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The Relationship Between Child Anthropometry and Mortality in Developing Countries: Implications for Policy, Programs and Future Research¹

Cornell Food and Nutrition Policy Program, Division of Nutritional Sciences, Cornell University, Ithaca, NY 14853

The prevention of child mortality is a commonly stated health goal in developing countries and the target of much international assistance in the health sector. Over the past decade the primary strategy for accelerating the reduction in child mortality has been the dissemination of simple, low-cost technologies, such as immunization, oral rehydration therapy and antibiotics, that target specific diseases (Huffmann and Steel 1994). This is done despite the knowledge that malnutrition and disease have a synergistic relationship (Scrimshaw et al. 1968) and that the optimal strategy may involve a combination of health and nutrition interventions. In the 1970s, for instance, it was estimated that malnutrition (notably protein-energy malnutrition—PEM) was the underlying or contributing cause of death for roughly half of all deaths to children aged 1–4 years in several Latin American countries (Puffer and Serrano 1973). Apart from this early study, however, there has been little effort to quantify the contribution of malnutrition to child mortality in other regions of the world in ways which are meaningful to policy. This paper reviews the results of 28 community-based, prospective studies, in 12 Asian and Sub-Saharan African countries, which examined the relationship between anthropometric indicators of malnutrition and child mortality. One purpose is to estimate the contribution of malnutrition to child mortality—distinguishing the effects of severe malnutrition from mild-to-moderate malnutrition—and to examine a number of related issues relevant to policy, programs and research in this area.

The accumulated results are consistent in showing that the risk of mortality is inversely related to anthropometric indicators of nutritional status and that there is elevated risk even in the mild-to-moderate range of malnutrition. This latter result contradicts the findings from an earlier, landmark study which suggested that mild-to-moderate malnutrition was not associated with an increased risk of mortality (Chen et al. 1980). The present results indicate that somewhere between 20% and 75% of child deaths are statistically attributable to anthropometric deficits, with most estimates falling in the range 25–50%. When taking account of the relative proportions of severe versus mild-to-moderate malnutrition in the population, the results show further than 16–80% of all nutrition-related deaths are associated with mild-to-moderate malnutrition rather than severe malnutrition. In most studies 46–80% of all nutrition-related deaths are in the mild-to-moderate category. This represents the proportion of nutrition-related deaths that would be missed by policies and programs focusing primarily or exclusively on the severely malnourished, a bias that does exist in many public health programs in practice if not by design.

Another important result is the confirmation that malnutrition has a potentiating (multiplicative) effect on mortality within populations, as predicted from the theory of synergism. This means that malnutrition has its biggest impacts in populations with already high mortality levels and that morbidity has its biggest impacts in the most malnourished populations. This finding has far-reaching implications for child survival policy and programs, suggesting that greater attention should be paid to nutritional improvement than at present.

A potential limitation of the above conclusion is the possibility that the relationship between mortality and malnutrition may be confounded by behavioral and socioeconomic factors (e.g., caretaker knowledge and practices and access to health care). Several studies have addressed this question by controlling for confounders (through proxy socioeconomic variables), and these studies reveal that the anthropometry-mortality relationship is not due to such confounding. Usually this has been applied to severe cases of malnutrition, where the link to mortality is strongest, but one study indicated similar results among mild-to-moderate cases.

The results further suggest the possibility that, for a given anthropometric deficit, child mortality in South Asian children is lower than in children from other regions. This result is consistent with the findings from earlier cross-national comparisons (Haaga et al. 1985). It may relate to small maternal stature in these populations, which contributes to the exceptionally high rate of low birth weight (31%) and relatively benign carry-over effects on the size of preschool children. It is hypothesized that child anthropometric deficits arising in this fashion may not have the same functional consequences as deficits arising from poor maternal health and nutrition during pregnancy or from similar conditions in early childhood, an area requiring further research.

On the basis of a priori expectations as well as the results from the few studies examining these issues, the review concludes that the child anthropometry-mortality relationship is likely to be modified by a number of other factors, a result with important implications for policy and programs. Some of these factors include the age of the child, possibly sex of the child in some settings, length of follow-up after measurement, seasonality and breastfeeding. The policy importance is well illustrated by the breastfeeding results, which indicate that the elevated risk of death among severely malnourished children (>12 mo) is made even worse (four times worse) by the absence of breastfeeding. The programmatic importance of effect modifiers relates to such issues as deciding the optimal interval between measurements for screening purposes, choosing the most efficient anthropometric indicator and deciding the priority to be given to children of different ages when using a single screening indicator. Most studies have been limited in their ability to examine these issues due to small sample sizes, variation in analytical methodologies and failure to collect and/or use ancillary data in the analysis. However, future research should include consideration of these issues and may benefit from pooling the data from previous studies.

Finally, it is suggested that observational (i.e., nonintervention) studies of the type reviewed here may be inherently limited in their ability to answer a central policy question, namely the extent to which reductions in child mortality through health sector interventions may be compromised by persistently high rates of malnutrition. A stronger approach would be through careful evaluation of on-going, large-scale intervention programs, especially those that have successfully controlled severe malnutrition and are shifting attention to mild-to-moderate forms.

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