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We aimed to investigate the long-term effect of daily Calanus oil supplementation on maximal oxygen uptake (VO₂max) in healthy 30- to 50-year-old participants. The study was motivated by preclinical studies reporting increased VO₂max and metabolic health with omega-3 rich Calanus oil. In a double-blinded study, 71 participants were randomized to receive 2 g/day of Calanus or placebo supplementation for a total of 6 months. The participants underwent exercise testing and clinical investigations at baseline, 3 months, and 6 months. Main study endpoint was change in VO₂max from baseline to 6 months. Fifty-eight participants completed the 6-month test and were included in the final data analysis (age: Calanus, 39.7 [38.0, 41.4] and placebo, 38.8 [36.8, 40.9] years; body mass index: Calanus, 24.8 [24.0, 25.6] and placebo, 24.8 [23.7, 25.8] kg/m²; and VO₂max: Calanus, 50.4 [47.1, 53.8] and placebo, 50.2 [47.2, 53.1] ml·kg⁻¹·min⁻¹). There were no between-group differences at baseline, nor were there any between-group differences in absolute (Calanus, 3.74 [3.44, 4.04] and placebo, 3.79 [3.44, 4.14] L/min) or relative VO₂max (Calanus, 49.7 [46.2, 53.2] and placebo, 49.5 [46.0, 53.1] ml·kg⁻¹·min⁻¹) at 6 months (mean [95% confidence interval]). There were no between-groups change in clinical measures from baseline to 3 and 6 months. In conclusion, VO₂max was unaffected by 6 months of daily Calanus oil supplementation in healthy, physically fit, normal to overweight men and women between 30 and 50 years old.

Blackcurrant juices and extracts containing anthocyanin may provide ergogenic benefits to sports performance. However, there are no studies examining the effects of coingestion of blackcurrant and caffeine. This investigation examined the effects of acute supplementation with a proprietary blackcurrant beverage administered in isolation or in combination with caffeine on repeated high-intensity cycling. Twelve well-trained male cyclists (mean ± SD: age, 39.5 ± 11.4 years; height, 177.9 ± 5.7 cm; weight, 78.2 ± 8.9 kg; and peak oxygen consumption, 4.71 ± 0.61 L/min) completed experimental sessions consisting of repeated (8 × 5 min) maximal intensity efforts. Four experimental treatments were administered in a double-blind, balanced Latin square design: blackcurrant + caffeine, blackcurrant + placebo, caffeine + placebo and placebo + placebo. Differences in power output, heart rate, oxygen consumption, muscle oxygen saturation, rate of perceived exertion, and cognitive function (Stroop) were compared between treatments using two-way repeated-measures analysis of variance and effect size analysis. There were no significant differences (p > .05) in either physiological or cognitive variables with any supplement treatment (blackcurrant + caffeine, blackcurrant + placebo, and caffeine + placebo) relative to placebo + placebo. Moreover, any observed differences were deemed trivial (d < 0.2) in magnitude. However, power output was lower (p < .05) in blackcurrant + placebo compared with blackcurrant + caffeine. A blackcurrant extract beverage administered in isolation or combination with caffeine provided no beneficial effect on cycling performance or physiological measures relative to a placebo control.

During the athletic season, changes in body composition occur due to fluctuations in energy expenditure and energy intake. Literature regarding changes of energy availability (EA) is still scarce. The aim was to estimate EA of athletes from nonweight and weight-sensitive sports during the athletic season (i.e., preparatory and competitive phase). Eighty-eight athletes (19.1 ± 4.2 years, 21.8 ± 2.0 kg/m², 27% females, self-reported eumenorrheic) from five sports (basketball [n = 29]; handball [n = 7]; volleyball [n = 9]; swimming [n = 18]; and triathlon [n = 25]) were included in this observational study. Energy intake and exercise energy expenditure were measured through doubly labeled water (over 7 days and considering neutral energy balance) and metabolic equivalents of tasks, respectively. Fat-free mass (FFM) was assessed through a four-compartment model. EA was calculated as EA = (energy intake − exercise energy expenditure)/FFM. Linear mixed models, adjusted for sex, were performed to assess EA for the impact of time by sport interaction. Among all sports, EA increased over the season: basketball, estimated mean (SE): 7.2 (1.5) kcal/kg FFM, p < .001; handball, 14.8 (2.9) kcal/kg FFM, p < .001; volleyball, 7.9 (2.8) kcal/kg FFM, p = .006; swimming, 8.7 (2.0) kcal/kg FFM, p < .001; and triathlon, 9.6 (2.0) kcal/kg FFM, p < .001. Eleven athletes (12.5%) had clinical low EA at the preparatory phase and none during the competitive phase. During both assessments, triathletes’ EA was below optimal, being lower than basketballers (p < .001), volleyballers (p < .05), and swimmers (p < .001). Although EA increased in all sports, triathlon’s EA was below optimal during both assessments. Risk of low EA might be seasonal and resolved throughout the season, with higher risk during the preparatory phase. However, in weight-sensitive sports, namely triathlon, low EA is still present.

