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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

Matheus Simionato Firmino 
1   School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
,
Matheus S. Norberto
2   Ribeirão Preto Medical School, Universidade de São Paulo, Ribeirão Preto, Brazil
,
Germano Marcolino Putti 
1   School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
,
Carolina Lemos de Oliveira
1   School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
,
Bianka da Silva Rumayor
1   School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
,
João Victor Gatto Torini
1   School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
,
Marcelo Papoti
1   School of Physical Education and Sports of Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, Brazil
2   Ribeirão Preto Medical School, Universidade de São Paulo, Ribeirão Preto, Brazil
› Author Affiliations Funding Information Fundação de Amparo à Pesquisa do Estado de São Paulo — http://dx.doi.org/10.13039/501100001807; 2021/14576-8
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Abstract

This investigation aimed to assess whether the alternative method of estimating the maximal accumulated oxygen deficit (MAODalt) can detect changes in energy system contribution in different substrate availabilities. Following a graded exercise test to determine maximal oxygen uptake intensity (iVO2max), 26 recreational runners performed a time to exhaustion effort (TTE) as baseline at 110% iVO2max. 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, MAODalt 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


Publication History

Received: 10 May 2024

Accepted: 23 July 2024

Accepted Manuscript online:
25 July 2024

Article published online:
20 November 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Hargreaves M, Spriet LL. Skeletal muscle energy metabolism during exercise. Nat Metab 2020; 2: 817-828
    CrossrefPubMedSearch in Google Scholar
  • 2 Noordhof DA, Skiba PF, De Koning JJ. Determining anaerobic capacity in sporting activities. Int J Sports Physiol Perform 2013; 8: 475-482
    CrossrefPubMedSearch in Google Scholar
  • 3 Foster C, Dekoning JJ, Hettinga F. et al. Effect of competitive distance on energy expenditure during simulated competition. Int J Sports Med 2004; 25: 198-204
    Thieme ConnectPubMedSearch in Google Scholar
  • 4 Rønnestad BR, Mujika I. Optimizing strength training for running and cycling endurance performance: A review. Scand J Med Sci Sports 2014; 24: 603-612
    CrossrefPubMedSearch in Google Scholar
  • 5 Spencer MR, Gastin PB. Energy system contribution during 200- to 1500-m running in highly trained athletes. Med Sci Sports Exerc 2001; 33: 157-162
    CrossrefPubMedSearch in Google Scholar
  • 6 Losnegard T, Myklebust H, Hallén J. Anaerobic capacity as a determinant of performance in sprint skiing. Med Sci Sports Exerc 2012; 44: 673-681
    CrossrefPubMedSearch in Google Scholar
  • 7 Medbø JI, Sejersted OM. Acid-base and electrolyte balance after exhausting exercise in endurance-trained and sprint-trained subjects. Acta Physiol Scand 1985; 125: 97-109
    CrossrefPubMedSearch in Google Scholar
  • 8 Green S, Dawson B. Measurement of Anaerobic Capacities in Humans: Definitions, Limitations and Unsolved Problems. Sports Med 1993; 15: 312-327
    CrossrefPubMedSearch in Google Scholar
  • 9 Duffield R, Dawson B, Goodman C. Energy system contribution to 100-m and 200-m track running events. J Sci Med Sport 2004; 7: 302-313
    CrossrefPubMedSearch in Google Scholar
  • 10 Medbø JI. Is the Maximal Accumulated Oxygen Deficit an Adequate Measure of the Anaerobic Capacity?. Can J Appl Physiol 1996; 21: 370-383
    CrossrefPubMedSearch in Google Scholar
  • 11 Medbø JI, Mohn AC, Tabata I. et al. Anaerobic capacity determined by maximal accumulated O2 deficit. J Appl Physiol 1988; 64: 50-60
    CrossrefPubMedSearch in Google Scholar
  • 12 Noordhof DA, De Koning JJ, Foster C. The maximal accumulated oxygen deficit method: A valid and reliable measure of anaerobic capacity?. Sports Med 2010; 40: 285-302
    CrossrefPubMedSearch in Google Scholar
  • 13 Bertuzzi R, Kiss MAPDM, Damasceno M. et al. Association between anaerobic components of the maximal accumulated oxygen deficit and 30-second Wingate test. Braz J Med Biol Res 2015; 48: 261-266
    CrossrefPubMedSearch in Google Scholar
