and education outcomes for students experiencing socioeconomic disadvantage. These school feeding/meal programs exist in lower and middle‐income countries (LMIC), upper‐middle‐income, and high‐income countries ( Wang 2020 ;  WFP 2019 . The goals of school feeding programs can include relieving short‐term hunger ( Drake 2017 ;  Drake 2020 ) and improving micronutrient status ( Drake 2017 ), growth ( Drake 2017 ), cognition ( Cohen 2021 ), and academic performance ( Anderson 2018 ;  Cohen 2021 ) in both higher‐ and lower‐income countries. In LMIC, school feeding also aims to increase demand for schooling, enrolment, and attendance ( Rutledge 2016 ).

School feeding programs involve full meals and/or snacks (including milk) for participating children aged 5 to 19 years at school; take‐home rations may also be provided as an additional initiative for families ( Wang 2020 ). Take‐home rations can take the form of food provided to students to take home to their families after school hours or involve cash‐based transfers. Both forms reduce food‐related stresses on students and their families, contribute to a productive at‐home learning environment, and encourage student attendance ( WFP 2020 ). They can be offered individually or within the same school feeding program.

Many LMICs are now running 'home‐grown' school feeding programs. These programs connect local smallholder farmers to the school meal programs and have several aims. They benefit school children by giving them access to fresh, local food. They can also benefit smallholder farmers and their communities by providing a stable market for the farmers ( FAO and WFP 2018 ). 

How the intervention might work

Our conceptual model of how the intervention might work is shown in  Figure 1 . This model is based on Kristjansson's previous school meals review and process evaluation ( Greenhalgh 2007 ;  Kristjansson 2007 ) and her review of feeding programs for children aged six months to five years ( Kristjansson 2015 ). Our team and advisory board have also given valuable input. Additionally, we have gained insight from previous nonsystematic reviews. These include those by  Adolphus 2013 ,  Grantham‐McGregor 2005 ,  Krishnaratne 2013 ,  Levinger 1986 ,  Levinger 1996 ,  Papamandjaris ,  Pollitt 1978 ,  Pollitt 1995 , and  Walker 1986 . 

Conceptual model of the school meal program. 

The model details how aspects of the intervention (shown in blue) relate to important contextual and process moderators (shown in yellow),  intervention outputs (shown in red rounded rectangles), and intervention outcomes (shown in purple ovals). 

School feeding is intended to supplement the food and nutrition given at home so children can eat more nutritious food. School meal design and delivery (e.g. the type of intervention (meals, snacks, or milk), meal palatability, the timing and frequency of feeding, nutritional quality, energy content, and factors contributing to study protocol adherence) can all influence school enrolment and attendance, food consumption, and substitution. Substitution refers to the fact that some children who receive food at school, especially in families who are experiencing extreme socioeconomic disadvantage, receive less or eat less food at home, allowing other family members to consume more. This reallocation may have mixed effects if the school child is malnourished; it can reduce the benefits of school feeding for that child, but it can improve the nutritional status of siblings ( Gelli 2019 ). Child characteristics and contextual factors such as home environment, classroom quality, school quality, and the social context moderate the effectiveness of the intervention. School meals can also consist of income transfer to families which may boost the local economy ( Jomaa 2011 ). Improved enrolment, attendance, attention, behaviour, nutritional status, and cognition can improve educational attainment.

Educational attainment is associated with benefits to adult health, gender equity, and economic outcomes.  Viner 2017  found that secondary education was associated with more health benefits than primary education across low‐, middle‐, and high‐income countries. They also found that each additional year of education was associated with an 8% to 16% reduction in mortality ( Viner 2017 ). Education is related to women's decision‐making authority in households across 70 developing countries ( Le 2021 ). Furthermore, as measured by student achievement, educational attainment has been associated with economic outcomes and growth over time and across regions ( Hanushek 2015 ). Given the link between educational attainment and adult health ( Viner 2017 ), gender equity ( Le 2021 ), and economic outcomes ( Hanushek 2015 ), it is primarily through increased educational attainment that school meal programs are thought to have a wide societal impact.

Why it is important to do this review

In 2018, the World Food Program supported school feeding programs in 61 countries, covering 16.4 million school children ( WFP 2019 ). A great deal of hope, time, and money is invested in these programs. It is therefore important to learn whether or not school meals are an effective and cost‐effective intervention for improving the health, nutritional status, cognitive functioning, school enrolment, and school performance of children who live in poor socioeconomic circumstances worldwide.

Although existing reviews provide valuable information, they fail to give us a comprehensive picture of the effectiveness of school feeding across the globe. All are limited in their scope: some to just a few countries, most to either developing or industrialised countries, others to one feeding time (e.g. morning), and others to just a few outcomes. Furthermore, none are systematic reviews. Thus, except for the  Kristjansson 2007  review, systematic methods were not used; some lack details on search strategies, inclusion and exclusion criteria, and the number of studies found and considered; furthermore, for some, the quality of studies was not formally assessed.

The first systematic review on school feeding programs, by Kristjansson and colleagues, was published in 2007 and is now more than 14 years old ( Kristjansson 2007 ). The review included 18 studies from across the world and found that school meals in LMIC can improve growth, attendance by four to six days a year, and math scores. This current review will not only update the previous review but will also involve a new and broader search of all the literature to ensure that we do not miss any relevant studies. This systematic review may contribute to the discourse surrounding the importance of school feeding programs in enhancing food security in LMIC and upper‐middle‐ and high‐income countries. Using this review, national authorities may be able to draw conclusions about the effectiveness of school meal programs for outcomes such as student nutrition, performance, and school attendance ( Jomaa 2011 ;  Kristjansson 2007 ;  Wang 2020 ). Additionally, with our systematic analysis of the process of school feeding programs, the design and execution of these programs may be better understood and thus easier to apply. This review may inform many aspects of school meal implementation. This may allow for the development of context‐specific frameworks that meet community needs ( WFP 2019 ). In the case that this review may result in further programs being introduced around the world, the hypothesized outcomes may involve reduced hunger, improved food and income security, and enhanced access to, and quality of, education ( FAO and WFP 2018 ). Using the evidence‐based conclusions drawn from this review, limited national resources and funding may be effectively allocated to advance national nutrition standards — shaping the lives of future generations through reduced inequality ( Kristjansson 2015 ). 

Criteria for considering studies for this review

Types of studies.

We will accept the following types of studies.

Experimental studies

• Randomised controlled trials (RCTs) in which individuals are randomly allocated to a treatment arm and to a control arm. We will also accept cross‐over RCTs ( Higgins 2019a ).
• Cluster‐randomised controlled trials (c‐RCTs) in which groups of people are allocated to different interventions by clusters such as school or area ( Higgins 2019a ). These may include stepped wedge RCTs. All c‐RCTs are required to have at least two intervention sites and two control sites.

Non‐randomised studies

We will also accept the following types of non‐randomised studies (NRS) because it is often impossible to randomise policy or program interventions. 

• Quasi‐randomised studies. These controlled trials use inappropriate methods for allocating people to interventions ( Reeves 2019 ).
• Controlled before‐after studies (CBAs) in which measurements are taken from both an experimental and a control group before and after the intervention and in which the researcher has control over which people are allotted to which group.
• Interrupted time series (ITS). ITS studies may use data routinely collected for monitoring and surveillance in 'natural experiments' ( Petticrew 2005 ) or data collected for a specific intervention. ITS studies must include at least three observations before the intervention and three observations after the intervention.
• Prospective cohort studies are those in which the intervention and control groups are assembled before the intervention and followed through time ( Reeves 2019 ). 
• Retrospective cohort studies are those in which intervention and control groups are assembled based on past records.

To be included, all NRSs must be longitudinal and have at least two measurements of the outcome ‐ one near the start of the study and one just at the end of the intervention. We will not include NRSs that only have endpoint data.

Results for each type of study will be tabulated and analysed separately.

Types of participants

The participants for this review will comprise children and adolescents aged 5 to 19 who attend primary or secondary schools in any country. For our purposes, we will classify countries into two groups: low‐ and lower‐middle‐income countries (LMIC); and higher‐income countries (upper‐middle‐ and higher‐income countries). We will use the World Bank List of Country Incomes for the year of study inception ( World Bank 2021 ). Studies must meet the following inclusion and exclusion criteria, which are somewhat different for these two groups.

Low‐ and lower‐middle‐income countries

We will include studies in which children are classified as experiencing socioeconomic disadvantage by one or more criteria.

• Children live in rural areas or villages.
• Children live in an urban area and are described as experiencing socioeconomic disadvantage (e.g. poor or low‐income) or from lower‐income areas (e.g. slums).
• Statistics show that 30% or more of the children in the sample suffer from undernutrition (nutritionist judgment).
• The study is implicitly or explicitly aimed at children who live with socioeconomic disadvantage, and indicators of disadvantage are provided in the paper.

We will also include studies in which a proportion of children are advantaged, but results can be broken down by socioeconomic status (SES; or other measures of social disadvantage) or baseline nutritional status.

We will exclude studies if children are from urban areas only if: a large proportion (more than 50%) of children are living in high SES circumstances, and results are not broken down by SES or other proxy variables; or where information is insufficient to allow us to judge the extent of disadvantage.

Higher‐income countries

We will include studies in which a large percentage of children (60% or more) are classified as living in disadvantaged socioeconomic circumstances by one or more of the following criteria.

• They are from areas described as economically marginalized or disadvantaged (e.g. low‐income areas, ghettos, social housing projects, lower‐income rural towns, or mining communities).
• The children are from low SES backgrounds.
• The children are from families that are described as experiencing socioeconomic disadvantage (including having unemployed parents).
• The children are described as marginalized or 'at‐risk' due to social circumstances.

We will also include studies in which a significant proportion of children are advantaged, but results can be broken down by SES or baseline nutritional status.

We will exclude studies if more than 40% of students are described as advantaged and results are not broken down by SES or other proxy variables.

Types of interventions

We will include interventions that include providing meals (breakfast or lunch), snacks (including milk), and/or take‐home rations in a school setting.

To be included in our review, the meal/snack given must meet at least 10% of the daily energy requirement and at least 10% of the daily protein requirement for that age group. 

If a multi‐armed study includes multiple independent comparisons, we will include all independent comparisons ( Higgins 2019b ). If a multi‐armed study includes several arms and one control group, we will choose the arm that is most relevant to our study question ( Higgins 2019b ). For example, if the study provides both in‐school feeding and take‐home rations, we will select the in‐school feeding arm. If the study has two intervention groups based on energy given, we will select the intervention group with the highest amount of energy given. 

We will exclude the following interventions: micronutrient supplementation or fortification of existing meals alone, stand‐alone nutrition education in schools or at home, obesity prevention programs, breastfeeding programs, food stamps, modifications to school meals to change nutrient content, community kitchens, food banks, and feeding centres.

Because of the increasing emphasis on reducing obesity, programs built around school meals increasingly aim to enhance the nutritional content of children's diets by increasing availability of, and access to, low‐fat choices, fruits, and vegetables ( Coleman 2005 ;  Luepker 1996 ). However, the focus of this review is not on changing the content of school meals but on the effect of the provision of food to children. Thus, we will not include these types of interventions in this review.

Comparators

Comparators can be either no treatment or placebo (low‐calorie drinks/snacks). The placebos must contain less than 3% of the daily energy requirement and less than 5% of the daily protein requirement.

Main Comparisons

We will include the following five comparisons.

• Meals only versus control.
• Snacks only versus control.
• Take‐home rations only versus control.
• Meals and snacks versus control.
• Meals and take‐home rations versus control.

Types of outcome measures

Although we will prioritise the primary outcome measures, we will also consider secondary outcome measures.

Primary outcomes

• Anthropometry (weight and height for age z‐scores and weight for height z‐scores).
• Educational outcomes (reading, math, and science performance; school attendance; and enrolment).
• Cognitive outcomes (verbal fluency, intelligence, reasoning, attendance, and memory assessed by a reliable and valid test).
• Adverse outcomes (overweight/obesity and disruptive behaviour at school).

Secondary outcomes

• Anthropometry (weight, height, and bone mineral density).
• Physical health (nutritional status; vitamin A status; vitamin B12 status; zinc status; and haemoglobin and hematocrit as indices of anaemia, a condition in which the blood cannot carry enough oxygen, most often due to iron deficiency).
• Behavioural outcomes (physical activity).
• Adverse outcome (stigmatisation).
• Consumption of healthier and unhealthier foods.

Timing of outcome measurement

We will consider both short‐term outcomes (less than three months) and longer‐term outcomes (three months or more) as some behavioural changes may be seen rapidly. Attention and behaviour are examples of short‐term outcomes. Longer‐term outcomes include growth, school achievement, and intelligence. 

Search methods for identification of studies

This review focuses on studies that investigate feeding programs and initiatives implemented in elementary and secondary schools. The search strategy in the previous Cochrane review published in 2007 used outcomes such as growth, body mass, weight, and height to limit the search ( Kristjansson 2007 ). This may have contributed to a narrower, more precise, and potentially biased strategy. We have updated the strategy to increase sensitivity. We also considered keywords, subject headings, and databases used in the strategy of a 2020 protocol on school feeding interventions in LMICs when designing the revised strategy ( Wang 2020 ). We will conduct searches using both keywords and database‐specific controlled vocabulary in relevant databases, in addition to complementary searches to identify additional studies as well as pertinent grey literature.

Electronic searches

We will conduct searches in subject‐specific and multidisciplinary databases and registries to identify relevant published studies and clinical trials to include in this review. PL will execute searches in the following databases and registries.

• Cochrane Central Register of Controlled Trials Ovid (current issue).
• MEDLINE Ovid (1946 onward).
• Embase Ovid (1947 onward).
• Allied and Complementary Medicine Ovid (1985 onward).
• APA PsycInfo Ovid (1806 onward).
• CAB Abstracts CAB Direct (1973 onward).
• CINAHL EBSCO (1981 onward).
• Education Source EBSCO (1880 onward).
• ERIC Ovid (1965 onward).
• Food and Science Technology Abstracts EBSCO (1969 onward).
• Global Health EBSCO (1973 onward).
• Web of Science Core Collection Clarivate (1970 onwards; includes Science Citation Index Expanded, Social Sciences Citation Index, Arts & Humanities Citatio Index, Conference Proceedings Citation Index ‐ Science, Conference Proceedings Citation Index ‐ Social Science & Humanities, and Emerging Sources Citatation Index).
• ProQuest Dissertations & Theses Global ProQuest (1637 onward).
• ClinicalTrials.gov (clinicaltrials.gov/).
• World Health Organization International Clinical Trials Registry Platform (WHO ICTRP; trialsearch.who.int/).
• Cochrane Database of Systematic Reviews (current issue) in the Cochrane Library.
• Campbell Collaboration (www.campbellcollaboration.org/better-evidence.html).
• Epistemonikos (www.epistemonikos.org/en/).

