Importance of dimensional changes on glycolytic metabolism during growth
Résumé
Purpose
The aim of the present study was to investigate (i) how glycolytic metabolism assessed by accumulated oxygen deficit (AODgly) and blood metabolic responses (lactate and pH) resulting from high-intensity exercise change during growth, and (ii) how lean body mass (LBM) influences AODgly and its relationship with blood markers.
Methods
Thirty-six 11- to 17-year olds performed a 60-s all-out test on a rowing ergometer. Allometric modelling was used to investigate the influence of LBM and LBM + maturity offset (MO) on AODgly and its relationship with the extreme post-exercise blood values of lactate ([La]max) and pH (pHmin) obtained during the recovery period.
Results
AODgly and [La]max increased while pHmin decreased linearly with LBM and MO (r2 = 0.46 to 0.72, p < 0.001). Moreover, AODgly was positively correlated with [La]max (r2 = 0.75, p < 0.001) and negatively correlated with pHmin (r2 = 0.77, p < 0.001). When AODgly was scaled for LBM, the coefficients of the relationships with blood markers drastically decreased by three to four times ([La]max: r2 = 0.24, p = 0.002; pHmin: r2 = 0.30, p < 0.001). Furthermore, by scaling AODgly for LBM + MO, the correlation coefficients with blood markers became even lower ([La]max: r2 = 0.12, p = 0.037; pHmin: r2 = 0.18, p = 0.009). However, MO-related additional changes accounted much less than LBM for the relationships between AODgly and blood markers.
The aim of the present study was to investigate (i) how glycolytic metabolism assessed by accumulated oxygen deficit (AODgly) and blood metabolic responses (lactate and pH) resulting from high-intensity exercise change during growth, and (ii) how lean body mass (LBM) influences AODgly and its relationship with blood markers.
Methods
Thirty-six 11- to 17-year olds performed a 60-s all-out test on a rowing ergometer. Allometric modelling was used to investigate the influence of LBM and LBM + maturity offset (MO) on AODgly and its relationship with the extreme post-exercise blood values of lactate ([La]max) and pH (pHmin) obtained during the recovery period.
Results
AODgly and [La]max increased while pHmin decreased linearly with LBM and MO (r2 = 0.46 to 0.72, p < 0.001). Moreover, AODgly was positively correlated with [La]max (r2 = 0.75, p < 0.001) and negatively correlated with pHmin (r2 = 0.77, p < 0.001). When AODgly was scaled for LBM, the coefficients of the relationships with blood markers drastically decreased by three to four times ([La]max: r2 = 0.24, p = 0.002; pHmin: r2 = 0.30, p < 0.001). Furthermore, by scaling AODgly for LBM + MO, the correlation coefficients with blood markers became even lower ([La]max: r2 = 0.12, p = 0.037; pHmin: r2 = 0.18, p = 0.009). However, MO-related additional changes accounted much less than LBM for the relationships between AODgly and blood markers.
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