This is the old United Nations University website. Visit the new site at http://unu.edu
Ernesto Pollitt
Abstract
As the final chapter in a monograph by the same title, this article presents an overview of the evidence discussed in the book. It demonstrates that poor nutrition and health pose a significant educational problem and suggests means to address this problem. Nutrition and health conditions are reviewed in terms of the developmental period in which a child is exposed and the effect on school learning. A summary table of salient findings lists a number of nutrition and health conditions that are educational-risk-factors contributing to educational inefficiency.
Statement of intent
Highly prevalent nutrition and health conditions among school-age children are important determinants of educational outcomes which educational policy makers and planners can no longer afford to overlook. There are ways to intervene to improve the nutrition and health of today's school-age populations that offer ministries of education promising avenues for improving the quality of primary education.
Formal elementary education has substantive beneficial effects for the individual in particular and society in general. Nonetheless, school enrolment in countries in Africa, Asia, and Latin America is strikingly lower than the expected enrolment based on the number of children of school age. Attrition and repetition of grades are also highly prevalent. Thus, the picture that emerges of the education sector in many developing countries is one of vast inefficiencies.
Countries in those three areas were forced to make profound economic adjustments in this decade as a result of the crisis in the world economy and of the reduction in economic growth in industrialized countries [2; 3]. Internal and external economic and political demands pressured governments to assess the efficiency of their different sectors. Within the education sector these analyses generally pointed to the need to increase enrolment at marginal cost and to decrease wastage.
Ernesto Pollitt is professor of human development in the Department of Behavioral Sciences at the University of California at Davis, Davis, California, USA.
This article is adapted from the final chapter of Malnutrition and Infection in the Classroom [1].
Problems of efficiency in a specific context are illustrated in chapter 2 of Malnutrition and Infection in the Classroom [1] by demarcating the school trajectory of 89 children in four villages in rural Guatemala. A year of school per child is used as a unit of analysis in order to estimate the investment the Guatemalan government would have had to make in order for these 89 children to graduate from primary school (sixth grade). Under ideal conditions, each child would represent a six-year investment-a total of 534 years for 89 children. In reality, only 15 children graduated in six years. At the rate of progress observed, 1,131 years would have been needed for the 89 children initially enrolled to have graduated-212% of the ideal, an excess of 597 years.
The crooked educational trajectory of most of those 89 rural Guatemalan children also raises questions regarding their nutritional and health history. At issue is whether the efficiency of the schools in question would have been higher if the health and nutritional status of the children involved had been better. A thesis implicit in the monograph is that nutrient deficiencies and disease interfered with the school progress of many of those children. Appropriate nutritional and health interventions would have benefited the educational progress of many children and also enhanced the efficiency of the educational system.
Briefly, my intent has been to provide the conceptual and empirical background necessary to infer that highly prevalent nutrition/health conditions are important determinants of educational outcomes. Ultimately, the objective is to persuade planners, educators, public health and nutrition professionals, and government officials that nutrition/health conditions should be taken into account in educational planning. Improvements in health and nutrition offer a possibility to improve educational efficiency.
Nutrition/health, economics, and education variables
Research on the effects of health status on economic growth in developed and developing countries has expanded greatly in the last two to three decades and has turned into a well-defined area of investigation. This is particularly the case in connection with tropical diseases [4] However, critical conceptual and methodological obstacles remain in the process of inquiry. In particular, health outcomes are often difficult to define and translate into economic terms [5].
On the other hand, the use of education variables as a health/nutrition outcome in order to assess the costs of investment and the rates of return lessens such problems. Rates of enrolment, age at enrolment, attrition, repetition, and grades attained are among the variables that can be clearly operationalized and scaled in terms of costs and benefits. In addition, they refer to components of different aspects of the educational process, and are potentially capable of affecting the final educational outcome through separate mechanisms.
Exclusions
The criteria for the inclusion of the nutrition and health conditions that were discussed were (1) high prevalence among children of school age in developing countries, (2) documented effects on school-learning variables or on health, which in turn could affect school learning, and (3) the feasibility of appropriate interventions. This study does not claim to be a comprehensive review of all relevant conditions. Other conditions that might not have met the criteria above, but that are as important in terms of affecting educational efficiency as those discussed, were omitted. Among these, respiratory infections (viral and bacterial), otitis media, and diarrhoeal diseases are particularly important.
Respiratory infections are the most frequent cause of mortality and morbidity in the developing world [6]. The number of episodes annually decreases after the age of five; still, the frequency among school-age children may be excessive. Even in the developed countries viral respiratory diseases may be a cause of up to 80% of absenteeism from school [7]
Otitis media is an inflammation of the inner ear. Some ears develop a fluid residual effusion during the healing phase that may take weeks or months to resolve. The prevalence of otitis media in the first 24 months of life is generally very high; in some industrialized countries as many as 70% of all children have had at least one acute episode before the age of three years. The incidence over a 12-month period declines after the first two years of life, but it is still high in the pre-school and school-age years [810]. Otitis media in infancy and early childhood has been negatively related to later cognitive (language) development and school achievement; possibly these deficits are mediated by a loss of hearing, which is a common outcome.
Diarrhoeal diseases, a cause of dehydration, are the fourth major determinant of death and morbidity in the developing world [6] Children up to the age of five generally suffer from one to ten episodes per month; thereafter, it gradually decreases and in adulthood the mean is about one episode yearly. Although no statistics are available for less-developed countries, diarrhoeal diseases are likely to be a major cause of school absence. In California, gastrointestinal diseases account for an estimated 24%26% of days lost from school [7].
School-learning model
The information that is reviewed is classified according to a theoretical model of school learning that includes aptitudes, time-on-task, perseverance, and quality of instruction as the critical components [11; 12]. Because my primary concern is the child, I have omitted the last component of the model from the review. On the other hand, I have added school achievement (test achievement scores and grades attained) as a final outcome.
The model is used to point to the pathways through which nutrition/health factors influence formal education. It is particularly helpful in showing how school progress can be placed in jeopardy without any involvement of the intellectual abilities required for school learning. This demonstration is important because there has been a restricted concern with the effects of nutritional deficiencies such as protein-energy malnutrition (PEM) on cognition, disregarding the possibility that such deficiencies could affect schooling through much simpler mechanisms.