We will not use database limits or restrictions related to languages, dates, or publication types when searching the above resources.

The search strategy developed for MEDLINE Ovid was peer‐reviewed by another research librarian following the Peer Review of Electronic Search Strategies (PRESS) guideline for systematic reviews ( McGowan 2016 ). This strategy is available in  Appendix 1 .

We will add included studies to Zotero, which integrates notifications from Retraction Watch, to determine if any of the studies have been retracted. We will also access each included study on its original publisher platform to verify whether any corrections or updates were made since the original text was published.

Searching other resources

To identify relevant grey literature beyond theses and conference presentations that will be found through electronic searches, we will target the web sites and catalogues of the following organizations: UNESCO (via UNESDOC; unesdoc.unesco.org/), the World Food Programme (WFP; www.wfp.org/publications), and other United Nations publications (via the UN Digital Library; digitallibrary.un.org/), the WHO (www.who.int/publications), the World Bank (via its eLibrary; elibrary.worldbank.org/), and reports indexed on ReliefWeb’s site (reliefweb.int/updates?view=reports).  

In addition, we will hand search reference lists from relevant knowledge syntheses (systematic and non‐systematic reviews) and all of those from included primary studies to see if other relevant studies should be considered. We will also search for citations of included articles. In addition, authors of conference presentations identified through the electronic searches will be contacted to see if their research has been published as articles.

Data collection and analysis

In this section, we describe our data extraction and the analyses that we will perform.

Selection of studies

We will use  Covidence 2021  to manage studies identified in the search. Due to the breadth of the concepts and the diversity of sources to be searched, the initial search process will likely return more than 40,000 citations. Teams of two review authors each (EK, MO, AH, PCH, MD, AE, AN) will independently screen the titles and abstracts for inclusion. Review authors will classify each abstract as eligible, possibly eligible, or not eligible. We will retrieve full copies of all studies deemed eligible or possibly eligible by at least one review author for full‐text examination by two of the same seven review authors who will mark them as included or excluded. Where eligibility is unclear, we will mark the report as awaiting classification and contact the study authors for further information. Review authors will resolve disagreements by discussion. If necessary, we will consult with one of the other review authors.

We will provide details of studies that appear relevant but, after a thorough reading of the full text, should not be included, in the 'Characteristics of Excluded Studies' table ( Lefevbre 2019 ). This table will also include well‐known studies that were excluded. We intend to review all studies found in hand searching that are not duplicates of the ones found in the formal search; EK will first double‐check the titles selected from hand‐searching for relevance. After the inclusion/exclusion process is finished, we will enter the articles that we identified in hand searching into a Microsoft Excel sheet ( Microsoft Excel 2019 ) which we will check against studies found in the electronic search.

Data extraction and management

We will set up our data extraction form in Microsoft Excel ( Microsoft Excel 2019 ) and pilot test it before full use. Pairs of review authors (MO, MD, AH, AN, PCH) will independently extract data in duplicate. If there are any discrepancies between the two authors in the data extraction, we will resolve these discrepancies by discussion.

We will extract author and publication details, context, and study design data, including the allocation level. We will also extract data on the description of the intervention, including duration, baseline nutritional status, and whether the population is described as experiencing adverse socioeconomic circumstances. We will also report all interventions in a multi‐armed study. We will use PROGRESS‐PLUS ( O'Neill 2014 ;  Welch 2019 ) as an organizing framework to assess social circumstances. Thus, we will extract data on place of residence, race/ethnicity, occupation, gender/sex, religion, education, SES, social capital, age, disability, and other participant characteristics. We will also extract data on outcome measures and tools, statistical analyses, and the fixed and marginal costs of the feeding program. Ideally, these would be separate from research costs. Finally, we will extract data on results, including intention to treat (ITT) analyses, treatment on the treated, standard error (SE), and standard deviation (SD).

In cases where two articles use the same data set, same waves, and the same outcomes, we will choose the most recent article. 

If information is missing from the report, we will contact the study authors directly by email.

Process variables

To address Objective 3, several process elements will be extracted. Our list was chosen to represent factors that could impact the effectiveness of these programs and includes the following. 

• The intensity of the feeding (e.g. energy content of the meal/snack, percentage of average daily energy or protein requirement, and whether it is categorized as lower (interventions providing less than 15% of the average daily requirement for that age group) or higher (interventions providing 15% or more of the average daily requirement for that age group)).
• Context (country and area).
• Type of feeding (snack, meal, drink, and whether fortified or unfortified) and the time of day food was given.
• Quality/acceptability of the food given.
• The provider (who delivered the intervention).
• Whether intake was monitored.
• Child/youth adherence.
• Substitution.
• The cost of providing school meals.

Process evaluation

Contemporary research practice recommends process evaluation alongside empirical trials of complex interventions to identify how the intervention was implemented in practice, the mechanism by which it achieved its impact, and any local contextual issues that may have influenced outcomes ( Calnan 2003 ;  Campbell 2000 ). The process evaluation will be used to aid the interpretation of the findings. 

Process evaluation can also be undertaken as part of a systematic review by extracting, analysing, and synthesising any data from the included studies that may help explain the mechanism(s) of action, heterogeneity of outcomes, or both. Thus, when a complex social intervention appears to have had a significant effect in one trial but no effect (or a negative effect) in another, an analysis of the link between the context, intervention, and outcome aims to generate further hypotheses about the circumstances in which this intervention might be more or less successful.

Study quality may also impact findings; studies of lower quality will often show higher effect sizes than those of higher quality. For example, biased outcome assessment is possible in situations where those who assess the outcome variables are not blinded to the study group (i.e. intervention or control).

MO and MD will tabulate the effects for each study in Excel ( Microsoft Excel 2019 ) and sort them by the possible process elements to better understand the influence of process factors. We will begin with the study type, quality, and high versus low energy food. Energy content is an important process element, which will be assessed by the team's nutritionists (SL and JK). If possible, we will also estimate the recommended dietary intake (RDI) for other nutrients.

Rules used in calculating the energy content

• When the total energy content or percent of average daily energy requirement is provided in the text of the study, this value will be used. When the energy content is not provided, but the descriptions of food are sufficient (quantity and type of food), the energy content of the meal/snack will be estimated using Food Data Central ( USDA 2021 ).
• When meals/snacks with different energy contents are provided on different days (e.g.  Powell 1983 ), a weighted average will be taken (e.g. if a meal with 400 kcal was provided three days a week and a meal with 60 kcal was provided two days a week, then the weighted average of 264 kcal would be used).
• When the number of days on which different meals/snacks are given is not specified ( Agarwal 1989 ) or when the energy content is different in year one than year two of the study ( Neumann 2003 ), a straight average will be used for the energy content.

Calculating the percent average daily requirement for energy

The percent of the average daily requirement for energy will be calculated by dividing the given or estimated average energy content of the meal/snack by the requirement for the age/sex‐specific target group in each study ( FAO 2004 ). When the intervention group of a study is comprised of various age and sex groups, and outcomes are given for the entire group only, a weighted average for the average daily energy requirement will be used to calculate the percent average daily energy requirement. In addition, as a check, the percent average daily energy requirement will be calculated for each age and sex group for which there is a corresponding average daily energy requirement by dividing the total energy provided by the meal/snack by the age and sex‐specific average daily energy requirement. Energy intensity will be considered as a continuous variable. However, for purposes of helping to interpret the data, interventions will also be characterised as having two levels of energy content: lower (interventions providing less than 15% of the average daily energy requirement for that age group) and higher (interventions providing 15% or more of the average daily energy requirement for that age group).

After data extraction is completed, the 'Characteristics of included studies' table will be developed.

Assessment of risk of bias in included studies

We are interested in the effect of intervention and control group assignment on the study outcomes. We will use several tools; one for the RCTs, one for the NRSs except for ITS, and one for the ITS studies. At least two reviewers (EK, BS, MO, MD) will independently rate each aspect of risk of bias. Disagreements will be resolved by discussion with a third author. Two nutritionists (JK, SL) will assess the risk of bias for anthropometric measurements. A registered clinical psychologist (LJ) will assess the risk of bias for psychological measures.

To rate the risk of bias for RCTs, we will use the Cochrane RoB 2 tool ( ROB2 2021 ;  Sterne 2019a ;  Sterne 2019b ) as outlined in Chapter Eight of the Cochrane Handbook for Systematic Reviews of Interventions (hereafter referred to as the Cochrane Handbook ;  Higgins 2019c ). We will also use the Crib Sheet ( Higgins 2019d ) and the Excel implementation sheet to guide us in our decision‐making ( RoB Excel Tool 2022 ).

• Bias arising from the randomisation process (allocation sequence generation and allocation concealment, baseline differences).
• Bias due to deviations from intended interventions (non‐protocol interventions, the effect of assignment, blinding, and appropriate analyses).
• Bias due to missing outcome data.
• Bias due to measurement of the outcome.
• Bias due to selection of the outcome.

For each of these domains, we will judge the result as low risk of bias, some concerns, or high risk of bias. To reach this judgment, we will follow signalling questions, which will help us to decide on these levels. These signalling questions have five response options: yes, probably yes, no, probably no, and no information. 

Based on the judgments of the five domains, we will determine the overall risk of bias for each outcome within a study. This will be related to the highest risk in any domain; e.g. if all domains are low risk the overall ROB for that outcome will be low risk, but if any of the domains are judged to be of some concern the overall risk will be judged to be of some concern. If any of the domains are at high risk or if there are some concerns in multiple domains, the overall ROB for that outcome will be judged to be at high risk.

Cluster RCTs

For this, we will follow the criteria outlined in Chapter 23 of the Cochrane Handbook ( Higgins 2019b ). We will also as use the guidance document ( Eldridge 2021 ), the Crib Sheet ( Higgins 2019d ), and the Excel Tool ( RoB Excel Tool 2022 ).

The criteria are as follows. 

• Bias due to timing of identification or recruitment of participants (recruitment before randomisation, preventing knowledge of assignment to clusters, baseline imbalance).
• Bias due to deviations from intended interventions (awareness of trial and their assigned intervention, caregiver's awareness, deviations from intended intervention, and appropriate analyses).
• Bias due to missing outcome data (data for all clusters, number of missing in each cluster, missingness related to outcome variable).
• Bias due to measurement of the outcome (measurement of appropriate, measurement different between groups, participants blinded to trial, outcome assessor aware of assignment, assessment influenced by knowledge of assignment).
• Bias due to selection of reported results.

The overall risk of bias for a study/outcome is judged as low, moderate, serious, or critical using the criteria in Chapter 23 of the Cochrane Handbook ( Higgins 2019b ).

Please note that this tool for cluster‐RCTs can also be used with stepped wedge trials, realising that it does not cover the need for adjusting data for time trends ( Higgins 2019b ). 

Crossover RCTs

To assess the ROB in a crossover trial, we will use the draft version of the ROB 2 tool for crossover trials ( Higgins 2021 ). We will also use the Crib Sheet and Excel Tool. The criteria for crossover trials are as follows. 

• Bias that arises from the randomisation process; here, the randomisation is to sequence A or B of the cross‐over trial.
• Domain S: Bias arising from period and carryover effects.
• Bias in the measurement of the outcome.
• Bias in the selection of the reported result.

Criteria for controlled cohort studies and CBAs

We will assess the risk of bias for this group of studies using the ROBINS‐I tool for non‐randomised studies ( Reeves 2019 ;  Sterne 2016 ). The domains are as follows.

• Bias due to confounding.
• Bias in the selection of participants for the study.
• Bias in the classification of interventions.
• Bias due to deviations from intended interventions.
• Bias due to missing data.
• Bias in the measurement of outcomes.
• Bias in the selection of the reported result. 

For each domain, there are five possible levels of bias: low, moderate, serious, critical, and no information. For each domain, signalling questions help the judgment of the level of bias. These signalling questions have five response options: yes, probably yes, no, probably no, and no information ( Sterne 2016 ).

The judgment of the overall risk of bias will be the least favourable assessment across the domains. This judgment will be low risk of bias across all domains, some concerns in at least one domain but not at high risk of bias for any domain, or high risk of bias in at least one domain.

Criteria for ITSs

In assessing the methodological quality of ITS studies, we will use the Suggested risk of bias criteria for EPOC reviews ( Cochrane EPOC 2022 ). The domains include the following.

• Intervention is independent of other changes.
• The shape of the intervention is prespecified.
• Intervention unlikely to prevent data collection.
• Knowledge of allocation.
• Incomplete outcome data are adequately taken care of.
• Selective outcome reporting.
• Other risks of bias.  

We will rate each domain as having low risk, unclear risk, or high risk of bias as per the criteria outlined within .

Measures of treatment effect

Rcts , continuous outcomes.

For continuous outcomes, the effect estimate of interest is the change or the mean difference between the experimental and control groups in the end‐of‐study outcome, adjusted for baseline outcome measure. Thus, we will enter the unstandardised regression coefficient that compares the change scores between experimental and control groups. We will use the model with adjustment for the highest number of covariates. 

In cases where regression has not been performed, but when the baseline and end‐of‐study means and SDs are available (or the SD could be derived based on statistics provided e.g. 95% confidence interval (CI)), we will calculate the mean change for each of the two groups (end‐of‐study mean minus baseline mean). The SDs for change will be calculated using the formula: SQRT ((SD 2 baseline + SD 2 end‐of‐study) *2ρ) * (SDbaseline*SD end‐of‐study)). We will generally use 0.8 for the correlation between the baseline and the end of the study values, as recommended by our statistician. However, we will use 0.9 for the correlation between the weight, height, and BMI baseline and end‐of‐study measures; this was based on coefficients supplied by  Du 2005  for the first Kristjansson school feeding review ( Kristjansson 2015 ). 

We will conduct sensitivity analyses for both growth and psychological outcomes with a P of 0.7.

Dichotomous outcomes

For dichotomous outcomes, the effect estimate of interest will be the risk ratio (RR) of the risk in the experimental group relative to the risk in the control group, or the odds ratio (OR) or the odds that a given outcome will occur. To get these statistics, we will enter the log of the OR or RR plus the SE. In cases where multiple coefficients are presented in the paper, we will select the one representing the analysis with the most control variables.

CBAs and controlled cohort studies

For continuous outcomes, the effect estimate of interest is the change or the mean difference between the experimental and control groups in the end‐of‐study outcome, adjusted for baseline outcome measure. Thus, we will enter the unstandardised regression coefficient that compares the change scores between experimental and control groups. We will use the model with adjustment for the greater number of covariates. 

