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1 From the Military Nutrition Division, US Army Research Institute of Environmental Medicine, Natick, MA (HRL, CMF, and SSS).
2 SSS was a United Kingdom Exchange Officer assigned to the US Army Research Institute of Environmental Medicine and the US Army Soldier and Biological Chemical Command, Natick, MA. 3 We dedicate this article to the memory of Irwin Taub, a dedicated scientist who will be greatly missed. 4 The views, opinions, and findings in this report are those of the authors and should not be construed as an official Department of the Army position, policy, or decision, unless so designated by other official documentation. 5 The citation of commercial organization and trade names in this report does not constitute an official Department of the Army endorsement or approval of the products or services of these organizations. 6 Supported by the US Army Medical Research and Materiel Command (USAMRMC). 7 Address reprint requests to HR Lieberman, Military Nutrition Division, US Army Research Institute of Environmental Medicine, Natick, MA 01760-5007. E-mail: harris.lieberman{at}na.amedd.army.mil.
ABSTRACT
Background: The brain requires a continuous supply of glucose to function adequately. During aerobic exercise, peripheral glucose requirements increase and carbohydrate supplementation improves physical performance. The brain's utilization of glucose also increases during aerobic exercise. However, the effects of energy supplementation on cognitive function during sustained aerobic exercise are not well characterized.
Objective: The effects of energy supplementation, as liquid carbohydrate, on cognitive function during sustained aerobic activity were examined.
Design: A double-blind, placebo-controlled, between-subjects design was used. Young, healthy men (n = 143) were randomly assigned to 1 of 3 treatment groups. The groups received either a 6% (by vol) carbohydrate (35.1 kJ/kg), 12% (by vol) carbohydrate (70.2 kJ/kg), or placebo beverage in 6 isovolumic doses, and all groups consumed 2 meals (3200 kJ). Over the 10-h study, the subjects performed physically demanding tasks, including a 19.3-km road march and two 4.8-km runs, interspersed with rest and other activities. Wrist-worn vigilance monitors, which emitted auditory stimuli (20/h) to which the subjects responded as rapidly as possible, and a standardized self-report mood questionnaire were used to assess cognitive function.
Results: Vigilance consistently improved with supplemental carbohydrates in a dose-related manner; the 12% carbohydrate group performed the best and the placebo group the worst (P < 0.001). Mood-questionnaire results corroborated the results from the monitors; the subjects who received carbohydrates reported less confusion (P = 0.040) and greater vigor (P = 0.025) than did those who received the placebo.
Conclusions: Supplemental carbohydrate beverages enhance vigilance and mood during sustained physical activity and interspersed rest. In addition, ambulatory monitoring devices can continuously assess the effects of nutritional factors on cognition as individuals conduct their daily activities or participate in experiments.
Key Words: Cognition • psychomotor performance • brain • aerobic exercise • glucose • ambulatory monitoring • energy • ergogenic aids • nutritional supplements
INTRODUCTION
The beneficial effects of acute carbohydrate supplementation on endurance exercise are well documented. Administration of solid or liquid carbohydrates during moderate or intense aerobic activity substantially improves various types of physical performance (1–3). Consumption of carbohydrates before and immediately after exercise is also beneficial (2,4). Supplemental carbohydrates are essential because carbohydrate stores, including muscle glycogen, are rapidly expended by sustained exercise (2). Liquid carbohydrate feeding during
In this study we continuously examined the influence of liquid carbohydrate supplementation on a critical cognitive function, the ability to maintain vigilance, during sustained periods of high energy expenditure and during rest. Maintaining vigilance requires detecting and responding to stimuli over long periods of time, often against a background of distracting stimulation (19). In addition, the effects of carbohydrate supplements on mood state, including moods that are highly associated with vigilance and maintaining responsiveness to the external environment, were assessed with a standardized questionnaire.
