High- and Low-carb Diet and Fasting State Modify Alternative Maximal
                    Accumulated Oxygen Deficit

Matheus Simionato Firmino; Matheus S. Norberto; Germano Marcolino Putti; Carolina Lemos de Oliveira; Bianka da Silva Rumayor; João Victor Gatto Torini; Marcelo Papoti

doi:10.1055/a-2373-0102

International Journal of Sports Medicine, Table of Contents

Int J Sports Med 2025; 46(02): 79-89
DOI: 10.1055/a-2373-0102

Physiology & Biochemistry

High- and Low-carb Diet and Fasting State Modify Alternative Maximal Accumulated Oxygen Deficit

Authors

Matheus Simionato Firmino

¹School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
Matheus S. Norberto

²Ribeirão Preto Medical School, Universidade de São Paulo, Ribeirão Preto, Brazil
Germano Marcolino Putti

¹School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
Carolina Lemos de Oliveira

¹School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
Bianka da Silva Rumayor

¹School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
João Victor Gatto Torini

¹School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
Marcelo Papoti

¹School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil

²Ribeirão Preto Medical School, Universidade de São Paulo, Ribeirão Preto, Brazil

Abstract

This investigation aimed to assess whether the alternative method of estimating the maximal accumulated oxygen deficit (MAOD_alt) can detect changes in energy system contribution in different substrate availabilities. Following a graded exercise test to determine maximal oxygen uptake intensity (iVO_2max), 26 recreational runners performed a time to exhaustion effort (TTE) as baseline at 110% iVO_2max. The same TTE was performed in fasting state, then, a muscle glycogen depletion protocol was executed. Subsequently, participants received a low-carbohydrate diet and beverages containing high (H-CHO, 10.8±2.1 g·kg^− 1), moderate (M-CHO, 5.6±1.1 g·kg^− 1), or zero (Z-CHO, 0.24±0.05 g·kg^− 1) carbohydrates. Another TTE was performed 24 h later. Each energy system contribution was assessed. Generalized linear mixed models were used for statistical analysis (p<0.05). H-CHO increased relative anaerobic capacity (slope effect [baseline –intervention]x[H-CHO – M-CHO]) due to the relative lactic contribution maintenance (slope effect [baseline – intervention]x[H-CHO – Z-CHO] or [H-CHO – M-CHO]) and increase in relative alactic contribution (6.3±3.5 kJ·min^− 1). The aerobic contribution was lower (− 8.7±4.0 kJ·min^− 1), decreasing performance (− 34±16 s) for H-CHO. M-CHO and Z-CHO maintained anaerobic capacity due to increase in alactic contribution (slope effect [fasting – intervention]x[M-CHO – H-CHO]; and Z-CHO was 7.3±3.4 kJ·min^− 1 higher than baseline). Fasting increased relative alactic (2.9±1.7 kJ·min^− 1) but decreased aerobic contribution (− 3.3±2.3 kJ·min^− 1), impairing performance (− 17±12 s). In conclusion, MAOD_alt can detect changes in energy system supply in different nutritional states. Therefore, participantʼs nutritional state must be considered prior to conducting the test.

Keywords

glycogen - fasting - exercise - energy metabolism - carbohydrate loading diet - carbohydrate-restricted diet

Full Text

References

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