Predicting VO2max in competitive cyclists: Is the FRIEND equation the optimal choice?

Predicting VO2max in athletes is vital for determining endurance capacity, for performance monitoring, in clinical diagnostic procedures, and for disease management. This study aimed to assess the most suitable equation for predicting VO2max in competitive cyclists. Competitive cyclists (496 males, 84 females, Caucasian, 580 total) were included in the study from 1 January 2014 to 31 December 2019. Only subjects who were actively participating in national or international competitions and who were registered competitive cyclists and part of cycling teams at the time of the measurements were included. Subjects performed an incremental test on a cycle ergometer, and VO2max was measured as indicated by a plateau in VO2. In addition, four prediction equations (the FRIEND, Storer, Fairbarn, and Jones) were used to estimate VO2max. The predicted VO2max using the FRIEND equation was in good agreement with the measured VO2max in male and female athletes. This was reflected by a high correlation with r = 0.684 for men and r = 0.897 for women (p = 0.000), with ICC = 0.568 (95% CI 0.184, 0.752) for men and ICC = 0.881 (95% CI 0.813, 0.923) for women. Total error was 1.56 and 1.48 ml/min/kg and a minimal bias of-3.6 and -1.1 ml/min/kg (men and women, respectively). Using other equations resulted in a slight decline in agreement with the measured standard. The FRIEND equation predicted VO2max accurately with small total error, small prediction errors, and with the smallest constant error in our study cohort, indicating the potential value of using FRIEND equation also in competitive cyclists. This equation proved to have the highest accuracy both in male and female cyclists.

A Meta-Analysis of Sampled Maximal Aerobic Capacity Data for Boys Aged 11 Years Old or Less Obtained by Cycle Ergometry.

The aim of this study was to develop distributions of VO2max based on measured values that exist in the literature in prepubertal boys using cycle ergometry. PRISMA guidelines were followed in conducting this research. One database was searched for peak and maximal VO2 values in healthy boys with mean age under 11 years old. Data were split into articles reporting absolute and relative VO2max values and analyzed accordingly. Multilevel models grounded in Bayesian principles were used. We investigated associations between VO2max and body mass, year of the study, and country of origin. Differences in "peak" and "maximal" VO2 were assessed. Absolute VO2max (Lmin-1) increases with age (P ~100%) but mean relative VO2max does not change (P ~100%). Absolute VO2max is higher in more recent studies (P = 95.7 ± 0.3%) and mean relative VO2max is lower (P = 99.6 ± 0.1%). Relative VO2max in the USA is lower compared with boys from other countries (P = 98.8 ± 0.2%), but there are no differences in absolute values. Mean aerobic capacity estimates presented as "peak" values are higher than "maximal" values on an absolute basis (P = 97.5 ± 0.3%) but not on a relative basis (P = 99.6 ± 0.1%). Heavier boys have lower cardiorespiratory fitness (P ≈ 100%), and body mass seems to be increasing faster with age in the USA compared with other countries (P = 92.3 ± 0.3%). New reference values for cardiorespiratory fitness are presented for prepubertal boys obtained with cycle ergometry. This is new, as no reference values have been determined so far based on actual measured values in prepubertal boys. Aerobic capacity normalized to body weight does not change with age. Cardiorespiratory fitness in prepubertal boys is declining, which is associated with increasing body mass over the last few decades. Lastly, this study did not find any statistically significant difference in the sample's mean aerobic capacity estimates using the "peak" and "maximum" distinctions identified in the literature.

Prediction of Maximal Oxygen Consumption in Cycle Ergometry in Competitive Cyclists.

Models for predicting maximal oxygen consumption (VO2max) in average adults might not be suitable for athletes, especially for competitive cyclists who can have significantly higher VO2max than normally active people. The aim of this study was to develop a clinically applicable equation for predicting VO2max during cycle ergometry in competitive cyclists and to compare its accuracy to the traditional American College of Sports Medicine (ACSM) equation. Maximal cycle ergometry tests were performed in 496 male and 84 female competitive cyclists. Six predictors were initially used to model the prediction equation (power output, body weight, body height, fat mass, fat-free mass and age). Power output and body weight were the most important parameters in the model predicting VO2max. Three new equations were derived: for male (VO2max = 0.10 × PO - 0.60 × BW + 64.21), female cyclists (0.13 × PO - 0.83 × BW + 64.02) and the non-gender-specific formula (0.12 × PO - 0.65 × BW + 59.78). The ACSM underestimated VO2max in men by 7.32 mL/min/kg (11.54%), in women by 8.24 mL/min/kg (15.04%) and in all participants by 7.45 mL/min/kg (11.99%), compared to the new equation that underestimated VO2max in men by 0.12 mL/min/kg (0.19%) and in all participants by 0.65 mL/min/kg (1.04%). In female cyclists, the new equation had no relative bias. We recommend that medicine and sports practitioners adapt our proposed equations when working with competitive cyclists. Our findings demonstrate the need to evaluate prediction models for other athletes with a special focus on disciplines that demand high aerobic capacity.

Reducing energy availability in male endurance athletes: a randomized trial with a three-step energy reduction.

