Abstract

The persistent malnutrition crisis among children in India remains a cause for significant concern. In the face of rapidly advancing technology, ensuring access to essential nutrients for every child becomes an achievable goal. This chapter delves into the nutritional factors contributing to impaired growth in children and proposes targeted interventions for the Indian context. Utilizing data from the Indian Demographic and Health Survey (2015–16) focusing on underprivileged children aged two to five years, three malnutrition outcome measures height-for-age, weight-for-height, and weight-for-age were calculated according to WHO standards. Binary and multinomial logistic regression models reveal three key findings. Firstly, the study emphasizes the substantial impact of child anaemia on the risk of malnutrition in various forms. As a potential solution, the study suggests the integration of new Artificial Intelligence (AI) applications, such as the Anaemia Control Management (ACM) software, to enhance routine clinical practices in managing child anaemia. Secondly, recognizing the crucial role of dietary diversity in promoting a child's linear growth, the chapter advocates for the adoption of AI-based food and nutrient intake assessment systems. This includes platforms such as FatSecret and GoCARB for comprehensive nutritional evaluations of diets. Lastly, the results underscore the heightened risk of stunted growth in children due to the limited effectiveness of the Anganwadi/ICDS programme for lactating mothers. The integration of an AI-based virtual assistant application, such as Momby, within the Anganwadi/ICDS programme is proposed to improve access to health services and information for mothers, particularly those facing challenges in accessing essential pre- and postnatal care. Overall, the findings emphasize the imperative need to strategically implement AI as an advanced approach to address malnutrition stemming from nutritional deficiencies and associated health issues.