Efeitos do enxague bucal com hidratos de carbono no desempenho de triatletas numa prova de ciclismo de 40 km

https://orcid.org/0000-0001-7668-6131

ronaldoedfisica@gmail.com

evelynmaia9@yahoo.com.br

https://orcid.org/0000-0001-7554-1926

lucianosalesprado@hotmail.com

https://orcid.org/0000-0002-0755-6138

marcosedfisio@gmail.com

https://orcid.org/0000-0001-6089-8375

reginaldociclismo@hotmail.com

https://orcid.org/0000-0002-5622-1297

zangmarcos@gmail.com

(Brasil)

Reception: 07/02/2026 - Acceptance: 10/07/2026

1st Review: 09/19/2026 - 2nd Review: 10/03/2026

Accessible document. Law N° 26.653. WCAG 2.0

Suggested reference: Silva, R.A.D. da, Assis, E.S.M. de, Prado, L.S., Santos, M.A.P. dos, Gonçalves, R., & Drummond, M.D.M. (2026). Effects of Carbohydrate Mouthwash on 40 Km Cycling Performance in Triathlete. Lecturas: Educación Física y Deportes, 31(342), 149-165. https://doi.org/10.46642/efd.v31i342.9026

 

Abstract

    The aim of this study was to investigate the effects of carbohydrate mouth rinse on triathletes’ performance in a 40 km cycling test, following 1.5km swim. In the randomized, blinded, and crossover experimental design, thirteen male triathletes (age: 29.69 ± 7.8 years; training experience: 2.5 ± 1.19 years; VO2max: 51.33 ± 6.04 ml.kg^-1.min^-1) performed a time trial with self-regulated speed in two conditions: placebo mouth rinse (PLA) and carbohydrate mouth rinse (CHO). The results showed no significant differences in the mean durations of the time trial (PLA: 72min13s ± 3min30s and CHO: 72min55s ± 3min20s; p = 0.789; d = 0.08), relative power output (PLA: 2.74 ± 0.23w/kg; CHO: 2.74 ± 0.25w/kg; p = 0.945; d = 0.02), mean speed (PLA: 33.04 ± 1.28km/h; CHO: 32.98 ± 1.21km/h; p = 0.785; d = 0.09), mean Heart Rate (PLA: 148.00 ± 11.51bpm; CHO: 149.00 ± 10.78bpm), and Rate of Perceived Exertion (PLA: 5.41 ± 0.99; CHO: 5.50 ± 1.22; p = 0.704; d = 0.08). In conclusion, carbohydrate mouth rinse may not be effective to improve performance in triathletes.

    Keywords: Athletic performance. Endurance. Ergogenic resource. Sports nutrition science supplementation. Triathletes.

 

Resumen

    El objetivo de este estudio fue investigar los efectos del enjuague bucal con carbohidratos en el rendimiento de triatletas en una prueba de ciclismo de 40 km, tras nadar 1,5 km. En un diseño experimental aleatorizado, ciego y cruzado, trece triatletas varones (edad: 29,69 ± 7,8 años; experiencia de entrenamiento: 2,5 ± 1,19 años; VO2máx: 51,33 ± 6,04 ml·kg⁻¹·min⁻¹) realizaron una contrarreloj con velocidad autorregulada en dos condiciones: enjuague bucal placebo (PLA) y enjuague bucal con carbohidratos (CHO). Los resultados no mostraron diferencias significativas en las duraciones medias de la prueba contrarreloj (PLA: 72 min 13 s ± 3 min 30 s y CHO: 72 min 55 s ± 3 min 20 s; p = 0,789; d = 0,08), la potencia relativa (PLA: 2,74 ± 0,23 W/kg; CHO: 2,74 ± 0,25 W/kg; p = 0,945; d = 0,02), la velocidad media (PLA: 33,04 ± 1,28 km/h; CHO: 32,98 ± 1,21 km/h; p = 0,785; d = 0,09), la frecuencia cardíaca media (PLA: 148,00 ± 11,51 lpm; CHO: 149,00 ± 10,78 lpm) y la frecuencia cardíaca de Esfuerzo Percibido (PLA: 5,41 ± 0,99; CHO: 5,50 ± 1,22; p = 0,704; d = 0,08). En conclusión, el enjuague bucal con carbohidratos podría no ser efectivo para mejorar el rendimiento en triatletas.

