The presence of simultaneous under- and over-nutrition has been widely documented in low- and middle-income countries, but global nutritional research has seen only a few large-scale population studies from Indonesia. We investigate the social determinants as well as the geographical variations of under- and over-nutrition in Indonesia using the largest public health study ever conducted in the country, the National Basic Health Research 2007 (N=645,032). Multilevel multinomial logistic regression and quantile regression models are fitted to estimate the association between nutritional status and a number of socio-economic indicators at both the individual and district levels. We find that: (1) education and income reduce the odds of being underweight by 10–30% but at the same time increase those of overweight by 10–40%; (2) independent from the compositional effect of poverty, income inequality is detrimental to population health: a 0.1 increase in the Gini coefficient is associated with an 8–12% increase in the odds of an individual׳s being both under- and overweight; and (3) the effects that these determinants have upon nutritional status are not necessarily homogeneous along the continuum of body mass index. Equally important, our analysis reveals that there is substantial spatial clustering of areas with elevated risk of under- or over-nutrition across the 17,000-island archipelago. As of 2007, under-nutrition in Indonesia remains a ‘disease of poverty’, while over-nutrition is one of affluence. The income inequality accompanying Indonesia׳s economic growth may aggravate the dual burden of under- and over-nutrition. A more equitable economic policy and a policy that improves living standards may be effective for addressing the double burden.

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The notion of poverty as an experience of multiple deprivation has been widely acknowledged. In Indonesia, however, poverty assessment has almost exclusively been conducted within the monetary space; even when multidimensionality is admitted, it has always been computed using variants of marginal method that are indifferent to joint deprivation. Applying a novel measurement method that is sensitive to both the incidence and the intensity of multiple deprivation to data from the National Socio-economic Survey (Susenas), this paper investigates the extent and the patterns of multidimensional poverty in Indonesia from 2003 to 2013 (). An Indonesian version of the multidimensional poverty index is constructed by augmenting the existing consumption poverty measure with information on health and education. Results suggest that there was an unambiguous poverty reduction over the last decade at both national and sub-national levels. The data also reveal that progress has been inclusive across population subgroups, although spatial variation remains notable. The new poverty measurement method proves to be easily adaptable to the Indonesian context and could complement the methods currently employed by the Indonesian Statistical Bureau.

BackgroundDespite being one of the world’s most affected regions, only little is known about the social and spatial distributions of malaria in Indonesian Papua. Existing studies tend to be descriptive in nature; their inferences are prone to confounding and selection biases. At the same time, there remains limited malaria-cartographic activity in the region. Analysing a subset (N = 22,643) of the National Basic Health Research 2007 dataset (N = 987,205), this paper aims to quantify the district-specific risk of malaria in Papua and to understand how socio-demographic/economic factors measured at individual and district levels are associated with individual’s probability of contracting the disease.MethodsWe adopt a Bayesian hierarchical logistic regression model that accommodates not only the nesting of individuals within the island’s 27 administrative units but also the spatial autocorrelation among these locations. Both individual and contextual characteristics are included as predictors in the model; a normal conditional autoregressive prior and an exchangeable one are assigned to the random effects. Robustness is then assessed through sensitivity analyses using alternative hyperpriors.ResultsWe find that rural Papuans as well as those who live in poor, densely forested, lowland districts are at a higher risk of infection than their counterparts. We also find age and gender differentials in malaria prevalence, if only to a small degree. Nine districts are estimated to have higher-than-expected malaria risks; the extent of spatial variation on the island remains notable even after accounting for socio-demographic/economic risk factors.ConclusionsAlthough we show that malaria is geography-dependent in Indonesian Papua, it is also a disease of poverty. This means that malaria eradication requires not only biological (proximal) interventions but also social (distal) ones.