Introduction
Peak oxygen uptake (peak
\(\dot{{V}}{\text{O}}_{2}\)) is internationally recognized; as the criterion measure of youth aerobic fitness and in paediatric exercise laboratories, it is routinely determined either running on a treadmill or pedaling on a cycle ergometer (Falk and Dotan
2018; McManus and Armstrong
2017). Current understanding of the development of aerobic fitness in youth is based on an amalgam of data from these ergometers, but the influence of mode of exercise in relation to sex-specific, concurrent changes in body mass, fat-free mass (FFM), and maturity status on peak
\(\dot{{V}}{\text{O}}_{2}\) is unexplored.
Cross-sectional comparisons of boys aged 10–14 years have reported cycle ergometer- and treadmill-determined values of peak
\(\dot{{V}}{\text{O}}_{2}\) to be highly correlated but treadmill-determined values have consistently been noted as 7–15% higher than those achieved on a cycle ergometer (Boileau et al.
1977; Duncan et al.
1996; Macek et al.
1976). This is probably due to the greater muscle mass, enhanced venous return, increased stroke volume (SV), and reduced peripheral resistance during treadmill running. Peak
\(\dot{{V}}{\text{O}}_{2}\) when running on a treadmill is therefore more likely to be limited by cardiovascular factors than peripheral factors such as local muscle fatigue. Despite well-documented sex differences in the development of peak
\(\dot{{V}}{\text{O}}_{2,}\) there are no comparative data on girls. Yet, regularly cited reviews have interpreted the extant literature on the development and training of youth aerobic fitness in both sexes by pooling treadmill- and cycle ergometer-determined peak
\(\dot{{V}}{\text{O}}_{2}\) values (e.g., Bacquet et al.
2003; Bar-Or and Rowland
2004; Pfeiffer et al.
2008). Other authors have ‘corrected’ for ergometer differences by multiplying cycle ergometer values by different fixed percentages and pooling data regardless of sex, age, or maturity status (e.g., Aadland et al.
2018; Krahenbuhl et al.
1985; Stavnsbo et al.
2018).
There is a plethora of both treadmill- and cycle ergometer-based cross-sectional studies of youth aerobic fitness with the vast majority attempting to control for growth by focusing on a single anthropometric variable and interpreting peak
\(\dot{\text{V}}{\text{O}}_{2}\) in ratio with body mass (see Armstrong and Welsman
1994 for review). Longitudinal studies are sparse with some founded on cycle ergometer determinations of peak
\(\dot{{V}}{\text{O}}_{2}\) (e.g., Cunningham et al.
1994; Janz et al.
1998; Rutenfranz et al.
1981) and others on treadmill determinations (e.g., Mirwald and Bailey
1986; Rowland et al.
1997; Sprynarova et al.
1987), but no longitudinal studies have investigated performance on both ergometers. Data analysis generally consists of a series of annual cross-sectional examinations of peak
\(\dot{{V}}{\text{O}}_{2}\) (i.e. in L·min
− 1) and peak
\(\dot{{V}}{\text{O}}_{2}\) ratio-scaled with body mass (i.e., in mL·kg
− 1·min
− 1). Collectively longitudinal studies indicate boys’ peak
\(\dot{{V}}{\text{O}}_{2}\) to increase in a near-linear manner from 11 to 16 years with girls’ peak
\(\dot{\text{V}}{\text{O}}_{2,}\) showing a similar trend before levelling-off from ~ 13 years of age. Boys’ peak
\(\dot{{V}}{\text{O}}_{2}\) ratio-scaled with body mass has been reported to remain unchanged from 11 to 16 years, while girls’ values decrease with age, particularly from ~ 13 years of age (see Armstrong and McManus
2017 for review). The experimental designs, statistical analyses, and data interpretation in the extant literature have, however, revealed limited insights into the development of youth aerobic fitness which is influenced by concurrent changes in several variables.