    Palabras clave: Rendimiento atlético. Resistencia. Recursos ergogénicos. Nutrición deportiva. Suplementación. Triatletas.

 

Resumo

    O objetivo deste estudo foi investigar os efeitos do enxague bucal com carboidratos no desempenho de triatletas em um teste de ciclismo de 40 km, após 1,5 km de natação. Em um delineamento experimental randomizado, cego e cruzado, treze triatletas do sexo masculino (idade: 29,69 ± 7,8 anos; experiência de treinamento: 2,5 ± 1,19 anos; V̇O2máx: 51,33 ± 6,04 ml.kg^-1.min^-1) realizaram uma prova de tempo com velocidade autorregulada em duas condições: enxague bucal placebo (PLA) e enxague bucal com carboidratos (CHO). Os resultados não mostraram diferenças significativas na duração média da prova de tempo (PLA: 72 min 13 s ± 3 min 30 s e CHO: 72 min 55 s ± 3 min 20 s; p = 0,789; d = 0,08), na potência relativa (PLA: 2,74 ± 0,23 W/kg; CHO: 2,74 ± 0,25 W/kg; p = 0,945; d = 0,02), na velocidade média (PLA: 33,04 ± 1,28 km/h; CHO: 32,98 ± 1,21 km/h; p = 0,785; d = 0,09), na frequência cardíaca média (PLA: 148,00 ± 11,51 bpm; CHO: 149,00 ± 10,78 bpm) e na frequência cardíaca de Percepção de Esforço (PLA: 5,41 ± 0,99; CHO: 5,50 ± 1,22; p = 0,704; d = 0,08). Em conclusão, o enxague bucal com carboidratos pode não ser eficaz para melhorar o desempenho em triatletas.

    Unitermos: Desempenho atlético. Resistência. Recurso ergogênico. Suplementação em nutrição esportiva. Triatletas.

 

Lecturas: Educación Física y Deportes, Vol. 31, Núm. 342, Nov. (2026)

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Introduction 

 

    Triathlon is a sport that involves three modalities, swimming, cycling, and running (Ambrosini et al., 2022; García-Giménez, 2024). This sport has distinct official distances, including Sprint, Long Distance, Mixed Relay, Half Ironman, and Olympic. In the Olympic competition, athletes perform 1.5 km of swimming, 40 km of cycling and 10km of running (World Triathlon, 2023; Duric et al., 2024). Therefore, a determining factor in triathlon is the athlete's ability to produce and efficiently utilize large amounts of energy for extended periods (Ambrosini et al., 2022; García-Giménez, 2024). This requires nutritional strategies to provide adequate substrates to meet energy demands, while also aiding cognitive function, reducing, or delaying factors that would cause fatigue. (Morton et al., 2026; Grivas, & Alkasasbeh, 2026)

 

    The performance of prolonged high-intensity exercise is enhanced with strategies that maintain high carbohydrate availability, through mechanisms that spare glycogen stores, prevent hypoglycemia, and activate reward centers in the central nervous system (Morton et al., 2026; Grivas, & Alkasasbeh, 2026). It is important to highlight the limited size of glycogen stores in the body, which can be influenced by food intake and/or training (Silva et al., 2014; Miguel-Ortega et al., 2025). The depletion of these reserves is associated with fatigue, impaired ability and concentration, and an increased perception of effort. (Morton et al., 2026; Grivas, & Alkasasbeh, 2026)

 