A problem with the model is that the demarcation of the areas covered by each component (for example, aptitudes and time-on-task) is not always clear. Illustrative is the case of distractibility in the classroom, which could be associated with problems either in cognition or in motivation. For example, poor attention in the classroom could reflect a cognitive dysfunction such as is often observed among hyperactive children, or it could result from a lack of perseverance in an otherwise healthy child.
In the two sections that follow, evidence concerning the effects of nutrition and health conditions on educational variables from various studies presented in chapters 2-10 [1], classified on the basis of this model, is reviewed according to the developmental period of exposure and expression of effects. The first section deals with the later effects of early deficiencies, and the second with the effects of current health problems in school-age children.
Early deficiency and later school-learning variables
Aptitudes
The aptitudes component of the model of school learning is operationally defined as the time it takes a child to learn or master a particular task, holding other relevant variables constant. IQ is used as the closest approximation to aptitudes. Performance in tests of attention and concentration are generally used as indicators of aptitudes. In a few instances (e.g. iron-deficiency anaemia) tests of attention are also used as indicators of perseverance.
Cretinism implies severe or profound mental retardation and is a direct result of iodine deficiency. Cretins are not able to participate in regular schooling [13]. Blindness or visual impairment secondary to a severe deficiency of vitamin A creates special educational needs that are not generally met in a regular classroom [14]. Severe PEM during the pre-school period affects cognition and learning. In a population where malnutrition is endemic, children with a history of severe and chronic PEM are handicapped in school [15-18]. In those cases where the child's educational, social, and physiological needs are met after rehabilitation from the episode of severe malnutrition [1820] the handicap may be negligible.
The neurodevelopment of otherwise normal children is likely to be at risk in areas where iodine deficiency is endemic. This assumption is supported by a body of literature that shows a striking consistency between findings. Conclusive clinical trials to support the statement are not available. Among the most susceptible cognitive domains are visual-perceptual organization, visual-motor coordination, and speed of information processing [21; 22]. Interventions providing iodine to women of child-bearing age in endemic populations prevent goitre and cretinism [23]. It is expected that they also prevent neuro-developmental impairments in otherwise normal children.
Mild-to-moderate PEM in early life shapes the school trajectory of children. Two types of studies have supported this assertion. One includes correlational research designs, in which a dimension of body growth that reflects the nutritional history of the individual (e.g. height for age) is correlated with the score in an aptitude test (e.g. IQ). The other includes experimental studies that gauge the effects of dietary supplementation on aptitude tests.
Correlational study designs preclude conclusive inferences, particularly in those situations where the two variables in the equation (nutrition and behaviour) are measured at about the same time. In such cases the direction of the hypothetical effects cannot be determined. This problem of interpretation is further complicated, in connection with the issue under review, by the inextricable association that exists between PEM and the big-social syndrome of poverty. Deficits in aptitudes (e.g. low IQ) observed among children with a history of undernutrition (e.g. low height for age) are potentially attributable to malnutrition, to the environmental factors associated with poverty, or to a combination of malnutrition and environmental factors.
On the basis of the available evidence, it can be concluded without a reasonable doubt that, in populations where malnutrition is endemic, body size (e.g. height for age) and scores from aptitude tests (e.g. IQ) are moderately correlated. Thus, undernourished children reared in environments characterized by severe economic impoverishment are at a disadvantage compared to well nourished peers reared in the same types of environments [24-27].
Studies on functional effects of early PEM of the second type, which include dietary supplementation as an experimental variable, address the issue of causality head-on. In one group of studies of this type, the interventions were restricted to a dietary supplement and health care. In a second group educational and social interventions, targeted either to the child or to the mother, were added to the dietary supplement and health care. Both groups were intended to fit scientific requirements of internal validity and followed rigorous protocols, including the experimental manipulation of the dietary-intake variable and careful assessments of the aptitude variables. The data generated by studies in the first group showed weak, but statistically significant, beneficial effects of dietary supplementation on aptitude tests during the preschool period [28]. The studies in the second group observed robust beneficial developmental effects [20]. Effects from early supplementation were observed in tests of cognitive function during the pre-school period and later on school performance [29-31].
Correlational and experimental studies complement each other. Correlational studies have pointed out that early undernutrition jeopardizes the educational progress of children living in poverty. Experimental studies have indicated that those effects are remedied and prevented by adequate improvement of the environmental conditions to which undernourished children are generally exposed. Both sets of findings make sense not only in connection with undernutrition but also in terms of developmental theory. The data also fit well with the present understanding of the consequences of early biological risk and the self-correcting tendencies of the organism [32] Sceptics who attribute the developmental deficits observed among children with a history of undernutrition solely to the social environment face a formidable task of finding evidence that supports their position.
Geohelminth infections (ascariasis, trichuriasis, hookworm infection) are often a contributory cause to PEM among pre-school and school children [33]. As such, they are a risk factor that works against the educational progress of children.
Lead poisoning results in severe neurological damage [34; 35], and high lead levels in pregnant women are associated with low birth weight and congenital abnormalities in the offspring [36]. Children should not be exposed to more than 100-150 µg of lead per day. Young children living in urban centres in the United States have elevated blood-lead levels (e.g. >=25 µg/dl with an erythrocyte protoporphyrin >=35 µg/dl [35]. Children living in high-density urban centres where leaded gasoline is used such as Lagos, Jakarta, and Mexico City may ingest up to 175-200 µg of lead per day.
Pre-school children in Port Pirie, Australia, had elevated blood-lead levels and low IQ and performed poorly on cognitive tests [37]. These associations remained statistically significant after the effects of social and economic factors were controlled for. Covariations between blood lead in infancy and the preschool period and deficits in aptitudes in school-age children have been assessed, but most results have not supported the existence of sustained effects [38-40]. There is evidence that elevated blood-lead levels in infancy are negatively correlated with scores in cognitive tasks administered at the end of the pre-school period [37].
Most developmental data on elevated blood-lead levels are derived from studies in industrialized countries (e.g. Australia, the United Kingdom, and the United States) and include children likely to be well nourished (except for possible iron deficiency) and in otherwise healthy status. Children in urban centres in developing countries who are at risk for elevated blood-lead levels are also at risk of having poor health and malnutrition. Possible synergistic interactions between lead and nutrition and health status may exist that could not have been detected in the studies reported. What has been reported is that the effects of lead are more likely to be observed when other variables of a disadvantaged environment (such as low income) are present [41; 42].
