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Brief Review

Does Carbohydrate Intake During Endurance Running Improve Performance? A Critical Review

Wilson, Patrick B.

Author Information
Journal of Strength and Conditioning Research: December 2016 - Volume 30 - Issue 12 - p 3539-3559
doi: 10.1519/JSC.0000000000001430
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Abstract

Introduction

Carbohydrate ingestion during exercise has been studied extensively over the past half century (30), resulting in widespread recommendations to consume carbohydrate during prolonged exercise (28,52). This research has also contributed to—albeit indirectly—the growth of the multibillion dollar carbohydrate supplements industry (4). Indeed, studies assessing nutritional intake during endurance competition confirm that the majority of athletes ingest carbohydrate (46).

Numerous reviews and meta-analyses have examined the effects of carbohydrate ingestion during endurance exercise (30,56,59,61). None of these reviews, however, has comprehensively examined exogenous carbohydrate specific to endurance running, and the majority of studies included in several of these reviews used cycling (59,61). This lack of focus on running is concerning given that the exercise modality modifies substrate use (1,33) and gastrointestinal (GI) tolerance to feedings (17). Rates of substrate (carbohydrate and fat) utilization differ between running and cycling, at least when comparing across the same relative intensity (e.g., %V̇o2peak: 1,33), and these differences persist even when carbohydrate is ingested (19). In addition, moderate-to-high intensity exercise reduces splanchnic blood flow, which may contribute to GI symptoms during exercise (17,70). Somewhat surprisingly, few experiments have directly compared the frequency and severity of GI symptoms between running and cycling. With that said, limited laboratory data suggest that running causes more symptoms when exogenous carbohydrate is consumed (42,43), which is supported by field data showing that triathletes experience more symptoms during running (6,76).

In addition to the exercise modality, sex is another potential modifier of substrate use and feeding tolerance. Compared with men, women rely more on fat to fuel a bout of endurance exercise (20). In addition, relative fuel and glycogen utilization varies throughout the menstrual cycle, re-enforcing the importance of standardizing menstrual status when studying carbohydrate ingestion (20). Furthermore, although Wallis et al. (71) have shown that exogenous carbohydrate oxidation rates are similar between men and women during cycling, they did not assess the GI tolerability of feedings. Importantly, women may experience more GI symptoms during running (48) and therefore may not tolerate as much carbohydrate despite a comparable capacity for oxidation. Taken together, sex could potentially modify the effects of carbohydrate feeding on running performance, particularly because GI tolerance is an important factor influencing the efficacy of carbohydrate feeding (59). Notably, most of the aforementioned review articles did not provide more than a cursory discussion of the potential sex-based differences with carbohydrate feeding during exercise (30,59,61).

The popularity of distance running provides additional rationale for reviewing the effects of exogenous carbohydrate in a modality-specific manner. In the United States, roughly 541,000 individuals finished a marathon in 2013, while an additional 1.96 million completed a half-marathon (54). More than 75% of marathoners believe that consuming carbohydrate beverages improves their performance (41). Furthermore, it is ubiquitous for aid stations at running events to supply carbohydrate, re-enforcing the notion that it improves their performance. Of all supplements, carbohydrate supplements are one of the most frequently consumed by runners (55).

Given (a) that substrate use and GI tolerability of carbohydrate feedings vary with exercise modality, (b) the lack of review articles specific to running, and (c) the popularity of distance running, the purpose of this article is to systematically review the evidence for carbohydrate ingestion during endurance running, with emphases on performance and GI comfort.

Methods

Search Strategy

Articles analyzed were identified through (a) reviews and meta-analyses, (b) Pubmed, and (c) the author's knowledge. A Pubmed search was conducted in August of 2015 using the following terms: carbohydrate running, glucose running, sucrose running, fructose running, maltodextrin running, carbohydrate treadmill, glucose treadmill, sucrose treadmill, fructose treadmill, maltodextrin treadmill, carbohydrate marathon, glucose marathon, sucrose marathon, fructose marathon, and maltodextrin marathon.

