Abstract
AimsMalnutrition is a major health issue among Bangladeshi under-five (U5) children. Children are malnourished if the calories and proteins they take through their diet are not sufficient for their growth and maintenance. The goal of the research was to use machine learning (ML) algorithms to detect the risk factors of malnutrition (stunted, wasted, and underweight) as well as their prediction.MethodsThis work utilized malnutrition data that was derived from Bangladesh Demographic and Health Survey which was conducted in 2014. The selected dataset consisted of 7079 children with 13 factors. The potential risks of malnutrition have been identified by logistic regression (LR). Moreover, 3 ML classifiers (support vector machine (SVM), random forest (RF), and LR) have been implemented for predicting malnutrition and the performance of these ML algorithms were assessed on the basis of accuracy.ResultsThe average prevalence of stunted, wasted, and underweight was 35.4%, 15.4%, and 32.8%, respectively. It was noted that LR identified five risk factors for stunting and underweight, as well as four factors for wasting. Results illustrated that RF can be accurately classified as stunted, wasted, and underweight children and obtained the highest accuracy of 88.3% for stunted, 87.7% for wasted, and 85.7% for underweight.ConclusionThis research focused on the identification and prediction of major risk factors for stunting, wasting, and underweight using ML algorithms which will aid policymakers in reducing malnutrition among Bangladesh’s U5 children.
Highlights
Malnutrition is one of the most serious health and welfare issues in any developing country, including Bangladesh
This research focused on the identification and prediction of major risk factors for stunting, wasting, and underweight using machine learning (ML) algorithms which will aid policymakers in reducing malnutrition among Bangladesh’s U5 children
We have considered three types of response variables as stunted, underweight, and wasted, which were measured based on height-for-age Z-score (HAZ), weight-for-height Z-score (WHZ), and weight-for-age Z-score (WAZ)
Summary
Malnutrition is one of the most serious health and welfare issues in any developing country, including Bangladesh. Malnutrition is a general term that refers to two distinct conditions as under-nutrition and overweight. Undernutrition includes stunting, wasting, and being underweight, whereas overweight/obesity is associated with a number of non-communicable diseases (diabetes, cancer, stroke, and heart disease) [1,2,3]. According to the WHO, approximately 1.9 billion adults worldwide were overweight, while 462 million were underweight. It was noted that there were 47 million wasted U5 children, 14.3 million severely wasted, and 144 million stunted children, with 38.3 million overweight/obese children. 2.6 million children die per year due to malnutrition and 45% of U5 deaths were due to under-nutrition [4, 5]
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