ISSN 1842-4562
Member of DOAJ

Does Economic Status Matter for the Regional Variation of Malnutrition-Related Diabetes in Romania? Temporal Clustering and Spatial Analyses



Malnutrition-related diabetes, Time series clustering, Spatial clustering, Spatial-lag model, County


Among the different types of diabetes, in Romania the malnutrition-related diabetes displays the highest territorial inequality. In this paper, we combined two types of statistical tools, temporal clustering and spatial analysis, to find some relevant patterns in its territorial distribution. Firstly we conducted a time series clustering for the 41 counties and Bucharest Municipality, over 2007-2014, based on CORT and ACF dissimilarity distances and choose four clusters in each case. Within each cluster the evolution of malnutrition diabetes is similar. The clusters were then included as dummy variables in a spatial model testing the determinants of malnutrition-related diabetes incidence at county level. Malnutrition-related diabetes is a disease that might be linked to the economic status, therefore GDP per capita and average wage have been tested and found significant as factors of influence in various model specifications. The dummies representing the temporal clusters are also significant determinants of the regional incidence of malnutrition-related diabetes in Romania. We found that when introducing the cluster dummies in the spatial model, it becomes less appropriate than classic OLS regression, which suggests that temporal clusters were able to capture the spatial dependence in our data. The contribution of our work is three folded. First, we applied time series clustering in R and in doing so we added a real – data application to this scarce stream of literature. Secondly, we combined two techniques relatively new in Romanian data: spatial analysis and time series clustering. Last, but not least, we discussed the malnutrition – related diabetes, mellitus, as a possible proxy of poverty, and tried to advocate our claim by relating this disease’s territorial distribution with some economic variables.