Inclusion Criteria

Since the focus of this review is performance, only trials including time to exhaustion (TTE) or self-paced performance trials (e.g., time trial [TT]) were included. Only investigations reported in English language using an experimental design were included. Studies with running durations lasting 1 hour or less were excluded because carbohydrate is unlikely to benefit performance for shorter durations (52). Carbohydrate mouth-rinsing trials were excluded because the primary mechanism involves central nervous system effects and most of these trials used durations less than 1 hour (28). Trials that used an intermittent-intensity task were excluded, because these reflect team-based sports. Some previous review articles on ergogenic aids have exclusively focused on blinded, placebo-controlled trials (61). However, the present review also aimed to examine strategies that are difficult to blind but commonly used. Accordingly, studies that used water as a control, compared solid vs. liquid forms of carbohydrate, compared different carbohydrate dosages, or compared different feeding strategies were included.

The identified studies were grouped into 3 categories: (a) comparing an equivalent volume of carbohydrate beverage(s) with nonsweetened water, (b) comparing an equivalent volume of carbohydrate beverage(s) with placebo, and (c) evaluating other carbohydrate-based feeding strategies during exercise. Overall, 8,142 articles were identified through Pubmed. Ultimately, 25 articles met the inclusion criteria, and 2 presented results from 2 separate studies, increasing the number to 27. Three studies were identified from previous reviews or from the author's knowledge. Consequently, 30 studies were included (Tables 1–3).

T1
Table 1.:
Studies comparing the effects of carbohydrate beverage(s) with an equivalent volume of water on endurance running performance.*
table1-a
Table 1-A.:
Studies comparing the effects of carbohydrate beverage(s) with an equivalent volume of water on endurance running performance.*
T2
Table 2.:
Studies comparing the effects of carbohydrate beverage(s) with an equivalent volume of placebo on endurance running performance.*
table2-a
Table 2-A.:
Studies comparing the effects of carbohydrate beverage(s) with an equivalent volume of placebo on endurance running performance.*
table2-b
Table 2-B.:
Studies comparing the effects of carbohydrate beverage(s) with an equivalent volume of placebo on endurance running performance.*
table2-c
Table 2-C.:
Studies comparing the effects of carbohydrate beverage(s) with an equivalent volume of placebo on endurance running performance.*
T3
Table 3.:
Studies evaluating other carbohydrate-based feeding strategies during running.*
table3-a
Table 3-A.:
Studies evaluating other carbohydrate-based feeding strategies during running.*
table3-b
Table 3-B.:
Studies evaluating other carbohydrate-based feeding strategies during running.*
table3-c
Table 3-C.:
Studies evaluating other carbohydrate-based feeding strategies during running.*
table3-d
Table 3-D.:
Studies evaluating other carbohydrate-based feeding strategies during running.*

Statistical Analyses

Between-treatment differences were calculated for studies comparing a carbohydrate beverage(s) with water or a placebo, and the standardized effect sizes were calculated using Hedge's g adjustment for small samples. Calculations were based on mean and SDs, or when SDs were unavailable, SEs and sample sizes were used to calculate SDs. For parallel trials, 95% confidence intervals (CIs) and SEs for standardized effect sizes were calculated using a published spreadsheet (12). For crossover trials, calculations for 95% CIs and SEs for standardized effect sizes were modified by imputing an assumed correlation of 0.5 to account for the between-period correlation of outcomes, in accordance with a previous analysis (61). To facilitate visualization of effects, forest plots were generated based on 4 subgroups: (a) studies comparing a carbohydrate beverage(s) with water with a TTE, (b) studies comparing a carbohydrate beverage(s) with water with a TT, (c) studies comparing a carbohydrate beverage(s) with a placebo with a TTE, and (d) studies comparing a carbohydrate beverage(s) with a placebo with a TT.

A meta-analysis of the standardized effect sizes was not conducted owing to the small number of trials in each subgroup, the heterogeneity in exercise protocols, and the heterogeneity in feeding protocols (22). Standardized effect sizes and forest plots were not generated for studies in Table 3 because of the extreme variation in the study objectives.

Results

Carbohydrate Beverage(s) vs. Water

Six studies compared a carbohydrate beverage(s) with an equivalent volume of water (Table 1; 11, 63, 65, 66, 68, 73). Of these studies, 4 exclusively involved men, and ultimately, 134 of the 145 (92%) participants were men. The 2 studies enrolling women made no mention of standardizing menstrual status. All 6 studies used a randomized crossover design, and 5 studies had the participants fast or failed to report the pre-exercise diet. Beverage concentrations ranged from 5.0 to 6.9%, while rates of fluid ingestion were roughly 150 ml every 15–20 minutes. Mean exercise durations ranged from 78 to 194 minutes. Four studies were conducted using a treadmill, whereas 2 used an outdoor course.

