Factorial approach of determining energy expenditure pattern is dependent on the time spent in various types of activities and the energy cost of those activities. Physical training time, volume and intensity is in turn dependent on age, type of sport and the phase of training [26]. In this study athletes were in the adolescent stage with majority of them involved in sport-specific training for more than two years, added to the general conditioning received for at least a year and participating at the national-level. However, they participated in three different sports involving different physiological energy systems and having different training regimes. The primary observation of this study was that majority of the training or non-training activities showing differences in heart rate across sex, also showed differences in METS across sex. Sex differences in METs may be attributed to be a representation of the differences in intensity (in terms of heart rate) of an activity carried out by boys and girls. Further, the METs of majority of the non-training or training activities of junior athletes, irrespective of the sex or event, showed more similarity to CPA, than CEEY with RMR of Indian junior athletes exhibiting significant differences from existing compendiums.
Metabolic Equivalents or METs have been considered as an important determinant of energy cost of activities and majority of the sports nutrition practitioners and other clinicians make use of the compendium of physical activity for adults [5] or compendium of energy expenditure for youth [1] to arrive at the energy expenditure pattern of individuals and athletes. However, Ainsworth, Haskell, Whitt, Irwin, Swartz, Strath, O Brien, Bassett, Schmitz and Emplaincourt [5] has assigned a common MET value, which is not reflective of individual differences in terms of age and body composition. Previous researches have shown sex differences to be negligible for METs across different activities in children, adolescents and adults [4,5,15]. Pfeiffer, Watson, McMurray, Bassett, Butte, Crouter, Herrmann, Trost, Ainsworth and Fulton [14] found less than 2 percent variance in MET across sex. However, Goran [27] reported a higher MET for resting energy expenditure among boys than girls. Similar to the findings in this study, where the RMR was higher among boys compared to girls, irrespective of the event. Further, sex differences in heart rate related to the differences in METs of most of the physical activities across sex. There was strong positive correlation between measured MET and Heart rate (r = 0.846; P-value < 0.01) and the predictability of MET from heart rate was also significant (R2 = 0.848, SEE = 1.196; MET = -5.264 + 0.086 × Heart rate) and a similar association was also found between energy cost and heart rate (R2 = 0.810, SEE = 1.205; Energy Cost = -4.523 + 0.076 × Heart rate). This strong association reflects a possible variation in intensity with which a specific training activity is carried out across sex. Thus, resulting in the sex differences observed for measured METs among activities in the present study and this needs to be explored further.
Byrne, et al. [28] reported significant differences in MET across age and body mass index, with lower age and BMI exhibiting higher RMR, compared to higher age and BMI. Other studies have reported that resting energy expenditure of children was higher than adults [14,29]. Therefore, while arriving at energy expenditure of an activity, the MET of that activity corrected using RMR (either predicted or measured) resulted in minimal difference with measured MET [28] and this correction minimizes the error while using METs [29]. However, Pfeiffer, Watson, McMurray, Bassett, Butte, Crouter, Herrmann, Trost, Ainsworth and Fulton [14] reported that one MET value across 9–15 years of age can increase chances of error up to 15–20% and suggested age-grouping as a best approach over assessing pubertal stages to assign MET. Among soccer players, a comparison was made between junior and senior boys. In the present study, most of the warm up and weight training activities showed similar METs across senior and junior soccer players. Activities which showed a significantly higher MET among junior boys, were sedentary activities like sitting & walking and lower to moderate intensity training activities like Technical warm up, wrist curl, interspersed rest and cool down stretching etc. This was in line with the findings of Pfeiffer, Watson, McMurray, Bassett, Butte, Crouter, Herrmann, Trost, Ainsworth and Fulton [14] that as age increases the MET for sedentary or light intensity activity decreases. However, contrary to the findings of Trost, Drovandi and Pfeiffer [4] that MET for sedentary or light activities remain stable across children and adolescent aged 6–16 years, while MET for sporting and fitness activities, especially walking and running tend to increase with age. In the present study, even the RMR MET of Junior boys were lower than senior boys, without correcting for body mass. This disparity might be due to the limited sample size of Junior boys and need further exploration for its relation to the improved efficiency of junior boys.