School aptitudes among three- to six-year-old children are affected by iron-deficiency anaemia. These effects continue into the school period if the nutritional deficit is not corrected. There are no data to sup port the contention that cognitive deficits observed among pre-schoolers will persist after appropriate treatment.
In summary, conclusive evidence exists that cretinism due to iodine deficiency and visual impairment due to vitamin-A deficiency irreversibly impair basic aptitudes required for regular schooling. There is also conclusive evidence that, in populations where malnutrition is endemic, children with a history of severe PEM in infancy and the pre-school period are educationally at a disadvantage compared to their peers without such a history. There is strong evidence that, in populations were iodine deficiency is endemic, the aptitudes of children even without signs of cretinism are at risk; this is also the case among children with a history of chronic mild-to-moderate energy deficiency. The issue of whether iron-deficiency anaemia and elevated blood-lead levels in infancy and the preschool period are related to poor performance on aptitude tests among school-age children remains to be investigated.
Public-health-type interventions among infants and children who are nutritionally at risk that include dietary supplementation, health care, and an educational component result in developmental gains during the pre-school and school-age periods. The developmental consequences of interventions restricted to dietary supplementation and health care availability are limited.
Time-on-task
"Time-on-task," as a component of school learning, refers to such indicators as enrolment, age at enrolment, absenteeism, and duration in school, all of which speak to issues of opportunity for learning in schools. Illiteracy, a widespread educational problem in countries in Africa, Asia, and Latin America, illustrates the consequences of absence of opportunity. Note that time-on-task interacts reciprocally with aptitudes. On the one hand, brighter children enrol earlier and stay in school longer [43]; on the other, children who stay in school will perform better than children who drop out early.
The evidence on the effects of early nutrition is strongest in children with a history of chronic undernutrition (e.g. Iow height for age). For example, a study in Nepal [26] showed that, after income (rice and wheat output), the most significant contributor to the child's school enrolment was body size. Specifically, the predicted conditional probability for the highest income (Rs 12,000) was 0.398, while that for a height for age >=100% of the norm was 0.271 [44].
Body size and time of enrolment may be related to the parents' perception of their child's readiness for school [45] Parents may use the criteria of body size and maturity rather than age to decide when to enrol their children. Attrition has also been related to weight for age; children who dropped out early were more likely to be underweight [46]
In goitrous areas in Indonesia and Spain, children spent less time in school than children from nongoitrous areas [22] Differences in the availability of schools may have been one reason for the differences in years of schooling. An alternative explanation is that children in endemic areas enrol late and drop out early because of comparatively poor intellectual competence.
In summary, in populations where malnutrition is endemic and body size is determined by nutritional history, shorter children enrol later and spend less time in school. In such populations, where public health interventions (nutrition, health, and education) among infant and pre-school children have significant developmental beneficial effects, brighter children enrol in school early. Similarly, children in areas of endemic iodine deficiency who are otherwise normal have, on the average, fewer years of schooling than children of similar ethnic and cultural background and socio-economic status living in non-endemic areas.
Perseverance
Perseverance, the third component of the model, refers to affective behaviours that determine the amount of time a student is willing to spend on-task. In this section the emphasis is on perseverance as a trait, which refers to a relatively stable personality attribute defined by a complex compound of interests, beliefs, and attitudes that determine the value attributed to investing time-on-task. Perseverance may also refer to a transient emotional state that determines, in part, the time-on-task and the effort at a particular moment.
Very few of the reviewed studies addressed the issue of the effects of early nutritional deficiencies and infection on perseverance in the school period. Those studies with such a focus related PEM and scores on tests of attention (e.g. observation of attention in the classroom). In one particular study in Embu district, Kenya, the investigators observed classroom behaviour and rated distractibility as a percentage of time involved in off-task behaviours [46]. Significant associations were found for female students; girls with higher calorie, fat, protein, and animal-protein intake were more likely to be on-task than those with lower intakes. Likewise, children with a history of severe PEM in Barbados were also rated as having poor attention in the classroom [47].
The data reported on distractibility are insufficient to decide whether the attention deficits observed were strictly cognitive or motivational. This distinction is needed to the extent that we attribute value to discriminating the nature of the effects on the components of the school-learning model.
Achievement
An array of studies on the educational consequences of early severe and mild-to-moderate PEM are reviewed. Most of the results point out that the school attainment, measured by grades attained [24; 26], and achievement test scores of children with a history of malnutrition are respectively less and poorer than those of their peers [48; 49].
Interventions that combine nutrition, health, and education inputs and that are implemented in infancy and the pre-school period have substantive effects on school aptitudes. On the other hand, the beneficial effects of interventions restricted to dietary supplementation during infancy and the preschool period are weak in early childhood. It still remains to be determined whether the effects of such interventions carry over through the school years.
Conclusions
A recapitulation of the effects described of early nutritional deficiencies on school-learning variables leads to the conclusions listed below. The order in which these conclusions are presented is determined by the strength of the internal validity of the findings and the magnitude of the effects.
Iodine deficiency.
School-age children with cretinism are unable to participate in regular schooling. These children have educational needs that must be met by special education systems generally unavailable in those populations where iodine deficiency is endemic.
School-age children without signs of cretinism in populations where iodine deficiency is endemic are likely to have neurodevelopmental deficits that place them at an educational disadvantage compared to children from similar social and economic backgrounds in non-endemic areas.
Interventions providing iodine to women of childbearing age in endemic areas will result in a significant decrement in cretinism and have similar preventive effects on the neurodevelopmental effects among otherwise normal children observed in such populations.
Vitamin-A deficiency
School-age children who are visually impaired or blind because of severe vitamin-A deficiency have educational needs that must be met by special educational systems that are unavailable in most populations with endemic vitamin-A deficiency.
Protein and energy deficiency
In populations where malnutrition is endemic, children with a history of severe PEM enrol late in school, drop out early, and manifest school-aptitude deficits. The severity of these problems during school age varies as a function of the extent to which the environment to which these children were exposed following nutritional rehabilitation met their nutritional, physiological, emotional, and educational needs. When these needs are met, the school aptitudes of children with a history of severe PEM are not likely to be a hurdle to learning in the classroom.