Four studies used a TT, whereas 2 used a TTE. Of the 4 studies using a TT, 2 found significant between-condition differences in favor of carbohydrate, with a magnitude of benefit of roughly 2%. The shortest TT (18 km) failed to find a benefit with carbohydrate. Both TTE studies found significant between-condition differences with carbohydrate, and the magnitude of benefit was larger with these TTE tasks (12–14% greater endurance). Two studies compared 5.5 and 6.9% beverages and found no clear added benefit with higher concentrations. Overall, no study found a detriment with carbohydrate. Forest plots of standardized effects are shown in Figures 1 and 2.

F1
Figure 1.:
Forest plot of standardized effects sizes and 95% confidence intervals for time-to-exhaustion studies comparing an equivalent volume of carbohydrate beverage(s) with water. Tsintzas et al. (66) used 2 carbohydrate beverages, so standardized effects relative to water are shown for each.
F2
Figure 2.:
Forest plot of standardized effects sizes and 95% confidence intervals for time trial studies comparing an equivalent volume of carbohydrate beverage(s) with water. Williams et al. (73), Tsintzas et al. (65), and van Nieuwenhoven (68) used 2 carbohydrate beverages, so standardized effects relative to water are shown for each.

With respect to GI disturbances, 6.9% beverages increased reflux and flatulence in one study. Two additional studies found suggestive evidence for greater GI distress with 6.9% beverages.

Carbohydrate Beverage(s) Vs. Placebo

Eleven studies compared a carbohydrate beverage(s) to an equivalent volume of placebo (Table 2; 2, 10, 37–39, 49–51, 60, 64, 72). Eight of these exclusively involved men, 2 exclusively involved women, and 1 was mixed (157 of 185 were men [85%]). Both studies exclusively enrolling women standardized for the menstrual status, with exercise trials conducted during the follicular phase, whereas the mixed-sex study made no mention of standardizing menstrual status. Ten studies used a crossover design, whereas 1 used a parallel-groups design. Ten studies had participants fast, whereas 1 fed a sugar-free placebo before. Beverage concentrations ranged between 5.5 and 8.0%, while rates of fluid ingestion ranged from 2 ml·kg−1 of body weight every 20 minutes to 1,000 ml·h−1 Mean exercise durations ranged from roughly 90 minutes to 4.5 hours. Eight studies were conducted using a treadmill, whereas 3 used an outdoor course. Eight studies reported double-blinding, and 3 reported single-blinding.

Six studies used a TT, whereas 5 studies used a TTE. Five of the 6 TT studies found either a clear between-condition difference with carbohydrate or a suggestive benefit after accounting for other factors. The magnitude of benefit ranged from approximately 4–10%. The sole TT study failing to find a benefit was likely statistically underpowered with 8 runners. Four of 5 TTE studies found significant between-condition differences with carbohydrate, and the magnitude of benefit ranged from 9 to 27%. No study found a performance detriment with carbohydrate. Forest plots of standardized effects are shown in Figures 3 and 4.

F3
Figure 3.:
Forest plot of standardized effects sizes and 95% confidence intervals for time-to-exhaustion studies comparing an equivalent volume of carbohydrate beverage(s) with placebo.
F4
Figure 4.:
Forest plot of standardized effects sizes and 95% confidence intervals for time trial studies comparing an equivalent volume of carbohydrate beverage(s) with placebo. Millard-Stafford et al. (38) used 2 carbohydrate beverages, so standardized effects relative to placebo are shown for each. The standardized effect sizes for Robson-Ansley et al. (50) and (51) were inverted for presentation because the outcome was measured as distance covered or speed instead of time.

No consistent differences emerged for GI disturbances, although 1 study found reduced nausea and postrun stomach upset with carbohydrate.