In cases where regression has not been performed, but when the baseline and end‐of‐study means and SDs are available (or the SD could be derived based on statistics provided e.g. 95% CI), we will calculate the mean change for each of the two groups (end of‐study‐mean minus baseline mean). The SD for change will be calculated using the formula: SQRT ((SD 2 baseline + SD 2 end‐of‐study) *2ρ) * (SDbaseline*SD end‐of‐study)) where P is the correlation between baseline and end‐of‐study. We will typically use 0.8 for the correlation between the baseline and end‐of‐study values, as recommended by our statistician. However, we will use 0.9 for the correlation between weight, height, and BMI baseline and end‐of‐study measures; this was based on coefficients supplied by Du 2005 for the Kristjansson school feeding review ( Kristjansson 2007 ).

For dichotomous outcomes, the effect estimate of interest will be the RR of the risk in the experimental group relative to the risk in the control group or the OR, representing the odds that a given outcome will occur. For these, we will enter the log of the OR or RR plus the SD. In cases where multiple coefficients are presented in the paper, we will select the one representing the analysis with the most control variables.

For these studies, we will use estimates from time series regression. We will examine the trends/slopes and changes in the outcome level before and after the intervention and the mean change in the outcome level.

Unit of analysis issues

Cluster studies (crcts, cbas, and itss).

For c‐RCTs and non‐randomised studies (CBAs and ITSs), we anticipate that the study authors will have presented their results after appropriately controlling for clustering effects (robust SEs or hierarchical linear models). We will document clustering and analysis methods used within the studies to control for this. We will correct the design effect using the variance inflation factor (VIF) if needed.

Calculating the VIF

• First, we will calculate cluster size. When the numbers of participants in each analysis are provided, we will divide these numbers by the number of clusters to calculate the average cluster size. Otherwise, we will use the number of participants provided in the methods sections of the primary studies and divide that by the number of clusters.
• Then, we will use appropriate intra‐cluster correlations (ICCs). For growth and biochemical outcomes, we will use the ICCs published in Du's 2005 letter to the editor ( Du 2005 ). Thus, we will use ICCs of 0.025 and 0.016 for weight and height, respectively. We will conduct sensitivity analyses with ICCs of 0.01, 0.05, and 0.10 for weight and height. We will conduct further sensitivity analyses for each outcome to assess how large the ICC will need to be to change the results. For math, reading, science, attendance, and intelligence outcomes, we will use ICCs of 0.15, with sensitivity analyses at 0.10 and 0.20. This will be based on recommendations from the Schochet report for math and reading ( Schochet 2008 ).
• Then, for experimental and control groups separately, we will calculate the VIF as follows: (1+ (m‐1) multiplied by ICC), where m is the average cluster size ( Ukoumunne 1999 ). We will then multiply the original SD by the square root of the VIF for experimental and control groups separately. We will then enter these adjusted SDs into Review Manager Web ( RevMan Web 2022 ) data tables.

Dealing with missing data

As noted in the ' Data extraction and management ' section, we will contact the authors for missing data. We will contact authors directly by email if there is information missing from the reports that would help us to conduct this review. We will ask for statistical data (e.g. SE) or information about their study design, or both.

We will consider missing participant data as well as missing statistics.

• Did the authors do an ITT analysis taking into consideration loss to follow‐up in the study using imputation methods?
• Did they provide us with the needed statistics (e.g. SD/SE) to conduct the meta‐analysis?

If SDs or SEs are not reported in the primary studies and we do not receive the data after contacting the authors, we will calculate such information from exact P values or from CIs using the  RevMan Web 2022  online calculator ( Drahota 2021 ). 

Assessment of heterogeneity

 We will use the following methods to assess clinical, methodological, and statistical heterogeneity.

• First, we will visually examine forest plots for visible outliers and between‐study differences.
• Second, we will use the I 2  statistic to assess the level of heterogeneity. Specifically, we will use the rough interpretation guide presented in  Deeks 2019  as a reference point (i.e. 0% to 40%: might not be important; 30% to 60%: moderate heterogeneity; 50% to 90%: substantial heterogeneity; 75% to 100%: considerable heterogeneity). When the I 2 statistic is > 0.75, we will not perform a meta‐analysis with the studies but instead will look for the source of the heterogeneity.
• Third, we will explore heterogeneity by conducting subgroup analyses, when possible. Sources of heterogeneity could include differences in participants, study type, intervention implementation, and context (e.g. rural versus urban).

Assessment of reporting biases

If more than ten studies are summarised in any one meta‐analysis, we will plot the possible trial effect against the SE and show it as a funnel plot ( Higgins 2019a ). Asymmetry could be caused by a relationship between effect and sample size or publication bias ( Egger 1997 ). If we detect asymmetry, we will interpret the results in combination with a visual examination of the plots. This will allow for the exploration of small study effects and outliers. If we identify small study effects, we will conduct a sensitivity analysis to explore the impact on the meta‐analysis. We will apply this approach to the results of both RCTs and other types of studies. 

Data synthesis

Quantitative meta‐analyses.

We will conduct meta‐analyses when we have a minimum of two studies that can be combined (e.g. same intervention, outcome, and study design, I 2 below 75). We will perform these meta‐analyses in RevMan Web ( RevMan Web 2022 ). 

We will perform meta‐analyses separately for each type of study design (RCTs, cluster RCTs, cross‐over RCTs, NRCTs, CBAs, controlled cohort, and ITSs). We will also complete separate meta‐analyses for higher‐income and lower‐income countries. 

The generic inverse variance method will be used as the preferred method of meta‐analysis. Using this method, for continuous variables, we will enter unstandardised regression coefficients and SEs, which have been adjusted for relevant covariates. These statistics will be converted to the same units. For dichotomous outcomes, which may be adjusted for relevant covariates, we will enter the log of the RR and SEs, or the OR and SE. 

For each meta‐analysis, we will provide an estimate with 95% CI; we will also generate a forest plot. In many instances, we will need to derive SEs from CIs using the RevMan calculator ( Drahota 2021 ). We will use a random‐effects model for all analyses ( Higgins 2019a ), as clinical and methodological heterogeneity between studies is anticipated in terms of the type and implementation of interventions, participant groups, or outcomes measured. We will discuss the extent of the evidence against homogeneity in each analysis.

For cross‐over RCTs, we will use a paired t‐test with generic inverse variance ( Higgins 2019b ).

As noted above, we will determine whether the interventions, participants, or outcomes are similar or too different to combine. We will not combine different types of study designs. If the I 2 for any meta‐analysis is > 75%, we will not combine all studies in the meta‐analysis.

Syntheses without meta‐analysis

If the effect sizes are given but do not have the variability estimate, we will summarise the data using medians and interquartile ranges.

We will also prepare an effect direction plot for studies that we could not use to conduct a quantitative meta‐analysis ( Thompson 2013 ). We will narratively synthesise reports for studies based on effect direction as well, as suggested on page 327 in the Cochrane Handbook ( Higgins 2019a ). We will use the SWiM guidelines to ensure that we report our qualitative syntheses appropriately ( Campbell 2020 ). These guidelines concern grouping studies together, the metric and transformation method used, the synthesis method used, priority setting, reporting of heterogeneity and certainty of the evidence, data presentation, and reporting results and limitations.

Drawing conclusions

When drawing our conclusions, we will consider the risk of bias, the certainty of the evidence, effect size, CI, statistical significance, and real‐world meaningfulness.

Avoiding dependency

To avoid dependency, we will be careful not to double‐count the same participants in the analyses. For multi‐arm studies, we will follow methods outlined in Chapter 23 in the Cochrane Handbook ( Higgins 2019b ).

Synthesizing data from process evaluations

We will follow a realist approach to synthesise the data collected from process evaluations. As recommended by the RAMESES methodological standards ( Wong 2013 ), analysis and synthesis of findings will be an interpretive process, reached through reflection and discussion and requiring repeated reading and re‐reading of primary studies in light of the emerging synthesis. We will give particular attention to identifying and exploring the mechanisms by which study participants drew upon resources available to achieve the intended outcome.

This approach will result in a series of context‐mechanism‐outcome (CMO) configurations that represent hypotheses concerning which outcomes are generated through which mechanisms in which context ( Rycroft‐Malone 2012 ). We will iteratively test theories and refined based on integrating evidence of effectiveness (i.e. what works) with evidence derived from process evaluations and implementation research (i.e. how and why it works). The effectiveness evidence will contribute to the outcome and mechanism components of a CMO, whereas the process/implementation evidence will contribute to the mechanism and context components of a CMO ( Harden 2018 ). We will synthesise this data using the following steps.

• Organization of extracted data into evidence tables. This may include the theory of change proposed by study authors, why they felt the intervention was needed and what they thought it would achieve, and authors’ conclusions about why the intervention had worked or not worked; differences in subgroups, and any explanations for these differences; and additional mechanisms proposed by authors.
• Theming of context, mechanisms, and outcomes by individual reviewers.
• Comparison of reviewers' themes for a specific article and formulation of chains of inference from the identified themes.
• Linking of the chains of inference and tracking and linking of articles.
• Hypothesis formulation (context, mechanism, and outcome configurations).
• Integration of analysis of the underlying theories of how the feeding interventions are expected to bring about change, and ii) the findings of the trials and the process evaluations of how the theory worked or did not work in practice.

As an output of this synthesis, we will identify factors that enhance or reduce the effectiveness of school feeding programs. 

Subgroup analysis and investigation of heterogeneity

Subgroup analyses  .

We will conduct subgroup analysis across SES, age, and sex for the three primary outcomes: physical health, educational, and cognitive outcomes. 

To address Objective 2, we will perform subgroup analyses by SES or baseline nutritional status (as an indicator of socioeconomic disadvantage), or both, to determine whether school feeding works as well or better for children with socioeconomic disadvantage. This, in turn, would decrease socioeconomic inequities. 

Furthermore, different treatment effects of school meals for children from various socioeconomic and nutritional statuses are expected. In high‐income societies where, for instance, obesity is a concern, school feeding aims to enhance access to fruit, vegetables, and low‐fat food ( Coleman 2005 ;  Luepker 1996 ), whereas, in lower‐income societies, the effects might include fighting against malnutrition. Studies also suggest that children from lower‐income countries are more likely to benefit from school meals.

Age and sex

Because growth rates and caloric needs may vary by age, we will conduct a subgroup analysis across two age groups for weight and height. These age groups are 5 to 11 years and 12 to 19 years. This age grouping was chosen because caloric needs vary by those ages. We also plan to do subgroup analyses by these two age groups for cognition, as it is possible that the effectiveness of school meals in changing cognitive outcomes may vary according to age. We also will conduct subgroup analyses by sex, as sex differences in development may occur. Furthermore, there may be cultural differences in how boys and girls are treated.

% RDI for energy given 

In the earlier  Kristjansson 2007  review, we found that effectiveness differed between studies that gave meals/snacks with high energy content and those that gave meals/snacks with low energy content. Therefore, we will run subgroup analyses by the level of energy given, dividing energy given into higher/lower groups using a median split.

The credibility of subgroup analyses

We will assess seven criteria to evaluate the credibility of subgroup analyses ( Guyatt 2011 ).

• Is the difference suggested by comparisons within rather than between studies?
• Does the interaction test suggest a low probability that chance explains the apparent subgroup effect?
• Were the subgroup analyses and their direction specified beforehand?
• Is the subgroup analysis one of a few tested?
• Is the magnitude of the subgroup effect large?
• Was the same comparison with the same result done within a primary study?
• Did the difference follow a common‐sense rationale?

Sensitivity analysis

If possible, we will perform sensitivity analysis to assess the impact of risk of bias and industry funding on the overall result of studies.

• Risk of bias: we will re‐analyse the data, excluding studies at high risk of bias.
• Bias due to industry funding: we will re‐analyse the data, excluding studies that are industry‐funded.

We will report the results of these sensitivity analyses for each source of bias.

Summary of findings and assessment of the certainty of the evidence

We will use  GRADEpro GDT  to create 'Summary of findings' tables for each of the following five comparisons.

• Snack only versus control.

In each table, we will present information on the populations and experimental and comparison interventions examined, as well as the magnitude of the effect of the interventions, the sum of available data on the outcomes (including the timing of the observations (whether short‐term or longer‐term)), and the certainty ratings of the evidence ( Schünemann 2019 ). Where there is evidence for a particular outcome from both RCTs and non‐randomised studies, we will report the data from the RCTs and non‐randomised studies separately; we will report data from the RCTs first. 

We will include the following outcomes in each table.

• Change in height or height for age z‐score.
• Change in reading performance.
• Change in math performance.
• Change in attendance.
• Change in verbal fluency.
• Adverse outcomes of overweight/obesity and behaviour problems.

Working independently, two review authors will use the GRADE approach to assess the certainty of the evidence for each outcome ( Schünemann 2019 ); for narrative syntheses, we will follow  Murad 2017 . We will resolve differences in opinions by discussion with a third review author. We will judge the certainty of the evidence for each outcome as high, moderate, low, or very low ( Schünemann 2019 ). We will base this rating on the presence of risk of bias, inconsistency, indirectness, imprecision, and publication bias, outlined in detail in  Appendix 2 . Non‐randomised studies assessed with ROBINS‐I will start as high certainty. All studies (RCTs and non‐randomised studies) can be downgraded to a lower level.

Acknowledgements

We would like to acknowledge the Cochrane Developmental, Psychosocial, and Learning Problems Review Group for their contributions and valuable feedback. We would also like to acknowledge the IMPACT Community of Practice with the WFP. We would also like to acknowledge the important contributions of the Cochrane Copy Editor, Carolyn Wayne.

We acknowledge the contribution of Allison Smith, Research Librarian at the University of Ottawa Library, who peer‐reviewed the MEDLINE search strategy using the Peer Review of Electronic Search Strategies (PRESS) guideline for systematic reviews ( McGowan 2016 ).

The CRG Editorial Team are grateful to the following peer reviewers for their time and comments: Dr. Amanda Brand, Centre for Evidence‐Based Health Care, Stellenbosch University, South Africa, and Cochrane Nutrition; and Denny John, Adjunct Assistant Professor, Amrita Institute of Medical Sciences & Research Centre, Amrita Vishwa Vidyapeetham, Kochi, India.

Appendix 1. MEDLINE Ovid search strategy

• exp nutrition policy/
• nutrition therapy/
• food, fortified/
• food services/
• ((feed* or food* or nutrition* or diet*) adj3 (program* or policy or policies or therap* or initiative* or intervention* or plan*)).ti,ab,kf.
• ((breakfast* or break‐fast* or break fast* or lunch* or dinner* or supper* or meal* or snack*) adj3 (program* or policy or policies or initiative* or intervention* or plan*)).ti,ab,kf
• ("food service*" or cater* or cafeteria* or canteen* or "tuck shop*" or "meal service*" or lunchroom*).ti,ab,kf
• ((beverage* or milk or meat* or egg* or fruit* or vegetable*) adj3 (program* or policy or policies or initiative* or intervention* or plan*)).ti,ab,kf.
• ((fortif* or enrich*) adj3 (food* or diet* or spread* or flour* or cereal*)).ti,ab,kf
• ((supplement* or complement*) adj3 (food* or feed* or diet* or nutrition* or nutrient* or micronutrient* or micro‐nutrient* or macronutrient* or macro‐nutrient*)).ti,ab,kf.
• or/1‐11
• (school*).ti,ab,kf.
• or/13‐14
• (school* adj3 (feed* or food* or breakfast* or break‐fast* or break fast* or lunch* or dinner* or supper* or meal* or snack*)).ti,kf.