    Therefore, the intake of carbohydrates is one of the most important nutritional strategies, playing a crucial role in training adaptation and performance, especially in endurance sports (Silva et al., 2014; Miguel-Ortega et al., 2025). Several studies demonstrate that regardless of the distance, dehydration and carbohydrate depletion are the most likely causes of fatigue, while gastrointestinal issues, hyperthermia, and hyponatremia are potentially health-threatening, especially in longer events such as triathlon. (Morton et al., 2026; Miguel-Ortega et al., 2025)

 

    However, carbohydrate intake increases the potential incidence of gastrointestinal issues such as bloating, flatulence, and the urge to defecate (Sareban et al., 2016). These issues appear to be individual and may be genetically determined, but they can also be related to the consumption of hyperosmotic beverages, particularly solutions highly concentrated in carbohydrates. (Jeukendrup et al., 2005; Jeukendrup, 2011)

 

    To avoid gastrointestinal discomfort and increase performance, studies have started to explore the carbohydrate mouth rinse as an alternative ergogenic resource in the prolonged exercise (Hartley et al., 2024; Silva et al., 2014). Carbohydrate mouth rinse is initially defined as the distribution of carbohydrate fluids, with a 6.0 to 6.4 % concentration, around the mouth for approximately 5 to 10 seconds, followed by subsequent removal of the liquid (Silva et al., 2014; Hartley et al., 2024; Deng et al., 2025). It was expected that the carbohydrate mouth rinse stimulates brain regions involved in reward and motor control (Deng et al., 2025). Another study demonstrated that carbohydrate mouth rinse with a 16 % concentration could increase oral receptor saturation, leading to greater stimulation of reward pathways (Devenney et al., 2016; Painelli et al., 2022). These effects can occur without carbohydrate ingestion and consequently gastrointestinal issues.

 

    The carbohydrate mouth rinse has been the subject of studies in association with performance in various sports and exercises (Deng et al., 2025), such as cycling (Jeukendrup, 2011; Pires, 2018), running (Chryssanthopoulos et al., 2018), and strength tests (Karayigit et al., 2021). The study by Carter et al. (2004) report performance improvement in a 1-hour cycling time trial with carbohydrate mouth rinsing, with reduction in test duration and an increase in average power compared to a placebo. Equivalent results were found in other studies (Deng et al., 2025). Brietzke et al. (2019), in a meta-analysis that analyzed 13 studies aiming to find an improvement in mean power, but not in the time to complete the cycling time trial.

 

    Therefore, the literature indicates that carbohydrate mouth rinse could be an effective alternative for enhancing performance in triathlon, avoiding gastrointestinal discomfort. However, no studies were identified that specifically investigated this topic or examined the combination of modalities commonly included in triathlon. In this regard, the present study aims to advance the evaluation of the effect of carbohydrate mouth rinse on triathletes’ performance. Therefore, the aim of the present study was to analyse the effects of carbohydrate mouth rinse on the performance of the cycling time trial in triathletes, following a swimming session. The hypotheses were that carbohydrate mouth rinsing can enhance triathletes’ performance and/or reduce subjective perception of effort.

 

Methods 

 

Ethical approval 

 

    This study was submitted and approved by the Ethics and Research Committee of the Universidade Federal de Minas Gerais (CAAE: 52927621.0.0000.5149).

 

Sample 

 

    The present study involved 13 male triathlon athletes (29.75 ± 8.15 years age; training experience: 2.5 ± 1.19 years; total body mass: 72.08 ± 5.86 kg; body fat: 11.53 ± 4.29 %; height: 1.75 ± 0.07m; VO2max: 52.10 ± 5.62 ml.kg^-1.min^-1).

 

    As an inclusion criterion, athletes were required to have a minimum of 12 months of triathlon practice experience, with a history of participating in national competitions in this sport. The exclusion criteria were sustaining an injury during the study, not maintaining the standard diet, and started consuming supplements.