Other Carbohydrate-Based Feeding Strategies During Exercise

Thirteen studies (11 articles) evaluated other carbohydrate-based feeding strategies during exercise (Table 3; 7, 14, 15, 24, 35, 36, 40, 45, 53, 62, 75). Eight exclusively enrolled men, whereas 5 involved a mix of men and women. Of the 251 participants, 214 were men (85%). Three mixed-sex studies used a crossover design with trials held 1–2 weeks apart, implying that menstrual status was not controlled (35,45). Of the remaining 2 mixed-sex studies, one had the women repeat trials within 26–29 days (75), whereas the other made no mention of controlling the menstrual status (24). Ten studies used a crossover design, whereas 3 used a parallel-groups design with matched groups. Ten studies had participants ingest a high-carbohydrate meal or supplement before protocols, whereas 3 had the participants fast or failed to report the diet. Blinding status was variable, and a number of investigations were unblinded because of the nature of intervention.

The earliest studies, from Noakes et al. (40), compared different carbohydrate sources and concentrations during 42.2- and 56-km TTs, and both failed to find performance differences. Millard-Stafford et al. (36) compared the effects of water, a 6% carbohydrate solution, and an 8% carbohydrate solution on the 15-km performance. Overall, both carbohydrate beverages led to faster running during the final 1.6 km, although there were no differences for GI ratings.

Daries et al. (15) addressed whether ad libitum or prescribed drinking was superior for performance and GI comfort. Participants completed trials of treadmill running, during which they consumed a 6.9% beverage ad libitum or at modest (150 ml·70 kg−1) or high (350 ml·70 kg−1) volumes every 15–20 minutes. During the 350 ml·70 kg−1 trial, stomach fullness was greater and 2 participants could not finish because of GI upset.

Burke et al. (7) evaluated whether carbohydrate gels along with ad libitum water improved half-marathon performance compared with placebo beverage. Despite no performance differences, 3 runners complained of GI discomfort during the gel trial, which produced a 2.4% performance impairment. In a similar fashion, 2 studies from Pfeiffer et al. (45) evaluated the saccharide source and dosage effects when ingesting carbohydrate gels during 16-km races. The initial study compared 2 dosages of glucose-fructose gels (1.0 vs. 1.4 g·min−1) with ad libitum water. Performance times did not differ, but the 1.4 g·min−1 condition caused greater nausea. A subsequent study compared glucose-only vs. glucose-fructose gels fed at a high rate (1.4 g·min−1). Again, performance did not differ, but several GI symptoms were more frequent in the glucose-fructose condition.

Rollo et al. (53) assessed the effects of carbohydrate fluid volume on performance and GI comfort during 10-mile TTs. Finishing time was possibly faster with ad libitum relative to no fluid and prescribed drinking. As expected, GI discomfort was greater for prescribed drinking.

Given the popularity of “natural” products, Too et al. (62) investigated the effects of carbohydrate from raisins vs. that from a supplement (chews). Although both conditions improved the performance compared with water, there were no differences between raisins and chews.

Coletta et al. (14) assessed the effects of carbohydrate alone or with protein on 19.2-km performance. The participants completed trials while consuming a 6% carbohydrate solution, a 6% carbohydrate + 1.4% protein solution, a 9% carbohydrate solution (isocaloric to the carbohydrate-protein solution), or a placebo. Ultimately, no performance differences were found.

Hansen et al. (24) used a matched-pairs design to evaluate 2 strategies during 42.2-km marathon running. One group chose their own strategy, whereas the other was instructed to consume 0.75 L of fluid, 60 g of carbohydrate, 0.06 g of sodium, and 0.09 g of caffeine every hour. Carbohydrate intake was greater in the prescribed group (65 vs. 38 g·h−1), and the finishing time was 10:55 minutes:seconds faster.

Lee et al. (35) aimed to (a) compare self-selected fluid intake with high carbohydrate gel intake with fluid intake based on traditional guidelines and (b) compare the effects of consuming glucose-fructose and glucose-only gels when carbohydrate is consumed at 60 g·h−1 Participants completed trials while consuming carbohydrate from a solution, glucose gels, or glucose-fructose gels. Participants were prescribed 1,557 ml of fluid during the solution trial, while they voluntarily consumed 473 and 404 ml of a noncaloric solution during gel trials. Performance was not different between the trials, although the glucose-fructose gel condition showed a roughly 2.7% nonsignificant slower time.

Finally, Wilson and Ingraham (75) compared the effects of glucose-only to glucose-fructose beverage ingestion (1.3 g·min−1 carbohydrate) during 120 minutes of running at 65% V̇o2peak followed by a 4-mile TT. The TT was likely 1.9% faster with glucose-fructose, and most GI symptoms were likely lower with glucose-fructose.