SUBJECTS AND METHODS
Subjects
The subjects were 143 healthy men from the US Army 2nd Battalion, 75th Ranger Regiment, an elite combat unit. The mean (±SD) age, height, weight, and body mass index (in kg/m2) of the subjects were 21 ± 3 y, 178.5 ± 5.4 cm, 78.0 ± 9.0 kg, and 24.9 ± 2.0, respectively. The fitness level of this group, as assessed by the standardized Army fitness test, was well above average in comparison with that of young men in the general population and relative to Army standards (20). The subjects reported that they engaged in aerobic exercise 7.5 ± 2.6 (
The study used a double-blind, placebo-controlled, between-subjects design. Subjects were randomly assigned to 1 of 3 groups: 6% (by vol) carbohydrate (CHO6), 12% (by vol) carbohydrate (CHO12), or placebo. Each subject, regardless of the treatment group to which he was assigned, received an equal fluid volume of the supplemental beverage based on his body weight (36 mL/kg). The week before testing, all subjects participated in a baseline test session during which demographic data were obtained. In addition, the subjects practiced various tests and were given detailed instructions regarding the events of the actual test day.
On the test day, subjects participated in a carefully designed and standardized series of events intended to simulate the physical-demand characteristics of a military mission that Rangers might be required to perform (Table 1). The principal aerobic activities were a 19.3-km (12-mi) march with a 17-kg load, most of which was carried in a backpack, and two 4.8-km (3-mi) runs without any load. Interspersed between these activities were 2 meals; various rest periods, including a long rest period during which most of the subjects chose to nap; and live-fire rifle marksmanship exercises. Subjects began the study in staggered groups over a 1-h period, and the march and runs were timed events that the subjects were encouraged to perform as rapidly as possible. The tests were conducted outdoors and the climatic conditions were generally temperate. Light rain showers were occasionally present. Air temperatures ranged from 1°C early in the morning to 14°C later in the day. The relative humidity was 76–83%. The testing was conducted over 3 d.
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TABLE 1 . Approximate schedule of events during the test day1
Testing began at 0445 (Table 1). Subjects were required to fast for 6 h before arrival at the testing site. When the subjects first reported for testing, various measurements, including measurements of body weight, height, and equipment weight, were taken. Subjects were then issued vigilance monitors and the time was recorded. The period from the time the monitors were issued until the start of the 19.3-km road march (45 min) was taken as a baseline measure of vigilance reaction time. Breakfast and the first dose of the test beverage were then administered. Immediately after eating, the first Profile of Mood States (POMS) mood questionnaire was administered. For each subject, the time from beginning to completing each individual event was recorded. This permitted accurate synchronization of the data collected by each subject's vigilance monitor with his actual participation in every event.
The subjects then began the timed road march, during which they had continuous access to water, which they carried in canteens. At the 6.4- and 12.9-km (4- and 8-mi) points in the march, the subjects received the 2nd and 3rd doses of the appropriate test beverage. The mean (±SD) time to complete the march for all groups was 179 ± 21 min. At the end of the march, the subjects and their equipment were weighed and the fourth dose of the test beverage was administered. The subjects rested for 30 min after the march and then ran 4.8 km in 21 min and 8 s ± 2 min and 26 s (
All beverages were initially prepared in dry form and reconstituted at the testing site with bottled spring water. The CHO6 and CHO12 beverages were formulated from maltodextrin (Maltrin QD M500; Grain Processing Corp, Muscatine, Iowa); aspartame; and an unsweetened, lemon-flavored, commercial soft drink mix (Kool-Aid; Kraft General Foods, Inc, White Plains, NY). The placebo drink consisted of the same components without maltodextrin. All treatments were formulated to be identical in taste and appearance, as confirmed by formal, blind taste-testing conducted before the study.
On the test day, the total isovolumic dose of carbohydrate or placebo treatment administered to every subject was 36 mL/kg in 6 equal doses (Table 1). The total carbohydrate supplement provided to the CHO6 and CHO12 groups was 2.1 and 4.2 g/kg (35.1 and 70.2 kJ/kg), respectively. At each of the 6 administration times, subjects received body weight–adjusted fluid volumes (6 mL/kg) of 1 of the 3 treatments: 0.35 g carbohydrate/kg body weight as a 6% solution; 0.7 g carbohydrate/kg body weight as a 12% solution; or the nonnutritive, artificially sweetened placebo beverage. The investigators verified that all subjects consumed the entire dose of the beverage when it was administered.