 

Procedures 

 

    This study utilized a balanced, randomized, double- blind design. The tests were conducted during a non-competitive period and consisted of two sessions, with a 7-day interval between them, all performed on the participants' own bicycles. Participants were instructed to maintain their regular diet and sleep routine, as well as abstain from physical activity for a 24-hour period prior to the test. The HOOPER index was used to verify the status of recovery of the volunteers before the tests started. (Hooper, & MacKinnon, 1995)

To measure body mass and height, athletes were instructed to step barefoot onto the Digital Welmy® scale (Welmy Indústria e Comércio Ltda., Brazil), with an accuracy of 0.02kg, and a built-in stadiometer with an accuracy of 0.5cm. Skinfold measurements were taken using the Lange Skinfold Caliper (USA®), following the Jackson and Pollock seven-site skinfold protocol. (Jackson, & Pollock, 1978)

 

    To ensure similar nutritional conditions in both experimental conditions, a 24-hour dietary recall was conducted prior to the tests using an app (Dietbox Informática Ltd., version 7.8.1, Brazil). The tables used for the recall calculations were the Brazilian Table of Food Composition (TACO), the Nutritional Composition Table of Foods Consumed in Brazil (IBGE), and the Sonia Tucunduva Philippi Table. (Silva et al., 2020)

 

    Their athlete’s maximal oxygen uptake was measured by an incremental test using a training roller (Computrainer, Racermate, USA). The test started at 100 watts and increased by 20watts every minute until fatigue, and the athletes were free to choose their own cadence throughout the test (Balke, & Ware, 1959). The respiratory gas exchanges were recorded by the gas analyzer (HandyMET – MDI Industrial, Brazil).

 

    The performance test protocol was a 40km cycling time-trial, with self-regulated speed and cadence, performed after a 1.5km swimming in an Olympic-sized swimming pool. The transition between swimming and cycling was 5 minutes. The athletes' water intake during the test was ad libitum, and the laboratory temperature was controlled between 21°C and 23°C. No incentives were offered during the test, and the athletes were only informed about the distance covered. These procedures were adopted to simulate the Olympic competition. Furthermore, the cycling time-trial test was selected because it represents the most suitable condition for carbohydrate mouth rinsing, given that bicycles are equipped with bottle holders that facilitate its administration. The running was not performed in this study because nutritional strategies are more difficult to perform and less usual in this modality in Triathlon.

 

    The volunteers received randomized, blinded, and crossover the administration of a 25ml bolus of placebo using a calorie-free sweetener with 0 % carbohydrate or a 25ml bolus with 16 % carbohydrate that contained maltodextrin. This solution was rinsed and remained in the mouth for 5 seconds and was administered at every 5km interval of the distance covered (Devenney et al., 2016). To ensure that the participants were unable to distinguish the samples, a taste test was conducted prior to the study, and the beverages were offered in opaque cups in a blind manner.

 

    At the beginning and end of the time trials, capillary blood glucose levels of the volunteers were measured using the FreeStyle glucometer (Abbott Laboratories of Brazil Ltda, Brazil). Capillary lactate was collected using the Accutrend lactate analyzer (Roche Diagnostics, Switzerland) at rest (pre-swimming), after swimming (pre-cycling), and after the cycling (post-cycling). The mechanical variables analysed during the tests were mean speed (km/h) and relative power output (w/kg), recorded at two moments during the time trial: before the start of the exertion protocol (relative power output pre) and at the end of the time trial (relative power output pos), with the aim of considering the variation in the athletes' total body mass. The rate of perceived exertion (RPE, 0-10) and heart rate (HR) were evaluated using the Polar H10 heart rate monitor (Polar Electro Ltd., Brazil) and measured after 5 km and 40 km of cycling. The time spent swimming was recorded to determine if there were any significant differences that could influence the results of the cycling test.

