Geographic Inequities in Youth Obesity – The Role of AI and Digital Innovation

Jay Tamirisa, Mia Jose and Dr. Praveen Kumar
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Jay Tamirisa: Internal Medicine and Cardiology Consultant, USA
Mia Jose: Internal Medicine and Cardiology Consultant, USA
Dr. Praveen Kumar: Internal Medicine and Cardiology Consultant, USA

International Journal of Research and Scientific Innovation, 2024, vol. 11, issue 12, 1026-1035

Abstract: Objective(s) Youth obesity is a global public health crisis, with rates quadrupling from 1990 to 2022 among both boys and girls, according to the Non-Communicable Disease Risk Factor Collaboration. Obesity among youth contributes to rising healthcare costs due to obesity-related conditions like diabetes and hypertension. Moreover, youth obesity negatively impacts mental health and academic performance and increases the risk of substance abuse in adulthood. This review examines the role of digital technology and artificial intelligence (AI) in preventing and managing youth obesity, highlighting its potential to close the gaps in care, regardless of geographical location. Methods This review utilized a PubMed search of articles published between 2015 – 2024, focusing on the role of digital technology and artificial Intelligence (AI) in preventing and managing youth obesity. Search terms included “youth obesity,†“digital health,†“artificial intelligence,†“machine learning,†and “childhood obesity prevention.†Articles were screened based on title, abstract, and full text, prioritizing studies on AI-powered tools, personalized interventions, and technologies addressing disparities in care. Key focus areas included neural networks, electronic health records, geographic information systems, and telemedicine platforms. For this review, “youth†refers to individuals aged 8–18 years. Findings AI and digital innovation have emerged as a transformative tool in preventing and managing youth obesity. Advanced technologies, including machine learning and neural networks, analyze vast datasets from healthcare records, nutrition surveys, and geographical information systems (GIS) to identify patterns and correlations in obesity across regions. AI systems like CHICA (Child Health Improvement through Computer Automation) integrate electronic health records to provide age-appropriate obesity screenings and data-driven decision support. Additionally, AI- powered apps and virtual coaches offer personalized, real-time nutrition and physical activity feedback. AI’s capacity to map food sectors and identify “food deserts†enables targeted interventions, while AI-driven telemedicine platforms offer remote consultations, particularly benefiting underserved regions. Conclusions By integrating AI and digital technologies, including virtual realities and telemedicine into youth obesity strategies, stakeholders can address geographical disparities, create equitable healthcare solutions, and guide personalized, region-specific interventions. Digital technology’s role in healthcare equity offers promising pathways for more effective, targeted youth obesity management in youth worldwide.

Date: 2024
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