Allometric scaling has challenged the ‘convenient and traditional’ (Bar-Or and Rowland
2004) interpretation of data and demonstrated, in contrast with ratio scaling, that with body mass appropriately controlled for there is a progressive increase in youth peak
\(\dot{{V}}{\text{O}}_{2}\) with age in both sexes (Welsman et al.
1996). However, it is the emergence (Aitkin et al.
1981) and regular refinement (Rasbash et al.
2018) of multilevel regression modelling which has opened up new analytical approaches to developmental exercise physiology. Multilevel modelling enables the effects of variables such as age, body mass, FFM, and maturity status to be partitioned concurrently within an allometric framework to provide a flexible and sensitive interpretation of exercise performance variables. In contrast to traditional methods that require a complete longitudinal data set, both the number of observations per individual and the temporal spacing of the observations may vary within a multilevel model. In an innovative re-analysis of previously published data of elite youth athletes Nevill et al. (
1998) introduced multiplicative, allometric modelling to paediatric sport science and with the present authors applied it to interpreting growth and maturation changes in peak oxygen uptake from 11–13 years (Armstrong et al.
1999). To date, no study has used this technique to analyze the development of youth peak
\(\dot{{V}}{\text{O}}_{2}\) determined concomitantly on a treadmill and a cycle ergometer.
As fat mass does not make a significant contribution to peak
\(\dot{{V}}{\text{O}}_{2}\) (Goran et al.
2000) FFM is likely to be a more relevant morphological variable than body mass in the development of aerobic fitness. A case can be made for determining FFM on each test occasion, but likely due to ethical and/or resource limitations, no study has been published which includes several hundred serial determinations of peak
\(\dot{{V}}{\text{O}}_{2}\) and FFM. Moreover, measures of body fat of the same young people have been shown to vary widely across established laboratory techniques (Ferri-Morales et al.
2018). In the few studies in which FFM has been reported estimates from body mass and skinfold thicknesses have provided a pragmatic morphological variable with which to study longitudinal changes in peak
\(\dot{{V}}{\text{O}}_{2}\) (e.g., Cunningham et al.
1994; Janz et al.
1998; Rowland et al.
1997). FFM is typically predicted from body mass and skinfold thicknesses using the youth-specific equations developed by Slaughter et al. (
1988), but validation studies of the equations have revealed wide limits of agreement and a tendency to under-predict fat in girls and over-predict fat in boys (Roemmich et al.
1997). Multiplicative, allometric modelling offers the opportunity to consider body mass and skinfold thicknesses together as a surrogate for FFM. A recent longitudinal study of 11–18-year-old youth demonstrated that skinfold thicknesses and body mass together explained more of the variance in short-term power output than the estimation of FFM from youth-specific equations (Armstrong and Welsman
2018a). Prior to the present project, this approach had not been investigated in relation with aerobic fitness.
Given the recent surge in papers calling for the raising of ‘clinical red flags’ or the establishment of cut points of ‘cardiometabolic risk’ based on values of peak
\(\dot{{V}}{\text{O}}_{2}\) ratio-scaled with body mass (e.g., Agbaje et al.
2018; Lang et al.
2017; Ruiz et al.
2016), the need to clarify the effects of concurrent changes in morphological covariates and maturity status on sex-specific changes in youth aerobic fitness with age has become critically important. Ratio scaling does not have a rigorous scientific rationale, is seldom statistically justified, favours lighter individuals, but penalizes heavier youth and leads to spurious correlations with other health-related variables (Tanner
1949; Welsman and Armstrong
2018; Winter and Nevill
2009). For example, the statistical association of cardiovascular risk factors with the ratio-scaled peak
\(\dot{{V}}{\text{O}}_{2}\) of overweight/obese children is likely to reflect overweight/obese status to a greater extent than aerobic fitness (Loftin et al.
2016).
‘Clinical red flags’ and ‘cardiometabolic risk’ cut points have been proposed without reference to mode of exercise. Cycle ergometer peak
\(\dot{{V}}{\text{O}}_{2}\)s have been ‘corrected’ to treadmill values by multiplying by 1.05 (Stavnsbo et al.