  • 14 Haseler LJ, Hogan MC, Richardson RS. Skeletal muscle phosphocreatine recovery in exercise-trained humans is dependent on O2 availability. J Appl Physiol 1999; 86: 2013-2018
    CrossrefPubMedSearch in Google Scholar
  • 15 Margaria R, Edwards HT, Dill DB. The Possible Mechanisms of Contracting and Paying the Oxygen Debt and the Role of Lactic Acid in Muscular Contraction. Am J Physiol Leg Cont 1933; 106: 689-715
    CrossrefPubMedSearch in Google Scholar
  • 16 Di Prampero PE, Ferretti G. The energetics of anaerobic muscle metabolism: A reappraisal of older and recent concepts. Respir Physiol 1999; 118: 103-115
    CrossrefPubMedSearch in Google Scholar
  • 17 Bertuzzi RCM, Franchini E, Ugrinowitsch C. et al. Predicting MAOD using only a supramaximal exhaustive test. Int J Sports Med 2010; 31: 477-481
    Thieme ConnectPubMedSearch in Google Scholar
  • 18 Zagatto AM, Nakamura FY, Milioni F. et al. The sensitivity of the alternative maximal accumulated oxygen deficit method to discriminate training status. J Sports Sci 2017; 35: 2453-2460
    CrossrefPubMedSearch in Google Scholar
  • 19 Zagatto AM, Redkva PE, de Poli RAB. et al. 3-Min All-Out Effort on Cycle Ergometer Is Valid To Estimate the Anaerobic Capacity By Measurement of Blood Lactate and Excess Post-Exercise Oxygen Consumption. Eur J Sport Sci 2019; 19: 645-652
    CrossrefPubMedSearch in Google Scholar
  • 20 Zagatto AM, Bertuzzi R, Miyagi WE. et al. MAOD determined in a single supramaximal test: A study on the reliability and effects of supramaximal intensities. Int J Sports Med 2016; 37: e9
    Thieme ConnectPubMedSearch in Google Scholar
  • 21 Zagatto AM, Gobatto CA. Relationship between anaerobic parameters provided from Maod and critical power model in specific table tennis test. Int J Sports Med 2012; 33: 613-620
    Thieme ConnectPubMedSearch in Google Scholar
  • 22 Bertuzzi RC, de M Franchini E, Kokubun E. et al. Energy system contributions in indoor rock climbing. Eur J Appl Physiol 2007; 101: 293-300
    CrossrefPubMedSearch in Google Scholar
  • 23 Campos EZ, Kalva-Filho CA, Silva MS. et al. Anaerobic Contribution Determined in Free-Swimming: Sensitivity to Maturation Stages and Validity. Front Sports Act Living 2022; 4
    CrossrefPubMedSearch in Google Scholar
  • 24 Kalva-Filho CA, Campos EZ, Andrade VL. et al. Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance. Biol Sport 2015; 32: 333-337
    CrossrefPubMedSearch in Google Scholar
  • 25 Kalva-Filho CA, Zagatto AM, Da Silva ASR. et al. Relationships among the Tethered 3-min All-Out Test, MAOD and Swimming Performance. Int J Sports Med 2017; 38: 353-358
    Thieme ConnectPubMedSearch in Google Scholar
  • 26 Panissa VLG, Fukuda DH, Caldeira RS. et al. Is oxygen uptake measurement enough to estimate energy expenditure during high-intensity intermittent exercise? Quantification of anaerobic contribution by different methods. Front Physiol 2018; 9
    CrossrefPubMedSearch in Google Scholar
  • 27 Dos Santos Alves I, Kalva-Filho CA, Aquino R. et al. Relationships between aerobic and anaerobic parameters with game technical performance in elite goalball athletes. Front Physiol 2018; 9
    CrossrefPubMedSearch in Google Scholar
  • 28 Foresti YF, Higino WP, De Carvalho CD. et al. Can Hypoxia Alter the Anaerobic Capacity Measured by a Single Exhaustive Exercise?. Int J Sports Med 2022; 44: 961-968
    PubMedSearch in Google Scholar
  • 29 Putti GM, Costa GP, Norberto MS. et al. Use of Inter-Effort Recovery Hypoxia as a New Approach to Improve Anaerobic Capacity and Time to Exhaustion. High Alt Med Biol 2024; 25: 68-76
    CrossrefPubMedSearch in Google Scholar
  • 30 Brisola GMP, Miyagi WE, da Silva HS. et al. Sodium bicarbonate supplementation improved MAOD but is not correlated with 200 and 400m running performances: A double blind, crossover and placebo controlled study. Appl Physiol Nutr Metab 2015; 40: 931-937
    CrossrefPubMedSearch in Google Scholar
  • 31 Norberto MS, Barbieri RA, Bertucci DR. et al. Beta alanine supplementation effects on metabolic contribution and swimming performance. J Int Soc Sports Nutr 2020; 17: 1-9
    CrossrefPubMedSearch in Google Scholar
  • 32 Correia-Oliveira CR, Santos RA, Silva-Cavalcante MD. et al. Prior low- or high-intensity exercise alters pacing strategy, energy system contribution and performance during a 4-km cycling time trial. PLoS One 2014; 9: 1-9
    CrossrefPubMedSearch in Google Scholar