In addition to liquid carbohydrate supplementation, all subjects received breakfast and lunch meals consisting of preprepared foods at specified times (Table 1). The meals were selected to be representative of meals typically consumed by young male soldiers. No additional food was available during the study. The breakfast meal (2339 kJ) contained 49% of energy as carbohydrate, 25% as protein, and 26% as fat. On the basis of their self-reports, the subjects consumed, on average, 1770 kJ of the breakfast. The lunch meal (2280 kJ) contained 29% of energy as carbohydrate, 22% as protein, and 48% as fat. On the basis of their self-reports, the subjects consumed, on average, 1430 kJ of the lunch meal. The meals were composed of standard, off-the-shelf ration components and included an entrée and a side dish. The subjects could choose from several available meals. There were no statistically significant differences in meal consumption between the treatment groups.
Cognitive and mood assessment
Vigilance monitors
At the start of testing, subjects were issued ambulatory vigilance and environmental monitors that were custom-designed and -manufactured (21,22). Only a subset of the subjects (n = 93) was issued vigilance monitors because there were not enough monitors to test all the subjects. The monitors were lightweight (68 g) devices somewhat larger than a large wristwatch, which were worn on the nondominant wrist. Each monitor contained an 8-bit microprocessor, 128 kilobytes of RAM (random-access memory), and various sensors that monitored, on a minute-by-minute basis, the subject's cognitive performance and patterns of rest and activity and the ambient environmental conditions. Once programmed, the monitors operated independently on internal battery power for up to 14 d. The monitors were fully programmable, and the data they recorded were retrieved from their internal memory via a custom-designed and -manufactured RS-232 interface with any standard IBM-compatible microcomputer.
Each monitor contained an accelerometer, a thermistor, a light sensor, a microphone, and 2 push buttons to record the response of the subject to stimuli presented by the monitor. The accelerometer assessed the subjects' motor activity, the thermistor continuously monitored the ambient temperature, and the light sensor recorded illumination levels in the range of human spectral sensitivity. The microphone monitored acoustic sound pressure in the environment. Each monitor also contained a tone generator and 3 LEDs (light-emitting diodes). In a series of previous studies (21,22), the monitors were shown to provide reproducible results that were consistent with data collected with the use of conventional environmental and behavioral assessment technologies.
For this study, the monitors were programmed to record activity and all environmental variables every minute. They were also programmed to assess vigilance by emitting an audible tone sequence at random intervals 20 times/h. Initially, the monitor presented a tone, to which the subjects were required to respond by pushing one of the buttons on the monitor. If the subject did not respond to the initial tone, a second, somewhat longer, more salient tone was presented 6 s later. Finally, if the subject failed to respond to the first 2 tones, a third, even longer tone was presented 11 s after the first tone. If a total of 20 s elapsed from the presentation of the first tone without a response by the subject, the monitor recorded the stimulus sequence as missed. An LED on the monitor was illuminated when the tones were emitted, providing a visual cue that a response was expected. In addition to determining whether or not the subject responded to the stimuli, the monitor also recorded, with millisecond accuracy, the time required for the subject to respond (reaction time).
Profile of mood states
Mood states were assessed with the use of the POMS. The POMS is a standardized, 65-item, paper-and-pencil questionnaire that consists of 6 subscales: Tension-Anxiety, Depression-Dejection, Anger-Hostility, Vigor-Activity, Fatigue-Inertia, and Confusion-Bewilderment (23). The subjects were asked to rate each adjective with regard to how they were feeling "right now" on a scale of 0 (not at all) to 4 (extremely). The POMS has been widely used in nutritional, psychopharmacologic, environmental, and exercise studies and is sensitive to the effects on mood of a variety of food constituents, including amino acids and caffeine (9,24–27). The POMS was administered to each subject once on the baseline assessment day and 3 times on the test day (Table 1).
