Examining the Impact of Macronutrient Composition on Caloric Value: A Structural Equation Modeling (SEM) Approach

Abstract

This study examined the impact of macronutrient composition on the caloric value of food items using a Structural Equation Modeling (SEM) approach· The research aimed to fill a gap in the literature by analyzing the combined effects of carbohydrates, proteins, and fats on caloric content, rather than focusing on individual macronutrients in isolation· Data were sourced from the Food Nutrition Dataset, which provided detailed nutritional information on a wide range of food items· The SEM analysis revealed that fats had the largest impact on caloric value, followed by proteins and carbohydrates· The study found that while fats contributed significantly to the overall caloric content, proteins and carbohydrates also played crucial roles· The findings underscored the importance of considering the synergistic effects of macronutrients when estimating caloric value· Practical applications of this research included aiding dietitians in designing balanced meal plans, helping food manufacturers optimize product formulations, and informing public health policies aimed at managing caloric intake· The study concluded that understanding the relationship between macronutrient composition and caloric value is essential for nutritional science, dietary guidelines, and public health interventions·