  • 33 Lima-silva AE, Pires FO, Bertuzzi R. et al. Effects of a low- or a high-carbohydrate diet on performance, energy system contribution, and metabolic responses during supramaximal exercise. Appl Physiol Nutr Metab 2013; 38: 928-934
    CrossrefPubMedSearch in Google Scholar
  • 34 Hearris MA, Hammond KM, Fell JM. et al. Regulation of muscle glycogen metabolism during exercise: Implications for endurance performance and training adaptations. Nutrients 2018; 10: 1-21
    CrossrefPubMedSearch in Google Scholar
  • 35 Gollnick PD, Armstrong RB, Sembrowich WL. et al. Glycogen depletion pattern in human skeletal muscle fibers after heavy exercise. J Appl Physiol 1973; 34: 615-618
    CrossrefPubMedSearch in Google Scholar
  • 36 De Feo P, Di Loreto C, Lucidi P. et al. Metabolic response to exercise. J Endocrinol Invest 2003; 26: 851-854
    CrossrefPubMedSearch in Google Scholar
  • 37 Cahill GF, Herrera MG, Morgan AP. et al. Hormone-Fuel Interrelationships during Fasting. J Clin Invest 1966; 45: 1751-1769
    CrossrefPubMedSearch in Google Scholar
  • 38 Iwayama K, Onishi T, Maruyama K. et al. Diurnal variation in the glycogen content of the human liver using 13C MRS. NMR Biomed 2020; 33
    CrossrefPubMedSearch in Google Scholar
  • 39 Shiose K, Yamada Y, Motonaga K. et al. Segmental extracellular and intracellular water distribution and muscle glycogen after 72-h carbohydrate loading using spectroscopic techniques. J Appl Physiol 2016; 121: 205-211
    CrossrefPubMedSearch in Google Scholar
  • 40 Ferreira VR, Bento APN, Silva MR. Consumo alimentar, perfil antropométrico e conhecimentos em nutrição de corredores de rua. Rev Bras Med Esporte 2015; 21: 457-461
    CrossrefPubMedSearch in Google Scholar
  • 41 Goston JL, Mendes LL. Nutritional Profile of Street Runners from a Sports Club in Belo Horizonte city, MG, Brazil. Rev Bras Med Esporte 2011; 17: 13-17
    PubMedSearch in Google Scholar
  • 42 Jeukendrup AE. Carbohydrate and exercise performance : The role of multiple transportable carbohydrates. Curr Opin Clin Nutr Metab Care 2010; 13: 452-457
    CrossrefPubMedSearch in Google Scholar
  • 43 Bussau VA, Fairchild ÆTJ, Rao ÆA. et al. Carbohydrate loading in human muscle : An improved 1 day protocol. Eur J Appl Physiol 2002; 87: 290-295
    CrossrefPubMedSearch in Google Scholar
  • 44 Fairchild TJ, Fletcher S, Steele P. et al. Rapid carbohydrate loading after a short bout of near maximal-intensity exercise. Med Sci Sports Exerc 2002; 34: 980-986
    CrossrefPubMedSearch in Google Scholar
  • 45 Kerksick C, Harvey T, Stout J. et al. International society of sports nutrition position stand: Nutrient timing. J Int Soc Sports Nutr 2017; 14: 33
    CrossrefPubMedSearch in Google Scholar
  • 46 Bertuzzi R, Melegati J, Bueno S. et al. GEDAE-LaB: A free software to calculate the energy system contributions during exercise. PLoS One 2016; 11
    CrossrefPubMedSearch in Google Scholar
  • 47 Manetta J, Brun JF, Perez-Martin A. et al. Fuel oxidation during exercise in middle-aged men: Role of training and glucose disposal. Med Sci Sports Exerc 2002; 33: 423-429
    CrossrefPubMedSearch in Google Scholar
  • 48 Gallucci M. gamlj: GAMLj Suite for linear models. https://www.gamlj.github.io/ Accessed 2024
    PubMed
  • 49 Hawley JA, Schabort EJ, Noakes TD. et al. Carbohydrate-loading and exercise performance. Sports Med 1997; 24: 73-81
    CrossrefPubMedSearch in Google Scholar
  • 50 Namma-Motonaga K, Kondo E, Osawa T. et al. Effect of Different Carbohydrate Intakes within 24 Hours after Glycogen Depletion on Muscle Glycogen Recovery in Japanese Endurance Athletes. Nutrients 2022; 14: 1320
    CrossrefPubMedSearch in Google Scholar
  • 51 Kiens B, Richter EA. Utilization of skeletal muscle triacylglycerol during postexercise recovery in humans. Am J Physiol Endocrinol Metab 1998; 275: E332-337
    CrossrefPubMedSearch in Google Scholar
  • 52 Cherif A, Meeusen R, Farooq A. et al. Three Days of Intermittent Fasting: Repeated-Sprint Performance Decreased by Vertical-Stiffness Impairment. Int J Sports Physiol Perform 2017; 12: 287-294
    CrossrefPubMedSearch in Google Scholar
  • 53 Loy SF, Conlee RK, Winder WW. et al. Effects of 24-hour fast on cycling endurance time at two different intensities. J Appl Physiol 1986; 61: 654-659
    CrossrefPubMedSearch in Google Scholar
  • 54 Gleeson M, Greenhaff PL, Maughan RJ. Influence of a 24 h fast on high intensity cycle exercise performance in man. Eur J Appl Physiol Occup Physiol 1988; 57: 653-659
    CrossrefPubMedSearch in Google Scholar