Appendix 2. GRADE criteria for downgrading and upgrading  the certainty of the evidence 

Criteria for downgrading the certainty in the body of evidence: rcts , study limitations.

We will base our judgments on the Cochrane RoB 2 across an outcome for different studies. 

We shall downgrade by one if:

• Most (70% or more) of the weight in the synthesis is given to studies with high risk of bias for allocation concealment; OR
• Most (70% or more) of the weight in the synthesis is given to studies with low risk of bias for allocation concealment, but high risk of bias for deviations from intended interventions and high risk of bias due to missing outcome data; OR
• Most of the weight (70% or more) in the synthesis is given to studies with 'some concerns' about allocation concealment, deviations from intended interventions, and incomplete outcome data; OR
• Most of the weight (70% or more) in the synthesis is given to studies that have overall high risk of bias for that outcome.

We will downgrade by two levels if most of the weight in the synthesis is given to studies that have high risk of bias for allocation concealment, deviations from intended interventions, and incomplete outcome data.

Indirectness

If the papers do not directly address our questions, we will downgrade one level for indirectness.

Inconsistency

If there is high and unexplained heterogeneity (I 2  = 75 or more) within the body of evidence, we will rate down one for inconsistency. If heterogeneity is explained by subgroup analysis, we will rate on the basis of number of participants required for an adequately powered individual study. However, it is important to note that we will not perform a meta‐analysis unless I 2  is less than 75  and/or I 2 is more than 75 and subgroup analyses help to explain the source.

Imprecision

We will judge imprecision in the following manner.

• If the 95% confidence interval (CI) excludes the null (e.g. a risk ratio (RR) of 1.0) and the total number of events or patients exceeds the optimal informations size (OIS) criterion, we will judge the precision to be adequate.
• If the 95% CI includes appreciable benefit or harm (e.g. an RR of under 0.75 or over 1.25), we will downgrade for imprecision even if the OIS criterion is met.
• If the OIS is not met, we will downgrade by one.
• If both 1 and 2 are true (e.g. OIS not met, 95% CI included appreciable benefit or harm), we will downgrade by two levels.

In calculating the OIS, we will assume that we are trying to detect a small difference (D = 0.02). We will calculate the OIS using the appropriate program modules on the Boston School of Public Health web site for differences in proportion ( LaMorte 2020 ), or Daniel Soper's sample size calculator ( Soper 2021 ). 

High probability of publication bias

We will judge this based on our funnel plots, if possible.

Criteria for downgrading the certainty in the body of evidence: controlled before and after, controlled cohort, or interrupted time series studies.

We will base our judgments of study limitations on the risk of bis from ROBINS‐I for each study outcome in the meta‐analysis. We shall downgrade by one if most (70% or more) weight in the synthesis was allotted to studies that were at overall serious risk of bias for that outcome.

We shall downgrade by two levels if most (70% or more) of the weight in the meta‐analysis was allotted to studies that were judged to have critical risk of bias for that outcome.

If there is high and unexplained heterogeneity (I 2  = 75 or more) within the body of evidence, we will rate down one for inconsistency. If heterogeneity is explained by subgroup analysis, we will rate on the basis of number of participants required for an adequately powered individual study. Please note that we will generally not perform a meta‐analysis if there is greater than 75% heterogeneity.

• If the 95% CI excludes the null (e.g. RR of 1.0) and the total number of events or patients exceeds the OIS criterion, we will judge precision to be adequate. It also will be judged to be adequate if the 95% CI does not include both appreciable benefit and appreciable harm. 
• If the 95% CI includes appreciable benefit or harm (e.g. an RR of under 0.75 or over 1.25), we will downgrade for imprecision even if the criterion is met.
• If the OIS is not met, we will downgrade by one. 
• If both 2 and 3 are true (e.g. OIS is not met, 95% CI included very appreciable benefit or harm), we will downgrade by two levels.

In calculating the OIS, we will assume that we are trying to detect a small difference (D = 0.02). We will calculate the OIS using the appropriate program modules on the Boston School of Public Health website ( LaMorte 2020 ) for differences in proportion or Daniel Soper's sample size calculator for linear regressions ( Soper 2021 ).

Upgrading the evidence from non‐randomised studies

We will apply the following criteria for upgrading.

Large effect

We will consider "not only the point estimate but also the precision (width of the CI) around that effect: one should rarely and very cautiously rate up quality of evidence because of apparent large effects, if the CI overlaps substantially with effects smaller than the chosen threshold of clinical importance" (Chapter 5.3,  Schünemann 2013 ).

We will follow the Cochrane Handbook for large effects of dichotomous data.

• Large effect: RR > 2 or < 0.5.
• Very large effect: RR > 5 or < 0.2.

For continuous variables, we will consider a Cohen's d of 0.5 as a large effect.

Dose‐response relationship

We will upgrade the evidence if there is clear evidence for a dose‐response relationship.

Plausible confounding

If plausible confounding in a rigorous non‐randomised study may have resulted in a underestimate of the effect, we will consider upgrading by one level. 

Contributions of authors

Developed the concept, obtained the funding, and is the guarantor for the review: Elizabeth Kristjansson.

Wrote and edited the protocol: Elizabeth Kristjansson, Muna Osman, Michael Dignam, Julia Krasevec, Patrick Labelle, Andrea Huerta Galacia, Paige Cooke Hughes, Arghavan Nepton, Aganeta Enns, George Wells, Bev Shea, Selma Liberato, Jennifer Garner, and Vivian Welch.

Coordinated the development and revision of the protocol: Muna Osman.

Developed the conceptual mode with input from all authors and our advisory committee: Michael Dignam.

Developed the procedures for calculating energy content of the meals as well as for calculating the average daily requirement for energy: Julia Krasevec.

Developed the search strategy and wrote the literature search section: Patrick Labelle.

Wrote the majority of the analysis section: George Wells.

Provided input into the risk of bias section: Bev Shea.

Provided input into the cognitive measures: Laura Janzen.

Sources of support

Internal sources.

Home institution of several review authors (BK, MO, MD, PL,  GW, VW, AHG, AN, PCH)

External sources

Provided funding for the Review. The WFP has no control over the design, planning or execution of this review; however, a few people from the WFP sit on the Advisory Board, to help develop the conceptual model and later disseminate the review's findings. 

Declarations of interest

Elizabeth Kristjansson (EK) is a co‐chair and editor with the Campbell Collaboration Nutrition group and a member of the Advisory board of Cochrane Nutrition.

Muna Osman has declared that she has no conflicts of interest.

Michael Dignam has declared that he has no conflicts of interest.

Patrick R Labelle has declared that he has no conflicts of interest.

Olivia Magwood has declared that she has no conflicts of interest.

Andrea Huerta Galicia has declared that she has no conflicts of interest.

Paige Cooke‐Hughes has declared that she has no conflicts of interest.

George A Wells has declared that he has no conflicts of interest.

Julia Krasevec (JK) was a coauthor on the 2007 Cochrane Review for this topic while she worked at the Canadian International Development Agency (now Global Affairs Canada). JK currently works for UNICEF as a Statistics and Monitoring Specialist on Nutrition data. UNICEF has various publications that discuss school feeding; JK is acknowledged on the 2019 SOWC report (www.unicef.org/media/60806/file/SOWC-2019.pdf) and other UNICEF and interagency reports that mention school feeding.

Aganeta Enns has declared that she has no conflicts of interest.

Arghavan Nepton has declared that she has no conflicts of interest.

Laura Janzen has declared that she has no conflicts of interest.

Beverly Shea is an Editor with Cochrane Musculoskeletal.

Selma C Liberato has declared that she has no conflicts of interest.

Jennifer Garner has declared that she has no conflicts of interest. 

Vivian Welch has declared that she has no conflicts of interest.

Additional references

Adolphus 2013.

• Adolphus K, Lawton CL, Dye, L. The effects of breakfast on behavior and academic performance in children and adolescents . Frontiers in Human Neuroscience 2013; 7 :425. [DOI: 10.3389/fnhum.2013.00425] [PMCID: PMC3737458] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Afridi 2019

• Afridi F, Barooah B, Somanathan R. Hunger and performance in the classroom . Bonn (DE): IZA Institute of Labor Economics; 2019 September. IZA Discussion Paper No.: 12627 2019.

Agarwal 1989

• Agarwal DK, Agarwal KN, Upadhyay SK. Effect of mid-day meal programme on physical growth & mental function . Indian Journal of Medical Research 1989; 90 :163-74. [PMID: ] [ PubMed ] [ Google Scholar ]

Anderson 2018

• Anderson ML, Gallagher J, Ramirez Ritchie E. School meal quality and academic performance . Journal of Public Economics 2018; 168 :81-93. [DOI: 10.1016/j.jpubeco.2018.09.013] [ CrossRef ] [ Google Scholar ]

Armijo‐Olivia 2012

• Armijo-Olivo S, Stiles CR , Hagen NA , Biondo PD, Cummings GG J. Assessment of study quality for systematic reviews: a comparison of the Cochrane Collaboration Risk of Bias Tool and the Effective Public Health Practice Project Quality Assessment Tool: methodological research . Eval Clin Practice 2012; 12 ( 8 ):1111. [ PubMed ] [ Google Scholar ]

Baretto 2017

• Baretto ML. Health inequalities: a global perspective . Ciência & Saude Coletiva 2017; 22 ( 7 ):2097–108. [DOI: 10.1590/1413-81232017227.02742017] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Calnan 2003

• Calnan M, Ferlie E. Analysing process in healthcare: the methodological and theoretical challenges . Policy & Politics 2003; 31 ( 2 ):185-93. [DOI: 10.1332/030557303765371672] [ CrossRef ] [ Google Scholar ]

Campbell 2000

• Campbell M, Fitzpatrick R, Haines A, Kinmonth AL, Sandercock P, Spiegelhalter D, et al. Framework for design and evaluation of complex interventions to improve health . BMJ 2000; 321 ( 7262 ):694-6. [DOI: 10.1136/bmj.321.7262.694] [PMCID: PMC1118564] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Campbell 2020

• Campbell M, McKenzie JE, Sowden A, Katikireddi SV, Brennan SE, Ellis S, et al. Synthesis without meta-analysis (SWiM) in systematic reviews: reporting guide . BMJ 2020; 368 :l6890. [DOI: 10.1136/bmj.l6890] [PMCID: PMC7190266] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Cochrane EPOC 2022

• Cochrane Effective Practice and Organisation of Care (EPOC). Suggested risk of bias criteria for EPOC reviews . epoc.cochrane.org/sites/epoc.cochrane.org/files/public/uploads/Resources-for-authors2017/suggested_risk_of_bias_criteria_for_epoc_reviews.pdf (accessed 5 May 2022).
• Cohen JF, Hecht AA, McLoughlin G, Turner L, Schwartz MB. Universal school meals and associations with student participation, attendance, academic performance, diet quality, food security, and body mass index: a systematic review . Nutrients 2021; 13 ( 3 ):911. [DOI: 10.3390/nu13030911] [PMCID: PMC8000006] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Coleman 2005

• Coleman KJ, Tiller CL, Sanchez J, Heath EM, Sy O, Milliken G, et al. Prevention of the epidemic increase in child risk of overweight in low-income schools: the El Paso coordinated approach to child health . Archives of Pediatric & Adolescent Medicine 2005; 159 ( 3 ):217-24. [DOI: 10.1001/archpedi.159.3.217] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Covidence 2021 [Computer program]

• Veritas Health Innovation Covidence . Version accessed 12 May 2021. Melbourne, Australia .. registered in Australia (ACN 600 366 274, ABN 41 600 366 274). : Veritas Health Innovation, 2022. Available at covidence.org.
• Deeks JJ, Higgins JP, Altman DG, editor(s). Chapter 10: Analysing data and undertaking meta-analyses. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019:241-84. [DOI: 10.1002/9781119536604] [ISBN-13: 978-1119536628] [ CrossRef ] [ Google Scholar ]

Diderichsen 2001

• Diderichsen F, Evans T, Whitehead M. The social basis of disparities in health. In: Evans T, Whitehead M, Diderichsen F, Bhuiya A, Wirth M, editors(s). Challenging Inequities in Health: From Ethics to Action . Oxford (UK): Oxford University Health, 2001:12-23. [DOI: 10.1093/acprof:oso/9780195137408.001.0001] [ISBN-13: 978-0195137408] [ CrossRef ] [ Google Scholar ]

DiGirolamo, 2020

• DiGirolamo AM,  Ochaeta L, Flores RMM. Early childhood nutrition and cognitive functioning in childhood and adolescence . Food and Nutrition Bulletin 2020; 41 ( 1 Suppl ):S31-S40. [DOI: 10.1177/0379572120907763] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Drahota 2021

• Drahota A,  Beller E. RevMan calculator . Available at training.cochrane.org/resource/revman-calculator (accessed 10 May 2021).
• Drake L, Fernandes M, Aurino E, Kiamba J, Giyose B, Burbano C, et al. School feeding programs in middle childhood and adolescence. In: Bundy DA, De Silva N, Horton S, Jamison DT, Patton GC, editors(s). Child and Adolescent Health and Development . 3rd edition. Vol. 8 . Washington (DC): International Bank for Reconstruction and Development/World Bank, 2017:147-64. [DOI: 10.1596/978-1-4648-0426-7] [ISBN-13: 978-1-4648-0423-6] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Drake LJ, Lazrak N, Fernandes M, Chu K, Singh S, Ryckembusch D, et al. Establishing global school feeding programme targets: how many poor children globally should be prioritized, and what would be the cost of implementation? Frontiers in Public Health 2020; 8 :530176. [DOI: 10.3389/fpubh.2020.530176] [PMCID: 10.3389/fpubh.2020.530176] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Du X, Zhu K, Trube A, Fraser DR, Greenfield H, Zhang Q, et al. Effects of school-milk intervention on growth and bone mineral accretion in Chinese girls aged 10-12 year: accounting for cluster randomisation . British Journal of Nutrition 2005; 94 ( 6 ):1038-9. [DOI: 10.1079/bjn20051584] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Egger M, Davey Smith G, Schneider M, Minder CE. Bias in meta-analysis detected by a simple, graphical test . BMJ 1997; 315 ( 7109 ):629-34. [DOI: 10.1136/bmj.315.7109.629] [PMCID: PMC2127453] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Eldridge 2021

• Eldridge S, Campbell MK, Campbell MJ,  Drahota AK, Giraudeau B, Reeves BC, et al. Revised Cochrane risk of bias tool for randomized trials (RoB 2): additional considerations for cluster-randomized trials  . Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License 2021.