Comparison of measured METs at rest and for activities with METs in existing compendium was carried out to understand the utility of existing databases for determining energy expenditure pattern. Most of these researches were conducted on children and adolescents in free-living conditions [2,14,15,29], however, to our knowledge similar assessment has not been made among junior athletes. Pfeiffer, Watson, McMurray, Bassett, Butte, Crouter, Herrmann, Trost, Ainsworth and Fulton [14] observed that among children aged 5–19 years the MET values for sedentary or light intensity activities tend to be similar to Compendium of energy expenditure for Youth (CEEY), however, MET values tend to be higher or lower for locomotor activities and bicycle riding. In the present study, the resting MET was found to be higher compared to METs of CPA and CEEY among majority of junior athletes, except for lower MET among soccer players (Junior boys and Girls). Further, the measured MET of majority of the non-training activities (Table 3) among junior athletes tend to be similar to adult compendium (CPA) than the youth compendium (CEEY). This may be due to physical and physiological conditioning of athletes being similar to adult counterparts. Harrell, McMurray, Baggett, Pennell, Pearce and Bangdiwala [29] carried out a study on children and adolescents aged 8–18 years and found that after correcting for resting energy expenditure, the adult compendium may also be used with minimum error among children and/or adolescents. And that after attaining puberty, CPA may be used among adolescents, without adjustment of RMR. In the present study, CEEY was found to either over or underestimate MET among junior athletes. In line with this, Brandes, Steenbock and Wirsik [15] reported that CEEY among pre-schoolers tend to substantially underestimate energy expenditure. Among training activities, warm up jogging and shuttle run exhibited similar MET as CPA. MET measured for majority of the weight training activities were higher than CPA or CEEY or both. This difference could due to the broad spectrum of weight training activities, which are listed under a single activity as “weight training” in both compendiums and also because the real time measurement of these activities was based on their regular training regime of athletes, rather than individual activity measured in isolation.
Comparing METs of activities carried out by Indian junior athletes in the present study with existing literature showed that the METs and energy cost of resting metabolic rate of junior Indian boys (n = 45) were similar to METs of 10-11-year-old children from North East England, while girls (n = 46) showed significant difference in MET with similar energy cost as 10-11-year-olds [9]. The self-paced walking MET of the total junior boys and girls in this study were significantly lower than self-paced walking of 10-11-year-old children from North East England,[9] 10-12-year-old children in youth compendium [7], 10-18-year-old from US[13] and 11-12-year-old from US [4]. Further, it was also lower than walking at 4 mph by both 8-11-year-old and 13-15-year-old from North Carolina [29]. They were only similar to 0.5 mph walking by 10-12-year-old from the youth compendium.[7] Standing MET of junior athletes in this study was significantly lower than 10-12-year-old and 13-15-year-old from the youth compendium [7]. Among training activities, jogging MET of junior athletes in both athletics and soccer events were similar to 5 mph (2.24 m/sec) jogging METs of 13-15-year-old children from North Carolina [29] and also 10-12-year-old children from US [10]. Junior athletes participating in athletics event, showed similarity across a range of METs from 8 to 8.8 for jogging at 4.5 to 5.5 mph (2.01–2.46 m/sec) of 13-15-year-old children in youth compendium [7]. Among soccer players, Joging MET of boys in the present study was comparable to running METs ranging from 7.2 to 8.1 in the youth compendium[7], while girls showed similarity to a range of 7.4 to 8.1 MET, irrespective of age category. Junior 11-year-old boys in soccer showed similarity with running MET in the range of 7.4 to 9.1 among 10-12-year-old in the youth compendium [7]. Cool down exercise METs were significantly higher among soccer players than 8–18 year-old children from US [29].
Among weight training activities, MET for push-ups of junior 11-year-old boys in soccer showed similarity to 10-12-year-old from youth compendium [7], while senior boys showed significantly higher MET. METs for activities like Bench press and Leg press among soccer players were significantly higher than youth compendium [7] and similar aged adolescents from US [29]. This higher MET for an anaerobic activity is because these activities were not carried out in isolation, but were in order of their regular protocol of starting with warm up jogging, followed by strength conditioning exercises like push-ups, crunches, jumps etc. This is also a pattern followed by athletes, and this was also a reason why the interspersed rest activities were separately measured, since they showed higher METs than regular non-training activities. Box Jump activity was compared with Jump Rope from Youth Compendium, where senior girls in soccer showed similarity in METs across both age-categories (10-12-year-old and 13-15-year-old), while junior boys showed significantly higher METs.
Although this study is limited by a smaller sample size with RMR and energy expenditure determined in a particular season and without position-specific assessment in case of soccer, it still forms a unique database for junior athletes in general and for Indian settings in particular. It could form the basis for further research on adolescent athletes and add to the database for developing an athlete specific compendium. Since, type of physical activity is most variable and important for determining energy expenditure among athletes, this will help nutritionists, researchers and other stakeholders to arrive at individualized energy needs of junior athletes using the factorial approach.
In conclusion, the energy cost and METs determined showed sex-specific differences, especially in weight training activities, this could be due to the difference in load or intensity of activities across sex. Further, a strong association was observed between METs and energy cost of activities with heart rate, indicating that any change in heart rates would reflect in changes in corresponding intensity (METs) and the energy cost. Measured METs of a majority of the non-training activities among junior athletes were similar to corresponding activity METs in the adult compendium (CPA) than children’s (CEEY). The METs specifically determined for junior athletes covered a wide range of sedentary, moderate and higher intensity activities (0.7 MET to 10.8 MET) and can be incorporated into existing compendiums for estimating energy expenditure pattern of junior athletes. Further research is warranted to validate the findings pertaining to the association between heart rate and METs and also for developing an athlete specific compendium.