Background: Low energy availability (EA) can be detrimental for athlete health. Currently, it is not known what the threshold for low EA in men is, and what effects it may have on performance. Methods: This study was set to determine potential effects of low EA by modulating male participants' exercise energy expenditure and controlling energy intake and consequently manipulating EA in three progressive stages (reducing EA by 25%%, and 75 %). Performance was measured with three specific tests for explosive power, endurance, and agility. Blood was drawn, resting energy expenditure was monitored and two questionnaires were repetitively used to address any changes in eating behaviors and well-being. Results: Repeated measured design showed poorer performance (power output 391.82 ± 29.60 vs. 402.5 ± 40.03 W, p = 0.001; relative power output 5.53 ± 0.47 vs. 5.60 ± 0.47 W/kg, p = 0.018; explosive power 0.28 ± 0.04 vs. 0.32 ± 0.05 m, p = 0.0001, lactate concentration 7.59 ± 2.29 vs 10.80 ± 2.46 mmol/L, p = 0.001). the quartile range for testosterone was lower (2.33 ± 1.08 vs. 2.67 ± 0.78, p = 0.026) and there was a tendency for lower triiodothyronine (4.15 ± 0.61 vs. 4.46 ± 0.54 pmol/L, p = 0.072). Eating behaviors and well-being were worse (46.64 ± 7.55 vs. 24.58 ± 7.13, p = 0.011 and 15.18 ± 2.44 vs. 17.83 ± 3.54, p = 0.002). The intervention also resulted in lower body fat (8.44 ± 3.15 vs. 10.2 ± 2.5%, p = 0.013). Conclusions: Analysis showed that most of the negative effects occurred in the range of 9-25 kCal·kg∙FFM·d-1. This is the range where we suggest a threshold for LEA in men could be. Reducing EA impaired explosive power first, then endurance. It was associated with a reduction in testosterone, triiodothyronine and there was a tendency for reduced IGF-1, but hormones were more resilient to changes in EA. Psychological assessment of eating behaviors and well-being proved to be very useful, whereas monitoring resting energy expenditure did not.

Inducing low energy availability in trained endurance male athletes results in poorer explosive power.

PURPOSE: Low energy availability in males needs more original research to understand its health and performance consequences. The aim of the study was to induce low energy availability in previously healthy male endurance athletes by reducing energy availability by 25% for 14 consecutive days and measure any potential changes in performance, health, mental state or energy markers. METHODS: Energy availability was reduced in 12 trained, well-trained and elite endurance athletes by increasing energy expenditure and controlling energy intake. After intervention, health was assessed by blood draw, body composition was measured, energy markers by measuring resting energy expenditure, performance with three specific tests (measuring endurance, agility and explosive power) and two questionnaires were used for psychological assessment (the Three Factor Eating Questionnaire and Well-being questionnaire). RESULTS: Reduced energy availability (22.4 ± 6.3 kcal/kg FFM/day) caused significantly lower haemoglobin values (t(12) = 2.652, p = 0.022), there was a tendency for lower iron and IGF-1 (p = 0.066 and p = 0.077, respectively). Explosive power was reduced (t(12) = 4.570, p = 0.001), lactate metabolism was altered and athletes reported poorer well-being (t(12) = 2.385, p = 0.036). Cognitive restriction was correlated with energy availability (r = 0.528, p = 0.039). CONCLUSION: This is the first research providing direct evidence that suboptimal energy availability negatively impacts explosive power before hormonal changes occur in male endurance athletes. It is also the first to show direct association of low energy availability and higher cognitive restriction. We also observed worse well-being and lower haemoglobin values. 25% of energy availability reduction as not enough to elicit changes in resting energy expenditure.

Relationship between energy availability, energy conservation and cognitive restraint with performance measures in male endurance athletes.

BACKGROUND: Low energy availability in male athletes has gained a lot of attention in recent years, but direct evidence of its effects on health and performance is lacking. The aim of this research was to objectively measure energy availability (EA) in healthy male endurance athletes without pre-existing relative energy deficiency signs during pre-race season. METHODS: Twelve trained endurance athletes (performance level 3, 4, and 5) participated in the cross-sectional controlled laboratory study. Fat-free mass, exercise energy expenditure, and energy intake were measured to calculate EA. Resting energy expenditure was measured and estimated to assess energy conservation. Three specific performance tests were used to assess endurance, agility, and explosive strength performance. For psychological evaluation, the Three Factor Eating Questionnaire and a short Well-being questionnaire were completed. RESULTS: Mean EA was 29.5 kcal/kg FFM/day. The majority (66.6%) had EA under the threshold for low EA in females. Critical cognitive restraint (≥13) was reported by 75% of participants. There were no differences in performance, blood values, or psychological evaluation when subjects were divided into two groups divided by EA = 30 kcal/kg FFM/day. Cognitive restraint was negatively associated with measured resting energy expenditure and energy conservation (r = -.578, p = .025 and r = -.549, p = .032, respectively). CONCLUSIONS: The mean EA measured in this study supports the theory that the threshold for low EA in endurance male athletes might be under the threshold for females. In addition, we confirmed cognitive restraint could be useful for early detection of energy conservation. The high cognitive restraint as measured in our sample stressed the need of eating behavior screening in endurance athletes in order to reduce risk of any disordered eating patterns.