FAO/IFAD/UNICEF/WFP/WHO 2020

• Food and Agriculture Organisation (FAO), International Fund for Agriculture (IFAD), United Nations International Children's Emergency Fund (UNICEF),  World Food Program (WFP), World Health Organization (WHO). The State of Food Security and Nutrition in the World 2020. Transforming Food Systems for Affordable Healthy Diets . Rome: FAO, 2020. [ISBN-13: 978-9251329016] [ Google Scholar ]
• Food and Agriculture Organization (FAO). Human energy requirements. Report of a Joint FAO/WHO/UNU expert consultation; 2004 . Available at www.fao.org/3/y5686e/y5686e.pdf . [ISBN-10: 9251052123]

FAO and WFP 2018

• Food and Agriculture Organisation (FAO), World Food Program (WFP). Home Grown School Feeding. Resource Framework. Synopsis; March 2018 . Available at www.fao.org/3/i8724en/I8724EN.pdf .
• Gelli A, Aurino E, Folson G, Arhinful D, Adamba C, Osei-Akoto I, et al. A school meals program implemented at scale in Ghana increases height-for-age during midchildhood in girls and in children from poor households: a cluster randomized trial . Journal of Nutrition 2019; 149  ( 8 ):1434-42. [DOI: 10.1093/jn/nxz079] [PMCID: PMC6686055] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

GRADEpro GDT [Computer program]

• McMaster University (developed by Evidence Prime) GRADEpro GDT . Hamilton (ON): McMaster University (developed by Evidence Prime), accessed 12 May 2021. Available at gradepro.org.

Grantham‐McGregor 2005

• Grantham-McGregor S. Can the provision of breakfast benefit school performance? Food and Nutrition Bulletin 2005; 26 ( 2 Suppl 2 ):S144-58. [DOI: 10.1177/15648265050262S204] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Greenhalgh 2007

• Greenhalgh, T Kristjansson, E and Robinson, V. Realist Review to Understand the Efficacy of School Feeding Programmes . BMJ  2007; 335 :858-861.http://dx.doi.org/10.1136/bmj.39359.525174.AD. [ PMC free article ] [ PubMed ] [ Google Scholar ]

Guyatt 2011

• Guyatt GH, Oxman AD, Kunz R, Woodcock J, Brozek J, Helfandf M, et al. GRADE guidelines: 7. Rating the quality of evidence—inconsistency . Journal of Clinical Epidemiology 2011; 64 ( 12 ):1294-302. [DOI: 10.1016/j.jclinepi.2011.03.017] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Gwatkin 2007

• Gwatkin DR, Rutstein S, Johnson K, Suliman E, Wagstaff A, Amouzou A. Socioeconomic differences in health, nutrition, and population within developing countries. An overview; September 2007 . Available at tinyurl.com/3n3xwrnj . [ PubMed ]

Hanushek 2015

• Hanushek EA, Woessmann L. The Knowledge Capital of Nations: Education and the Economics of Growth . Cambridge (MA): MIT press, 2015. [ISBM: 9780262029179] [ Google Scholar ]

Harden 2018

• Harden A, Thomas J, Cargo M, Harris J, Pantoja T, Flemming K, et al. Cochrane Qualitative and Implementation Methods Group guidance series—paper 5: methods for integrating qualitative and implementation evidence within intervention effectiveness reviews . Journal of Clinical Epidemiology 2018; 97 :70-8. [DOI: 10.1016/j.jclinepi.2017.11.029] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Higgins 2019a

• Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editor(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019. [DOI: 10.1002/9781119536604] [ISBN-13: 978-1119536628] [ CrossRef ] [ Google Scholar ]

Higgins 2019b

• Higgins JP, Eldridge S, Li T, editor(s). Chaper 23: Including variants on randomized trials. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019:569-93. [DOI: 10.1002/9781119536604] [ISBN-13: 978-1119536628] [ CrossRef ] [ Google Scholar ]

Higgins 2019c

• Higgins JP, Savović J, Page MJ, Elbers RG, Sterne JA. Chapter 8: Assessing risk of bias in a randomized trial. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019:205-28. [DOI: 10.1002/9781119536604] [ISBN-13: 978-1119536628] [ CrossRef ] [ Google Scholar ]

Higgins 2019d

• Higgins JP, Savović J, Page MJ, Sterne JA, editor(s), on behalf of the Cochrane ROB2 Development Group. Revised Cochrane risk-of-bias tool for randomized trials (RoB 2) SHORT VERSION (CRIBSHEET); August 2019 . Available at tinyurl.com/mt7uud2m .

Higgins 2021

• Higgins, JPT, Li, T and Sterne, J . Revised Cochrane risk of bias tool for randomized trials (RoB 2) Additional considerations for crossover trials Preliminary tool version, 18 March 2021 . https://drive.google.com/file/d/11LFgCuDpWk5-BvBNbHtNzbJv5-qVpTWb/view 2021; Downloaded from website on July 11, 2022 .
• Jomaa LH, McDonnell E,  Probart C. School feeding programs in developing countries: impacts on children's health and educational outcomes . Nutrition Reviews 2011; 69 ( 2 ):83-98. [DOI: 10.1111/j.1753-4887.2010.00369.x] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Krishnaratne 2013

• Krishnaratne S, White H, Carpenter E. Quality Education for All Children? What Works in Education in Developing Countries, Working Paper 20 . New Delhi: International Initiative for Impact Evaluation (3ie), 2013. [WEB PAGE: tinyurl.com/sh7bc6bu] [ Google Scholar ]

Kristjansson 2015

• Kristjansson E, Francis DK, Liberato S, Benkhalti Jandu M, Welch VA, Batal M, et al. Food supplementation for improving the physical and psychosocial health of socio-economically disadvantaged children aged three months to five years . Cochrane Database of Systematic Reviews 2015, Issue 3 . Art. No: CD009924. [DOI: 10.1002/14651858.CD009924.pub2] [PMCID: PMC6885042] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

LaMorte 2020

• Sullivan L. Power and sample size determination . sphweb.bumc.bu.edu/otlt/MPH-Modules/BS/BS704_Power/ (accessed prior to 14 December 2021).
• Last JM, editor(s). A Dictionary of Epidemiology . 3rd edition. New York (NY): Oxford University Press, 1995. [ISBN-13: 978-0195096682] [ Google Scholar ]
• Le K, Nguyen M. How education empowers women in developing countries . The B.E. Journal of Economic Analysis & Policy 2021; 21 ( 2 ):511-36. [DOI: 10.1515/bejeap-2020-0046] [ CrossRef ] [ Google Scholar ]

Lefevbre 2019

• Lefevbre C, Glanville J, Briscoe S, Featherstone R, Littlewood A, Marshall C, et al . Chapter 4: Searching for and selecting studies. . In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019:67-107. [DOI: 10.1002/9781119536604] [978-1119536628] [ CrossRef ] [ Google Scholar ]

Levinger 1986

• Levinger B. School feeding programs in developing countries: an analysis of actual and potential impact. AID evaluation special study No.: 30; January 1986 . Available at files.eric.ed.gov/fulltext/ED296785.pdf .

Levinger 1996

• Levinger B. Nutrition, Health and Education for All . Newton (MA): Education Development Centre, 1996. [ISBN: 9780963704436] [ Google Scholar ]

Luepker 1996

• Luepker RV, Perry CL, McKinlay SM, Nader PR, Parcel GS, Stone EJ, et al. Outcomes of a field trial to improve children's dietary patterns and physical activity. The Child and Adolescent Trial for Cardiovascular Health (CATCH) . JAMA 1996; 275 ( 10 ):768-76. [DOI: 10.1001/jama.1996.03530340032026] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Marchand 1998

• Marchand S, Wikler D, Landesman B. Class, health, and justice . Milbank Quarterly 1998; 76 ( 3 ):449-67. [DOI: 10.1111/1468-0009.00098] [PMCID: PMC2751091] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Mattei 2019

• Mattei D, Pietrobelli A. Micronutrients and brain development . Current Nutrition Reports 2019; 8 ( 2 ):99-107. [DOI: 10.1007/s13668-019-0268-z] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

McGowan 2016

• McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS peer review of electronic search strategies: 2015 guideline statement . Journal of Clinical Epidemiology 2016; 75 :40-6. [DOI: 10.1016/j.jclinepi.2016.01.021] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Microsoft Excel 2019 [Computer program]

• Microsoft Excel . Microsoft Corporation, Version 16.0. Microsoft Corporation, 2019. Available at office.microsoft.com/excel.

Murad 2017

• Murad MH, Mustafa RA, Schünemann HJ, Sultan S, Santesso N. Rating the certainty in evidence in the absence of a single estimate of effect . Evidence Based Medicine 2017; 22 ( 3 ):85-7. [DOI: 10.1136/ebmed-2017-110668] [PMCID: PMC5502230] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Neumann 2003

• Neumann CG, Bwibo NO, Murphy SP, Sigman M, Whaley S, Allen LH, et al. Animal source foods improve dietary quality, micronutrient status, growth and cognitive function in Kenyan school children: background, study design, and baseline findings . Journal of Nutrition 2003; 133 ( 11 Suppl 2 ):3941S-9S. [DOI: 10.1093/jn/133.11.3941S] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

O'Neill 2014

• O'Neill J, Tabish H, Welch V, Petticrew M, Pottie K, Clarke M, et al. Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health . Journal of Clinical Epidemiology 2014; 67 ( 1 ):56-64. [DOI: 10.1016/j.jclinepi.2013.08.005] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Papamandjaris

• Papamandjaris, A.  Breakfast and learning in children: a review of the effects of breakfast on scholastic performance . Breakfast for Learning.  Canadian Living Foundation  2000.
• Peter F, Evans T. Ethical dimensions of health equity. In: Evans T, Whitehead M, Diderichsen F, Bhuiya A, Wirth M, editors(s). Challenging Inequities in Health: From Ethics to Action . Oxford (UK): Oxford University Press, 2001:25-33. [DOI: 10.1093/acprof:oso/9780195137408.001.0001] [ISBN-13: 978-0195137408] [ CrossRef ] [ Google Scholar ]

Petticrew 2005

• Petticrew M, Cummins S, Ferrell C, et al. Natural experiments: an underused tool for public health? Public Health 2005; 119 ( 9 ):751-7. [ PubMed ] [ Google Scholar ]

Pollitt 1978

• Pollitt E, Gersovitz M, Gargiulo M. Educational benefits of the United States school feeding program: a critical review of the literature . American Journal of Public Health 1978; 68 ( 5 ):477-81. [DOI: 10.2105/ajph.68.5.477] [PMCID: PMC1653885] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Pollitt 1995

• Pollitt E. Does breakfast make a difference in school? Journal of the American Dietetic Association 1995; 95 ( 10 ):1134-9. [DOI: 10.1016/S0002-8223(95)00306-1] [PMID: ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Powell 1983

• Powell C, Grantham-McGregor S, Elston M. An evaluation of giving the Jamaican government school meal to a class of children . Human Nutrition. Clinical Nutrition 1983; 37C ( 5 ):381-8. [PMID: ] [ PubMed ] [ Google Scholar ]
• Read MS. Malnutrition, hunger and behavior. II. Hunger, school feeding programs, and behavior . Journal of the American Dietetic Association 1973; 63 ( 4 ):386-91. [PMID: ] [ PubMed ] [ Google Scholar ]

Reeves 2019

• Reeves BC, Deeks JJ, Higgins JP, Shea B, Tugwell P, Wells GA. Chapter 24: Including non-randomized studies on intervention effects. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019:595-620. [ Google Scholar ]

RevMan Web 2022 [Computer program]

• The Cochrane Collaboration Review Manager Web (RevMan Web) . Version 4.6.0. The Cochrane Collaboration, 2022. Available at revman.cochrane.org.
• Revised Cochrane  Risk-of-Bias tool for cluster-randomized trials. RoB 2 CRTSHORT VERSION (CRIBSHEET)  .  https://methods.cochrane.org/risk-bias-2 2021.

RoB Excel Tool 2022

• Excel tool to implement RoB 2 . Available at drive.google.com/uc?export=download&id=1malyRF_b-DgvAGHssrdt4N9R7Yhljmt0 .

Rutledge 2016

• Rutledge JG. Feeding the Future: School Lunch Programs as Global Social Policy . New Brunswick (NJ): Rutgers University Press, 2016. [DOI: 10.36019/9780813573342] [ISBN: 9780813573328] [ CrossRef ] [ Google Scholar ]

Rycroft‐Malone 2012

• Rycroft-Malone J, McCormack B, Hutchinson AM, DeCorby K, Bucknall TK, Kent B, et al. Realist synthesis: illustrating the method for implementation research . Implementation Science 2012; 7 :33. [DOI: 10.1186/1748-5908-7-33] [PMCID: PMC3514310] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Schochet 2008

• Schochet P. Technical methods report: guidelines for multiple testing in impact evaluations of educational interventions . Washington (DC): Institute of Education Sciences, US Department of Education; 2008 May. Report No.: NCEE 20084018 .

Schünemann 2013

• Schünemann H, Brożek J, Guyatt G, Oxman A, editor(s). Handbook for grading the quality of evidence and the strength of recommendations using the GRADE approach (updated October 2013). GRADE Working Group, 2013 . Available from gdt.guidelinedevelopment.org/app/handbook/handbook.html .

Schünemann 2019

• Schünemann HJ, Higgins JP, Vist GE, Glasziou P, Akl EA, Skoetz N, et al. Chapter 14: Completing ‘Summary of findings’ tables and grading the certainty of the evidence. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019:375-402. [DOI: 10.1002/9781119536604] [ISBN-13: 9781119536628] [ CrossRef ] [ Google Scholar ]

Soper 2021 [Computer program]

• A-priori sample size calculator for structural equation models . Soper DS. Fullerton (CA): DS Soper, accessed 13 July 2021. Available at www.danielsoper.com/statcalc.

