Adelphi University

03/20/2026 | Press release | Distributed by Public on 03/20/2026 10:07

Malnutrition Affects Millions of Children Worldwide. An Adelphi Professor Developed a New Framework to Address the Crisis

Published: March 20, 2026
by Lauren Bedosky, Contributing Writer
Professor of Education Pavan Antony, EdD, and fellow researchers have developed a new framework that analyzes the factors leading to child malnutrition.

Child malnutrition remains a global crisis. According to estimates from the World Health Organization, more than 150 million children under the age of 5 suffered from stunted growth, or chronic malnutrition, while over 42 million suffered from wasting-acute malnutrition-globally in 2024.

Behind these statistics, there are real consequences for health and overall quality of life. "Poor nutrition in the first years of life can cause irreversible physical and cognitive damage-it can lead to learning challenges, cognitive impairment, and it can affect the overall development of a child," said Pavan J. Antony, EdD, professor of education in the Ruth S. Ammon College of Education and Health Sciences at Adelphi University.

Resolving child malnutrition requires identifying the most significant contributing factors, which can then be used to develop effective, targeted programs. To take on that challenge, Dr. Antony and his research team created a novel scoring framework, which was published in the article "RISE: a novel unified framework for feature relevance in malnutrition analytics integrating statistical and expert insights" in Frontiers in Public Health (October 15, 2025).

Bridging the Gap Between Data and Reality

RISE (Relevance-based Integration of Statistics and Expertise) is a scoring system that prioritizes the most important factors driving malnutrition in children ages 0 to 23 months. While earlier frameworks relied solely on machine learning to identify these determinants, RISE integrates real-world data from the Nutrition Rehabilitation Centre at KR District Hospital in Mysore, India.

Machine learning models play a valuable role, but they often prioritize variables that improve prediction performance yet overlook social realities. "You're not only relying on numbers-you're also giving importance to real-world clinical experiences and established scientific evidence to interpret the findings," Dr. Antony said.

RISE combines three layers of analysis to create its scoring system. First, researchers took hospital records from 206 children admitted to the Nutrition Rehabilitation Centre between March 2024 and January 2025 who had been identified with moderate or severe acute malnutrition. Those records included data on 22 variables across three categories: child information, maternal information, and socio-demographic information. Then, researchers ran those variables through four statistical filter methods and a machine learning model.

"Instead of trusting one single method or one computer model, it combines three different ways of checking and identifying to find a balanced answer to the question of what leads to malnutrition," Dr. Antony said.

What the Framework Found

With the scoring system in place, a clearer picture of what drives child malnutrition began to emerge.

The framework identified child anthropometry-weight, height, and mid-upper arm circumference-as the most influential determinant of child malnutrition. But the second-ranked factor was less expected and had been overlooked by traditional scoring models: the mother's physical health and social status, including breastfeeding practices, employment, weight, height and even caste. The child's birth order was the third most influential factor, with more than 56 percent of malnourished children being second-born or later, suggesting that resources become increasingly stretched as the family grows.

This hierarchy of factors highlights a dual burden: the child's current physical growth status and the mother's nutritional condition together strongly shape malnutrition outcomes.

From Research to Real-World Impact

The framework highlights that child malnutrition is not caused by a single factor-and that there is no single solution. Moreover, the determinants of child malnutrition depend highly on region: According to Dr. Antony, "in countries like India, there are rural-urban differences-local food practices, sanitation, family structure-these all affect contributing factors."

By identifying region-specific factors that contribute to child malnutrition, RISE offers decision-makers in government and nongovernmental organizations clear, data-informed direction on where to direct limited resources.

It is also important to consider how those interventions are delivered. "I was in India for another study, and while people in some remote communities didn't have access to some basic needs such as proper housing or toilets, they had televisions and cellphones," Dr. Antony said. "So can we use cellphones as a tool and send small messages or small clips to educate people in the community?"

Next Steps to Resolving Child Malnutrition

Now that Dr. Antony and his research team have identified key factors driving childhood malnutrition, they are collaborating with clinicians in Mysore, India, to align the RISE framework with public health programs.

The RISE framework can also be replicated in other parts of the world-provided it's culturally responsive. "What works in India might not work in another region," Dr. Antony said. "But can the framework be modified? Absolutely yes."

Regardless of what form the framework takes, the global issue of child malnutrition demands a solution. While governments and international organizations continue to implement policies and programs, tens of millions of children worldwide continue to suffer from wasting and stunted growth.

"Child malnutrition is something that is preventable-it can be addressed in communities," Dr. Antony said. "You're talking about a new generation. This is something happening to children that can be controlled, but we are not doing enough."

Adelphi University published this content on March 20, 2026, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on March 20, 2026 at 16:07 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at [email protected]