Low energy availability (LEA) has been associated with several physiological consequences, but its impact on sleep has not been sufficiently investigated, especially in the context of young athletes. This study examined the potential association between energy availability (EA) status and objective sleep quality in 42 male rugby players (mean age: 16.2 ± 0.8 years) during a 7-day follow-up with fixed sleep schedules in the midst of an intensive training phase. Participants’ energy intake was weighed and recorded. Exercise expenditure was estimated using accelerometry. Portable polysomnography devices captured sleep on the last night of the follow-up. Mean EA was 29.3 ± 9.14 kcal·kg FFM⁻¹·day⁻¹, with 47.6% of athletes presenting LEA, 35.7% Reduced Energy Availability (REA), and 16.7% Optimal Energy Availability (OEA). Lower sleep efficiency (SE) and N3 stage proportion, along with higher wake after sleep onset (WASO), were found in participants with LEA compared to those with OEA (p = 0.04, p = 0.03 and p = 0.005, respectively, with large effect sizes). Segmented regression models of the EA-sleep outcomes (SE, sleep onset latency [SOL]), WASO and N3) relationships displayed two separate linear regions and produced a best fit with a breakpoint between 21–33 kcal·kg FFM⁻¹·day⁻¹. Below these thresholds, sleep quality declines considerably. It is imperative for athletic administrators, nutritionists, and coaches to conscientiously consider the potential impact of LEA on young athletes’ sleep, especially during periods of heavy training.

This study aimed to determine the short-term effect of two isocaloric diets differing in the ratio of protein–carbohydrate on melatonin levels, sleep, and subsequent dietary intake and physical activity in healthy young men. Twenty-four healthy men took part in a crossover design including two sessions of three days on isocaloric diets whether high-protein, low-carbohydrate (HPLC) or low-protein, high-carbohydrate (LPHC) followed by 24-h free living assessments. Sleep was measured by ambulatory polysomnography pre-post-intervention. Melatonin levels were assessed on the third night of each session on eight-point salivary sampling. Physical activity was monitored by accelerometry. On day 4, participants reported their 24-h ad-libitum dietary intake. LPHC resulted in better sleep quality and increased secretion of melatonin compared to HPLC. A significant difference was noted in sleep efficiency (p < 0.05) between the two sessions. This was mainly explained by a difference in sleep onset latency (p < 0.01) which was decreased during LPHC (PRE: 15.8 ± 7.8 min, POST: 11.4 ± 4.5 min, p < 0.001). Differences were also noted in sleep staging including time spent on REM (p < 0.05) and N1 (p < 0.05). More importantly, REM latency (PRE: 97.2 ± 19.9 min, POST 112.0 ± 20.7 min, p < 0.001) and cortical arousals (PRE: 7.2 ± 3.9 event/h, POST 8.5 ± 3.3 event/h) increased in response to HPLC diet but not LPHC. On day 4, 24-h ad-libitum energy intake was higher following HPLC compared to LPHC (+64 kcal, p < 0.05) and explained by increased snacking behavior (p < 0.01) especially from carbohydrates (p < 0.05). Increased carbohydrates intake was associated with increased cortical arousals.

Despite some reported benefits, there is a low quality of evidence for resistance training (RT) improving metabolic health of individuals with overweight or obesity. We evaluated the impact of RT on body composition, cardiorespiratory fitness (CRF) and physical performance, lipid–lipoprotein profile, inflammation, and glucose–insulin homeostasis in 51 postmenopausal women versus 29 controls matched for age, obesity, and physical activity. Exercised women were further subdivided for comparison of RT effects into those presenting metabolically healthy obesity (MHO) and those with metabolically unhealthy obesity (MUHO) classified according to Karelis and Rabasa-Lhoret or an approach based on adipose tissue secretory dysfunction using the plasma adiponectin(A)/leptin (L) ratio. Participants followed a 4-month weekly RT program targeting major muscle groups (3 × 10 repetitions at 80% one repetition maximum (1-RM)). Percent fat marginally decreased and lean body mass increased (0.01 < p < 0.05) while CRF and muscular strength improved in all women, after RT (effect size (ES): 0.11–1.21 (trivial to large effects), p ˂ 0.01). Fasting plasma triacylglycerol and high-density lipoprotein-cholesterol levels slightly increased and decreased, respectively, in participants with MHO using the A/L ratio approach (ES: −0.47 to 1.07 (small to large effects), p ˂ 0.05). Circulating interleukin-6 soluble receptor decreased in both groups and soluble tumor necrosis factor receptor-1/soluble tumor necrosis factor receptor-2 in women with MUHO only, irrespective of definition (ES: −0.42 to −0.84 (small to large effects), p ˂ 0.05). Glucose–insulin homeostasis was unchanged regardless of group or definition. RT improved physical performance and body composition but had a lesser impact on cardiometabolic risk in women with obesity, irrespective of their metabolic phenotype.

Rugby players must develop excellent levels of conditioning during adolescence. However, this pivotal period of life is also characterized by a surge in biological growth, which further increases the energy and nutritional requirements of this population. This study examined within-individual differences in energy intake (EI) and energy balance (EB) of 46 young rugby players during a pre-season micro-cycle. Two clusters were identified with significantly different characteristics and EB states, suggesting that young rugby players adjust their EI to match their body composition goals. The first cluster is characterized by players with a low body fat% (12.87 ± 2.53). They had a positive EB (330 ± 517 kcal), suggesting a goal of increasing muscle mass. Conversely, the second cluster is characterized by a higher body fat% (23.1 ± 1.6, p < 0.005) and reported a negative, lower EB (−683 ± 425 kcal, p < 0.005), suggesting a goal focused on reducing fat mass. Although our study provides more optimistic results than previous ones regarding the high risk of inadequate EI in young rugby players, we emphasize the importance of rigorous nutritional support, especially for players aiming to lose weight, to avoid severe caloric restriction, as well as the downstream effects of such practices on their nutritional status, given the higher risk of macro- (e.g., CHO < 6 g/kg/d) and micronutrient (e.g., iron < 11 mg/d, calcium < 1300 mg/d, vitamin D < 5 mg/d) deficiencies.