to 39% in 2006), and important reductions in open defecation (17% in 1990 to 2% in 2011) and in extreme poverty, with the proportion of the population living on <2 USD per day dropping from 21 to 5% over the same period [2]. Despite these promising cases, many countries are not on track to reach global targets of stunting and wasting reduction and no increase in overweight [7]. Unfortunately, well over 100 countries have no data to adequately track such targets [7].
Even where data exist, tracking national progress often masks substantial disparity of malnutrition in children within countries. A recent publication from India illustrates this issue dramatically. Using stunting prevalence data by district from a 2015 to 2016 survey, the authors illustrate the dramatic variation in stunting prevalence across India (Fig. 2) [25]. The variation between districts with the highest (>40%) and lowest (<20%) rates of stunting was explained by several maternal factors (low BMI, marriage <18 years of age, antenatal care), adequacy of the child diet, several demographic and economic factors (10+ years of schooling, household size, and assets), while 29% of the variation remained unexplained. This has important implications for policy and programmatic responses that must consider the severity of the issues and the diversity across regions of the underlying determinants.
While many countries lack data to assess variability of prevalence disaggregated to this level, several factors that strongly predict disparity in the prevalence of malnutrition are well documented. For example, globally and in all regions, children living in the poorest households are at least twice as likely to be stunted than the richest [9]. In Latin America and the Caribbean, the prevalence of stunting among poor families (30%) is 4.3 times higher than that among the richest (7%). Similar analyses to explore the prevalence of overweight in children among diverse population subgroups within countries have not yet been compiled at global level. Several publications suggest, however, that overweight among children, while once concentrated among the non-poor, may no longer track economic boundaries as stunting does (see for example [26]).
Fig. 2. Diversity in the prevalence of childhood stunting by district in India, using data from 2015 to 2016, reproduced from [25]. NFHS, National Family Health Survey.
Understanding the Etiology of Malnutrition
The determinants of undernutrition are well documented and have been recently updated to incorporate all forms of malnutrition [2]. Immediate causes include health-related behaviors (e.g., diet, activity, hygiene) and biological factors (e.g., disease state, genetics). Underlying these are several household- and community-level factors that facilitate or limit a household’s ability to provide health, care, and a quality diet, such as access to food and health care, social norms related to care and feeding, and the living environment (e.g., built spaces and water and sanitation services). These factors are in turn affected by income and inequality, trade, urbanization, existence of social protection and health systems, and agricultural development, among other factors. Finally, the extent to which such factors may favor nutrition depends on an enabling environment of political commitment, effective governance, and capacity. As illustrated above in the case of Brazil, progress to address malnutrition has typically been better when policies and programs address such determinants simultaneously, accompanied by economic growth [2].
Fig. 3. Conceptual framework on the determinants of child growth. Developed by the authors building on previously published frameworks [27, 28]. IUGR, Intra-uterine growth retardation; NCDs, Non-communicable diseases.
Stunting
Building on prior frameworks [27, 28], Figure 3 shows known determinants of child stunting organized along a simplified pathway. Being born small, unimproved sanitation, and diarrhea are important risk factors for stunting globally and particularly in South Asia [29]. Low maternal height and household wealth are also important predictors in South Asia [30]. The relationships between stunting and its determinants as well as their relative importance can vary substantially by context, even within a single country, as illustrated previously in India [27]. Within-country diversity in the drivers of stunting has also been documented in Vietnam [28]. Effective action to accelerate progress to address stunting may require interventions tailored to address these determinants, the composition of which may vary by geography or other factors. Path analyses of linear growth faltering using longitudinal data can also help identify where and how to intervene across the range of basic to immediate causes of stunting [31]. While data may be limiting in some contexts, in others, existing data have not been used to its full potential to document and understand the many determinants of child malnutrition and their variability by geographic or other factors like those from India and Vietnam. Longitudinal datasets are particularly powerful for understanding determinants but are rare and usually do not have sufficient geographically representation to explore variability within countries.
Anemia
As noted above, anemia continues to be the only indicator tracked consistently at a national level and used as a proxy for micronutrient status, and it is often interpreted as synonymous with iron deficiency. The determinants of anemia, however, include a complex pattern of biological, infectious, environmental, and genetic factors [32]. Anemia may be related to inadequate intakes of iron, folic acid, vitamin A, and/or vitamin B12. Conditions that cause increased loss or reduced absorption or utilization of iron such as soil-transmitted helminths, malaria, schistosomiasis, and other parasitic infections may also result in anemia, even if intakes appear adequate. Finally, genetic disorders that affect iron or hemoglobin metabolism also result in anemia.
Particularly in low- and middle-income countries, several risk factors may simultaneously cause anemia in an individual. For instance, in sub-Saharan Africa, malaria and iron deficiency are both highly prevalent. In these cases, common approaches to prevent and treat anemia, such as iron supplementation, may not be effective, and recent evidence suggests that iron supplementation may even exacerbate infection. In a study of children living in malaria-endemic Tanzania, prophylactic iron supplementation increased the risk of hospitalization, death, malaria, and other infections among those who were not iron deficient [33].
