PROTOCOL: School feeding for improving the physical and psychosocial health of disadvantaged elementary school children
Notice bibliographique
Résumé
The world has entered the new millennium inheriting an impressive legacy in health from the 20th century. Life expectancy in most countries has reached a new high and infant mortality a new low (Health Canada 1999). However, these averages obscure the fact that health is unevenly, and to some extent, unfairly distributed according to socioeconomic position; health and longevity are highest for the richest, and decrease steadily with decreasing income (Health Canada 1999; Wilkins 1983; Wilkinson 1996). Health inequalities may also be seen between different genders, ethnic, linguistic, or geographic groups. These 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). Many of these inequalities are avoidable and unfair; and hence termed health inequities (Tan-Torres 2001;Peter 2001). Socioeconomic inequities in health represent needless human suffering and lost productivity; and also have significant consequences for the economy and for social order and justice (Brown 1989; Feachem 2001). In a consultation organized by the Rockefeller Foundation in collaboration with the World Bank, participants agreed that the major health research need is “to shift the present static emphasis on measurement and analysis of health inequities towards dynamic identification and evaluation of policy measures that can effectively bring about greater equity” (Gwatkin 2001) Although there is controversy over the definition, one useful definition of health inequalities is, “the virtually universal phenomenon of variation in health indicators … associated with socioeconomic status” (p. 84, Last 1995). Health inequalities require three components for calculation: a valid measure of health status, a measure of social position or status, and a statistical method for summarizing the magnitude of the health differences between people in different social positions. Health inequities ‘are unfair and remediable inequalities’. Thus, health inequalities are measurable, while health inequities are normative judgments. Our ultimate interest is in the reduction of health inequities. However, we recognize that systematic reviews will only be able to focus on that which is measurable, or health inequalities. Systematic reviews are an important tool for studying the effectiveness of interventions designed to reduce socio-economic inequalities in health. They can also provide information on costs and benefits, and sometimes on the process of delivery. This systematic review assesses the effectiveness of one potentially valuable intervention for reducing socioeconomic inequalities in the health and development of children: school-based feeding programs. It will be the first in a series of systematic reviews that will provide evidence regarding the impacts of a variety of interventions on health outcomes in disadvantaged people in both developed and developing countries. Such reviews are especially timely in an era where governments and leading international organizations are placing increasing emphasis on evidence-based strategies to decrease socioeconomic inequities in health. There is also great interest from the World Food Program in school feeding programs as a strategy to combat poverty, hunger, and poor school performance. Importantly, this review will also contribute towards the development of new methodologies needed to conduct reviews in the area of socioeconomic inequalities in health. In particular, we will need to work through a definition of disadvantage, derive an operational definition of effectiveness in reducing health inequalities, develop new search strategies to identify appropriate studies (especially non-RCT), develop classification schemes for complex interventions and outcomes, develop methodologies for understanding the impact of process elements on outcomes, and use appropriate methodology for identifying and dealing with heterogeneity. Across the world, over 300 million children are chronically hungry; in developing countries, 1 in every 3 children under five fail to reach their full growth potential, largely because of chronic malnutrition (UN 2000). Malnutrition is inextricably linked to poverty; millions of families cannot meet basic needs for energy and protein; even more cannot provide their children with adequate micronutrients or with properly balanced diets (Martelin 1994; Darnton Hill 1998; WHO 1996). There is increasing evidence that malnutrition in childhood has devastating consequences, including poor physical and cognitive development, lowered resistance to illness, and mortality (WHO 1996; Nelson 2000). The Food and Agriculture Organization reports that 6 million children die each year because of hunger. Even mild malnutrition can lead to weight loss, stunted growth, and increased susceptibility to disease (Worobey 1999). Malnutrition and micronutrient deficiencies can lead to poor cognitive and behavioral functioning as well as to lower academic achievement (Worobey 1999; Meyers 1989; Pollitt 1995). School feeding programs have the potential to