Discussion

A major objective of this review was to evaluate whether carbohydrate ingestion during exercise improves endurance running performance. To facilitate the interpretation, the studies were categorized according to the various interventions and control treatments employed. The first category of studies compared carbohydrate beverage(s) with an equivalent volume of water. Four of these studies found a clear performance benefit with carbohydrate, whereas 2 found neither beneficial nor harmful effects. One of the studies failing to find a benefit actually showed roughly 3.5–4.5 minutes faster finishing times with carbohydrate, but these differences were not statistically significant (73). The other study failing to show a benefit used a relatively short protocol (∼78 minutes; 68). These results suggest that carbohydrate beverages (5.0–6.9% concentration) improve running performance relative to water, at least for durations lasting roughly 110 minutes or longer. Although several studies evaluated GI discomfort, only 1 found a clear increase in symptoms with carbohydrate (68). Notably, this study used a short TT (∼78 minutes), meaning that the intensity was higher than that of the other studies. Gastrointestinal reflux increases with exercise intensity (57), and competitors generally consume less carbohydrate during shorter, more intense events (46). Interpreted together, these data indicate that carbohydrate feedings are less tolerated during maximal runs lasting 60–90 minutes.

The second category of studies compared carbohydrate beverage(s) with an equivalent volume of placebo. The majority of these studies found that performance was improved with carbohydrate. Again, several studies failing to find a benefit showed trends favoring carbohydrate but were likely statistically underpowered for small effects (2,49) and none found performance detriments with carbohydrate. In addition, 3 studies suggest that carbohydrate improves performance for running lasting between 90 and 120 minutes (50,60,72). Beverage concentrations used in studies showing a performance benefit ranged from 5.5 to 8.0%. As such, the balance of evidence indicates that 5–8% carbohydrate beverages likely enhance running performance relative to water and placebo, and at the very least, there is little chance of harmful performance effects.

Several mechanisms could be responsible for performance improvements observed with carbohydrate intake during running. Prevention of hypoglycemia is a commonly cited mechanism, because both carbohydrate feeding and intravenous glucose infusion can maintain euglycemia and delay fatigue during prolonged exercise (29). Sparing muscle glycogen represents another mechanism, although studies to date are equivocal with regard to a glycogen-sparing effect of exogenous carbohydrate (9). However, the lack of clear glycogen-sparing effect is likely the result of a combination of factors, including variations in exercise modality, exercise duration, and the type of muscle fiber biopsied (9). Indeed, Tsintzas et al. (64) showed a 25% reduction in glycogen use with carbohydrate ingestion (vs. placebo) during running to exhaustion at 70% V̇o2peak and the effect was only significant in type I fibers. Lastly, central nervous system stimulation has recently drawn attention as a potential mechanism. In support of this, studies employing carbohydrate mouth rinsing have shown improvements in performance when compared with water or placebo mouth rinsing, which suggests that the oral cavity is receptive to carbohydrate structure (9). However, this strategy has primarily been examined during shorter bouts (30–60 minutes), and it is questionable whether this strategy would override reductions in blood glucose and muscle glycogen that occur with more prolonged exercise (27).

With regard to feeding tolerability, none of the studies from Table 2 showed a clear increase in GI symptoms with carbohydrate. In fact, 1 study actually reported less nausea and postrun stomach upset (38). The reason for the discrepancy between this study and the study by van Nieuwenhoven et al. (68) is unclear, but greater nausea and stomach upset observed with placebo in the study by Millard-Stafford et al. (38) could have been due to hypoglycemia. Hypoglycemia is known to induce nausea (58), and it is well established that carbohydrate ingestion during prolonged exercise maintains blood glucose (30). It is therefore plausible that the effects of carbohydrate ingestion on upper GI tract symptoms (nausea and reflux) are modified by duration, such that symptoms increase with carbohydrate during brief running but decrease during running that lasts several hours.