Sterne 2016

• Sterne JA,  Hernán MA, Reeves BC, Savović J,  Berkman ND,  Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions . BMJ 2016; 355 :i4919. [DOI: 10.1136/bmj.i4919] [PMCID: PMC5062054] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Sterne 2019a

• Sterne JA, Hernán MA, McLeenan A, Reeves BC, Higgins JP. Chapter 25: Assessing risk of bias in a non-randomized study. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch V, editors(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019:621-41. [DOI: 10.1002/9781119536604] [ISBN-13: 9781119536628] [ CrossRef ] [ Google Scholar ]

Sterne 2019b

• Stern, JAC, Savovic, J, Page MJ, Elbers, RG, Blencowe, NS, Boutron, I, et al,  . RoB 2: a revised tool for assessing risk of bias in randomised trials . BMJ 2019; 366 4898 | :1-8. [ PubMed ] [ Google Scholar ]

Tan‐Torres Edejer 2001

• Tan-Torres Edejer T. Health for some: health, poverty and equity at the beginning of the 21st century. In: Neufeld V, Johnson N, editors(s). Forging Links for Health Research. Perspectives from the Council on Health Research for Development . Ottawa (ON): International Development Research Centre, 2001:29-46. [ISBN-13: 978-0889369351] [ Google Scholar ]

Thomas 2004

• Thomas, B H, Ciliska, D, Dobbins, M & Micucci, S. A process for systematically reviewing the literature: providing the research evidence for public health nursing interventions . Worldviews on Evidence-Based Nursing 2004; 1 ( 3 ):176-184. [ PubMed ] [ Google Scholar ]

Thompson 2013

• Thomson HJ, Thomas S. The effect direction plot: visual display of non-standardised effects across multiple outcome domains . Research Synthesis Methods 2013; 4 ( 1 ):95-101. [DOI: 10.1002/jrsm.1060] [PMCID: PMC3688329] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Ukoumunne 1999

• Ukoumunne OC, Gulliford MC, Chinn S, Sterne JA, Burney PG. Methods for evaluating area‐wide and organisation‐based interventions in health and health care: a systematic review . Health Technology Assessment 1999; 3 ( 5 ):iii‐92. [PMID: ] [ PubMed ] [ Google Scholar ]
• Coleman-Jensen A, Rabbitt MP, Gregory CA, Singh A,  US Department of Agriculture, Economic Research Service. Household food security in the United States in 2018, ERR-270; September 2019 . Available at www.ers.usda.gov/publications/pub-details/?pubid=94848 .
• Agricultural Research Service United States Department of Agriculture (USDA). FoodData Central (FDC) . tinyurl.com/ts4prcjj (accessed 14 April 2021).
• Viner RM, Hargreaves DS, Ward J, Bonell C, Mokdad AH, Patton G. The health benefits of secondary education in adolescents and young adults: an international analysis in 186 low-, middle- and high-income countries from 1990 to 2013 . SSM - Population Health 2017; 3 :162-71. [DOI: 10.1016/j.ssmph.2016.12.004] [PMCID: PMC5742637] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Walker 1986

• Walker, A, and Walker, B. School nutrition programmes: do they fulfill their purpose?  Applied Nutrition 986; 40A :125-135. [ PubMed ] [ Google Scholar ]
• Wang D, Fawzi WW. Impacts of school feeding on educational and health outcomes of school-age children and adolescents in low- and middle-income countries: protocol for a systematic review and meta-analysis . Systematic Reviews 2020; 9 ( 1 ):55. [DOI: 10.1186/s13643-020-01317-6] [PMCID: PMC7075040] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Welch VA, Petkovic J, Jull J, Hartling L, Klassen T, Kristjansson E, et al. Chapter 16: Equity and special populations. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA, editors(s). Cochrane Handbook for Systematic Reviews of Interventions . 2nd edition. Chichester (UK): John Wiley & Sons, 2019:433-49. [DOI: 10.1002/9781119536604] [ISBN-13: 978-1119536628] [ CrossRef ] [ Google Scholar ]
• World Food Programme (WFP). Two minutes on school feeding; November 2019 . Available at tinyurl.com/5bpy2yyy .
• World Food Programme. State of school feeding worldwide 2020; February 2021 . Available at www.wfp.org/publications/state-school-feeding-worldwide-2020 .

Wilkins 1983

• Wilkins R, Adams O. Healthfulness of Life . Montreal (QC): Institute for Research on Public Policy [L'Institut de recerches politiques], 1983. [ISBN-10: 0-920380948] [ Google Scholar ]

Wilkinson 1996

• Wilkinson RG. Unhealthy Societies: The Afflictions of Inequality . London (UK): Routledge, 1996. [ISBN-13: 978-0415092357] [ Google Scholar ]
• Wong G, Greenhalgh T, Westhorp G, Buckingham J, Pawson R. RAMESES publication standards: realist syntheses . BMC Medicine 2013; 11 :21. [DOI: 10.1186/1741-7015-11-21] [PMCID: PMC3558331] [PMID: ] [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

World Bank 2021

• World Bank. World Bank Country and Lending Groups . Available at datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups (accessed 7 February 2021).

World Vision 2021

• World Vision. Africa hunger, famine: facts, FAQs, and how to help . www.worldvision.org/hunger-news-stories/africa-hunger-famine-facts (accessed 21 May 2021).

References to other published versions of this review

Kristjansson 2007.

• Kristjansson B, Petticrew M, MacDonald B, Krasevec J, Janzen L, Greenhalgh T, et al. School feeding for improving the physical and psychosocial health of disadvantaged students . Cochrane Database of Systematic Reviews 2007, Issue 1 . Art. No: CD004676. [DOI: 10.1002/14651858.CD004676.pub2] [ PubMed ] [ CrossRef ] [ Google Scholar ]

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

PRACTICE AND CHALLENGES FOR IMPLEMENTATION OF SCHOOL FEEDING AT ADDIS ABABA PUBLIC PRIMARY SCHOOLS

ABSTRACT School feeding is simply providing of food to children by using in-school meals or take-home rations in both developed and developing countries for achieving the sustainable development goal of universal primary education. The objective of the study was to assess the current practice and challenges for implementation of school feeding program at Addis Ababa public primary schools. Institutional based descriptive cross-sectional study of mixed method was implemented. The data collected from teachers, school directors, food handlers and regional coordinators with sample size of 383 by using structured and non-structured questionnaire. Descriptive statistics were used to summarize categorical and continuous variables. For qualitative content analysis was used. Based on the study community participation and involvement is not as expected, Infrastructures in the schools is not standardized and good enough. The fund is not enough and considers the current market. Decision-making process related to the program is not participatory and inclusive. Monitoring and Evaluation is not adequate and capable. Related to challenges lack of effective monitoring and evaluation system, absence of organizational structure and community involvement, legal framework and policy, absence of infrastructure and training, effective communication, manager and management team are challenges. To summarize and conclude; the practice of the school feeding program is not as a standard and expected. So concerned body should give attention and focused to standardize the program. Key words: School feeding program, Practice, Challenge

Related Papers

International Journal of Scientific Research in Science and Technology IJSRST , John Mensah

This study sought to assess the relevance and challenges of the Ghana School Feeding Programme (GSFP) in some Basic schools in the Mpohor-Wassa East District. The study employed the descriptive survey research design. The purposive sampling procedure was used to select 21 respondents made up of one (1) coordinator of the GSFP; five (5) head teachers; five (5) caterers and ten (10) Basic school teachers (2 teachers each) from five (5) Basic schools where GSFP have been implemented for more than the past two (2) decades. Data was analysed using descriptive statistics mainly frequency and percentages. The study revealed that since the inception of the GSFP in the District there have been significant improvements in pupils " enrolment and attendance rates, leading to reduction in absenteeism and drop-out rates. It was also found out that GSFP did not cover all the Basic schools in the District but covers only few selected schools. It was also observed that the feeding cost per pupil per day was insufficient and also not released on time. Finally, it was observed that caterers did not have suitable kitchen for cooking and pupils " also did not have proper canteens and that they eat the food in open spaces. It was recommended that Ghana government should extend the GSFP to cover all the Basic schools so as to reduce short-term hunger of pupils during classes " hours; and also stakeholders should provide suitable kitchen for cooking and proper canteens for the pupils so as to avoid eating in unhygienic open spaces.

IOSR Journals

This study was attempted to explore the sustainability of school feeding program in Ethiopia Somali Regional State. Practices, challenges, contributions and sustainability of school feeding program in the region was captured. Different zones such as Gode, Jigjiga, Deghabour and KebriDehar were selected for the study. Different participants such as teachers, directors, parents, students, Woreda education offices, Region education bureau and WFP focal person were participated in the study. To select participants, primary schools of the respective zone were included in the study. All teachers and directors existed in the selected primary school were purposely selected. In the same vein, purposive sampling technique was employed to select students and parent feeding committee who are jointly working with the schools as well as purposive sampling technique was used to select region heads, woreda education bureau heads and WFP focal person. Percentage and thematic analysis were used to analyze quantitative and qualitative data respectively. The main finding of the study revealed that imbalance or clash between demands of SFP (School Feeding Program) which was expressed in terms of expected and unexpected demand and the supply side of the SFP were found. Region education bureau, schools (directors) and parents were not jointly working to generate new way to sustain the SFP in the region though community and the regional government were committed to support the program. The process of SFP in terms of distribution of food service and the actual distribution was not properly managed. In spite of the fact that there were gaps in SFP practices, SFP has contributed lot for student’s education. It tried to enhance student’s moral and vision to education, increase enrolment and attendance, enhance pastoral parent’s awareness and value to education, enhance quality of education since students motivation to education, concentration and attention in learning were increased after the commencement of food service in the respective schools. Besides, implementation of SFP in the schools change pastoral community’s view towards modern education, shape pastoral parents knowledge to education and increased student’s academic achievement. Despite the fact that there were benefits reported different challenges such as increasing number of students from year to year, lack of government and community commitment to support the program, lack of sectorial engagement, lack of financial and institutional capacity as well as lack of independent SFP structure at different levels affect the implementation of SFP and Future sustainability of the program. To sustain the program opportunities were identified in the study such as the existence of enough land at each school, surplus production, enough rivers, committed (in terms of readiness and perspective) government, parents and community to support the program. On the bases of the identified findings, the regional government is expected to establish new independent structure to run SFP, redesign SFP so as to accommodate the interest different sectors in the program, use the existed opportunity effectively and mobilize pastoral community resource for the program.

School Feeding Program and its Contribution to Quality Education in First Cycle Government Primary Schools of Yeka Sub City, Addis Ababa

mulat abebel

ABSTRACT School Feeding Program (SFP) is one of the components of education sector development program (ESDPIV) and School health and nutrition strategy that implemented by Ministry of Education with collaboration of Ministry of Health. This research aimed at assessing the appropriateness of SFP and contribution of it to quality education particularly, for the indicators of academic achievement, completion rate (minimize school dropout rates) and create good psychological makeup for learning (create child-friendly school environments, readiness to learn (attendance, concentration or class room ethics and initiation to continue their education to the higher level). The research was employed mixed research approach and the design different according to the natures of research objectives i.e., to achieved the objective contribution of SFP to academic performance, psychological makeup and completion rate across groups (beneficiaries and non-beneficiaries but needy) students quasi (nonequivalent groups posttest-only (two or more groups) design, and to assessed the practice of school feeding program non-experimental (descriptive) were employed. For this study, 118 SFP beneficiary and 133 non-beneficiary but needy totally 251 students were participated in the research. The data collection instruments were student roster card analysis, questionnaire and interview. The study conducted two statistical tests; inferential (independent sample T-test, correlation and linear regression) and descriptive statistics by using SPSS version 21. The main findings of the study were that, the contribution of School Feeding Program to academic achievement of student was positive and significant; the program had contribution to develop both negative and positive psychological makeup of students; the implementation process also both appropriate and inappropriate and the program contribute positively to the target of decreasing dropouts. Based on the findings the study recommended that, stakeholders should give due consideration for practical interventions to enhance the program effectiveness. Key Words: School Feeding, Quality Education

FATAWU ALHASSAN

Journal of social development in Africa

MAHAMA SAAKA

This paper seeks to generate debate on the theme of factors that are critical in school feeding programmes for better results. The information used in developing the paper is derived from data that were collected from the evaluation of the CRS/Ghana Development Assistants Project (DAP Title II programme FY2004-08). The findings show that school feeding programmes have the potential to stimulate enrolment and retention of children, particularly the girl child, and to improve the academic outcomes of children depending on how the programme blends feeding with nutritional and other health needs of children on the one hand, and the nature of targeting mechanisms in order to reach deprived families and needy school children, on the other. The findings also show that the institutionalisation of structures for partner participation and capacity building enhances programme effectiveness. However, in order to sustain the benefits of improved enrolment and attendance, especially of the girl c...

Asian Journal of Education and Social Studies

Issah Iddrisu

The study focused on whether there is any involvement and the need for the Ghana Education Service (GES) in the operations of the school feeding programme in Ghana. The Ghana Education Service has supervised similar programmes as the main agency in charge to improve efficiency in delivery. The purpose and intent of the Ghana education service will better be served if they are in control of the school feeding programme. The study sampled 350 teachers as the target group and other stakeholders which included directors of education, school feeding programme, parents and students. With a mixed method and the use of questionnaire and interviews, the study analyzed responses based on percentages and themes respectively. The study concluded that the Ghana Education Service (GES) is not involve in the operations of the school feeding programme. They are stated as partners in its operations but are not consulted in the recruiting of schools and caterers as part of the programme operations. B...

Samuel H. Nyarko

Sani Yakubu

The study assessed the implementation of Home Grown-School Feeding Programme in UBE Schools in South-West Nigeria. The study was guided by two research questions with corresponding two objectives and hypotheses. The research design used for this study was the crosssectional survey research design. The population of the study consisted of 38, 423 (154 Local Government Educational secretaries 2814 principals and 35455 teachers). The sample size of this study consisted of 379 using Krejcie and Morgan (1970) Table and simple random technique respectively. The researcher developed a questionnaire for data collection from the respondents. The questionnaire is tagged ‘‘Implementation of Home Grown School Feeding Programme in UBE Schools Questionnaire’ (IHGSFPUBESQ). The instrument was duly validated and it yielded 0.80 as logical validity index. The coefficient of internal consistency of 0.75 was obtained after pilot testing the instrument. Descriptive statistics of mean and standard devia...

BMC Public Health

Tsegaye Getachew

ADAM BAWA YUSSIF

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

International Journal of Nursing, Midwife and Health Related Cases

Olawale Stephen .G.

Michael Fiadzigbey

Eric H Yeboah

International Journal of Advanced Research (IJAR)

IJAR Indexing

International Journal of Education

mark amponsah

Directorate Research & Innovation

Asmamaw Guta

International Journal of Advanced Research

Bismark Asante

Brenda alemura

John Adanse

Advance Knowledge for Executives

Advance Knowledge for Executives (AKE)

Frontiers in Sustainable Food Systems

Hosea Mpogole

michael chaula

International Journal of Child Health and Nutrition

Joan Vaccaro

Scientific Research Journal

susan chepkonga

Jeph Ighodaro

Professor Dr. Emmanuel Ohene Afoakwa

Benzies Isaac Adu-Okoree

Ennie Chima

Journal of Research in Health and Sports Science, 20(1): 17-30

Obasuyi Osato

Priya Pandey

International Journal of Innovation and Applied Studies

Abayomi Oloruntoba

IOSR Journal of Humanities and Social Science

John A L U K O Orodho

International Journal of Innovative Research and Development

Dr. Evanson M Muriithi (PhD)

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Two Minutes on School Meals 2023

While the world is still facing multiple crises due to conflict, climate change, and rising food and fuel prices, governments worldwide are increasingly convinced that school meals are a powerful and cost-effective way of ensuring that vulnerable children get the food they need and have made school meals one of their priorities.