2018), based on a previous observation of a 5% difference in 20 9-year-old boys (Mamen et al.
2009). Another recent report promoted age-related ‘aerobic fitness thresholds’ to define poor metabolic health from 8–18 years extrapolated from cross-sectional cycle ergometer-determined peak
\(\dot{{V}}{\text{O}}_{2}\) values from 9 to 15 years and suggested that, ‘raising our cut-points by ~ 2–3 mL·kg
− 1·min
− 1, would make them equivalent to values obtained by a treadmill protocol’ (Aadland et al.
2018). It is apparent that current ‘clinical red flags’ (and similar health-related peak
\(\dot{{V}}{\text{O}}_{2}\) cut-points) for the age range 8–18 years do not take appropriate account of mode of exercise, maturity status, morphological variables other than body mass (ratio-scaled with peak
\(\dot{{V}}{\text{O}}_{2}\)), and, in some cases, age. They, therefore, have the potential to misinform clinical practice, mislead policy statements and misguide recommendations designed to promote youth health (Armstrong and Welsman
2018b) and require further scrutiny within a longitudinal framework across different modes of exercise.
To inform developmental exercise physiology and to contribute to a sound scientific foundation for health-related recommendations for youth, clarification of the influence of exercise mode and concurrent sex-specific changes in age, maturity status, and morphological covariates is required. The purposes of the present study were, therefore, (1) to adopt a multiplicative allometric approach to investigate the influence of mode of exercise on peak \(\dot{{V}}{\text{O}}_{2}\) from 11–16 years in relation with sex and concurrent changes in age, body mass, FFM, and maturity status and (2) to evaluate the data in relation with current proposals of ratio-scaled ‘clinical red flags’ and similar health-related cut-points for youth peak \(\dot{{V}}{\text{O}}_{2}\).
Discussion
The descriptive data and multilevel models demonstrate the need to distinguish between exercise modes and to adopt a sex-specific analysis of concurrent changes in anthropometric variables with age and maturity status when exploring the development of peak \(\dot{{V}}{\text{O}}_{2}\) from 11–16 years. Multiplicative, multilevel models of peak \(\dot{{V}}{\text{O}}_{2}\) were sex-specific but within sex models were similar on both ergometers. FFM was identified as the dominant morphological influence on the peak \(\dot{{V}}{\text{O}}_{2}\) of both sexes.
Mean treadmill-determined peak
\(\dot{{V}}{\text{O}}_{2}\) values were higher than cycle ergometer-determined values at each test occasion but individual variations, with some children eliciting higher values on a cycle ergometer, illustrate the misjudgement of predicting treadmill-determined values by adding a fixed % regardless of age and sex. The individual data presented in Figs.
1 and
2 reflect previous cross-sectional (Armstrong and Welsman
1994) and longitudinal (Armstrong and McManus
2017) studies. On both ergometers peak
\(\dot{{V}}{\text{O}}_{2}\) increased with age, body mass, and estimated FFM but with wide individual variations, particularly in relation with age and less so in relation with estimated FFM. A statistical assumption underlying ratio scaling is a perfect correlation (i.e.,
r = 1.0) between peak
\(\dot{{V}}{\text{O}}_{2}\) and body mass (Tanner
1949; Katch
1973; Welsman and Armstrong
2018) which is showed not to be met in the current data set (
r = ~ 0.73–0.86). The fallacy of the ratio-scaled peak
\(\dot{{V}}{\text{O}}_{2}\) interpretation of age-related aerobic fitness is reinforced by the allometric exponents identified for body mass in baseline models 1.1, 1.2, 2.1, 3.1, 4.1, and 4.4 ranging from 0.57 to 0.73 with an exponent of 1.0 (a necessary assumption in ratio scaling) falling outside the 95% confidence limits on each occasion. Descriptions of youth peak
\(\dot{{V}}{\text{O}}_{2}\) in ratio with single anthropometric variables are ‘convenient and traditional’ (Bar-Or and Rowland
2004), but both the descriptive data and all models are in direct conflict with the ratio-scaled interpretation of youth peak
\(\dot{{V}}{\text{O}}_{2}\) (Welsman and Armstrong
2018). Collectively, they expose the fallacy of using peak
\(\dot{{V}}{\text{O}}_{2}\) values in ratio with body mass as cut-points for healthy levels of aerobic fitness or for raising ‘clinical red flags’ for boys and girls between 11 and 16 years of age.