Children with a history of chronic mild-to-moderate malnutrition as reflected in stunting will, on the average, perform less well in school than their peers.
Children with a history of early severe or mild-to-moderate PEM who are subsequently exposed to public health interventions that combine nutritional, health, and educational inputs will have major advantages in school aptitudes and performance compared with children with similar history but without exposure to such programmes.
Geohelminths and schistosomes
Ascariasis, trichuriasis, hookworm infection, and schistosomiasis are involved in the causation of PEM. As such, they contribute to the educational deficits listed in connection with early chronic malnutrition and should be considered educational risk factors.
Iron deficiency
A relationship between pre-school iron-deficiency anaemia and poor school performance has not been documented. However, chronic iron-deficiency anaemia during the pre-school period will have cumulative adverse effects on learning variables that interfere with school performance.
Iron treatment reverses the adverse effects of iron-deficiency anaemia on school aptitudes.
Lead
Pre-school children with elevated blood-lead levels have poorer school aptitude test scores than controls. A relationship between pre-school elevated blood-lead levels and poor school performance has not been documented.
Malnutrition, hunger, and infection in school-age children
This section deals with evidence on the effects of current nutritional deficiencies, hunger, parasitosis, and elevated blood-lead levels on aptitudes, time-on-task, perseverance, and achievement. There is a wide variability in the nature of the effects observed in connection with the nutrition/health conditions in question. On one hand, a condition such as elevated blood-lead levels could result in biochemical and neuro-physiological changes in the brain that in turn would affect specific functions. For example, based on the known impairments in the central nervous system due to lead poisoning, it is justified to suspect that elevated lead levels in school-age children impair cognition. On the other hand, exposure could leave higher cortical activities unaltered but produce systemic effects and stress that would affect cognitive processes such as attention. For example, attention processes are adversely affected by stress conditions such as hunger [52].
Of concern here are conditions that are present in school-age children and result in changes in the state of the organism that are adverse to learning. Thus, iron-deficiency anaemia, geohelminth infections, and schistosomiasis are of particular importance. Iron-deficiency anaemia is the second most prevalent nutritional deficiency around the world, and there is strong evidence of adverse effects on learning processes. Geahelminth infections and schistosomiasis are highly prevalent among school-age children and produce clinical changes that are likely to interfere with efficient information processing.
Aptitudes
One of the conclusions of the previous section on the later effects of early deficits was that iron-deficiency anaemia affects aptitude test performance in preschoolers. The concern at that point was the possibility that such effects among pre-schoolers could remain into the school period. However, the evidence required to support such a concern is not yet available. In this section, it is emphasized that the evidence available on iron-deficiency anaemia suggests that aptitudes in school-age children are affected. Thus, although schoolchildren may be more physiologically mature than pre-schoolers, cognitive function may be at risk in both age groups. Significant associations between iron-deficiency anaemia and comparatively low IQs among primary-school children have been reported in some studies [53; 54]. In others, the two variables were independent of each other [48; 55].
Among schoolchildren with iron-deficiency anaemia attention is impaired. In Baroda, India, iron treatment among anaemic boys resulted in a significant improvement in clerical and maze tests [54; 55]. In the first of these tests the subjects had to encircle the matras (short metrical units) in a script in a five minute period; in the second, the objective was to match components of two different sets of visual symbols. Both tests assess elements of attention discrimination and attention maintenance. Similar findings were reported using the Bourden-Wisconsin test of concentration in Indonesian children with iron deficiency anaemia [56]. This test requires the identification of a particular probe within an array of symbols. Adequate iron treatment over no more than three months ameliorated the deficits observed [54; 56]
These observations have not yet been coupled with definitive evidence regarding the breadth of the deficit, however. At issue is whether other more complex and higher cognitive activities are also implicated. If it were restricted to a particular process such as attention, then the underlying mechanisms could be limited to systemic changes. Evidence of a restricted focus, however, would not preclude the existence of long-term effects. Poor attention in the classroom over a whole school year could obstruct school attainment. Effects of iron deficiency on attention are also discussed briefly in the section on perseverance.
Hookworm infection and schistosomiasis are often a contributory cause of iron-deficiency anaemia [57; 58]. The mechanism for causation in the case of hookworm is the parasites' feeding on blood in the intestine and spillage, while for schistosomiasis it is blood loss through either urine (S. haematobium) or stools (S. mansoni). As iron-deficiency anaemia is associated with low IQ and attention deficits, hookworm infection and schistosomiasis should be considered educational-risk factors. At issue is the possibility, discussed below in more detail, that helminth infections affect school-learning variables through pathways not connected with nutritional-status variables.
Low IQs and poor performance in tests of information processing (e.g. reaction time) among schoolchildren are correlated with elevated blood-lead levels [35]. These associations were observed in samples of school-age children in England, Scotland, and the United States among other places. In at least two studies, associations have also been found between lead levels and sensory processing [59; 60].
When children skip breakfast after fasting overnight, their ability at midday to detect environmental cues necessary to solve simple visual tasks of attention is affected. The stress response to the induced hunger also results in increased attention to peripheral information not relevant to the problem at hand. These effects were observed both among well-nourished, healthy, middle-class children [61; 62] and among nutritionally at-risk children [63]. There is suggestive evidence that such effects are exacerbated in children who are stunted because of previous malnutrition.
Benefits from school meals on school-learning aptitudes have not been well documented, largely because of the absence of tightly controlled randomized trials including pre- and post-treatment evaluations. Most evaluations have been based on pre-existing school feeding programmes, which precluded adequate control of confounders and appropriate measures of effect modifiers. One of the better controlled evaluations of school feeding did not assess aptitudes but did find effects on achievement measures, which are referenced in the section on achievement [64].
Time-on-task
Nutritional deficiencies and helminth infections are directly related to absenteeism, which is negatively related to school performance [65]. Of particular concern are iron and vitamin-A deficiency, since both are associated with a weakened resistance to infection [66]. Information on the epidemiology of iron-deficiency anaemia and vitamin-A deficiency in schoolchildren is scarce, and research data on their role in absenteeism among schoolchildren are not yet available.
Geohelminth infections and schistosomiasis are highly prevalent among school-age children and are also likely to be a frequent cause of absenteeism. In addition to their strong debilitating effects on nutritional status, they produce clinical symptoms that can prevent children from attending daily classes in regular schools.