address several of these problems (Macdonald 1979). Their major objectives are to improve nutrient intake, decrease hunger and malnutrition, increase school attendance and enrolment, and to improve cognition and academic performance (Levinger 1984; Gleason 1995). Those who implement school feeding programs feel that, over the long term, they may encourage students to stay in school longer, and that literacy rates, particularly among women will rise (GHC 2002; Arya 1991). Many school feeding programs are aimed specifically at poor and low-income children. Yet, there is some controversy over both the short and long-term effectiveness of school feeding programs. According to one supporter “Research has shown that when food is provided at school, hunger is immediately alleviated, and school attendance is doubled” p 1, (GHC 2002). Others say that school feeding programs are not a cost-effective solution, and that they address a symptom, rather than the root causes of hunger (MacIntyre 1992). Furthermore, there is a potential danger that the delivery of some school feeding programs may lead to stigmatization and dependency (MacIntyre 1992; Levinson 1995). Regardless of their viewpoint, most experts agree that more thorough evaluation of school feeding programs is needed in order to resolve this controversy, and to determine whether school feeding programs are indeed a cost-effective and equity promoting use of resources. We have thus far been unable to identify an existing systematic review on the effectiveness of school feeding programs. However, we have identified some non-systematic reviews and summaries (Pollitt 1995; Levinger 1984; Politt 1998; Felson 1995). These reviewers have noted that most studies on school feeding programs are observational, and that it is difficult to draw firm conclusions from them. There is some evidence that school feeding programs have the potential to enhance school attendance and nutrient intake, but these are based either on single studies or on narrative reviews. Evidence of effects on school performance is similarly equivocal. One reviewer (Levinger 1984) has suggested that school feeding may be more effective for poor children, but observes that effectiveness for children in different socio-economic positions has not been systematically summarized or evaluated. None of these reviews have provided a comprehensive, systematic picture of the effectiveness of school feeding programs or of their potential for reducing socioeconomic inequalities in health: Many countries and organizations have invested large amounts of money in school feeding programs. It is therefore important to learn whether or not this is an effective and cost-effective intervention for improving the health, nutritional status, school enrolment and school performance of disadvantaged children. It is also important to learn whether these feeding programs have the potential to decrease socio-economic inequalities in health. This review seeks to answer these questions. It focuses on the effectiveness of school feeding for disadvantaged elementary school children. It is the first in a series of eight reviews on school feeding/supplementation. The reviews will be broken down by type of feeding and age of the children. The overarching reviews will summarize the most important findings from the smaller reviews in a policy-relevant manner. Data from Randomized Controlled Trials (RCTs), non-randomized Controlled Clinical Trials (CCTs), Interrupted Time Series (ITS), and Controlled Before and After (CBA) will be examined. Results from each type of study will be tabulated and analyzed separately. All other types of studies will be excluded. We will also exclude studies done in laboratories rather than in the school setting, as laboratory studies do not have direct programmatic relevance. We will accept either no treatment controls (lunch, breakfast at home or no feeding) or placebo controls (e.g. very low energy foods or drinks). Social interventions such as school feeding are highly complex and political. Because these programs give food to children who need it, there is resistance to having some students or schools in a no-meals control group for the sake of research; there is also sometimes resistance to random allocation (Leiberman 1976). Thus, researchers studying school meals have to work within existing structures; randomized controlled trials may be impractical or impossible to carry out under these conditions. Often, however, researchers are able to use interrupted time series designs or controlled before and after studies. Moreover, while the randomized controlled trial (RCT) has an important place in determining whether a particular complex intervention produces a particular predefined outcome (the ‘can it work?’ question), traditional RCTs rarely answer ‘what’, ‘why’ and ‘how’ questions such as ‘Why was (or wasn't) this delivery approach used in practice? or ‘what are the barriers to this initiative working outside the research setting? Children and adolescents aged 5 to 13 who attend elementary school. We will cover both developing and developed countries, although they will be dealt with