The baseline models 1.1 and 1.2 illustrated in Table
1 are each founded on 320 peak
\(\dot{{V}}{\text{O}}_{2}\) determinations and they illustrate that data from both ergometers present a similar picture of the development of peak
\(\dot{{V}}{\text{O}}_{2}\) from 11 to 16 years of age. The models demonstrate that with body mass controlled for both treadmill- and cycle ergometer-determined peak
\(\dot{{V}}{\text{O}}_{2}\)s increase with age in both sexes. The negative sex term shows boys’ peak
\(\dot{{V}}{\text{O}}_{2}\) to be higher than girls’ values and the negative age by sex interaction term demonstrates that peak
\(\dot{{V}}{\text{O}}_{2}\) increases with age at a greater rate in boys. Sex differences have generally been attributed to lower maximal SVs in girls (Rowland et al.
2000; Vinet et al.
2003), although girls have also been reported to have significantly lower maximal arterio-venous oxygen differences (a-vO
2 diff max) (Winsley et al.
2009) and poorer matching of muscle oxygen delivery to oxygen utilization (McNarry et al.
2015). However, although the physiological mechanisms underlying sex differences in youth aerobic fitness are emerging they remain to be fully elucidated (for review, see Armstrong and McManus
2017).
Girls normally enter puberty before similarly aged boys and, for example, a 13-year-old girl in PH stage 4 is not equivalent to a 15-year-old boy at the same pubertal stage (Malina
2017). It is, therefore, appropriate to analyse data in sex-specific models (Tables
2,
3,
4) which provide more sensitive explorations of the development of girls’ and boys’ peak
\(\dot{{V}}{\text{O}}_{2}\) than the combined data in Table
1. The within sex models of treadmill- and cycle ergometer-determined peak
\(\dot{{V}}{\text{O}}_{2}\) in Tables
2 and
3 (boys) and Table
4 (girls) are remarkably similar and suggest that, although the magnitude of peak
\(\dot{{V}}{\text{O}}_{2}\) is exercise mode-specific, either ergometer can be used to interpret the development of boys’ or girls’ aerobic fitness. Although there were marked sex differences in the relative concurrent contributions of age, body mass, and maturity status, FFM was the most powerful influence on peak
\(\dot{{V}}{\text{O}}_{2}\) in both sexes.
In boys, baseline models 2.1 and 3.1 show that age exerts a positive effect on peak
\(\dot{{V}}{\text{O}}_{2}\) in addition to body mass. When maturity status was entered, as in Models 2.2 and 3.2, PH stages 3–5 were shown to exert significant, positive effects on both treadmill- and cycle ergometer-determined peak
\(\dot{{V}}{\text{O}}_{2}\) in addition to those of body mass, with the age exponent becoming non-significant. The additional effect of maturity status on peak
\(\dot{{V}}{\text{O}}_{2}\) not only reflects the development of cardiorespiratory variables but also factors such as increasing muscle mass and, therefore, FFM. The introduction of sum of skinfold thicknesses into Models 2.3 and 3.3 provided the best statistical fit for both treadmill and cycle ergometer data with significant negative exponents for sum of skinfolds and increased body mass exponents. The marked increase in the body mass exponents with the introduction of skinfold thicknesses has been previously observed and attributed to the effect that excess fat mass has on increasing body mass without an increase in the exercise variable (Vanderburgh et al.