Increase in enrolment and decrease in absenteeism are often objectives of school feeding programmes. In such cases, it is generally assumed that school feeding serves as an incentive to augment time-on-task. Studies that have evaluated the educational impact of such programmes have not yielded consistent results as to whether or not those objectives are met. One study that had positive findings and that was based on a robust study design was conducted in Lawrence, Massachusetts, USA [64]. Children enrolled from the third to the sixth grade in six schools were included in the evaluation. Participation in the breakfast programme was operationally defined by attendance on at least 60% of the days on which breakfast was available. Programme participation over one year was associated with changes in absenteeism and tardiness; those who participated were less likely to be absent or tardy than those who did not participate.
Perseverance
As noted in the section on aptitudes, iron-deficiency anaemia affects attention and concentration among pre-school and school-age children. Conceivably, the low attention-test performance among iron-deficient-anaemic children could be related to motivational factors (e.g. perseverance) rather than a specific impairment in function of the cognitive apparatus. This issue has not yet been sufficiently analysed to be conclusively eliminated as an alternative explanation.
The effects of geohelminth infections and schistosomiasis on school-learning variables-through pathways not related to nutritional status-remain undefined. Yet clinically it seems reasonable to assume that such infections affect, at least, the motivation to learn and work in a school classroom. The infections produce biochemical and immunological changes and, Often, structural alterations in organs such as the intestine or the liver. Both pathology and the associated clinical symptomatology are likely to produce profound alterations in the general well-being of the child and cut down the mental energy required to pay attention, concentrate, and learn.
Achievement
In light of the deficits observed among children with iron-deficiency anaemia, it is not surprising to observe that these children are, on average, behind in school attainment. The study in Indonesia [56] and a study in Chon Buri, Thailand [53] provide good examples. The former study included an achievement test in arithmetic, reading, social science, and biology. The study in Thailand included tests in arithmetic and language. In both studies, the iron-deficient-anaemic children obtained significantly lower scores than the controls. The Indonesian study observed that iron treatment had a significant beneficial effect on test performance, while the Thai study failed to do so.
As iron-deficiency anaemia affects school aptitudes, chronic iron deficiency is likely to have cumulative adverse effects on school learning and educational progress. By the same token, iron treatment will correct those cognitive impairments that are secondary to the previous deficiency, but will have no remedial effects on accumulated educational deficiencies (e.g. information lag). The remedy for cumulative deficit is likely to be strictly educational. In particular, the failure to observe a significant improvement in test performance following iron treatment in the Thai study may have been due to cumulative deficits and a restricted focus on school achievement tests. In hindsight it seems reasonable to postulate that effects would have been more likely to be observed in tests of specific cognitive processes.
The face validity of school feeding programmes does not have the empirical back-up that would be expected. As previously noted, evaluations in developed and developing countries have not yielded consistent support for the notion that regular participation in school breakfast or lunch benefits school learning. The Massachusetts study cited above did find that participation in the breakfast programme over an academic year had significant effects on school achievement measures among children enrolled in primary school [64] A study in Jamaica showed that a government-provided school breakfast had beneficial effects on an achievement task in arithmetic [67].
Among school-age children, elevated blood-lead levels have been associated with poor achievement-test scores after controlling for social and economic variables. For example, a study in Edinburgh, Scot land, showed a close statistical relationship between lead and reading scores in third- and fourth-grade children [59] That study found evidence of an interaction between lead level and the child's age. The effect of lead was greatest when the child was young and when the child's interest score was low. Elevated lead levels have also been associated with poor performance on measures of auditory and verbal processing and distractibility in the classroom [60]
The possibility of differential responses to elevated blood-lead levels as a function of some of the characteristics of the individual was also supported by data from two studies in London. In one there were significant inverse associations between blood-lead level and reading, spelling, and intelligence test scores [68] The other study found that such an association was not statistically significant [41] A reason for the difference in the findings may lie in the differences between the socio-economic backgrounds of the two samples. Those in the second study were mostly children of middle-class parents, while those in the first study were children of blue-collar workers. Thus, as in other developmental conditions, lead may be more likely to affect school performance in cases where other risk conditions are also present [42]
Conclusions
The following are conclusions derived from the data reviewed in this section on current health and nutritional problems.
Iron-deficiency anaemia
Iron-deficiency anaemia among school-age children has adverse effects on function in specific cognitive processes such as attention and concentration. These effects on learning in school increase the time needed to master a school task.
The mechanisms behind the effects of iron deficiency remain undefined. Iron deficiency produces changes in the biochemistry of the brain that are potentially capable of affecting the functions in question. Alternatively, changes in the state of the organism related to the iron deficiency could also explain most of the functional impairments currently documented.
Deficits in cognitive processes resulting from iron-deficiency anaemia are likely to be reversed after successful treatment of the nutrient deficiency. Cumulative schooling deficits will require educational remedies.
Geohelminths and schistosomes
Helminths involved in the causation of iron-deficiency anaemia among schoolchildren contribute to the presence of functional deficits (e.g. in aptitudes) and thus interfere with school learning.
TABLE 1. Strength of relationships (internal validity) between nutritional and disease conditions and educational outcome variables
Aptitudes | Time-on-task | Perseverance | ||
Enrolment | Absenteeism | |||
Protein-energy malnutrition (PEM) | + + + | + + | NRa | NA |
Iron-deficiency anaemia | + + + | + b | NR | + |
Iodine-deficiency disordersc | + + + | + + | NR | NA |
Hunger | + +d | NRe | NA | + |
Intestinal parasitesff | + + +g | NA | ++ | NA |
Schistosomiasis | + +h | NA | NA | NA |
Lead | +++ | NA | NR | NA |
NR = not likely to be related, except in cases of severe present undernutrition.