 

Statistical analysis 

 

    The data were expressed as mean and standard deviation. Normality and sphericity of the data were assessed using the Shapiro-Wilk and Mauchly tests, respectively. Student's t-test or the non-parametric Wilcoxon test was used for the mean speed, relative power, and duration of the time trial, swimming duration, and food intake. Furthermore, a two-way repeated measures ANOVA (time x condition) was used for the variables RPE and HR means at 5km and 40km of cycling, lactate, and blood glucose. Bonferroni post-hoc analysis, when applicable, was used to identify where the differences occurred. The adopted significance level was α = 0.05. The effect size (d) was calculated according to Cohen (1998), with classifications as follows: insignificant (<0.19), small (0.20 - 0.49), medium (0.50 - 0.79), and large (0.80 - 1.29) (20). Statistical analysis was performed using SSPS software version 2.0.

 

Results 

 

    There was no significant difference between the mean durations of the cycling time trial, expressed in minutes (PLA: 72min13s ± 3min30s and CHO: 72min55s ± 3min20s; p = 0.789; d = 0.08). Furthermore, there was also no statistically significant difference in relative power output pre (PLA: 2.71 ± 0.22w/kg; CHO: 2.71 ± 0.25w/kg; p = 0.973; d = 0.01), or post (PLA: 2.74 ± 0.23w/kg; CHO: 2.74 ± 0.25w/kg; p = 0.945; d = 0.02), and mean speed (PLA: 33.04 ± 1.28km/h; CHO: 32.98 ± 1.21km/h; p = 0.785; d = 0.09) in the time trial. The Figure 1 below show these results.

 

Notes: 1A: durations of the cycling time trial; 1B: relative power output; 1C: Mean Speed; PLA: Placebo;

CHO: carbohydrate; Pre: relative power output pre; Post: relative power output post. Source: Authors

 

    For the RPE, there was no significant difference (p = 0.704; d = 0.08) between the PLA (5.41 ± 0.99) and CHO (5.50 ± 1.22). However, in the PLA condition, the mean RPE was significantly higher (p = 0.001; d = 2.88) at the 40km (8.15 ± 1.34) compared to the 5km (3.61 ± 1.50). Similarly, in the CHO condition, the mean RPE was significantly higher (p = 0.001; d = 3.36) at the 40km (8.23 ± 1.36) compared to the 5km (3.76 ± 1.30). There were no significant differences in the mean RPE between the experimental conditions at the 5km (p = 0.548) or the 40km (p = 0.749).

 

    Among the experimental conditions, no significant differences were found between the lactate concentrations pre swimming (p = 0.186; d = 1.56), pre-cycling (p = 0.276; d = 0.6), and post-cycling (p = 0.685; d = 0.35). The blood glucose levels also showed no significant differences between the experimental conditions, pre-cycling (p = 0.315; d = 1.27) and post-cycling (p = 0.475; d = 1.01). Regarding the mean heart rate there was no significant difference (p = 0.422; d = 0.09) between the conditions. The values are shown in Table 1 below.

 

    In the PLA condition, lactate concentration was statistically higher at pre-cycling (p = 0.005; d = 5.80) and post-cycling (p = 0.028; d = 4.53) compared to pre-swimming. However, there was no difference between pre-cycling and post-cycling (p = 1.000; d = 0.59). In the CHO condition, lactate concentration was statistically higher at pre-cycling (p = 0.004; d = 6.20) compared to pre-swimming. There was no significant difference between post-cycling (p = 0.062; d = 3.95) and pre-swimming, and between pre-cycling (p = 0.749; d = 1.22) and post-cycling moments. Regarding blood glucose, in the PLA condition, there was no difference between the pre-cycling and post-cycling moments (p = 1.000; d = 1.11). Similarly, there was no difference between the pre-cycling moment (p = 0.721; d = 1.44) and the post-cycling moment in the CHO condition. In the PLA condition, the mean HR at the 5km moment was significantly lower (p = 0.009; d = 0.87) compared to the mean HR at the 40km moment. Similarly, in the CHO condition, the mean HR at the 5km moment was significantly lower (p = 0.037; d = 0.72) compared to the mean HR at the 40km moment of the time trial. When analysing the 5km and 40km moments between the PLA and CHO conditions, no statistical differences were found (p = 0.415; p = 0.864, respectively). The values are shown in Table 1 below.