More than 85 countries and 95 partners have joined the School Meals Coalition, a country-led initiative that strives for every child to have the opportunity to receive a healthy, nutritious meal in school by 2030. Thanks to political leadership, 418 million children benefit from school meals worldwide today, 30 million more than before the pandemic in early 2020.

WFP supports the Coalition by acting as its secretariat. In addition, in 2022, WFP supported governments worldwide to establish or expand national school feeding programmes, while also directly providing healthy meals, snacks or cash-based transfers in 59 countries.

Publications

The state of school feeding worldwide 2022.

A Chance for every Schoolchild - WFP School Feeding Strategy 2020 - 2030

Advanced search

Virtual Tour

Experience University of Idaho with a virtual tour. Explore now

• Discover a Career
• Find a Major
• Experience U of I Life

More Resources

• Admitted Students
• International Students

Take Action

• Find Financial Aid
• View Deadlines
• Find Your Rep

Helping to ensure U of I is a safe and engaging place for students to learn and be successful. Read about Title IX.

Get Involved

• Clubs & Volunteer Opportunities
• Recreation and Wellbeing
• Student Government
• Student Sustainability Cooperative
• Academic Assistance
• Safety & Security
• Career Services
• Health & Wellness Services
• Register for Classes
• Dates & Deadlines
• Financial Aid
• Sustainable Solutions
• U of I Library

• Upcoming Events

Review the events calendar.

Stay Connected

• Vandal Family Newsletter
• Here We Have Idaho Magazine
• Living on Campus
• Campus Safety
• About Moscow

The largest Vandal Family reunion of the year. Check dates.

Benefits and Services

• Vandal Voyagers Program
• Vandal License Plate
• Submit Class Notes
• Make a Gift
• View Events
• Alumni Chapters
• University Magazine
• Alumni Newsletter

SlateConnect

U of I's web-based retention and advising tool provides an efficient way to guide and support students on their road to graduation. Login to SlateConnect.

Common Tools

• Administrative Procedures Manual (APM)
• Class Schedule
• OIT Tech Support
• Academic Dates & Deadlines
• U of I Retirees Association
• Faculty Senate
• Staff Council

College of Graduate Studies

Physical Address: Morrill Hall Room 104

Mailing Address: College of Graduate Studies University of Idaho 875 Perimeter Drive MS 3017 Moscow, ID 83844-3017

Phone: 208-885-2647

Email: [email protected]

Thesis and Dissertation Resources

You will find all you need to know about starting and completing your thesis or dissertation right here using ETD (Electronic submission of Dissertations and Theses).

• Create your ETD account
• General ETD Help from Proquest
• Theses and Dissertations template  (Word)
• Example of a thesis
• Note: COGS at this time is unable to provide any troubleshooting support or tutorials on LaTeX. Please use only if you are knowledgeable and familiar with the program.
• Writing Assistance Services
• Format Review Services
• Survey of Earned Doctorates  (for Ph.D. students only)
• University Repository Agreement Form  (PDF)
• Dates and Deadlines
• Sign up with ORCID (take 5 minutes to establish your academic identity)
• U of I Theses and Dissertations , 2013-present
• Data and Digital Services Workshops
• Open Access, Scholarly Communication, and Copyright LibGuide
• Quick Guide - Committee Electronic Review/Authorization - Student View pdf
• Quick Guide - Committee Electronic Review/Authorization - Faculty View pdf
• ETD Checklist jpg
• T/D Format/Component Checklist pdf
• Handbook - reference pdf
• Handbook - example docx

• INNOVATION FESTIVAL
• Capital One

08-06-2024 2024 ELECTION

How Tim Walz made school meals free for all Minnesota students

As Governor, new vice presidential pick Tim Walz worked on a program that eliminated income requirements for school lunch.

[Photos: Stephen Maturen/Getty Images, kcline/Getty Images]

BY  Kristin Toussaint 3 minute read

When it comes to setting students up for success, making sure they eat lunch is crucial. But as both poverty and hunger rates increase for children across the U.S., that isn’t always an easy feat. As governor of Minnesota, Tim Walz—who was officially announced as Kamala Harris’s running mate for her presidential bid—addressed that issue with a free school lunch program.

In March 2023, Tim Walz signed a bill to provide free school meals—both breakfast and lunch—for Minnesota students at participating schools, regardless of their family’s income. At the time, Minnesota was the fourth state in the country to provide free school meals for students. Currently, there are only eight states that provide free school meals, no matter household income, though more are currently planning such legislation.

Why free school meals matter for students 

Providing a free lunch, or free school meals in general, has been shown to reduce food insecurity, and can even lead to lower grocery bills for family’s home food purchases. Making sure students are fed during the day also improves kids’ health and improves their academic performance. A 2021 Brookings Institution report found that free school meals improve kids’ math performance, especially for elementary-age kids and Hispanic students. That report also found that free school meals reduced suspensions for some kids. 

“As a former teacher, I know that providing free breakfast and lunch for our students is one of the best investments we can make to lower costs, support Minnesota’s working families, and care for our young learners and the future of our state,” Tim Walz said in a statement when he signed the bill. 

Reaction to Tim Walz’s free school meals program

On the day Walz signed that free school meals bill into Minnesota law, a local news outlet featured a picture of him swarmed by e lementary kids , large smiles on their faces. 

Minnesota Governor Tim Walz has signed a law guaranteeing free breakfast and lunch for all students in the state, regardless of how much money their parents make. Tens of thousands of food-insecure kids will benefit. pic.twitter.com/500q4acTre — More Perfect Union (@MorePerfectUS) March 17, 2023

The program, MPR News reported months later in December, was quickly popular: that fall, schools saw demand for meals increase. In one school, 30% more kids were eating lunch in the cafeteria, and 50% more were eating breakfast. Schools across the state served 4.3 million more breakfasts, and 4.5 million more school lunches, in the fall of 2023, compared to the same period in 2022, per the state’s Department of Education . 

“The data is clear: more students are eating breakfast and lunch at school, ensuring they have the food they need to succeed and helping families save money on their grocery bills,” Walz said in a statement when those figures were released. “This investment is a win for our kids, our families, and the long-term success of our state.”

Not everyone has lauded the program, though. Especially after the costs to provide free school meals increased , Republican lawmakers called the effort a waste of taxpayer funds. From the outset, they also criticized the fact that any student, regardless of household income, was eligible, saying it was a giveaway for rich families who could easily afford to provide their kids with meals.

”Isn’t that rich? Our Republican colleagues were concerned this would be a tax cut for the wealthiest,” Walz said in response to the conservative critics. “The haves and have-nots in the lunchroom is not a necessary thing. Just feed our children.”

According to the Hunger-Free Schools initiative , the costs to the state for the free school meals program come out to less than $2 per student per day. The program has also been overwhelmingly popular with Minnesota voters, with more than 70%—”including majorities across every ideological and demographic category,” the Minnesota Reformer reported —saying they approve of the program.

Apply to the Most Innovative Companies Awards and be recognized as an organization driving the world forward through innovation. Early-rate deadline: Friday, August 23.

ABOUT THE AUTHOR

Kristin Toussaint is the staff editor for Fast Company’s Impact section, covering climate change , labor , shareholder capitalism , and all sorts of innovations meant to improve the world. You can reach her at [email protected].   More

Explore Topics

• 2024 election
• Tech Default app settings can pose a risk to user privacy
• Tech iMovie for everyone: This free video editor runs in your browser
• Tech The Google TV Streamer makes Apple TV look dated
• News What to expect at Fast Company’s 10th annual Innovation Festival: Panels
• News Housing market reset: 41 markets where the power is shifting to buyers
• News How this Montana gas station chain is using traffic data to build a mini empire of local hotels
• Design What Smithsonian historians are curating from the 2024 Democratic National Convention
• Design This app tracks America’s offensive street names
• Design The popcorn bucket wars are only just beginning
• Work Life How to turn your ‘wish idea’ into an actual side hustle
• Work Life How to find your power as a Black entrepreneur
• Work Life Polling on Harris shows that sexism is prevalent in American politics

This article is free to read if you register or sign in.

Simply register at no cost.

Questions or problems? Email [email protected] or call 0711 046 000 .

Nairobi county to launch 7 new kitchens for school feeding programme

The new kitchens are expected to serve over 310,000 students when schools reopen..

• Sakaja said the initiative is aimed at providing nutritious meals to students across the city and upon launch will bring the total number of operational kitchens to 17.

"The new kitchens are expected to serve over 310,000 students when schools reopen next week," Sakaja said.

Nairobi Governor Johnson Sakaja has announced that his adminstration will soon launch seven additional kitchens next week.

The move seeks to expand the county's school feeding program.

Sakaja said the initiative is aimed at providing nutritious meals to students across the city and upon launch,  the total number of operational kitchens in the county will rise to 17.

"The improvement will bolster the county’s efforts to ensure no child in Nairobi goes to school hungry."

Sakaja spoke during a church service at AIC Pipeline in Nairobi.

The county boss said the expansion reflects his commitment to improving the welfare of Nairobi’s students and addressing food insecurity among the city's young population.

With more students receiving regular meals,  Sakaja said his administration is optimistic that this will contribute to better attendance rates and enhanced academic outcomes.

The expansion of the school feeding program, he said, is just one of many steps his administration is taking to improve the quality of life for Nairobi residents.

During the service, Governor Sakaja emphasized the importance of collaborative governance.

He highlighted how working with leaders from different political parties has been crucial in fostering inclusivity and ensuring that the needs of all Nairobians are met.

“Our success in Nairobi has been driven by a united government that includes leaders from the opposition, who hold the majority of MCAs,” he said.

He lauded President William Ruto’s efforts to involve more leaders across the political divide in the national government.

Governor Sakaja assured Nairobi residents of his unwavering commitment to fulfilling his promises.

"We are dedicated to delivering on our pledges, and initiatives like the school feeding program are just the beginning," he stated.

Sakaja hosts national champions Highway Secondary ahead of Romania tour

How sakaja has stabilised nairobi two years on, most popular, we'll continue holding government to account – kalonzo, mwangaza on trial again as senators disrupt recess, ruto awarded degree of doctor of humane letters, nairobi county to launch 7 new kitchens for school feeding ..., judiciary is only arm yet to be captured by executive - ..., latest videos, make kenyans your first priority, ruto tells cabinet, ruto pledges to construct sh500m university at kiabonyoru, nyamira, sign up for the free star email newsletter and receive the latest kenya news daily..

Trending Topics

• Columbia president steps down

Get JTA's Daily Briefing in your inbox

I accept the JTA Privacy Policy .

By submitting the above I agree to the privacy policy and terms of use of JTA.org

The ‘Gestapo Game’ at the high school where Tim Walz worked was part of a trend Holocaust educators now reject

As Tim Walz was inveighing against trends in Holocaust education in his 2001 master’s thesis , the high school where he worked was employing one of those methods: a “game” that, by today’s standards, would repel almost every expert in the field.

A fellow teacher divided his class into halves: Some would have to wear yellow stars and play “Jews,” while the others would play the part of Gestapo officers charged with tormenting them.

A Jewish former student who was disturbed by the activity told the Jewish Telegraphic Agency last week that Walz had stepped in to stop the game after her father complained. But her father, Stewart Ross, subsequently told JTA that he did not recall anything beyond his daughter’s distress.

Bob Ihrig, the teacher who led the Gestapo activity, and John Barnett, Mankato West’s principal from the time, also told JTA that they did not recall such an incident. But Ihrig said Walz, now the Democratic candidate for vice president, had been aware of the activity.

“When students start wearing stars, walking down the hall, they go from my classroom down the hall past Tim’s classroom,” he said. “There’s no way that you could avoid that.”

What is certain is that in another context, Walz had cautioned against exercises like the one Ihrig used, which was called the “Gestapo Game” and was a trademarked activity conducted in settings around the world. In his thesis for his master’s degree in experiential education at Minnesota State University, Mankato, which argued for changes to Holocaust education, Walz noted that researchers had “deemed counterproductive” activities in which students were asked to play roles from the Holocaust.

“Trying to simulate the conditions that victims of the Holocaust experienced was absurd,” Walz wrote. “The result on student learning was a trivialization of the horrors experienced during the Holocaust.”

Walz was not alone in objecting to the game: The activity championed by Ihrig is anathema in the field of Holocaust education today. Yad Vashem, Israel’s Holocaust memorial; the U.S. Holocaust Memorial Museum; and the Anti-Defamation League all warn against Holocaust role plays.

“Even when great care is taken to prepare a class for such an activity, simulating experiences from the Holocaust remains pedagogically unsound,” the U.S. museum says on its website. “The activity may engage students, but they often forget the purpose of the lesson and, even worse, they are left with the impression that they now know what it was like to suffer or even to participate during the Holocaust.”

Looking at a pictorial story of their country’s history, German high school girls appear aghast as they wander through the Paulskirche in Frankfurt. The exhibition titled “Warsaw Ghetto,” staged in 1963 and 1964, was the first of its kind in Germany. (Getty Photos)

Walz completed his thesis at the same time that Agustin recalls being in Ihrig’s class. The thesis reflected a longstanding interest in teaching about Holocaust and genocide that predated Walz’s years at Mankato West and extended into his current tenure as Minnesota’s governor.

Walz’s thesis argued that schools would do better to remove teaching about the Holocaust from units about World War II and instead situate it within instruction about genocides and human rights. That way, he said, students could understand the root causes of the violence with the aims of preventing future genocides.

The belief appeared to be long-held. Walz had previously taught about the Holocaust and other genocides in an early teaching role in Alliance, Nebraska. There, after studying the Holocaust as one of several genocides, his class accurately predicted that Rwanda was the most likely place for a future genocide to take place ; one unfolded there the following year.

But Walz did not discuss his outlook on Holocaust education with some of his closest colleagues, several of them told JTA. Ihrig and Mike Sipe, another teacher who was also Mankato West’s wrestling coach, both said they had been surprised to learn last week that Walz had written a thesis about Holocaust education while they worked with him. They noted that completing a master’s degree conferred benefits including a pay raise and did not always reflect a teacher’s core interests.

Both recalled Walz as an inspiring teacher and good colleague who participated in the collaboration that took place informally in their department. (The student yearbook named Walz “Most Inspiring” the same year it called Ihrig “Most Likely to Conquer the World.”) Ihrig said Walz had been “encouraging” and “inquisitive” about the Holocaust activity, showing curiosity about elements of the exercise — which Ihrig recalls as a highlight of his teaching career more than a decade after he retired.

Ihrig said he first encountered the activity in a catalog for teachers in the late 1970s — making him one of thousands to purchase Rabbi Raymond Zwerin’s Gestapo game since its release in 1976.