NA = likely to be related, but information not available.
a. PEM has also been related to increased morbidity, which could be a reason for school absenteeism.
b. It has been established that iron-deficiency anaemia has an effect on aptitudes, which it has been suggested may be a criterion parents use in deciding the age of enrolment of their children.
c. Mild iodine-deficiency disorders; cretinism not included.
d. Information is available only on short-term effects on cognition; there is no documentation on whether such effects are cumulative.
e. While there is no research evidence on the relationship between hunger and enrolment, there is suggestive evidence that the availability of school feeding programmes may be a reason for enrolment and low absenteeism.
f. A. lumbricoides, T. trichuris, hookworm.
g. Intestinal parasites are a contributory cause of PEM and iron-deficiency anaemia. which in turn have adverse effects on school aptitudes. However, because of their profound effects on health, intestinal parasites might also affect the educational process through mechanisms other than changes in nutritional status.
h. Schistosomiasis is a contributory cause of iron-deficiency anaemia, which has been causally related to educational aptitudes; however. most research on schistomiasis and measures of school outcome have yielded
Hunger
Among well nourished and nutritionally at-risk school-age children, skipping breakfast after an overnight fast has adverse effects on visual attention. In particular, the competence to discriminate between stimuli and select relevant cues (i.e. information) for solving problems is impaired.
School feeding
Evaluations of school feeding programmes based on robust study designs have shown beneficial effects of school breakfast on achievement measures such as arithmetic scores. However, results from different evaluations on the educational benefits of school feeding have not been consistent with each other.
The incentive value of school feeding for increments in enrolment and attendance has not been fully demonstrated across different populations. In some cases, school breakfast has been clearly associated with drops in absenteeism and tardiness.
Lead
Elevated blood-lead levels in schoolchildren are associated with comparatively low IQ, poor performance in tests of information processing, and low achievement scores (e.g. in reading).
Among school-age children, the adverse effects of elevated blood-lead levels on school-learning variables are likely to be exacerbated in those situations where other environmental risk factors (e.g. low family income) are present.
Summary
Table 1 summarizes some of the main findings reviewed and judges the strength of such findings. At issue here is the internal validity of the relationships in light of the available evidence. The vertical axis of the table includes the nutritional and disease conditions reviewed, while the horizontal axis includes the educational outcome variables of concern. The three variables included in the table, aptitudes, time-on-task, and perseverance, are from Carroll's model of school learning [11; 12].
The table suggests that the nutritional and disease conditions that have been reviewed are powerful risk factors in connection with school aptitudes. However, the pattern of entries in the table is partly determined by the nature of the research that has been conducted and the information that is available, and does not necessarily mean that the conditions in question have little effect on time-on-task or perseverance. For example, there is little if any information on the effects that PEM, iron-deficiency anaemia, iodine deficiency, or helminth infections have on perseverance. However, given the nature of their effects, it seems highly likely that they do affect the activation of the organism, which, as noted in chapter 1 of the monograph [1], will have a significant impact on ability to solve tasks.
Reflections on the future
My objective has been to confront the current disregard for nutrition and health factors in educational-planning efforts with evidence that shows that some of those factors account in part for educational inefficiency. The thesis is that poor nutrition and health status in children in developing countries in Africa, Asia, and Latin America obstructs educational progress. A main ingredient of this thesis is that appropriate nutrition and health interventions in the pre-school and school-age periods result in higher and earlier enrolment, lower rates of absenteeism and dropping out, and higher school achievement. A corollary is that, in addition to the possible effects of specific nutritional deficiencies and health problems on the central nervous system, there are other risks of poor nutrition and health for school learning. These other effects are mediated by channels completely independent of brain function. The cases of body size and time of enrolment and attrition, and of infection and absenteeism are illustrative.
Among others, scientists and politicians concerned with the issues at hand will question the scientific merit of some of the data that were reviewed from correlational studies, or the internal validity of some of the experimental studies cited. Likewise, the proposal for health or nutrition interventions with an educational target could also be challenged because often there is a lack of full understanding of the mechanisms through which the risk factors in question affect school progress. Most such questions are likely to be scientifically justified and constructive, as they will promote further research and the generation of knowledge that has both applied and theoretical value.
The need for tighter research findings is evident in some areas, as is the need for comprehensive description of effects and identification of mechanisms. This is illustrated clearly in the case of helminth infections, where there are no sound reports that tie together any of these conditions with school-learning variables. Research on such a problem is needed. On the other hand, the existence of those needs does not mean that the information that is necessary for action is not available. Again, the case of helminth infections is illustrative. The associations between geohelminths and schistosomiasis, on the one hand, and PEM and iron-deficiency anaemia, on the other, have been conclusively demonstrated [33]. In addition, the information available on the pathological changes and symptoms associated with those infections provides strong clinical and developmental justification to assume that, at least in some cases, helminthic infections interfere with learning in the classroom. Thus, the well defined contributory causal role of geohelminths and schistosomiasis in PEM and iron-deficiency anaemia, coupled with existing knowledge of their clinical effects, provides a strong basis to address them as educational-risk factors and to recommend appropriate interventions.
The query behind this study was rooted in applied concerns and dealt with a well defined set of health and nutrition variables that must be added to the educational production functions of educational planners. Those concerns and the data we have reviewed on their effects on schooling were placed in the context of two other applied issues. One is the existing inefficiency in the educational sector and the low level of return from investments in traditional educational variables in many developing countries. The other is the disregard for the active participation of the child in the educational process and for the variables that determine whether a child is indeed active or not in such a process. Both issues underscore the need to point to a new direction in educational planning. The recommendation is to change courses and give greater attention to health and nutrition and to the characteristics and attributes of the child that determine his or her engagement in the learning process.
There is no intent to contest the need for a research agenda. In fact, I advocate it, as I am convinced that research will contribute to definition of the nature of the problems and increase the effectiveness and efficiency of the methods to deal with them. My intent is to demonstrate that there is an educational problem in the poor health and nutrition of children and that there are means to address it. A case must be elaborated because the role of health and nutrition in connection with school learning has not been included in most planners' and educators' manuals of operations.
Lastly, it must be emphasized that attending to the nutrition and health of schoolchildren in order to facilitate their school progress leads to a realistic view of how learning occurs and how children develop. As suggested here, health, nutrition, and education are not independent domains in a child's life. They maintain close reciprocal interactions throughout the different developmental stages that men and women go through.
In my view, the task ahead for those involved in policy making within the educational sector is to find effective and efficient ways to deal with prevalent nutritional and health problems that affect the progress of schoolchildren. Universal prescriptions are not available, as the nature and magnitude of the problems will differ among populations as a function of genetic variation, ecological settings, and cultural and socio-economic characteristics. Likewise, the solutions for the problems may differ for similar reasons. For example, the presence or absence of malaria may be a key factor in deciding whether or not to implement an iron supplementation programme in a school population with a high prevalence of iron-deficiency anaemia. Similarly, the use of shoes or thongs may be during infancy on a wiser choice to prevent iron deficiency than iron fortification or supplementation in areas where hook worm is prevalent.
