What Explains Cambodia’s Success in Reducing Child Stunting-2000-2014?

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.

Socio-demographic factors associated with normal linear growth among pre-school children living in better-off households: A multi-country analysis of nationally representative data

“…In this analysis, we included only the basic factors (socio-demographic factors) in our empirical models. We did this because there is evidence that in examining the association between child growth outcomes and exogenous factors, the proximate factors (endogenous factors) are usually excluded to avoid biased estimation of the regression parameters of the exogenous factors [47][48][49]. It is the case because the proximate factors are pathways through which the exogenous factors influence child nutrition [48].…”

Factors associated with normal linear growth among pre-school children living in better-off households: a multi-country analysis of nationally representative data

“…These basic determinants may be described as “exogenous” determinants, which influence child nutrition through their effect on the intervening proximate determinants (underlying determinants). In effect, the underlying factors are therefore, endogenously determined by the exogenous factors (44). In this analysis, we included only the basic factors (socio-demographic) in our empirical models.…”

“…In this analysis, we included only the basic factors (socio-demographic) in our empirical models. We did this because there is evidence that in examining the association between child growth outcomes and exogenous factors, the proximate factors are usually excluded to prevent biased and uninterpretable parameters (44-46). Besides the basic factors, we also included antenatal care (ANC) and breastfeeding practices, which relies mostly on exogenous public health provisions rather than socio-demographic endowments of the household (44).…”

“…We did this because there is evidence that in examining the association between child growth outcomes and exogenous factors, the proximate factors are usually excluded to prevent biased and uninterpretable parameters (44-46). Besides the basic factors, we also included antenatal care (ANC) and breastfeeding practices, which relies mostly on exogenous public health provisions rather than socio-demographic endowments of the household (44). The significance of including these two variables in the model is that changes in them are likely to be more responsive to policies, programmes and interventions rather than to changes in socio-demographic endowments of the household (44).…”

“…Besides the basic factors, we also included antenatal care (ANC) and breastfeeding practices, which relies mostly on exogenous public health provisions rather than socio-demographic endowments of the household (44). The significance of including these two variables in the model is that changes in them are likely to be more responsive to policies, programmes and interventions rather than to changes in socio-demographic endowments of the household (44). For example, there is evidence that policy, institutional and contextual settings are key determinants of the prevalence of breastfeeding practices (44, 47).…”