Although not directly evaluated by studies in this review, running and cycling produce disparate physiological responses in the GI tract. Running causes more gastroesophageal reflux (44), delays oral-cecal transit (26), and accelerates colonic transit (16). In addition, mechanical trauma with running may induce more frequent GI damage. More than 85% of ultramarathoners and triathletes test positive for fecal occult blood after a race (16), whereas competitors of cycling races show a considerably lower prevalence (31). Although direct evidence tying the jostling of running to GI bleeding is absent, running results in the doubling of accelerations/decelerations to the GI region (47). Furthermore, splanchnic hypoperfusion occurring with exercise may increase intestinal damage and symptoms (70). The author is not aware of published research directly comparing the degree of splanchnic hypoperfusion during cycling and running. With that said, occult bleeding occurs more often during running, suggesting greater damage and that splanchnic hypoperfusion may be more pronounced. In support of this hypothesis, limited data demonstrate that GI permeability is more pronounced with running (67).

Several important inferences can be drawn from the studies presented in Table 3. First, beverage volume is an important factor influencing GI distress and, ultimately, performance. As shown by Daries et al. (15), carbohydrate beverage intake well above ad libitum levels causes GI distress. Rollo et al. (53) confirmed these findings by showing that carbohydrate beverage intake at roughly 900 ml·h−1 provided no performance advantage relative to ad libitum intake but caused more GI discomfort. A similar study from Dion et al. (21) found that prescribed water intake offered no performance benefits over drinking to thirst, and again, prescribed intake caused more GI discomfort. Whether or not the carbohydrate content of a beverage influences these responses independently of volume is yet to be determined.

Regardless, the finding that fluid intake above the ad libitum levels increases GI discomfort has implications, especially because several organizations recommend consuming fluids to limit body weight loss <2% (8,52). Mean ad libitum intakes for competitive runners rarely exceed 0.5 L·h−1 (15,24,45,53), and given sweat rates of 0.5–1.5 L·h−1 among typical marathoners (32) and 2–3 L·h−1 among elite marathoners (5), a proportion of competitors relying on ad libitum intake fail to ingest sufficient fluid to prevent >2% body weight loss. Interestingly, GI discomfort accompanying aggressive fluid intake can be reduced with repeated exposures (34), but it remains unclear whether “training the gut” to tolerate large volumes leads to improved performance. Evidence specific to this systematic review, however, does not support a universal goal of drinking carbohydrate beverages to prevent >2% body weight loss. Instead, runners ingesting carbohydrate beverages may expect a performance benefit when consuming fluid at a modest rate (2–3 ml·kg−1 every 15–20 minutes) or when drinking ad libitum.

Another important inference from Table 3 is that carbohydrate gels do not influence performance for events lasting 16–21 km. Burke et al. (7) failed to find performance improvements with gels, although it is possible that the ingestion rate was overly aggressive (1.1 g·kg−1). Indeed, 3 runners reported GI discomfort with gels, which was associated with a 2.4% impairment in performance. Two other studies suggest that neither the gel composition nor the dosage affect performance during brief (16 km) events (45). Specifically, increasing carbohydrate from 1.0 to 1.4 g·min−1 had no effect on performance. Similarly, providing carbohydrate as glucose-only or glucose-fructose gels had no significant effect on performance.

Several studies from Table 3 investigated the effects of carbohydrate composition. Previous research with cyclists has shown that coingestion of glucose-fructose improves performance and reduces GI distress when carbohydrate is fed aggressively (>60 g·h−1) during prolonged cycling (>2.5 hours; 74). Lee et al. (35) found that a glucose-fructose gel did not improve running performance relative to a glucose-only gel or glucose-only beverage. Moreover, the glucose-fructose gel was associated with lower blood glucose and a roughly 2.7% nonsignificant slower time. All conditions provided carbohydrate at 60 g·h−1, which is the threshold where glucose-fructose coingestion has shown benefits (74). In contrast, Wilson and Ingraham (75) found that glucose-fructose coingestion likely enhanced the 4-mile TT performance after 2 hours of running. Exogenous carbohydrate was supplied more aggressively (1.3 g·min−1), which may explain the discrepancy with Lee et al. (35), while the longer duration may explain the discrepancy with Pfeiffer et al. (45). Overall, it seems that runners may benefit from glucose-fructose coingestion only if the duration is longer than 2 hours and if carbohydrate intake is ≥1.3 g·min−1 The applicability of this research, however, may be limited given that a small proportion of runners voluntarily consume carbohydrate ≥1.0 g·min−1 during marathons (46).

