EFFECTS OF AI-BASED NUTRITIONAL PLANNING (ABNP) ON BODY COMPOSITION AND WEIGHT MANAGEMENT AMONG COLLEGE STUDENT ATHLETES

Abstract

This study investigated the effects of AI-based nutritional planning on body composition and weight management among college student athletes in District Dera Ismail Khan, Khyber Pakhtunkhwa, Pakistan. Artificial intelligence is increasingly being used in sports nutrition to provide personalized dietary guidance based on individual health and performance data. A quantitative correlational research design was adopted, and data were collected from three hundred college student athletes selected through stratified random sampling. A structured questionnaire based on a five-point Likert scale was used to measure AI nutritional planning, body composition, and weight management. The reliability of the instrument ranged from zero point eight six to zero point nine zero, indicating good to excellent internal consistency. Data were analyzed using SPSS through descriptive statistics, Pearson correlation, and simple linear regression. The results showed significant positive relationships among all variables. AI nutritional planning was moderately associated with body composition and strongly associated with weight management. Regression analysis revealed that AI nutritional planning significantly predicted both body composition and weight management, with a stronger effect on weight management. The study concludes that AI-based nutritional planning is an effective predictor of improved body composition and weight management among college athletes, particularly for weight control outcomes.