separately. Participants must be either: Programmes can comprise: These interventions must be administered in the elementary school setting. We will exclude nutrition education in schools or at home, obesity prevention programs, breastfeeding programs, food stamps, modifications to school meals to change nutrient, fat content, or appeal to participants, community kitchens, and food banks. Changes in the intervention group and changes relative to the control/comparison group will be examined. Physical Health outcomes: nutritional status (weight and height gain (adjusted for age and sex when given), peak bone mass, micronutrient status). Cognitive outcomes: intelligence test scores, psychomotor and mental development, attention, memory, reasoning, vocabulary, on-task behaviour, and school achievement. Behavioural outcomes: school enrolment, school attendance, and behaviour problems. All outcomes should be relevant for the age group. Reduction of dental caries will be excluded, as will increased nutritional knowledge. Intermediate physical health outcomes such as reduction of hunger and nutrient intake will also be excluded. Adverse outcomes: stigmatization, dependency, disruptive behaviour at school, and obesity or excessive weight loss. Cost outcomes: where possible, we will consider cost-effectiveness Reductions in socio-economic inequalities in health: Interventions will be classified as effective for reducing inequalities in health, potentially effective for reducing inequalities in health, ineffective for reducing socio-economic inequalities in health, or uncertain. We have worked with an information specialist (JM) to develop a search strategy. This search strategy will continue to be refined to identify articles that we know to be relevant. The search will be performed on the following electronic databases: MEDLINE and PreMedline, EMBASE, Cinahl, PsycINFO, ERIC, Sociofiles, HMIS (Health Management Information Consortium), Healthstar, LILACS, System for Grey literature in Europe, Cochrane Controlled Trials Register, C2-SPECTR (Social, Psychological, Educational and Criminological Trials Register), Health Development Agency database of interventions to reduce health inequity, Social Science Index, and Dissertation Abstracts International. Search strategy (which will be modified as required across databases): An Internet search will be carried out using Google. In addition to this, key people from organizations focusing on nutrition, hunger, and international development will be contacted by email. These e-mails will introduce our review, and ask for help in identifying studies on school feeding programs which we may have missed. The organizations we intend to approach are listed below: We will hand-search the American Journal of Clinical Nutrition, Journal of Nutrition, European Journal of Clinical Nutrition, Nutrition Reviews, Public Health Nutrition, and Social Sciences and Medicine for the past five years. In addition, references of retrieved articles and relevant reviews will be scanned for eligible studies. We plan to contact Sally Grantham Mc-Gregor, Ernesto Pollitt, and other authors of the primary studies. Leading resesearchers on interventions to reduce health inequities including Johann MacKenbach, Anne-Marie Gepkens, and Margaret Whitehead will also be contacted. The abstracts and titles of articles retrieved by the electronic and hand searches will be scanned independently by two reviewers (BK and VR) for eligibility, according to the inclusion criteria above. Full copies of all those deemed eligible by one of the reviewers will be retrieved for closer examination. All studies which initially appear to meet inclusion criteria from this first screening but on closer inspection do not meet the inclusion criteria will be detailed in the table of excluded studies. Data will be independently extracted by three reviewers (BK, VR, and DF) who will thoroughly review each other's work. Our data abstraction forms are based on the data collection forms from the Effective Practice and Organization of Care (EPOC) review group, albeit heavily modified for the purposes of this review. We will extract data on study design, description of the intervention (including process), details about participants (including number in each group), length of intervention and follow-up, definition of disadvantaged, health, cognitive and behavioural outcomes, cost-effectiveness, critical appraisal (see below), and statistical analysis. Where possible, we will record effects by socio-economic position, and by other socio-demographic variables, including place of residence, gender, race/ethnicity, and age. Consensus will be reached by discussion and consultation with a third reviewer, if necessary. After the data abstraction is complete, tables of included and excluded studies will be drawn up. Separate sets of tables will be completed for developing and developed countries. Within each of these sets of tables, interventions will be further grouped according to type of study, and intensity and type of intervention. 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Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».