Journal of Nutrition & Food Sciences
Open Access

Machine learning algorithms for predicting undernutrition among under-five children in Ethiopia

3^rd World Summit on Food and Nutrition

August 24-25, 2022 | Webinar

Fikrewold H Bitew, Corey S Sparks and Samuel H Nyarko

University of Texas, USA

Scientific Tracks Abstracts: J Nutr Food Sci

Abstract :

Back ground: Child undernutrition is a global public health problem with serious implications. In this study, we estimate predictive algorithms for the determinants of childhood stunting by using various machine learning (ML) algorithms. Design: This study draws on data from the Ethiopian Demographic and Health Survey of 2016. Five ML algorithms including eXtreme gradient boosting, k-nearest neighbours (k-NN), random forest, neural network and the generalised linear models were considered to predict the socio-demographic risk factors for undernutrition in Ethiopia. Conclusions: This study shows considerable regional variations in childhood undernutrition and how commonly used ML algorithms could be applied to predicting child stunting, wasting and underweight determinants in Ethiopia. The findings show that the xgbTree algorithm offers better predictive accuracy than the traditional algorithm GLM. Furthermore, the best-predicting ML algorithm has shown diverse combinations of important predictors for stunting, wasting and underweight, even though there are a few common top-five predictors among them. The algorithms may, therefore, be useful to child nutrition and other population health researchers, and aid workers among Predicting child undernutrition in Ethiopia other stakeholders, particularly where large data areavailable. The study, thus, provides evidence on how the ML approach can be leveraged to better predict the underlying risk factors of childhood undernutrition among other population health outcomes. This may create a better understanding of a child’s nutritional status and help to develop more effective policies to advance childhood nutritional status in the country. The findings reinforce the need for committed efforts to improve upon access to potable water supply and food security, as well as the Socio-economic wellbeing of women in Ethiopia. There is also the need for policies and interventions to put special focus on children of small birth size, children who are over 30 months old and children of underweight mothers.