1995). The models founded on estimated FFM (i.e., Models 2.4 and 3.4) were also superior to models based on body mass (i.e., Models 2.1 and 3.1). Taken together, skinfold thicknesses and body mass provide a surrogate for FFM which explains more of the variance in peak
\(\dot{{V}}{\text{O}}_{2}\) than the estimation of FFM from the youth-specific equations developed by Slaughter et al. (
1988). The introduction of body mass and skinfold thicknesses (or estimated FFM) masks the effects of age and maturity status and demonstrates the strong influence of FFM on peak
\(\dot{{V}}{\text{O}}_{2}\).
The girls’ models 4.1 and 4.4 for treadmill and cycle ergometer data, respectively, revealed a different story as the baseline models were not statistically improved by the introduction of stages of maturation. This finding is in agreement with Nevill et al.’s (
1998) seminal multilevel modelling study where in boys, but not girls, maturity status effects on the peak
\(\dot{{V}}{\text{O}}_{2}\) of elite athletes were additional to those due to body size. In contrast, our multilevel modelling study over a longer age range (10–18 years) and founded on 1057 treadmill determinations of peak
\(\dot{{V}}{\text{O}}_{2}\) noted maturity status to have significant effects in addition to those of age and body mass in both sexes (Armstrong and Welsman
2018c). Nevertheless, as with boys, the strongest statistical model (i.e., Model 4.2) for treadmill-determined peak
\(\dot{{V}}{\text{O}}_{2}\) was created by the introduction of sum of skinfolds which resulted in a negative skinfold exponent and a concurrent increase in the body mass exponent. Model 4.5, with body mass and skinfold thicknesses acting as a surrogate of FFM, and Model 4.6, founded on estimated FFM, were the strongest statistical models of cycle ergometer data. These findings emphasise the dominant effect of changes in FFM on the development of peak
\(\dot{{V}}{\text{O}}_{2}\) in both sexes on both ergometers.
Increases in peak
\(\dot{{V}}{\text{O}}_{2}\) are manifest through changes in SVmax, a-vO
2 diff max, or both but increases in muscle mass, reflected by gains in FFM, not only enhance total muscle
\(\dot{{V}}{\text{O}}_{2}\) during exercise but, through the peripheral muscle pump, also augment venous return to the heart and increase SVmax. Driven by maturation, FFM increases by ~ 40% and ~ 90% in girls and boys, respectively, from 11 to 16 years. The influence of the timing and tempo of maturation on FFM is evidenced in boys by an ~ 83% increase over the period 2 years pre-peak height velocity (PHV) to 2 years post-PHV. The greatest increase in girls’ FFM (~ 31%) occurs over a shorter 2-year period centred on PHV and then levels-off in accord with the development of peak
\(\dot{{V}}{\text{O}}_{2}\) (Armstrong
2018)
In conclusion, the present data demonstrate that (1) changes in maturity status-driven FFM exert a powerful influence on the development of peak \(\dot{\text{V}}{\text{O}}_{2}\)from 11 to 16 years, in both sexes on both ergometers; (2) the use of concurrent changes in body mass and skinfold thicknesses as a surrogate for FFM can be recommended for future investigations of the development of peak \(\dot{{V}}{\text{O}}_{2}\); (3) it is untenable to base interpretation of youth aerobic fitness on peak \(\dot{{V}}{\text{O}}_{2}\) ratio-scaled with body mass; (4) it is misleading to combine treadmill and cycle ergometer data or to use fixed conversion factors to ‘correct’ for differences when investigating the development of peak \(\dot{{V}}{\text{O}}_{2}\); and (5) current ‘clinical red flags’ (and similar health-related peak \(\dot{{V}}{\text{O}}_{2}\) cut-points) established without consideration of exercise mode and founded on peak \(\dot{{V}}{\text{O}}_{2}\) ratio-scaled with body mass are fallacious and have the potential to misinform clinical practice and misguide recommendations designed to promote youth health.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.