 

	PLA	CHO
[Lac] pre swim	2.52±0.15	2.30±0.13
[Lac] pre cycling	4.94±0.57*	4.61±0.51*
[Lac] post cycling	5.38±0.88*	5.76±1.23
BG pre cycling	92.00±2.01	95.53±3.35
BG post cycling	89.69±2.14	91.61±1.85
HR mean	148.00±11.51	149,00±10.78
HR 5km	147,30±14.41	149.38±13.82
HR 40km	159.38±13.11#	159.76±14.83#

Note: [Lac]: lactate concentration; BG: Blood Glucose; HR: Heart Rate; *Statistically significant difference compared

to the pre-swimming moment; #Statistically significant difference compared to the 5km moment. Source: Authors

 

    In both experimental conditions, there were no statistically significant differences in the amount of energy intake (kcal/kg) during the intervention (PLA: 30.96 ± 7.15; CHO: 32.80 ± 12.51; p = 0.224; d = 0.18). Additionally, there was no difference in macronutrient intake (g/kg), carbohydrates (PLA: 4.19 ± 1.87; CHO: 4.01 ± 1.41; p = 0.188; d = 0.10), proteins (PLA: 1.56 ± 0.47; CHO: 1.55 ± 0.55; p = 0.108; d = 0.02), and lipids (PLA: 1.07 ± 0.40; CHO: 1.17 ± 0.75; p = 0.989; d = 0.16).

 

    The total duration of swimming in the PLA (28min09s ± 5min31s) and CHO conditions (28min58s ± 6min23s) did not show a statistically significant difference between the conditions (p = 0.409; d = 0.08). On the Hooper scale, there were no statistically significant differences in the variables of sleep (PLA: 2.69 ± 1.31; CHO: 2.38 ± 1.38; p = 0.21; d = 0.23), stress (PLA: 2.69 ± 1.10; CHO: 3.15 ± 1.40; p = 0.25; d = 0.36), fatigue (PLA: 3.07±1.03; CHO: 3.46±1.50; p = 0.42; d = 0.30), and pain (PLA: 2.53 ± 1.33; CHO: 2.38 ± 1.32; p = 0.75; d = 0.11). When calculating the Hooper index, it was also observed that there was no statistical difference (p = 0.739; d = 0.09) between PLA (11.00 ± 3.6) and CHO (11.38 ± 4.40).

 

Discussion 

 

    The aim of the present study was to investigate the effect of carbohydrate mouth rinse on cycling performance in triathlon. The formulated hypotheses were that carbohydrate mouth rinse would enhance cycling performance and/or reduce subjective perception of effort. The findings demonstrate that there was no improvement in time and relative power in the CHO compared to the PLA condition. Additionally, there was no significant difference in psychobiological parameters between the experimental conditions. Therefore, based on these results, the hypotheses of the study were not confirmed.

 

    Corroborating the results of the present study, some authors suggest that carbohydrate mouth rinse does not provide ergogenic advantage (Ferreira et al., 2018; Pires, 2018). The results of Ferreira et al. (Ferreira et al., 2018) demonstrated that carbohydrate mouth rinse did not improve the performance of 11 trained cyclists in the 30km time trial test, compared to other traditionally recommended fluid ingestion strategies. In turn, Pires et al. (2018) found that carbohydrate mouth rinse was not an effective ergogenic strategy to improve performance in the 4 km cycling time trial. Therefore, the expected effect of stimulating brain regions involved in reward and motor control (Korohod et al., 2026), may not have occurred, or may not have been sufficient to influence performance in the self-regulated test.