Data analysis
All statistical analyses were performed with the use of SPSS for WINDOWS (version 10; SPSS Inc, Chicago). For the reaction time data from the vigilance monitors, means were calculated across discrete time intervals corresponding to the specific events in which the subjects participated. The events for which data were averaged were the baseline assessment (the time from when the subjects arrived for testing until they began the road march), the road march, the 30-min rest, the first 4.8-km run, the 4-h rest, and the second 4.8-km run. The time intervals were determined individually for each subject on the basis of the log of when he began and finished a particular event. Mean differences in reaction time from the baseline scores were calculated for each event. These data were analyzed with repeated-measures analysis of variance (ANOVA), with a between-subjects factor for treatment condition (CHO6, CHO12, or placebo) and a within-subjects factor associated with event (march, 30-min rest, first 4.8-km run, 4-h rest, or second 4.8-km run). An orthogonal component analysis to test for dose-related effects of the carbohydrate treatment was also conducted, as were one-way ANOVAs at each time period. Post hoc analyses across treatment conditions were performed with two-tailed Dunnett's multiple comparison tests. When appropriate, selected results were contrasted with the use of F tests across the time factor for each treatment.
For the 6 subscales of the POMS, descriptive statistics were obtained across treatment groups and multiple assessment times. The mean difference between the pretest baseline POMS collected on the week preceding the test and each of the 3 POMS administered on the test day was derived for each subject. These scores were analyzed with repeated-measures ANOVAs, with a between-subjects factor associated with treatment condition (CHO6, CHO12, or placebo) and a within-subjects factor for time of test. An orthogonal components analysis was also conducted to test for dose-response effects. One-way ANOVAs were run for the difference scores at each test time to determine which groups were significantly different at a specific administration of the POMS. When appropriate, post hoc analysis of this data was performed with two-tailed Dunnett's multiple comparison tests.
RESULTS
A vigilance monitor record from a representative subject is shown in Figure 1. The various activities in which he participated can be readily distinguished in channels 1 and 2, in which physical activity, which was maximal during the march and the two 4.8-km runs, was recorded. The reaction time of the subject to the auditory stimuli emitted by the monitor is shown in channel 4, clearly indicating the ability of this subject to respond rapidly to the tones during all segments of the study, with the exception of portions of the 4-h rest period. During most of that time period the subjects rested in a dark, warm tent, as confirmed by their lack of physical activity (channels 1–3), the low level of ambient light (channel 5), and the warm temperature (channel 6) (Figure 1). Most of the subjects used parts of this rest period as an opportunity to sleep and therefore frequently did not respond to the vigilance monitor stimuli.
FIGURE 1. . Representative vigilance monitor data from one subject continuously collected over the 10 h of the study. The 7 channels of data that were acquired are labeled individually on the y axis. The activities in which the subject participated, the time of administration of the treatments, and clock hours are indicated on the lowest x axis. Channels 1–3 contain data in which physical motion (acceleration) was sensed, and these data are similar to those of a standard actigraph (activity monitor) (22,28,29). The vertical height of each line plotted on the y axis of channels 1–3 represents the number of movements detected in 1 min. Each channel was optimized to detect motion with different physical characteristics. The first and second channels of activity data varied with regard to the amplitude of the acceleration. The third channel was sensitive to accelerations of longer duration. These variations in recording characteristics were achieved by changing the internal sensitivity of the accelerometer. Channel 4 displays the responses of the subject to the presentation of a sequence of tones at random intervals. The height of each line represents the speed of response to the tone. A line that reaches the top of the graph indicates that the subject did not respond to that stimulus. Channel 5 is the illumination level recorded at the subject's wrist. Channel 6 displays the ambient temperature recorded continuously at the subject's wrist. Channel 7 is a continuous record of ambient sound levels.
The mean (±SEM) results from the auditory vigilance testing for each treatment group are shown in Figure 2. The results are plotted as the mean difference from baseline across the different activities in which the subjects participated. Difference scores were calculated by subtracting the raw reaction time score for a given activity from the baseline score. Results from the ANOVA conducted on these data showed that carbohydrate treatment had a significant main effect on mean reaction time difference scores (P < 0.001). The subjects who received carbohydrate supplements responded more rapidly to the auditory stimuli emitted by the vigilance monitor than did those who received the placebo beverage. The interaction factor between treatment condition and different activities (road march, 30-min rest, 1st run, 4-h rest, and 2nd run) was also significant (P = 0.019). In addition, when this effect was decomposed using an orthogonal components analysis, there was a significant (P < 0.001) linear, dose-related relation across treatment conditions. One-way ANOVAs to analyze between-group differences during each activity showed that reaction time was faster with carbohydrate treatment than with placebo at every time period (march, P = 0.045; 30-min rest, P = 0.008; run 1, P = 0.005; 4-h rest, P = 0.011; run 2, P < 0.001). The Dunnett's multiple comparison post hoc tests indicated that across all activities the CHO12 group consistently responded more rapidly than did the placebo group (march, P = 0.028; 30-min rest, P = 0.005; run 1, P = 0.003; 4-h rest, P = 0.007; run 2, P = 0.002). The reaction time of the CHO6 group was significantly faster (P = 0.045) than that of the placebo group during the first run, and the difference between the 2 groups was nearly significant (P = 0.056) during the 4-h rest period, as determined by Dunnett's post hoc tests.
