{'fraction_non_alphanumeric': 0.04503367003367004, 'fraction_numerical': 0.026936026936026935, 'mean_word_length': 4.898263027295285, 'pattern_counts': {'":': 0, '<': 2, '<?xml version=': 0, '>': 1, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The Relationships Between Real Time Energy Balance , Hunger , and Body Composition

The Relationships Between Real Time Energy Balance, Hunger, and Body Composition Delk A, Benardot D, Nucci A, & Thompson WR. Georgia State University Introduction: Previous research has indicated that hunger is associated with the quantity, volume, and macronutrient composition of food intake. Hunger has never been assessed from the viewpoint of real time energy balance, although there is limited research on hunger and eating frequency. Purpose: The purpose of this study was to evaluate the relationships between real time energy balance, hunger, and body composition in college students between the ages of 18-30. Methods: Participants were assessed for body composition using a Tanita scale and energy balance was determined on an hourly basis using NutriTiming® software. A hunger scale was used to assess participant hunger every hour. Results: There is a statistically significant relationship for the entire population between energy balance average and body fat percent (R= -0.376; P=0.037). Hours spent in energy deficient is positively associated with body fat percent (R=0.467; P=0.008), while hours spent in an optimal energy balance is negatively associated with body fat percent (R= -0.465; P=0.009). Hours spent in an energy balance surplus (+400 kcals) were not significantly associated with body fat percent. However, hours spent in an anabolic state (>0 kcals) was negatively associated with body fat percent (R=-.457; P=.010). Conversely, hours spent in a catabolic state (<0 kcals) were positively associated with body fat percent (R=.457; P=0.10). Using linear regression analysis with body fat percentage as the dependent variables and age, height, weight, gender, and hours in optimal energy balance, we determined that we could predict a large amount of variance in body fat percentage (R= .931; P= <.001). The only time during the day that there was a significant correlation between body fat percent and hunger was at 5pm (R= -0.391, P = 0.029). Conclusions: These data suggest that that the more time spent in energy deficit is associated with a higher body fat percent. This should encourage college students between the age of 18-30 to avoid restrictive eating patterns and strive to maintain optimal energy balance in order to achieve a low body fat percent.