 

    Unlike the findings of the present study, Hartley et al. (2024), Painelli et al. (2022), Deng et al. (2025) found that carbohydrate mouth rinse enhances the performance in the 40km cycling time-trial compared to rinsing with water. Other studies also found that carbohydrate mouth rinse does not enhance sports and exercise performance (Ferreira et al., 2018; Pires et al., 2018). Differences in the results may be related to the concentration of the rinse and the nutritional status of the individual (Deng et al., 2025; Korohod et al., 2026). However, Clark et al. (2017) did not find a dose-response effect of carbohydrate mouth rinse with maltodextrin concentrations (0 %, 3 %, 6 %, or 12 %) on 5-km running performance in recreational athletes. Devenney et al. (2016) compared solutions of 6 % and 16 % maltodextrin, and both concentrations improved performance compared to the placebo condition but did not find a difference between the carbohydrate conditions. These authors suggest that using a higher concentration of mouth rinse may increase the saturation of oral receptors, leading to greater stimulation of reward pathways. In contrast to these findings, the present study also used a 16 % carbohydrate concentration in the mouth rinse composition, but no improvements were found in the test when compared to the placebo solution. Therefore, the differences in the concentration of carbohydrate mouth rinse may not alter the effects of carbohydrate mouth rinse.

 

    Regarding nutritional status, studies that directly compared the effectiveness of carbohydrate mouth rinse in fed versus fasted states have shown that in the fed state, the nutritional strategy is not as effective as in the fasted state (Silva et al., 2014; Deng et al., 2025). These findings align with the present research, in which the athletes performed the test in the fed state. Additionally, it has been suggested that the duration of fasting can influence the effectiveness of the carbohydrate mouth rinse (Silva et al., 2014; Deng et al., 2025). Therefore, the results of the present study support these claims, suggesting the possibility that carbohydrate mouth rinse may not be effective in improving performance in a fed state (Clark et al., 2017; Ferreira et al., 2018; Pires et al., 2014). Therefore, carbohydrate mouth rinse may not be necessary when the athlete consumes a pre-training meal.

 

    However, it is important to highlight that there were no studies found that have investigated the effect of carbohydrate mouth rinse in combined sports or events, such as triathlon. Based on the studies presented, it is observed that the effects of mouth rinse in cycling have been evaluated (Carter et al., 2004; Devenney et al., 2016; Ferreira et al., 2018). However, none of them assessed the effects of combining swimming prior to cycling, as it occurs in triathlon events. This limits the discussion of the results and highlights the need for further specific research on this topic.

 

    In the present study, athletes were instructed to perform swimming before cycling to simulate the standard situation and to observe if the accumulated fatigue from this activity would have any influence on the time trial test with carbohydrate mouth rinse. The results indicate that there was no significant difference in the mean duration of swimming, thus demonstrating that the effort was similar in both conditions. Finally, it is expected that the lack of influence of carbohydrate mouth rinse on cycling performance after swimming may indicate that the rinse performed at that moment would not affect the final performance in the Triathlon race after running.

 

    Regarding RPE, in the present study, there was no change between the experimental conditions. Consistent with this finding, a review found that perceived exertion ratings did not differ between carbohydrate mouth rinse and placebo in eight studies, while only one study reported a reduction in RPE with carbohydrate mouth rinse (Silva et al., 2014). In line with these findings, Carter et al. (2004) mentioned in their study that despite finding an improvement in power when performing carbohydrate mouth rinse, there was no difference in RPE between the conditions in the time trial. This possibly occurred due to a characteristic of self-regulated exercise, where athletes tend to increase the workload but maintain the RPE. The expected reduction in RPE with carbohydrate mouth rinse should occur as a result of the stimulation of reward neural pathways (Devenney et al., 2016). However, Silva et al. (2014) found in their review that only one study investigating brain areas activated by carbohydrate mouth rinse found significant activation in reward-associated brain regions, including the insula/frontal operculum, orbitofrontal cortex, and striatum. Furthermore, Jeffers et al. (2015) observed reduced evidence of neuromuscular fatigue with carbohydrate mouth rinse compared to placebo, which did not translate into a significant effect on cycling time trial performance. Therefore, the scientific literature suggests that the method of carbohydrate mouth rinse does not affect the subjective perception of effort or that these perceptions are too small to be detected or significant during exercise. (Chryssanthopoulos et al., 2018)

 

    In addition to using RPE to assess psychobiological parameters, the Hooper index was also used in the present study. According to Chamari et al. (2012), the Hooper index allows for the detection of individual pre-fatigue signs and is a low-cost strategy. Thus, the application of the Hooper index in the current study provided a better evaluation of individual pre-fatigue signs, indicating that the athletes were in similar conditions of fatigue, sleep, stress level, and muscle soreness in both the CHO and PLA situations for perform the tests.