Identifying the existing nutritional problem, defining its epidemiological profile, selecting effective, low-cost interventions, building a functional administrative infrastructure, and planning for evaluations are some of the basic challenges for the future. The claim that the problem does not exist should be left in the past.
References
1. Pollitt E. Malnutrition and infection in the classroom. Paris: Unesco, 1990.
2. Bell DE. Reich MR, eds. Health, nutrition and economic crises: approaches to policy in the third world. Dover, Mass, USA: Auburn House, 1988.
3. Cornia GA, Jolly R, Stewart F, eds. Adjustment with a human face: protecting the vulnerable and promoting growth. Oxford: Clarendon Press, 1987.
4. Herrin AN, Rosenfield PL, eds. Economics, health and tropical diseases. Manila: University of the Philippines School of Economics, 1988.
5. Andreano R, Helminiak T. Economics, health and tropical diseases: a review. In: Herrin AN, Rosenfield PL, eds. Economics, health and tropical diseases. Manila: University of the Philippines School of Economics, 1988: 12-39.
6. Walsh JA. Establishing health priorities in the developing world. New York: United Nations Development Programme, 1988.
7. Task Force on Infectious Diseases in School Age Children. Infectious diseases in school-age children. Sacramento, Calif, USA: California State Department of Education, 1988.
8. Brostoff LM, Cantekin El, Flaherty MR, Doyle WJ, Bluestone CD, Fria TJ. Otitis media with effusion in preschool children. Laryngoscope 1985;95:428-36
9. Biles RW, Buffler PA, O'Donnell AA. Epidemiology of otitis media: a community study. Am J Public Health 1980;70:593-98.
10. Vinther B, Elbrond O, Pedersen CB. A population study of otitis media in childhood. Acta Otolaryngology (Suppl) 1979;360:135-37.
11. Carroll J. A model of school learning. Teachers' College Record 1963;64:723-44.
12. Carroll J. The model of school learning: progress of an idea. In: Fisher C, Berliner D, eds. Perspectives on instructional time. New York: Longman, 1984:29-58.
13. Stanbury JB. The iodine deficiency disorders: introduction and general aspects. In: Hetzel BS, Dunn JT, Stanbury JB, eds. The prevention and control of iodine deficiency disorders. New York: Elsevier, 1987:35-47.
14. Sommer A. Nutritional blindness, xerophthalmia and keratomalacia. New York: Oxford University Press, 1982.
15. Stoch MB, Smythe PM. Fifteen year development study on effects of severe undernutrition subsequent physical growth and intellectual functioning. Arch Dis Child 1976;51:327-31.
16. Galler JR, Ramsey F, Solimano G, Lowell WE. The influence of early malnutrition on subsequent behavioral development: 11. Classroom behavior. J Am Acad Child Psychiatry 1983;22(1):16-22.
17. Galler JR, Ramsey F, Forde V. A follow-up study of the influence of early malnutrition on subsequent development: IV. Intellectual performance during adolescence. Nutr Behavior 1986;3:211-22.
18. Richardson SA. The relation of severe malnutrition in infancy to the intelligence of school children with differing life histories. Pediatr Res 1976;10:57-61.
19. Winick M, Meyer KK, Harris RC. Malnutrition and environmental enrichment by early adoption. Science 1975;190:1173-75.
20. Pollitt E. A critical view of three decades of research on the effects of chronic energy malnutrition on behavioral development. In: Schürch S, Scrimshaw NS, eds. Chronic energy deficiency: consequences and related issues. Lausanne, Switzerland: IDECG, Nestle Foundation, 1988:77-93.
21. Pharoah POD, Connolly KJ, Ekins RP, Harding AG. Maternal thyroid hormone levels in pregnancy and the subsequent cognitive and motor performance of the children. Clin Endocrinology 1984;21:265-70.
22. Bleichrodt N, Garcia I, Rubio C, Morreale de Escobar G, Escobar del Rey F. Developmental disorders associated with severe iodine deficiency. In: Hetzel BS, Dunn JT, Stanbury JB, eds. The prevention and control of iodine deficiency disorders. New York: Elsevier, 1987:65-84.
23. Hetzel BS. An overview of prevention and control of iodine deficiency. In: Hetzel BS, Dunn JT, Stanbury JB. eds. The prevention and control of iodine deficiency disorders. New York: Elsevier, 1987:731.
24. Jamison D. Child malnutrition and school performance in China. J Develop Econ 1986;20:299-309.
25. Johnston FE, Low SM, De Baessa Y, MacVean RB. Interaction of nutritional and socioeconomic status as determinants of cognitive development in disadvantaged urban Guatemalan children. Am J Physical Anthropol 1987;73:501 -06.
26. Moock PR, Leslie J. Childhood malnutrition and schooling deficit in the Terai region of Nepal. J Develop Econ 1986;20:33-52.
27. Kotchabhadki N, Hathirat P, Valyasevi A, Pollitt E. Biological and social factors related to school performance in Thai children. Bangkok, Thailand: Mahidol University, 1989.
28. Joos S, Pollitt E. Comparison of four supplementation studies. In: Brozek J, Schürch B, eds. Malnutrition and behavior: critical assessment of key issues. Lausanne, Switzerland: Nestle Foundation, 1984:507-19.
29. McKay H, Sinisterra L, McKay A, Gomez H, Lloreda P. Improving cognitive ability in chronically deprived children. Science 1977;200:270-78.
30. McKay A, McKay H. Primary school progress after preschool experience: troublesome issues in the conduct of follow-up research and findings from the Cali, Colombia study. In: Preventing school failure: the relationship between pre-school and primary education. Proceedings of a workshop on pre-school research held in Bogota, Colombia. IDRC Publication no. 172e. Ottawa, Canada: International Development Research Centre, 1983.
31. Super C, Herrera G, Mora JO. Effects of food supplementation and maternal tutoring on physical growth. Child Development (in press).
