Double burden of malnutrition in Nepal: A trend analysis of protein-energy malnutrition and High Body Mass Index using the data from Global Burden of Disease 2010–2019

Abstract

Background The co-existence of undernutrition and overnutrition is a global public health threat. We aim to report the burden of both nutritional deficiency (Protein-Energy Malnutrition) and overweight (high Body Mass Index) in Nepal over a decade (2010–2019) and observe the changes through trend charts. Methods We did a secondary data analysis using the Institute for Health Metrics and Evaluation (IHME)’s Global Burden of Disease (GBD) database to download age-standardized data on Protein Energy Malnutrition (PEM) and high Body Mass Index (BMI). We presented the trend of death, Disability Adjusted Life Years (DALYs), Years of Life Lost (YLL), and Years Lost due to Disability (YLD) of PEM and high BMI in Nepal from 2010 to 2019 and also compared data for 2019 among South Asian countries. Results Between 2010 and 2019, in Nepal, the Disability Adjusted Life Years (DALYs) due to PEM were declining while high BMI was in increasing trend. Sex-specific trends revealed that females had higher DALYs for PEM than males. In contrast, males had higher DALYs for high BMI than females. In 2019, Nepal had the highest death rate for PEM (5.22 per 100,000 populations) than any other South Asian country. The burden of PEM in terms of DALY was higher in under-five children (912 per 100,000 populations) and elderly above 80 years old (808.9 per 100,000 populations), while the population aged 65–69 years had the highest burden of high BMI (5893 per 100,000 populations). In the last decade, the DALYs for risk factors contributing to PEM such as child growth failure (stunting and wasting), unsafe water, sanitation and handwashing, and sub-optimal breastfeeding have declined in Nepal. On the contrary, the DALYs for risk factors contributing to high BMI, such as a diet high in sugar-sweetened beverages, a diet high in trans fatty acid, and low physical activity, have increased. This could be a possible explanation for the increasing trend of high BMI and decreasing trend of PEM. Conclusion Rapidly growing prevalence of high BMI and the persistent existence of undernutrition indicate the double burden of malnutrition in Nepal. Public health initiatives should be planned to address this problem.

A Deep Learning Approach for Malnutrition Detection

“…AdamW handles weight decay more effectively than Adam and RMSProp. Figures 4,6 In Figures 10, 11, and 12, it is evident that the misclassification rates for learning rates 0.1, 0.01, and 0.001 are notably higher when compared to the misclassification rate associated with a learning rate of 0.0001 for the Adamax, AdamW, and RMSprop optimizers. Specifically, when utilizing a learning rate of 0.0001, ResNet-18 misclassifies 62, 54, and 57 instances with the Adamax, AdamW, and RMSprop optimizers, respectively, resulting in misclassification rates of 13.77%, 10.8%, and 12.52%.…”

“…The Puskesmas Ubung dataset was used to test the model [16]. A decision tree that made use of the Gini index metric was created in order to address problems associated with Protein-Energy Malnutrition (PEM), which results in stunting, wasting, and underweight in babies [6].…”

“…It is observed that, in most children, low to moderate malnutrition affects their growth and development at early ages. Diagnosing malnutrition at an early age reduces healthcare expenses and helps in maintaining good health [6]. In literature, several works have attempted to classify children in the categories ranging from malnourished to nourished based on machine learning (ML) algorithms.…”

Secular trends and sociodemographic determinants of thinness, overweight and obesity among Chinese children and adolescents aged 7–18 years from 2010 to 2018

“…These effects of globalization may slow progress in reducing undernutrition while increasing risk factors for overnutrition. Malnutrition in this study refers to thinness, and DBM has now been identified in many developing countries ( 5 – 9 ), including China, and it is critical to explore the current state of development and the drivers of DBM.…”

“…Therefore, attention to the nutritional statuses of school-aged children and adolescents and the imposition of appropriate interventions are essential for their healthy transition to adulthood. Thinness was associated with premature mortality, physical suboptimal health, impaired neurocognitive function, and low productivity ( 9 – 11 ), and mortality and morbidity were 9–11 times higher in children with severe malnutrition than in well-nourished children ( 12 ); obesity in children and adolescents was associated with the development of ischemic heart disease ( 13 ), type II diabetes, respiratory disease, and psychological and social problems ( 14 , 15 ) and had a strong tracking effect in adulthood ( 16 ). In addition, lifestyle changes such as less sleep time and physical activity and longer screen time in children and adolescents have been reported worldwide in recent years ( 17 – 20 ) and have played a negative role in the prevention and control of overweight and obesity.…”