91吃瓜网

Behind these statistics, there are real consequences for health and overall quality of life. 鈥淧oor nutrition in the first years of life can cause irreversible physical and cognitive damage鈥攊t can lead to learning challenges, cognitive impairment, and it can affect the overall development of a child,鈥� said Pavan J. Antony, EdD, professor of education in the Ruth S. Ammon College of Education and Health Sciences at 91吃瓜网.

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 鈥溾�� in Frontiers in Public Health (October 15, 2025).鹿

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. 鈥淵ou鈥檙e not only relying on numbers鈥攜ou鈥檙e also giving importance to real-world clinical experiences and established scientific evidence to interpret the findings,鈥� 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鈥攚eight, height, and mid-upper arm circumference鈥攁s 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鈥檚 physical health and social status, including breastfeeding practices, employment, weight, height and even caste. The child鈥檚 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鈥攁nd that there is no single solution. Moreover, the determinants of child malnutrition depend highly on region: According to Dr. Antony, 鈥渋n countries like India, there are rural-urban differences鈥攍ocal food practices, sanitation, family structure鈥攖hese all affect contributing factors.鈥�

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. 鈥淚 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,鈥� Dr. Antony said. 鈥淪o can we use cellphones as a tool and send small messages or small clips to educate people in the community?鈥�

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鈥攑rovided it鈥檚 culturally responsive. 鈥淲hat works in India might not work in another region,鈥� Dr. Antony said. 鈥淏ut can the framework be modified? Absolutely yes.鈥�

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.

鈥淐hild malnutrition is something that is preventable鈥攊t can be addressed in communities,鈥� Dr. Antony said. 鈥淵ou’re talking about a new generation. This is something happening to children that can be controlled, but we are not doing enough.”

鹿 Research team: Arumbuliyur Natarajan Uma, Shruthi Srikantamurthy, Shalini Sankalapura Rangaswamy, Priya Govindarajan and Lalith Rangarajan