Zwerin, a congregational rabbi in Denver who was married to a Holocaust survivor, designed the game in response to clamor from classroom educators for more engaging curriculum materials about the Holocaust, according to a 2022 story in the Forward . He told the news outlet that the game was meant to illustrate the role that luck — mazel, in Yiddish — played in survival.

“I think about my wife’s situation. Her parents were killed, her sister was killed, and she escapes,” he said. “Somebody found her on the street, as a little kid, and got her to the right ship at the right time. Total mazel.”

Israeli schoolchildren visit the “From Holocaust to Revival” Museum in Kibbutz Yad Mordechai in southern Israel on May 4, 2016 on the eve of the Holocaust Remembrance Day. (Menaham Kahana/AFP via Getty Images)

Zwerin’s game landed in a receptive climate. An explosion of interest in the Holocaust had generated an NBC miniseries , best-selling books and courses in high schools and colleges across the country. Simulation activities abounded: A made-for-TV movie released in 1981, “The Wave,” dramatized a classroom activity that turned students against each other without ever mentioning the Holocaust. Even some Jewish schools and camps engaged in simulations, with one boasting the slogan “Creative camping personalizes the Holocaust,” according to a 1980 New York Times story about the growing popularity of Holocaust narratives .

But qualms were already emerging. The Times story reported that Elie Wiesel, the survivor and novelist who became the face of Holocaust memory and would later win a Nobel Prize, was “appalled by the fact that well-meaning teachers think they have conveyed the meaning of the Holocaust to children by locking them in small rooms to simulate gas chambers” — a move that he traced to the NBC miniseries. “When he asked one teacher why she used simulation techniques,” the newspaper reported, “he was told, ‘If NBC could do it, if they could create fake gas chambers for their audience, why can’t we do it for children?’”

Ihrig’s classroom was never made to resemble a gas chamber. But the Gestapo activity morphed and expanded as generations of Mankato West students experienced it, Ihrig said. Students suggested that some of them act as the Gestapo. The stars, he said, were his own innovation. So was the decision to have the activity extend beyond his classroom walls.

“I wanted the students to understand that the Jewish people didn’t stop being a Jew and stop being persecuted, that it was a constant 24/7,” he told JTA. “It was too easy for these students, when the bell rang at the end of the period, to pick up and leave and life was back to normal. And so I wanted that stress, that tension, that experience, to last longer.”

But “Gestapo” students started harassing the “Jewish” ones in uncomfortable ways, Ihrig recalled, including in the bathrooms. The escalation was problematic but also instructive, he said.

“They hadn’t been coached, they hadn’t been taught. They took this upon themselves,” he said. “Probably 95% of the students were just totally compliant and obedient, which is exactly what happened in Nazi Germany.”

Borka Marinkovic, far left, talks about her experiences as the daughter of Holocaust survivors with a group of Serbian teachers during an August 2023 TOLI education seminar in Šabac, Serbia. (Larry Luxner)

Holocaust educators today say there are far better ways to teach that lesson: through survivor testimonies, by examining primary source materials and by learning about psychology and human behavior. They say role plays serve to traumatize students and trivialize the experiences of survivors and victims while not teaching anything about history.

“In the Holocaust education field, it’s universally frowned upon in the strongest way — role plays are inappropriate — and I think we’ve done a good job. All the organizations are communicating that to teachers,” said Deborah Lauter, executive director of the Olga Lengyel Institute for Holocaust Studies and Human Rights.

“Today it would not be seen as common,” Lauter added. “It happens once in a while, and it’s shut down pretty quickly.”

A Florida middle school was inundated with criticism in 2006 after dividing students between the “privileged” and “persecuted” groups as part of a unit that included reading “The Diary of Anne Frank”; according to the ADL, one student told his parents, “The only thing I learned today is that I don’t want to be Jewish.”

A 2015 article in an Indiana newspaper described a one-day simulation participated in by teachers and students alike — and where the teacher who had conducted the activity for over a decade said he was increasingly having to combat Holocaust denial among his students.

Sipe, who still teaches at Mankato West, says there are no longer Holocaust simulations conducted in history classes there.

“I certainly don’t think it’s something that should be part of public education today,” he said. “No, the activity is certainly not part of something we do anymore.”

Ihrig said he understood that times have changed and that many would see the simulation as “traumatizing” today. But he also recalled years of positive feedback about the Gestapo activity that he said had predated Agustin’s experience, and followed it.

“I had a mother who was a school board member who talked to me and said, ‘You know, this was really emotionally draining for my daughter, and she’d come home at the end of each day and all of the stress and tension,’ because I told the students that, you know, you take this seriously, it’s going to have an impact on you,” Ihrig said. “And she said, ‘You know, that was really difficult to deal with in the week before vacation break,’ but she says, ‘I’m glad that you did that for my daughter and other students, because they needed that experience.’”

Share this:

Recommended from jta.

With major airlines scrapping flights, getting to and from Israel has become a costly, often madcap endeavor

Israel, Gaza and Josh Shapiro: What we’re watching for during the Democratic National Convention

Barbra Streisand, Susie Essman and 30,000 others join ‘Jewish women for Kamala’ call

Pittsburgh Jewish groups hope to quash a referendum that would force the city to boycott Israel

In speech about antisemitism, Trump blames Harris and focuses on anti-Israel forces

An online magazine of Art, Architecture, Media, Culture, Sounds, Territories, Technology)

The Lenin Institute for Librarianship by Ivan Leonidov (1927)

October 30, 2018 by Fosco Lucarelli 1 Comment

Ivan Illich Leonidov (1902-1957) designed the Lenin Institute for Librarianship (the collective scientific and cultural center of the USSR) in 1927 as his thesis project at the VKhUTEMAS, the art and technical School of Moscow, with Alexander Vesnin as his tutor.

The Institute is made of a series of individualized shapes embodied by clear geometrical forms – mostly rectangular boxes and a sphere – which are boldly composed together. The three main buildings of the institute are a massive library with five million books joined by the Institute of librarianship, both contained in a high-rise building; the auditorium which also functions as a planetarium and as a speaking platform for mass demonstrations, located in a huge glass sphere elevated from the floor through a metallic structure; and the actual research institute hosting the research labs, a horizontal slab, suspended, which also connects the two other buildings. The single volumes are related through the composition of two asymmetrical axes on a decentralized circular platform where both the auditorium and the library are located. The library axis is also prolonged by a straight suspended roadway leading to the city center.

An important feature of the overall design is the presence of steel cables with the double role of guy-wires in tension and radio communication antennae. The cables counterbalance the anti-gravitational effect of the highest buildings and especially that of the auditorium which appears as a hot-air balloon ready to take a flight. They also underline the idea of communication among the people working together in the institute and in the whole country.

The center was supposed to be located in Moscow, on the Lenin Hills, the highest spot in the city, just a few kilometers southwest of the Red Square. An aerial tramway with a central aerodrome and suspended roadway would have connected the institute with the center of the city while the radio station would have put it in communication with the whole country.

As to underline an era of unlimited faith in an upcoming technological world, the role of technology is formally and functionally expressed throughout the whole project, especially in the library where an automated book-delivery system with a vertical and horizontal conveyor system delivers the books directly from the stacks to the reading rooms.

The sphere is the most evolutive area: as an auditorium, it can host up to 4000 people, but it can be repartitioned through mobile suspended walls in order to contain smaller audiences. When half of the sphere is opened, and all the seats are withdrawn into the remaining half, it can also be used as a speaking platform for mass gatherings. The sphere of the Planetarium can turn into a science theater after projection screens are installed along the inside skin. A system of elevators provides access to the auditorium.

The whole institute is equipped with communication technology like telephones, radios, and remote televisual pieces of equipment so that the whole staff can work together at the same time.

Further reading : https://thecharnelhouse.org/2014/03/21/ivan-leonidovs-proposal-for-the-lenin-institute-in-moscow-1927/

Related Posts

In 1930, the Russian architects group OSA, with Ivan Leonidov as team leader, took part…

Ross Wolfe just published, on his Charnel House, these beautiful blueprints by early Soviet architects…

Mikhail Okhitovich was a singular figure in Soviet architecture of the 20's and 30's. As a…

Metropolis is probably the film that set a standard for 20th century science fiction. The…

Now that the 14th Venice Architecture Biennale finally came to an end, we think it…

June 29, 2020 at 6:27 pm

Hi there! Great essay and fantastic illustrations. I’d be keen to re-use some of the Leonidov ‘Lenin Institute’ images in academic publications. Would you be able to let me know where you sourced them from? I want to confirm that they are indeed free of copyright (or to find out who holds the copyright, so I can apply for permission/license to reproduce). Many thanks!

Leave a Reply

Your email address will not be published. Required fields are marked *

SOCKS is a project by Fosco Lucarelli and Mariabruna Fabrizi of MICROCITIES, Architecture Cityscape, Landscape . Except where otherwise noted, the content on this site is licensed under a Creative Commons Attribution-ShareAlike 3.0 license . Whenever possible we try to attribute content (images, videos, and quotes) to their creators and original sources. Please feel free to write us if you notice misattributions or wish something to be removed. SOCKS is powered by WordPress .

• Skip to primary navigation
• Skip to main content
• 110 Baker St. Moscow, ID 83843
• 208.882.1226

A Classical & Christ-Centered Education

Logos Times

To subscribe to Logos Times, please contact [email protected]

Logos Times , Fall/Winter 2023/2024. Volume 13, Issue 1, Current Issue

Logos Times , Summer 2023, Volume 12, Issue 2

Logos Times , Fall/Winter 2022/2023, Volume 12, Issue 1

Logos Times , Summer 2022, Volume 11, Issue 3

Logos Times , Spring 2022, Volume 11, Issue 2

Logos Times , Fall 2021. Volume 11, Issue 1

Logos Times , Summer 2021, Volume 10, Issue 3

Logos Times , Spring 2021, Volume 10, Issue 2

Logos Times , Fall 2020, Volume 10, Issue 1

Logos Times , Summer 2020, Volume 9, Issue 3

Logos Times , Spring 2020 (and Winter), Volume 9, Issue 2

Logos Times , Fall 2019, Volume 9, Issue 1

Logos Times , Summer 2019, Volume 8, Issue 4

Logos Times , Spring 2019, Volume 8, Issue 3

Logos Times , Winter 2018-2019, Volume 8, Issue 2

Logos Times , Fall 2018, Volume 8, Issue 1

Logos Times , Summer 2018, Volume 7, Issue 4

Logos Times , Spring 2018, Volume 7, Issue 3

Logos Times , Winter 2017-2018, Volume 7, Issue 2

Logos Times , Fall 2017, Volume 7, Issue 1

Logos Times , Summer 2017, Volume 6, Issue 4

Logos Times , Spring 2017, Volume 6, Issue 3

Logos Times , Winter 2016-2017, Volume 6, Issue 2

Logos Times , Fall 2016, Volume 6, Issue 1

Logos Times , Summer 2016, Volume 5, Issue 4

Logos Times , Spring 2016, Volume 5, Issue 3

Logos Times , Winter 2015-2016, Volume 5, Issue 2

Logos Times, Fall 2015, Volume 5, Issue 1

Logos Times , Summer 2015, Volume 4, Issue 4

Logos Times , Spring 2015, Volume 4, Issue 3

Logos Times , Winter 2014-2015, Volume 4, Issue 2

Logos Times , Fall 2014, Volume 4, Issue 1

Logos Times , Summer 2014, Volume 3, Issue 4

Logos Times , Spring 2014, Volume 3, Issue 3

Logos Times , Winter 2014, Volume 3, Issue 2

Logos Times , Fall 2013, Volume 3, Issue 1

Logos Times , April, May, June 2013, Volume 2, Issue 4

Logos Times , Spring 2013, Volume 2, Issue 3

Logos Times , Winter 2013, Volume 2, Issue 2

Logos Times , Fall 2012, Volume 2, Issue 1

Logos Times , April/May/June,2012, Volume 1, Issue 3

Logos Time s, January/February/March 2012, Volume 1, Issue 2, Corrected LogosTimes (Volume 1 Issue 2) corrections On page 8: The second, not the first,  graders had the fire station field trip. On page 11: Autumn Pratt is the author of the Knights’ Fest article.

Logos Times , January/February/March 2012, Volume 1, Issue 2

Logos Times , November/December 2011, Volume 1, Issue 1

• Share full article

Advertisement

Supported by

The ‘Orgasm Gap’ Isn’t Going Away for Straight Women

A new study suggests they still have fewer orgasms during sex than men do, even with age and experience.

By Catherine Pearson

Sex researchers and therapists have long known that women in heterosexual relationships tend to have fewer orgasms than men do. A large new study suggests that this “orgasm gap” persists — and does not improve with age.

The Numbers

The research, published recently in the journal Sexual Medicine, found that across all ages, men of all sexual orientations reported higher orgasm rates during sex — from 70 to 85 percent — compared with 46 to 58 percent for women. Lesbian and bisexual women between ages 35 and 49 reported higher orgasm rates than their heterosexual counterparts.

The analysis included data from eight Singles in America surveys, which are funded and conducted by Match.com annually in collaboration with The Kinsey Institute, the sexuality and relationships research program at Indiana University. The sample included more than 24,000 single Americans between the ages of 18 and 100.

Researchers were especially interested in the question of whether orgasm rates vary by age. Amanda Gesselman, a research scientist with the Kinsey Institute and lead author on the study, said she thought the team might find evidence that the orgasm gap narrows as women develop confidence and learn what they like (and, perhaps, their partners develop skills to help pleasure them).

However, while older gay and bisexual men and lesbian women did have higher orgasm rates, “we really didn’t see evidence of closing the orgasm gap overall,” she said, adding that she hopes future studies will explore the age-orgasm connection further.

“We really, as a society, sort of prioritize men’s pleasure and undervalue women’s sexual pleasure,” Dr. Gesselman said. “And I think that contributes to consistent disparities.”

The Limitations

Emily Nagoski, a sex educator and author of the book “Come Together” — who did not work on the new study — said a limitation of the study was that the survey asked: “When having sexual intercourse in general, what percentage of the time do you usually have an orgasm?” But it did not provide a more specific definition of what “sexual intercourse” means.

Research shows the majority of women require some form of clitoral stimulation in order to orgasm. So if straight women defined “sexual intercourse” as vaginal penetration alone, it makes sense that there was a significant gap in orgasm rates, she said.

A more revealing question might be, “What percentage of the sex you have do you like?” Dr. Nagoski said. “Orgasm is not the measure of a sexual encounter. Pleasure is the measure of a sexual encounter.”

We are having trouble retrieving the article content.

Please enable JavaScript in your browser settings.

Thank you for your patience while we verify access. If you are in Reader mode please exit and  log into  your Times account, or  subscribe  for all of The Times.

Thank you for your patience while we verify access.

Already a subscriber?  Log in .

Want all of The Times?  Subscribe .