Resting metabolic rate of Indian Junior Soccer players: Testing agreement between measured versus selected predictive equations

Cherian, Keren Susan; Shahkar, Faaiza; Sainoji, Ashok; Balakrishna, Nagalla; Yagnambhatt, Venkata Ramana

doi:10.1002/ajhb.23066

Cited by 15 publications

(11 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In accordance with changes in stature, body mass and FFM, we also observed an increase in RMR between the U12-U14 age groups (U12: 1655 ± 195 kcal.day -1 ; U13 1720 ± 205 kcal.day -1 ; U14: 1846 ± 218 kcal.day -1 ), thus highlighting the requirement to adjust total energy intake accordingly. Such data correspond with data from Indian soccer players where an increase in RMR of ~400 kcal.day -1 from the ages of 10 to 13 (Cherian et al, 2018) was also observed. It is noteworthy, however, that the RMR values in the present study are higher than those previously reported in youth soccer players.…”

Section: Discussionsupporting

confidence: 88%

“…In this regard, an assessment of RMR (a major component of total energy expenditure; TEE) at least provides a platform to begin to develop age-specific energy requirements. Indeed, data from Indian youth soccer players demonstrates that RMR increases by ~400 kcal.day -1 from the (chronological) ages of to 13 (Cherian et al, 2018). To the authors' knowledge, however, no research has yet quantified RMR in Premier League academy soccer players across the full age-range of a professional soccer academy, i.e.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cross-sectional comparison of body composition and resting metabolic rate in Premier League academy soccer players: Implications for growth and maturation

Hannon

Carney

Floyd

et al. 2020

Journal of Sports Sciences

View full text Add to dashboard Cite

show abstract

Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Cross-sectional comparison of body composition and resting metabolic rate in Premier League academy soccer players: Implications for growth and maturation

Hannon

Carney

Floyd

et al. 2020

Journal of Sports Sciences

View full text Add to dashboard Cite

show abstract

“…The differences in the value of the REE between the children from the circum and post groups were not statistically significant (p = 0.2804). These results are in agreement with the data of a previous study on Indian soccer players, where an increase in REE of about 400 kcal/day from the ages of 10 to 13 was also noticed [31]. A similar effect was observed by Hannon et al, who also showed an increase in REE between the U12 and U14 (Football Academy Categories) age groups [32].…”

Section: Discussionsupporting

confidence: 93%

The Influence of Maturity Status on Resting Energy Expenditure, Body Composition and Blood Pressure in Physically Active Children

et al. 2021

View full text Add to dashboard Cite

Peak height velocity (PHV) is the period where the maximum rate of growth occurs. The moment the sports player reaches PHV can be estimated by monitoring the growth of body structures. The aim of this study was to assess changes in resting energy expenditure (REE), body composition and blood pressure in young, male soccer players between the pre-PHV, circa-PHV and post-PHV periods. This transverse study was conducted among 184 children aged 9 to 17 and included measurements of the resting energy expenditure (REE) using indirect calorimetry, body composition (bioimpedance) and blood pressure (sphygmomanometer). In addition, births in each quartile were analyzed. Children in the pre-PHV group had significantly lower REE values compared to the other two groups (p < 0.0001). The differences in the value of the REE between the children in the circum and post groups were not statistically significant. Additionally, the fat-free mass was significantly lower in the pre-PHV period compared to the other two periods (p < 0.0001), and the same relationship concerned the z-score body mass index (BMI) and systolic blood pressure. Early-born players were overrepresented (p < 0.05).

show abstract

“…However, the IC technique is time-consuming, expensive, and, unavailable in daily practice. Accordingly, REE as well as TEE are often predicted via one of various prediction equations (Vander Weg et al, 2004;ten Haaf and Weijs, 2014;Cherian et al, 2018;Amaro-Gahete et al, 2019;Schofield et al, 2019). The Harris & Benedict (H&B), World Health Organization (WHO), Müller (MÜL), Müller-FFM (MÜL-FFM) and Cunningham (CUN) equations are most commonly used, but none of these standard prediction equations fits for every individual.…”

Section: Introductionmentioning

confidence: 99%

Resting Energy Expenditure of Master Athletes: Accuracy of Predictive Equations and Primary Determinants

et al. 2021

View full text Add to dashboard Cite

Resting energy expenditure (REE) is determined mainly by fat-free mass (FFM). FFM depends also on daily physical activity. REE normally decreases with increased age due to decreases in FFM and physical activity. Measuring REE is essential for estimating total energy expenditure. As such, there are a number of different equations in use to predict REE. In recent years, an increasing number of older adults continue to participate in competitive sports creating the surge of master athletes. It is currently unclear if these equations developed primarily for the general population are also valid for highly active, older master athletes. Therefore, we tested the validity of six commonly-used equations for predicting REE in master athletes. In conjunction with the World Masters Athletic Championship in Malaga, Spain, we measured REE in 113 master athletes by indirect calorimetry. The most commonly used equations to predict REE [Harris & Benedict (H&B), World Health Organization (WHO), Müller (MÜL), Müller-FFM (MÜL-FFM), Cunningham (CUN), and De Lorenzo (LOR)] were tested for their accuracies. The influences of age, sex, height, body weight, FFM, training hours per week, phase angle, ambient temperature, and athletic specialization on REE were determined. All estimated REEs for the general population differed significantly from the measured ones (H&B, WHO, MÜL, MÜL-FFM, CUN, all p < 0.005). The equation put forward by De Lorenzo provided the most accurate prediction of REE for master athletes, closely followed by FFM-based Cunningham’s equation. The accuracy of the remaining commonly-used prediction equations to estimate REE in master athletes are less accurate. Body weight (p < 0.001), FFM (p < 0.001), FM (p = 0.007), sex (p = 0.045) and interestingly temperature (p = 0.004) are the significant predictors of REE. We conclude that REE in master athletes is primarily determined by body composition and ambient temperature. Our study provides a first estimate of energy requirements for master athletes in order to cover adequately athletes’ energy and nutrient requirements to maintain their health status and physical performance.

show abstract

Resting metabolic rate of Indian Junior Soccer players: Testing agreement between measured versus selected predictive equations

Abstract: FFM explained variation in RMR across age and sex. The FFM-based Soares et al. (, British Journal of Nutrition, 79) equation for girls and body weight-based Wong et al. (, Singapore Medical Journal, 53) equation for boys are best suited for predicting RMR.

Cited by 15 publications

References 15 publications

Cross-sectional comparison of body composition and resting metabolic rate in Premier League academy soccer players: Implications for growth and maturation

Cross-sectional comparison of body composition and resting metabolic rate in Premier League academy soccer players: Implications for growth and maturation

The Influence of Maturity Status on Resting Energy Expenditure, Body Composition and Blood Pressure in Physically Active Children

Resting Energy Expenditure of Master Athletes: Accuracy of Predictive Equations and Primary Determinants

Contact Info

Product

Resources

About