Abstract
In many developing countries, high levels of child undernutrition persist alongside rapid economic growth. There is considerable interest in the study of countries that have made rapid progress in child nutrition to uncover the driving forces behind these improvements. Cambodia is often cited as a success case having reduced the incidence of child stunting from 51% to 34% over the period 2000 to 2014. To what extent is this success driven by improvements in the underlying determinants of nutrition, such as wealth and education, (“covariate effects”) and to what extent by changes in the strengths of association between these determinants and nutrition outcomes (“coefficient effects”)? Using determinants derived from the widely-applied UNICEF framework for the analysis of child nutrition and data from four Demographic and Health Surveys datasets, we apply quantile regression based decomposition methods to quantify the covariate and coefficient effect contributions to this improvement in child nutrition. The method used in the study allows the covariate and coefficient effects to vary across the entire distribution of child nutrition outcomes. There are important differences in the drivers of improvements in child nutrition between severely stunted and moderately stunted children and between rural and urban areas. The translation of improvements in household endowments, characteristics and practices into improvements in child nutrition (the coefficient effects) may be influenced by macroeconomic shocks or other events such as natural calamities or civil disturbance and may vary substantially over different time periods. Our analysis also highlights the need to explicitly examine the contribution of targeted child health and nutrition interventions to improvements in child nutrition in developing countries.
Highlights
There is heightened international interest in reducing the burden of child undernutrition [1]
The impact of maternal education on child nutrition status may be very different in the lower quantiles of the child height-for-age Z scores (HAZ) score distribution than in the upper quantiles, which would not be captured by using mean regression approaches
Our results are consistent with the findings from the previous literature [21, 22] that determinants derived from the UNICEF framework make a major contribution to improvements in child nutrition status
Summary
There is heightened international interest in reducing the burden of child undernutrition [1]. Stunting, derived from height-for-age measurements, captures the impacts of long term dietary inadequacy and infections, and is a key undernutrition metric in the international community [3]. The World Health Assembly Resolution set a 40% reduction in the number of children under-5 who are stunted as one of the six global nutrition targets for 2025 [2], a metric supported by the proposed Sustainable Development Goals [4]. Strong evidence suggests that stunting can have long-term effects on cognitive development, school achievement, economic productivity in adulthood and maternal reproductive outcomes [5,6,7] and it is a condition that may be very difficult to reverse [8]. There is a strong rationale for investments in nutritional interventions, as averting stunting can produce life-long economic benefits [12]
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