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.

Proper nutrition is critical for optimal performance in endurance athletes. However, it is unclear if endurance athletes are meeting all their energy and nutrient needs. We examined if endurance athletes are meeting their nutritional requirements and if this differed by sex. Ninety-five endurance athletes (n = 95; 50.5% men; 34.9 ± 12.9 y) participated in the study. Dietary intake was evaluated using the 24 h dietary recall method. Energy and nutrient intakes were calculated using the ESHA Food Processor Diet Analysis Software and compared against reference nutrient intakes. Endurance athletes did not consume the recommended amount of energy (76.8% of athletes), carbohydrates (95.8%), linoleic acid (75.8%), α-linolenic acid (ALA) (77.9%), eicosatetraenoic and docosahexaenoic acid (96.8%), dietary fiber (49.5%), vitamins D (93.7%), E (71.6%), and K (54.7%), folate (54.7%), pantothenic acid (70.5%), biotin (83.2%), manganese (58.9%), magnesium (56.8%), chromium (91.6%), molybdenum (93.7%), choline (85.3%), and potassium (56.8%), and consumed too much saturated fat (50.5%) and sodium (94.7%) than recommended. Fisher’s Exact test showed that the requirements for dietary fiber (70.8% vs. 27.7%), ALA (87.5% vs. 68.1%), and total water (70.8% vs. 44.7%) were not met by more men versus women (p < 0.05). The needs for protein (70.2% vs. 25%) and vitamin B12 (46.8% vs. 22.9%) were not met by more women compared to men (p < 0.05). These findings need to be confirmed by a larger study.

Most athletes use dietary supplements (DS) to improve health and performance beyond what can be achieved through diet. Improvements in health and exercise performance through the use of DS are especially attractive to older athletes (OA) challenged with age-related declines. However, there are few DS shown to improve endurance performance, and the prevalence of DS in OA are unknown. Two-hundred cyclists, runners, and triathletes (females = 108; age = 39.4 ± 13.5) completed a questionnaire regarding the prevalence and type of DS currently used, in addition to variables associated with using DS such as motivation and sources of information. Overall, 78.0% of athletes reported current DS use. OA used more DS (Total DS = 4.3 ± 3.0) than younger athletes (2.7 ± 1.8, p < 0.001), with ages 40–49 and 50–59 using more DS than ages 18–29 and 30–39 (p < 0.05). The majority of athletes (53.8%) used ≥ 3 DS. Age was the only significant predictor of total DS use (p = 0.002); OA used ≥ 3 DS more than younger (p < 0.001). Specifically, more athletes 40–49 (67.5%) and 50–59 (76.2%) used ≥ 3 DS compared to 18–29 (33.3%, p = 0.003). More OA used electrolytes (p = 0.005), probiotics (p = 0.045), melatonin (p = 0.004), and vitamin D (p = 0.016) than younger athletes. Motivations to use DS were related to age and were supplement specific. Sources of DS information varied by sex more than age. Age is a significant determining factor for DS use in a sample of cyclists, runners, and triathletes. The prevalence and trends of DS warrant further investigation into the benefits and risks of DS to develop safe, targeted, and age-specific DS strategies on a recreative competitive level.

Background: Frequent dieting is common in athletes attempting to achieve a body composition perceived to improve performance. Excessive dieting may indicate disordered eating (DE) behaviors and can result in clinical eating disorders. However, the current nutrition patterns that underly dieting culture are underexplored in endurance athletes. Therefore, the purpose of this study was to identify the sex differences in nutrition patterns among a group of endurance athletes. Methods: Two-hundred and thirty-one endurance athletes (females = 124) completed a questionnaire regarding their dieting patterns and associated variables. Results: The majority of athletes did not follow a planned diet (70.1%). For endurance athletes on planned diets (n = 69), males were more likely follow a balanced diet (p = 0.048) and females were more likely to follow a plant-based diet (p = 0.021). Female endurance athletes not on a planned diet (n = 162) were more likely to have attempted at least one diet (p < 0.001). Male athletes attempted 2.0 ± 1.3 different diets on average compared to 3.0 ± 2.0 for females (p = 0.002). Female athletes were more likely to attempt ≥ three diets (p = 0.022). The most common diet attempts included carbohydrate/energy restrictive, plant-based, and elimination diets. Females were more likely to attempt ketogenic (p = 0.047), low-carbohydrate (p = 0.002), and energy restricted diets (p = 0.010). Females made up the entirety of those who attempted gluten-/dairy-free diets (F = 22.0%, M = 0.0%). Conclusions: Being a female athlete is a major determinant of higher dieting frequency and continual implementation of popular restrictive dietary interventions. Sports dietitians and coaches should prospectively assess eating behavior and provide appropriate programming, education, and monitoring of female endurance athletes.

Extreme carbohydrate deficits during a ketogenic diet (KD) may result in metabolic adaptations reflective of low energy availability; however, the manifestation of these adaptations outside of exercise have yet to be elucidated in cyclists and triathletes. The purpose of this study is to investigate the chronic and postprandial metabolic responses to a KD compared to a high-carbohydrate diet (HCD) and habitual diet (HD) in trained competitive cyclists and triathletes. For this randomized crossover trial, six trained competitive cyclist and triathletes (F: 4, M: 2) followed an ad libitum KD and HCD for 14 d each after their HD. Fasting energy expenditure (EE), respiratory exchange ratio (RER), and fat and carbohydrate oxidation (FatOx and CarbOx, respectively) were collected during their HD and after 14 d on each randomly assigned KD and HCD. Postprandial measurements were collected on day 14 of each diet following the ingestion of a corresponding test meal. There were no significant differences in fasting EE, RER, FatOx, or CarbOx among diet conditions (all p > 0.050). Although postprandial RER and CarbOx were consistently lower following the KD meal, there were no differences in peak postprandial RER (p = 0.452), RER incremental area under the curve (iAUC; p = 0.416) postprandial FatOx (p = 0.122), peak FatOx (p = 0.381), or FatOx iAUC (p = 0.164) between the KD and HD meals. An ad libitum KD does not significantly alter chronic EE or substrate utilization compared to a HCD or HD; postprandial FatOx appears similar between a KD and HD; this is potentially due to the high metabolic flexibility of cyclists and triathletes and the metabolic adaptations made to habitual high-fat Western diets in practice. Cyclists and triathletes should consider these metabolic similarities prior to a KD given the potential health and performance impairments from severe carbohydrate restriction.