32. Farran DC, McKinney JD, eds. Risk in intellectual and psychosocial development. New York: Academic Press, 1986.
33. Stephenson LS. Impact of helminth infections on human nutrition. London: Taylor & Francis, 1987.
34. Boeckx RL. Lead poisoning in children. Analyt Chem 1986;58:274-84A.
35. United States Agency for Toxic Substance and Disease Registry. The nature and extent of lead poisoning in children in the United States: a report to Congress. Atlanta, Ga, USA: Department of Health and Human Services, Public Health Service, 1988.
36. Schwartz J. Low level health effects of lead: growth, developmental and neurological disturbance. In: Proceedings of the National Conference, Childhood lead poisoning: current perspectives. Washington, DC: Government Printing Office, 1987.
37. McMichael AJ, Baghurst PA, Wigg NR, Vimpani G, Robertson EF, Roberts RJ. Port Pirie cohort study: environmental exposure to lead and children's abilities at the age of four years. N Engl J Med 1988.319(8): 468-75.
38. Schroeder SR, Hawk B. Otto DA, Mushak P, Hicks RE. Separating the effects of lead and social factors in IQ. Environ Res 1985;38:144-54.
39. Ernhart CB, Landa B, Schell NB. Subclinical levels of lead and developmental deficit: a multivariate follow-up reassessment. Pediatr 1981;67(6):911-19.
40. Ernhart CB, Landa B, Wolf AW. Subclinical lead level and developmental deficit: re-analysis of data. J Learning Disabilities 1985;18(8):475-79.
41. Lansdown R, Yule W, Urbanowicz M, Hunter J. The relationship between blood-lead concentrations, intelligence, attainment and behavior in a school population: the second London study. Int Arch Occupational Environ Health 1986;57:225-35.
42. Harvey PG, Hamlin MW, Kumar R, Delves HT. Blood lead, behavior, and intelligence test performance in preschool children. Sci Total Environ 1984;4():45-60.
43. Irwin M, Engle PL, Yarbrough C, Klein RE, Townsend J. The relationship of prior ability and family characteristics to school attendance and school achievement in rural Guatemala. Child Develop 1978;49:415-27.
44. National Center for Health Statistics. NCHB growth charts. Monthly Vital Services Report 1976:25(3) Supp (HRA) 76-1120.
45. Balderston JB. Determinants of children's school participation. In: Balderston JB, Wilson AB, Freire ME. Simonen MS, eds. Malnourished children of the rural poor. Boston, Mass, USA: Auburn House, 1981:83-105.
46. Sigman M, Neumann C, Jansen AAJ. Bwibo N. Cognitive abilities of Kenyan children in relation to nutrition, family characteristics and education. Child Develop (in press).
47. Galler JR, Ramsey F, Solimano G. Lowell WE. Mason E. The influence of early malnutrition on subsequent behavioral development: 1. Degree of impairment of intellectual performance. J Am Acad Child Psychiatry 1983;22:8-15.
48. Agarwal DK, Upadhyay SK. Tripathi AM, Agarwal KN. Nutritional status, physical work capacity and mental function in school children. New Delhi: Nutrition Foundation of India, 1987.
49. Florencio CA. Impact of nutrition on the academic achievement and other school-related behaviors of grade one to six pupils. Quezon City, Philippines: University of the Philippines, 1987.
50. Soewondo S, Husaini M. Pollitt E. Effects of iron deficiency on attention and learning processes in preschool children: Bandung. Indonesia. Am J Clin Nutr (Suppl) 1989:30:667-73.
51. Guidelines for the eradication of iron deficiency anemia. Washington, DC: International Nutritional Consultative Group, 1977.
52. Broadbent DE. Decision and stress. New York: Academic Press, 1971.
53. Pollitt E, Hathirat P, Kotchabhakdi NJ, Missell L, Valyasevi A. Iron deficiency and educational achievement in Thailand. Am J Clin Nutr (Suppl) 1989;50:68796.
54. Seshadri S, Gopaldas T. Impact of iron supplementation on cognitive functions in preschool and school-aged children: the Indian experience. Am J Clin Nutr (Suppl) 1989;50:675-84.
55. Gopaldas T, Kale M, Bardwaj P. Prophylactic iron supplementation for underprivileged school boys. Indian J Pediatr 1985;22:737-43.
56. Soemantri AG, Pollitt E, Kim 1. Iron deficiency anemia and educational achievement. Am J Clin Nutr 1985; 42: 1221 -28.
57. Layrisse M, Roche M. The relationship between anemia and hookworm infection. Am J Hygiene 1964:79:279301.
58. Jordan P, Webbe G. Schistosomiasis: epidemiology, treatment and control. London: Heineman Medical Books, 1982.
59. Fulton M, Raab G. Thomson G, Laxen D, Hunter R, Hepburn W. Influence of blood lead on the ability and attainment of children in Edinburgh. Lancet 1987: 1:1221-26.
60. Needleman HL, Gunnoe C, Leviton A, Reed R. Peresie H, Maher C. Barrett P. Deficits in psychologic and class-room performance of children with elevate d dentine lead levels. N Engl J Med 1979;300(13)689-95.
61. Pollitt E, Leibel RL, Greenfield D. Brief fasting, stress and cognitive function. Am J Clin Nutr 1978;34:1526-33.
62. Pollitt E, Lewis NL, Garza C, Shulman RJ. Fasting and cognitive function. J Psych Res 1983;17:169-74.
63. Simeon DR, Grantham-McGregor S. Effects of missing breakfast on the cognitive functions of school children of differing nutritional status. Am J Clin Nutr 1989;49:64653.
64. Meyers AF, Sampson AK, Weitzman M, Rogers BL, Kayne H. School breakfast program and school performance. Am J Dis Child 1989;143:1234-39
65. Weitzman M. Excessive school absences. Advances Develop Behav Pediatr 1987;8:151-78.
66. Levin H, Pollitt E, Galloway R, McGuire J. Micro-nutrient deficiencies. In: Jamison DT, Mosley WH, eds. Evolving health sector priorities in developing countries. Washington DC: World Bank (in press).
67. Powell C, Grantham-McGregor S, Elston M. An evaluation of giving the Jamaican government school meal to a class of children. Humn Nutr Clin Nutr 1983;37c: 381-88.
68. Yule W, Lansdown R, Millar IB, Urbanowicz M. The relationship between blood lead concentrations, intelligence, and attainment in a school population: a pilot study. Develop Med Child Neurology 1981;23:567-76.