Purpose.: Determine the effect of menu labels displaying the energy content of food items or the exercise equivalent on energy ordered and consumed at lunch and energy intake for the remainder of the day in young adults. Design.: Subjects were randomized to a menu with no labels (no-labels), menu with kilocalorie labels displaying the energy content of the food items (kcal-labels), or menu with exercise labels displaying the minutes of brisk walking needed to burn the food energy (exercise-labels). Setting.: The study was conducted in one dining area located in a metabolic kitchen at the Texas Christian University and another located in a residence occupied by graduate students. Subjects.: Of the 300 subjects, 55.7% were female, 77.3% were college students, 88% were white, and 88% were non-Hispanic. Mean body mass index and age were 24.2 ± 4.5 kg/m ² and 21.9 ± 2.3 years, respectively. Intervention.: All menus contained the same food/beverage choices. Subjects ordered and consumed foods/beverages for lunch from the menu to which they were assigned. Subjects were blinded to study purpose. Measures.: Energy ordered and consumed at lunch were assessed from the weight of the food ordered and consumed, respectively, and the energy content of the same foods available on the restaurant Web site. Postlunch energy intake was assessed by food recall. Analysis.: Analysis of covariance, adjusted for premeal hunger levels and gender, determined the effect of menu type on energy ordered and consumed and postlunch energy intake. Results.: Significant menu effect was observed for energy ordered (p = .008) and consumed (p = .04) at lunch. The exercise-labels group ordered significantly (p = .002) less energy (adjusted mean [confidence intervals]: 763 [703, 824] kcal) at lunch, compared to the no-labels group (902 [840, 963] kcal) but not compared to the kcal-labels group (827 [766, 888] kcal). The exercise-labels group also consumed significantly (p = .01) less energy (673 [620, 725] kcal) at lunch, compared to the no-labels group (770 (717, 823) kcal) but not compared to the kcal-labels group (722 [669, 776] kcal). Energy ordered and consumed were not different between kcal-labels and no-labels groups. There was no difference in postlunch energy intake by menu type. Conclusion.: The menu with exercise-labels resulted in less energy ordered and consumed and this did not lead to greater energy consumption post lunch, compared to the menu with no-labels in young adults largely made up of normal-weight, non-Hispanic white college students.

In order to achieve optimal performance, endurance athletes need to implement a variety of recovery strategies that are specific to their training and competition. Recovery is a multidimensional process involving physiological, psychological, emotional, social, and behavioral aspects. The purpose of the study was to examine current implementation, beliefs, and sources of information associated with recovery strategies in endurance athletes. Participants included 264 self-identified endurance athletes (male = 122, female = 139) across 11 different sports including placing top three overall in competition (n = 55) and placing in the top three in their age group or division (n = 113) during the past year. Endurance athletes in the current study preferred hydration, nutrition, sleep, and rest in terms of use, belief, and effectiveness of the recovery strategy. Female endurance athletes use more recovery strategies for training than males (p = 0.043, d = 0.25), but not in competition (p = 0.137, d = 0.19). For training, top three finishers overall (p < 0.001, d = 0.61) and by division (p < 0.001, d = 0.57), used more recovery strategies than those placing outside the top three. Similar findings were reported for competition in top three finishers overall (p = 0.008, d = 0.41) and by division (p < 0.001, d = 0.45). These athletes are relying on the people around them such as coaches (48.3%) and fellow athletes (47.5%) along with websites (32.7%) for information and recommendations. Endurance athletes should be educated on other strategies to address the multidimensionality of recovery. These findings will be useful for healthcare professionals, practitioners, and coaches in understanding recovery strategies with endurance athletes.

Many endurance athletes have poor sleep quality which may affect performance and health. It is unclear how dietary intake affects sleep quality among athletes. We examined if sleep quality in endurance athletes is associated with consumption of fruit, vegetables, whole grains, dairy milk, and caffeinated beverages. Two hundred thirty-four endurance athletes (39.5 ± 14.1 year) participated in a survey. Participants provided information on demographics, anthropometry, sleep behavior and quality, and dietary intake via questionnaires. Sleep quality was assessed using the Athlete Sleep Screening Questionnaire (ASSQ) with a global score (ASSQ-global) and subscales including sleep difficulty (ASSQ-SD), chronotype (ASSQ-C), and disordered breathing while sleeping (ASSQ-SDB). A general linear model (GLM), adjusted for age, body mass index, sleep discomfort, sleep behavior, gender, race, and ethnicity, showed that higher caffeinated beverage intake was related to poorer global sleep quality (p = 0.01) and increased risk for disordered breathing while sleeping (p = 0.03). Higher whole grain intake was associated with a morning chronotype and lower risk for sleep issues (p = 0.01). The GLM did not reveal a relationship between sleep quality and dairy milk, fruit, and vegetable intake. In conclusion, caffeinated beverages and whole grain intake may influence sleep quality. This relationship needs to be confirmed by further research.