This study examines (a) the influence of exercise, lifestyle behavior components (sedentary time, physical activity, and sleep and dietary patterns), and physical fitness on maternal weight gain, postpartum weight retention, and excessive gestational weight gain and (b) whether exercise protects against the adverse effects of impaired metabolism and nonoptimal body composition related to excessive gestational weight gain. Subjects were assigned to either a supervised concurrent (aerobic + resistance) exercise program followed 3 days/week (n = 47) or a control group (n = 54). Sedentary time, physical activity, sleep and dietary patterns (assessed by accelerometry and questionnaires), muscle strength (handgrip test), and cardiorespiratory fitness (Bruce test) were determined at gestational Weeks 16 and 33 (early-middle and late pregnancy, respectively), and at 6 weeks postpartum. Weight gain and weight retention were calculated using recorded weights at prepregnancy, early-middle, and late pregnancy, and at 6 weeks postpartum. Birth complications, maternal postpartum body composition, cardiometabolic, and inflammatory markers in maternal and umbilical cord arterial and venous blood, and in colostrum, and mature milk were also recorded. The exercise intervention reduced late weight gain (B = −2.7, SE = 0.83, p = .003) and weight retention (B = −2.85, SE = 1.3, p = .03), independent of any lifestyle behavior component or physical fitness, but did not prevent excessive weight gain. Increasing cardiorespiratory fitness, muscle strength, and sleep duration were associated with a smaller mean weight gain and lower excessive weight gain values (p < .05). Among the participants who experienced excessive weight gain, those who were exercisers had a lower body mass index and systemic tumor necrosis factor-alpha concentration, lower umbilical cord venous tumor necrosis factor-alpha and arterial interferon gamma levels, higher cord arterial interleukin-10 levels, and improved placental function compared with controls (p < .05). In summary, exercise may help optimize gestational weight gain and weight retention, and may attenuate the impaired phenotype related to excessive weight gain. Increasing cardiorespiratory fitness, muscle strength, and sleep duration might help to prevent excessive weight gain during pregnancy.

The potential ergogenic benefits of caffeine (CAF) are well known within the athletic community, often leading to its use in adolescent swimming cohorts to enhance their performance. However, it has previously been reported that CAF has sleep-disturbing effects, which could be detrimental to performance over consecutive days in multiday competitions. Moreover, the effects that evening CAF ingestion has on sleep, side effects, and next-day performances are yet to be researched in trained adolescents. In a double-blind, randomized, crossover design, eight national-level swimmers (age: 18 ± 1 years, height: 1.76 ± 0.06 cm, body mass [BM]: 69.4 ± 6.4 kg) ingested a capsule containing 3 mg/kg BM CAF or a placebo 60 min before an evening 100-m swimming time trial. The next morning, sleep was analyzed (Core Consensus Sleep Diary) and 100-m time trials were repeated. Side effects were analyzed via visual analog scales throughout the study. No differences were found for swimming performance (p = .911) in the evening (CAF: 59.5 ± 7.8 s, placebo: 59.9 ± 7.9 s, g = 0.06) or morning (CAF: 59.7 ± 7.7 s, placebo: 60.2 ± 7.9 s, g = 0.07). In addition, no group differences were found for any subjective side effects (e.g., anxiety: p = .468, tachycardia: p = .859, alertness: p = .959) or sleep parameters (e.g., sleep latency: p = .395, total sleep time: p = .574). These results question the use of a standardized 3 mg/kg BM CAF ingestion strategy for 100-m swimming time trials in trained adolescents, although objective measures may be needed to confirm that CAF does not affect sleep within this cohort.

Energy availability (EA) is calculated by subtracting exercise energy expenditure from energy intake, adjusted for fat-free mass (FFM) obtained using accurate methods, such as dual-energy X-ray absorptiometry (DXA). Unlike DXA, the bioelectrical impedance analysis (BIA) is low in cost, simple and easy to carry out. This study aimed to test the concordance between the calculation of EA using FFM values from four BIA predictive equations and FFM obtained using DXA in female adolescent athletes (n = 94), recruited via social media. Paired Student’s t test, Wilcoxon test, Lin’s concordance correlation coefficient, root mean square error, limits of agreement, and mean absolute percentage error were used to evaluate agreement between the FFM values obtained by the four SF-BIA predictive equations and DXA. Regression linear analysis was used to determine the relation between FFM values obtained using DXA and the BIA predictive equations. Standardized residuals of the FFM and EA were calculated considering DXA values as reference. The most appropriate model for the FFM (limits of agreement = 4.0/−2.6 kg, root mean square error = 1.9 kg, mean absolute percentage error = 4.34%, Lin’s concordance correlation coefficient = .926) and EA (limits of agreement = 2.51/4.4 kcal·kg FFM⁻¹·day⁻¹, root mean square error = 1.8 kcal·kg FFM⁻¹·day⁻¹, mean absolute percentage error 4.24%, Lin’s concordance correlation coefficient = .992) was the equation with sexual maturity as a variable, while the equation with the greatest age variability was the one with the lowest agreement. FFM-BIA predictive equations can be used to calculate EA of female adolescent athletes. However, the equation should be chosen considering sex, age, and maturation status. In the case of athletes, researchers should use equations developed for this group.