Undernutrition is responsible for nearly half of all global deaths in children under 5 years old. The prevalence of chronic child undernutrition (stunting) at the global level stands at approximately 22%, with the highest prevalence regions being in sub-Saharan Africa and South Asia.
This project explores several multilevel approaches (e.g. spatial statistics, machine learning) to identify significant socioeconomic, demographic, cultural, climatic and environmental risk factors of child stunting from Demographic and Health Survey (DHS) datasets.
Such multilevel approaches provide a useful framework to elucidate spatially structured and significant indicators of child undernutrition that are in critical need of, and can respond well to, prioritized policy interventions.
López-Carr, D., & Mwenda, K.M., Pricope, N.G., Kyriakidis, P.C., Jankowska, M.M., Weeks, J., Funk, C., Husak, G., Michaelsen, J. (2016). Climate-Related Child Undernutrition in the Lake Victoria Basin: An Integrated Spatial Analysis of Health Surveys, NDVI, and Precipitation Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 9 (6): 2830 – 2835. DOI: 10.1109/JSTARS.2016.2569411