Background
Stunting in under-five children has been established as a risk factor for reduced intellectual performance and job productivity in later life, particularly when this stunting occurs in the first 2 years of life [
1]. Hence global and country level efforts have been directed to develop policies and programmes aimed at effective reduction in the number of stunted children, with changing emphasis from food security to multisectoral approaches [
2‐
6].
Stunting prevalence in children less than 5 years remained stagnant in Peru at around 30-40% from 1992 to 2007, with a rapid reduction thereafter [
7]. This trend occurred within a context of heavy emphasis on implementation of food assistance interventions during the 1990s and the early 2000s [
8,
9], which were not necessarily targeted to infants and pre-school children.
Although significant efforts have been made to explain the reasons for the initial lack of impact of the interventions and the underlying factors driving the more recent success story in Peru at national level [
3,
8‐
10], we are not aware of systematic studies addressed to assess potential influential factors at district level.
To overcome the caveat of analyses limited to the national level that hide sub-national disparities, we aimed to assess the role of different predictors on reduction of under-five stunting over time and across districts (departments) in Peru, during the period 2000 to 2012. This study is part of a wider Countdown to 2015 Country Case Study, which is reported elsewhere [
11]. We aimed at assessing predictors associated with departmental level prevalence of stunting.
Discussion
Our results show that social determinants were more important factors influencing the annual reduction of under-five stunting in Peru than coverage of specific RMNCH interventions. This is in line with previous studies performed at national level in Peru and in other developing countries [
4,
8,
25‐
27]. Of note, the departments where stunting prevalence was higher than 30% in 2000 and showed the greatest reduction by 2012 are all located in the Andean and the Amazon regions of the country. These are the regions that also show the highest rates of poverty and rural population in 2000, which were also reduced significantly during the study period. This highlights that the district level reduction of stunting in Peru followed a progressive pattern, with a clear reduction of the equity gaps between the richest and the poorest segments of the population and between urban and rural areas [
11], which is a remarkable achievement.
Interestingly, GDP per capita showed a significant correlation in the time-adjusted analysis, but this effect disappeared when confounding factors were included ever since the first step of our regressions. Of note, Gini coefficient was not significant in our analyses. Vollmer et al. obtained similar results in a DHS-based study of 36 low-income and middle-income countries, where stunting was one was the outcome variables [
28]. It seems that for economic growth to result in a measurable impact on stunting, various mediating factors need to play an enabling role, namely wealth distribution, poverty reduction, female education, improved access to safe water and sanitation, improved coverage and quality of maternal and child health interventions, as well as increased consumption of nutritious and safe food [
28‐
30]. In Peru, there is evidence that anti-poverty interventions such as the conditional cash transfer (JUNTOS) programme might impact on stunting through improvement of food consumption by children [
31], besides other factors, although its effect on nutrition may still need additional time, as our study did not reveal a positive impact of JUNTOS on stunting.
Mejía Acosta et al. tried recently to unveil the factors behind the remarkable reduction of child stunting in Peru, by using a veto players approach combined with quantitative information on time trends [
8]. They emphasize that a comprehensive explanation of this successful story should take into account economic growth, poverty reduction, increased women’s education, reduced fertility rates, improved access to basic sanitary facilities, and urbanization, but also the concurrent role of widely concerted enabling policy and system factors, leading to increased equity and efficiency of health and other sectors able to provide essential services that can ensure a safe pregnancy, delivery and infancy.
Our district level results, showing that stunting reduction seemed to be more responsive to improvement of social determinants than to better coverage of specific RMNCH interventions, need to be interpreted within the wider policy framework that characterized Peru around the study period. During the 2000s political consensus, national and regional agreements were established with the participation of political parties, the civil society and other stakeholders [
32‐
35]. They agreed on the need to prioritize multisectoral anti-poverty policies and to implement specific programmes aimed at improving maternal and child health. More specifically, specific goals for reduction of stunting were agreed on, which were translated into the implementation of specific crosscutting interventions such as reduction of poverty through quick introduction and scaling up of the conditional cash transfer programme JUNTOS in 2005 [
36], through improved access to improved water and sanitation and women’s empowerment [
36,
37], and through the extension of subsidized and semi-subsidized health provision through the health insurance system (SIS) to reach the poorest segments of the population. More recently, the Ministry of Economy and Finance led the implementation of multisectoral nutritional and maternal-neonatal programmes relying on the results-based budgeting approach, with the aim to increase the efficiency and the effectiveness of expenditure at central and local levels, and to further reduce stunting and maternal and neonatal mortality [
38‐
40]. Under these programmes, the budget is allocated based on the performance reached by each region, in terms of coverage and impact indicators [
38‐
40].
Conditional cash transfer and health insurance system (SIS) showed a significant association with stunting prevalence. That is, the higher the coverage of those interventions, the higher the stunting prevalence. This may be reflecting the fact that both programmes have been reaching effectively the poorest segments of the population, although further analyses may be warranted to reach a definitive conclusion. Similarly, the composite coverage index showed a significant and positive correlation with stunting, which is in the opposite direction to the expected. As this is a composite indicator and should overcome the limitations posed by insufficient sample size, we would have anticipated a significant and negative association instead, thus we do not have a clear explanation for this rather unexpected result.
There are potential limitations in our study that need to be acknowledged. Collinearity could have been an issue, although we tried to avoid this by excluding variables with similar construct, such as poverty and extreme poverty indicators. Sample size constraints could also explain the lack of influence of some variables on stunting reduction, particularly those related to specific RMNCH interventions such as coverage of vaccines and coverage of care-seeking for pneumonia. Possible relevant interactions between variables cannot be ruled out, although they are not easy to measure. Also, variables measuring quality of care could be better suited to identify actual effects on health in mixed effects regression models such as the one we used. Finally, there is the possibility that our model may need additional refinement to better capture the complex network of interacting variables of different dimensions that may influence stunting in under-five children.
We think that future studies at sub-national level should consider using a combination of quantitative and qualitative approaches that take into account the complex role of social, political, policy, financial, and technical aspects underlying the implementation of specific nutritional and proximal interventions more directly related to stunting. Such an approach will need significant improvement of availability, completeness and accuracy of departmental level data collected on a routine basis and through periodic surveys. Specifically, we suggest that DHS and other relevant surveys should include variables measuring quality of services provided rather than merely measuring quantity, such as quality of antenatal care visits and quality of birth attendance. It is encouraging that this is already happening in Peru, where DHS has incorporated recently quality indicators for interventions such as obstetric functionality and solving capacity of health facilities, quality of antenatal care visits, and quality of healthy child monitoring visits [
41,
42].
In addition, further strengthening of regional and local political, managerial and technical capabilities will be needed, to facilitate both effective crosscutting implementation of interventions and a fully functional monitoring and evaluation system, so as to ensure a sustained stunting reduction, with continued focus on the poorest areas of the country.
Acknowledgements
The authors are grateful to Cesar G. Victora and Maria Clara Restrepo-Méndez from the Federal University of Pelotas, for their technical support during the entire research project.