Factors affecting child malnutrition in Ethiopia
Ashenafi Argaw Yirga is a biostatistician and SSACAB Ph.D. Fellow based at the University of KwaZulu-Natal, in South Africa. SSACAB (the Sub-Saharan African Consortium for Advanced Biostatistical Training) is one of the eleven Developing Excellence, Leadership, and Training in Science in Africa (DELTAS Africa) programmes. DELTAS Africa funds Africa-based scientists to amplify the development of world-class research and scientific leadership on the continent while strengthening African institutions. DELTAS Africa is implemented through the AESA Platform. AESA (The Alliance for Accelerating Excellence in Science in Africa) is a funding, agenda-setting, programme management initiative of the a partnership of the African Academy of Sciences (AAS), the African Union Development Agency (AUDA-NEPAD), founding and funding global partners, and through a resolution of the summit of African Union Heads of Governments. DELTAS Africa is supported by Wellcome and the United Kingdom Foreign, Commonwealth and Development Office (FCDO formerly DFID).
Nutrition is a basic human need and right and is essential for good health. In developing countries, malnutrition is a major cause of child morbidity and mortality. In Africa, Ethiopia has one of the highest rates of child malnutrition. Mother’s age, mother’s BMI, mother’s work status, educational level of the mother, weight of the child at birth, and region (Affar, Dire Dawa, Gambela, Harari and Somali) significantly influences the nutritional status of children in Ethiopia. Therefore, policymakers need to focus on the influence of these significant factors to develop strategies that enhance the normal or healthy weight status of children in Ethiopia.
The Sustainable Development Goals aim to end all forms of hunger and malnutrition by 2030, making sure all people – especially children – have sufficient and nutritious food all year. Unfortunately, extreme hunger and malnutrition remain a huge barrier to development in many countries, with over 90 million children under five dangerously underweight. Undernourishment and severe food insecurity appear to be increasing in almost all regions of Africa.
This study sheds light on the public health challenge of child malnutrition in Ethiopia, where it is a major impact on child survival and their ability to thrive. The nutrition status of the most vulnerable age group, under five years of age, is an important outcome measure for child health. The highest rate of under-five malnutrition in the world is still in Africa, where an estimated 159 million children, approximately 24% of young children, experienced stunted growth in 2016. Even though this is a 16% decrease from the estimated 255 million malnourished young children in 1990 worldwide, the improvement is minimal as millions of children remain at risk. Because malnutrition is a cause of substantial health problems in children, reducing malnutrition in children is necessary to improve the health status of future generations, which is crucial not just for humanitarian reasons but also for economic growth and development.
Malnutrition in children is strongly tied to poor maternal nutritional status and the mother’s education. This study will inform policymakers to develop health policies aimed at reducing child mortality due to malnutrition.
Description of study
Our research analysed the 2016 Ethiopian Demographic and Health Survey (EDHS) data using an ordinal logistic regression model (OLR) to identify the predictors of child undernutrition. Based on weight-for-age anthropometric index, child nutrition status is categorized into four groups: underweight; normal; overweight; and obese. Since this leads to an ordinal variable for nutritional status, an OLR model was used for data analysis. Anthropometric measurements are a series of quantitative measurements of the muscle, bone, and adipose tissue used to assess the composition of the body.
The primary purpose of the study was to use a sound statistical method that takes into account the ordered nature of nutritional status from underweight to obese, and identify the determinants of under-five’s nutritional status as a function of age and other relevant factors. Thus the OLR statistical model takes account of the inherent natural ordering of the level of nutrition and makes full use of inherent information. This approach is more informative than just dealing with a binary outcome of whether a child is malnourished or not.
Thus, the study adapts this statistical model to identify risk factors associated with child malnutrition in Ethiopia. Ethiopia is among the countries with the highest rates of stunting in Africa. The proportion of underweight children is highest in the age range of two to three years (34%) and lowest among those under six months (10%). Twenty-nine percent of Ethiopian children under age five are underweight, and 9% are severely underweight.
Outcome of study
Study results reveal that for children under the age of five, the weight of a child at birth, mother’s age, mother’s Body Mass Index (BMI), marital status of mother and region (Affar, Dire Dawa, Gambela, Harari and Somali) influence significantly the nutritional status of children under age five in Ethiopia.
The effects of the key determinants of nutrition in the children studied can be used to develop strategies for reducing child malnutrition in Ethiopia. Moreover, these findings show that the OLR proportional odds model is appropriate for assessing the determinants of malnutrition for the ordinal nutritional status of under-five children in Ethiopia.
The study also accounted for certain socio-economic and environmental factors. Further research is needed to determine the impacts of specific socio-economic and environmental factors and how they affect the malnutrition status of these children. Further study will consider more flexible statistical approaches spatial-temporal analysis, and other advanced statistical models to better understand risk factors associated with stunting, and malnutrition for children under 5 years of age. In addition, we will try to identify the trends of malnutrition status of this group of children using the available EDHS survey results.