 

    Furthermore, the lactate and capillary blood glucose were also collected as physiological factors to be analysed in the time trial in the present study. In a review, Pacheco et al. (2012) reported that some studies found a negative relationship between blood lactate concentration at the end of swimming and the performance in subsequent disciplines, which may explain the results in the time trial. It is believed that swimming, being the first discipline in a triathlon, contributes to the initial lactate accumulation, which carries over to the following disciplines (Lopes et al., 2012). This statement supports the findings of the present study, as lactate concentration increased due to swimming effort but remained stable until the end of the cycling effort. This behavior may also indicate that the athlete adjusted the self-regulated intensity, maintaining the effort close to the anaerobic threshold (Pacheco et al., 2012).

 

    The blood glucose levels were also collected in the present study to ensure that athletes were not in a hypoglycemic state at the start of the time trial (Sareban et al., 2016). The results demonstrated that blood glucose did not significantly decrease in both experimental conditions. Clarke et al. (2017) also found no significant difference in blood glucose levels between the carbohydrate rinse conditions compared to the placebo rinse condition. Corroborating with these findings, Murray et al. (2018) assessed whether carbohydrate mouth rinse alters plasma insulin and glucose concentrations during the early stages of a 40km cycling time trial. The authors reported that orosensory detection of carbohydrates could have an immediate influence on insulin concentration and exercise performance, but their study did not find significant changes in plasma insulin and glucose concentrations at the start of the time trial in both the carbohydrate mouth rinse and placebo conditions, with no differences observed between the experimental conditions. Therefore, as expected, carbohydrate mouth rinse does not influence blood glucose levels because the solution is not ingested.

    

    Regarding heart rate, the present study found no difference in mean heart rate response between the two experimental conditions. However, there was a significant greater difference at the 40km compared to the 5km in both the PLA and CHO conditions, which is consistent with the study of Chryssanthopoulos et al. (2018). Supporting the findings of the present research, Clarke et al. (2017) found that carbohydrate mouth rinse did not significantly affect athletes' heart rate. Similar results were found by Carter et al. (2004). Thus, carbohydrate mouth rinse does not influence heart rate response. (Carter et al., 2004; Chambers et al, 2009; Chryssanthopoulos et al., 2018)

 

    In the present study, 24-hour dietary recalls were applied before the tests in both experimental conditions, aiming to investigate whether athletes maintained their dietary patterns throughout the study (Deng et al, 2025; Korohod et al., 2026). There was no significant difference in consumption between the experimental conditions, indicating that the nutritional state did not influence the performance in swimming and the cycling time trial.

 

    Based on the results obtained, compared to the findings of other studies, the present study advanced in science by demonstrating that performing carbohydrate mouth rinse in the fed state did not enhance triathletes performance in the 40km cycling time trial after 1500m swimming. In contrast to the existing literature, the present study simulated a situation similar to triathlon Olympic competition. These findings may guide the nutritional strategies adopted by coaches in Triathlon training. Furthermore, it is suggested that recent studies could improve carbohydrate mouth rinse protocols or combine mouth rinsing with liquid ingestion in order to evaluate the effects of this strategy in situations similar to triathlon competitions.

 

Conclusion 

 

    Carbohydrate mouth rinse does not affect performance, rating of perceived exertion, or substrate mobilization in Triathlon when conducted during cycling after swimming, especially in Olympic distances. Therefore, this nutritional strategy may not be an effective ergogenic aid in Triathlon.

 

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