Academic journal article Bulletin of the World Health Organization

An Analytical Framework for the Study of Child Survival in Developing Countries. (Public Health Classics)

Academic journal article Bulletin of the World Health Organization

An Analytical Framework for the Study of Child Survival in Developing Countries. (Public Health Classics)

Article excerpt

This essay proposes a new analytical framework for the study of the determinants of child survival in developing countries. The approach incorporates both social and biological variables and integrates research methods employed by social and medical scientists. It also provides for the measurement of morbidity and mortality in a single variable. The framework is based on the premise that all social and economic determinants of child mortality necessarily operate through a common set of biological mechanisms, or proximate determinants, to exert an impact on mortality. (1) The framework is intended to advance research on social policy and medical interventions to improve child survival.

Traditionally, social science research on child mortality has focused on the association between socioeconomic status and levels and patterns of mortality in populations (Figure 1A). Correlations between mortality and socioeconomic characteristics are used to generate causal inferences about the mortality determinants. Income and maternal education, for example, are two commonly measured correlates (and inferred causal determinants) of child mortality in developing country populations. Specific medical causes of death are generally not addressed by social scientists, and the mechanisms by which socioeconomic determinants operate to produce the observed mortality differentials remain largely an unexplained "black box."

[FIGURE 1 OMITTED]

Medical research focuses primarily on the biological processes of diseases, less frequently on mortality per se. The differing assumptions and methods are classified in Figure 1B. Studies of cause of death attribute mortality to specific disease processes (such as infections or malnutrition), using information obtained from death reports or clinical case records. Clinical trials assess the therapeutic effect of a particular medical technology. Field intervention studies measure the effectiveness of personal preventive measures on levels of morbidity and mortality in a population. Epidemiological studies may define mechanisms of disease transmission in the environment--for example, the connection between environmental contamination (polluted drinking water) and disease (cholera). Intervention studies alter the environment to reduce disease transmission (as with malaria vector control). Nutrition research focuses on breastfeeding, dietary practices, and food availability as they relate to nutritional status.

The dependent variable most commonly measured in medical research is morbidity, that is, the manifestations of disease processes among survivors--usually calculated as the incidence and prevalence of disease states in a population. The ultimate consequences of disease for mortality in populations at large tend to be neglected, and socioeconomic determinants are generally ignored or dealt with only superficially.

While both the social and medical sciences have made major contributions to our understanding of child mortality in developing countries, the differing concerns and methodologies have compartmentalized such knowledge and constrained the development of potentially more useful approaches to understanding child survival. An even more critical problem is that the selection of a particular research approach usually results in policy and program recommendations biased along disciplinary lines. A new analytical approach incorporating both social and medical science methodologies into a coherent analytical framework of child survival therefore is clearly needed.

The proximate determinants framework

The development of a proximate determinants approach to the study of child survival presented here (2) is based on several premises:

1 In an optimal setting, over 97 percent of newborn infants can be expected to survive through the first five years of life.

2 Reduction in this survival probability in any society is due to the operation of social, economic, biological, and environmental forces. …

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