PANEL 4.2 REGIONAL DRIVERS OF MALNUTRITION IN INDONESIA ENDANG ACHADI WITH ACKNOWLEDGMENT TO SUDARNO SUMARTO AND TAUFIK HIDAYAT
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ndonesia faces a paradox: national gross domestic product (GDP) per capita has grown steadily—from US$1,643 in 2006 to US$3,592 in 2012 (Statistics Indone- sia 2014)—but undernutrition has declined only slowly and obesity and overweight are increasing rapidly. Indonesia is marked by a high degree of geographic, and consequently economic, variation, depending on the district examined. Is this one of the factors driving variation in nutrition outcomes by district? A study by Sumarto et al. (2013) analyzed factors associated with Indonesia’s successful national poverty reduction at the district level in the context of decentralization. The data show that poverty incidence is lower in dis- tricts with higher GDP per capita, higher fiscal revenues as a share of GDP, higher average educational attainment, a larger share of local leaders with secondary education (as a proxy
for local capacity), a higher degree of urban- ization, and local offices for coordinating pov- erty reduction initiatives. We examined the relationship of these
same variables with childhood stunting, a marker of chronic undernutrition, using the Riskesdas National Basic Health Survey (Indonesia, Ministry of Health 2008). Risk- esdas 2007 nutrition data were matched with socioeconomic data for 2005–2010. Our preliminary analysis of 345 districts and municipalities finds results consistent with the Sumarto et al. (2013) study. Stunting prev- alence at the district level is associated with low GDP per capita, a larger share of local leaders with no or low levels of education, and low levels of urbanization.
Another factor in the persistence of the
variation in stunting among districts might be the decentralization of government functions
since 2000. Some have argued that Indonesia implemented decentralization using a radi- cal approach (Hofman and Kaiser 2002) and without a comprehensive policy (World Bank 2005). This may have led to less than optimal shifting of responsibilities and accountabilities from the central to the district level, poten- tially contributing to variations in the quality of nutrition services.
When looking at malnutrition data, it is important to take into account the local con- text: geography, local governance, socioeco- nomic status, demography, and educational attainment. In Indonesia, these dimensions vary strongly by district. Thus, ensuring better planning of health and nutrition programs requires looking deeply at district-level data, not just national data.
identify accountabilities, highlight data gaps, and strategize about action (Panel 4.3). The work so far has highlighted data gaps and incompatibilities, but also the availability of data that had not previously been brought into nutrition analyses.
Equity
As equity has moved up the global development agenda (Haddad 2014), equity gaps in nutrition have increasingly been highlighted (for example, Black et al. 2013). Malnourished children in the poorest income groups may need extra help from public finances given the limited private means they and their families have at their disposal. These children are most likely to face multiple deficits when it comes to intervention coverage and underlying drivers of malnutrition.
Figure 4.1 shows differences in stunting and overweight outcomes by household wealth quintile. Countries with wide disparities in stunting rates between the highest and lowest quintiles are found throughout the range of stunting prev- alences. The wealth disparities in overweight rates are less pronounced but with no obvious pattern to the differences: in many countries the lowest quintile has higher rates of under-five overweight than the highest quintile.
There are large disparities in stunting outcomes by wealth quintile, but as stunting rates decline, are these disparities wid- ening? One of the most comprehensive wealth-based studies is
26 GLOBAL NUTRITION REPORT 2014
a recent analysis of data from 52 countries from the mid-1990s to the mid- to late 2000s (Bredenkamp et al. 2014). The study concludes that for 30 of the 52 countries there is no statistically significant evidence that stunting outcomes are becoming more or less unequal across wealth groups within countries. For 11 countries stunting equity is increasing, and for a different set of 11 countries stunting equity is decreasing (Table 4.4). The au- thors report no obvious relationship between trends in stunting prevalence and trends in stunting inequality.
Equity is not only about wealth. Discrimination can have geographic, historical, and cultural roots that often manifest themselves in different cultural identities. This poses challenges for programming in the presence of different norms, different trust levels, and different ways of influencing behavior. Panel 4.4 draws some lessons from nutrition interventions within US Native American populations, who make up a marginalized group.
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