Multifactorial Analysis of Chronic Energy Deficiency in Adolescent Girls: Innovative RF-AR App for Early Detection and Effective Intervention

Introduction: Chronic Energy Deficiency (CED) in adolescent girls remains a significant public health concern influenced by various interrelated factors. This study aimed to analyze the multifactorial determinants of CED and to develop an innovative health intervention using the RF-AR application for early detection and effective management.Methods: An observational analytic study with a cross-sectional design was conducted involving adolescent girls from diverse socioeconomic and geographic backgrounds. Data were collected through structured surveys. Multifactorial analysis encompassed genetic, environmental, lifestyle, and psychological factors. The data were analyzed using univariate, bivariate, and multivariate approaches to identify significant predictors of CED.Results: The study revealed that poor nutritional intake, limited access to health information, and low socioeconomic status were significantly associated with higher rates of CED among adolescent girls. The multifactorial model underscored the complexity of CED etiology. Additionally, the RF-AR application demonstrated potential as a supportive tool for early screening and individualized intervention planning.Conclusions: The findings confirmed that adolescent girls with inadequate nutrient intake are at a greater risk of developing CED. A multifactorial intervention strategy, supported by technological tools like the RF-AR app, offers a promising approach to early detection and effective prevention of CED at a broader scale.