Hansen et al. (24) provided intriguing data suggesting that carbohydrate above ad libitum levels may improve marathon performance. A group that was assigned to high carbohydrate ingestion (65 g·h−1) finished a marathon 10:55 minutes:seconds faster than a group assigned to a freely chosen rate (38 g·h−1). Differences in fluid and caffeine intakes could explain the benefit, but fluid intakes were similar and caffeine intake was low in the prescribed group. Importantly, high carbohydrate ingestion was achieved through carbohydrate gels as opposed to large beverage volumes, which may have reduced excess GI distress associated with aggressive fluid intakes. Finally, participants were not elite (average time ∼3:45 hours:minutes). Given elite runners tend to consume less food and fluid during races (69), it is unknown whether this strategy would be effective among an elite cohort.

The remaining studies from Table 3 generally failed to find performance effects. Too et al. (62) found that carbohydrate from raisins improved performance similarly as carbohydrate chews. Coletta et al. (14) found no benefit to including protein in a carbohydrate beverage during 19.2-km running, while Noakes et al. (40) and Millard-Stafford et al. (36) failed to find performance differences between carbohydrate beverages with varying concentrations and sources.

Regarding limitations, relevant articles could have been unintentionally excluded from this review. A combination of search strategies was used to minimize this possibility, including reviewing systematic review articles and meta-analyses and searching Pubmed, which indexes more than 24 million citations. Another related limitation is the inability to identify studies that were never published, because of negative results, poor design, or lack of desire from investigators. This publication bias is difficult to quantify but may be more likely when studies have small sample sizes and are industry sponsored (23). Eleven studies had a sample of less than 10, while 19 had less than 15 participants. These small samples are potentially even more problematic given that meaningful effects for endurance races tend to be small (25). Regarding industry sponsorship, most reported either receiving funding (2,7,10,24,35,36,38–40,45,49,51,62,64,65,72) or treatments from industry (37). Given the concern others have raised over industry sponsorship (13), future research should carefully consider the impact—whether real or perceived—that industry funding has on results.

Limitations to studies identified within this review restrict the generalizability of findings. Most participants were young men. Consequently, inferences regarding women, adolescents, and older runners are hampered. Future studies comparing the efficacy of carbohydrate feedings between men and women are particularly warranted in light of the potential sex differences in carbohydrate metabolism and GI tolerance (20,48). Furthermore, a number of studies used artificial performance tasks that do not replicate conditions experienced during nonsimulated events, so effect sizes observed (10,11,60,64,66,72) may be inflated relative to what an athlete should expect. Along similar lines, the majority of studies comparing a carbohydrate beverage(s) with water or a placebo had participants fast, which fails to mimic practices of most runners (3) and may inflate effect sizes. Lastly, studies using a placebo often failed to provide information on the artificial sweetener used, which is concerning given that artificially sweetened beverages are difficult to blind (18).

Practical Applications

The notion that carbohydrate ingestion during exercise improves running performance is pervasive, despite much of the research being conducted using other exercise modalities, primarily cycling. Based on evidence analyzed in this review, it appears that:

  • Carbohydrate beverages (5–8% concentration) consumed at a modest rate (100–200 ml every 15–20 minutes) likely enhance running performance relative to water and placebo.
  • Performance benefits are most likely to occur during events >2 hours, although several studies showed benefits for tasks lasting 90–120 minutes.
  • It is questionable whether carbohydrate consumption—either through gels or beverages—during shorter events (≤90 minutes) provides any performance benefit. In addition, carbohydrate ingestion during these shorter events is more likely to elicit GI distress.
  • Consuming carbohydrate beverages substantially above ad libitum levels does not provide additional performance benefits and likely increases GI discomfort.

More research is required to address a number of literature gaps. Whether carbohydrate gels enhance performance during longer events (>2 hours) requires further study. Likewise, it remains unclear whether runners consuming a high rate of carbohydrate (1.0–1.3 g·min−1) benefit from ingestion of multiple saccharides. Finally, studies should conduct trials under fed conditions, enroll women and adolescents, and carefully document blinding procedures.

Acknowledgments

The author discloses no conflicts of interest. The entirety of this manuscript was conceived and drafted by PBW. No sources of funding were used to complete this manuscript.

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Keywords:

ergogenic; exercise; nutrition; supplement

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