FIGURE 2. . Mean (±SEM) differences from baseline in auditory vigilance reaction times over the 10 h of the study. Each subject's vigilance was tested continuously by the ambulatory monitor that he wore on his nonpreferred wrist. Each subject's performance was summed over 5 time periods as indicated in Figure 1. Because the values plotted are the differences from baseline values, the higher the number on the y axis, the better the performance. Carbohydrate treatment had a main effect on the difference scores (ANOVA, P < 0.001). The interaction between treatment and time was significant (ANOVA, P = 0.019). When this effect was decomposed after the use of an orthogonal components analysis, there was a linear, dose-related effect across treatment groups (ANOVA, P < 0.001). Based on one-way ANOVAs, reaction time was shorter with carbohydrate treatment than with placebo at every time period (march, P = 0.045; 30-min rest, P = 0.008; run 1, P = 0.005; 4-h rest, P = 0.011; run 2, P < 0.001). Dunnett's post hoc tests indicated that for all activities the CHO12 group responded more rapidly than did the placebo group (march, P = 0.028; 30-min rest, P = 0.005; run 1, P = 0.003; 4-h rest, P = 0.007; run 2, P = 0.002) and that the CHO6 group responded more rapidly than did the placebo group during the first run (P = 0.045).
Because there was a significant interaction between the 2 main factors, time and treatment condition (P < 0.019), selected F test contrasts were conducted to compare the results for vigilance performance during the march with those for each subsequent individual activity. These analyses allowed us to determine whether vigilance performance varied significantly over time depending on the treatment group to which a subject was assigned. The analyses indicated that, compared with performance during the march, performance over the course of the day in the placebo group was significantly worse at all time periods, performance in the CHO6 group declined somewhat, and performance in the CHO12 group declined the least (Table 2). The only time period in which vigilance performance significantly declined in the CHO12 group was during the long rest period (P < 0.001), when many subjects were sleeping.
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TABLE 2 . Mean difference scores (lower numbers indicate worse vigilance performance) and results of post hoc F test contrasts conducted to compare vigilance performance during the march with that during each subsequent time period1
Carbohydrate supplementation was also found to have a significant effect on the Confusion and Vigor subscales of the POMS (Figure 3). For the Confusion subscale, a significant main effect of treatment was observed (P = 0.040; n = 140): the groups who received carbohydrates reported less confusion than did the placebo group. A significant quadratic component (P = 0.048) was present when the orthogonal components analysis was conducted. The results of one-way ANOVAs for both the second and third POMS administrations showed that the groups who received carbohydrates reported significantly less confusion (P = 0.017 and 0.038, respectively) than did the placebo group. Dunnett's multiple comparison tests indicated that the CHO12 group reported significantly less confusion than did the placebo group at the second and third POMS administrations (P = 0.010 and 0.027, respectively).
FIGURE 3. . Mean (±SEM) differences from baseline on the Confusion (top) and Vigor (bottom) subscales of the Profile of Mood States. The questionnaire was administered 3 times over the course of the test day. On the plot for confusion, lower numbers on the y axis indicate reduced self-reported confusion. A main effect of carbohydrate treatment was observed (ANOVA, P = 0.040): both the 6% and 12% carbohydrate groups (CHO6 and CHO12) reported less confusion than did the placebo group. A quadratic component was associated with carbohydrate dose when the orthogonal components analysis was conducted (ANOVA, P = 0.048). The results of one-way ANOVAs for both the second and third POMS administrations showed that the subjects who received carbohydrates reported significantly less confusion (P = 0.017 and 0.038, respectively) than did those who received placebo and that the CHO12 group reported significantly less confusion than did the placebo group (P = 0.010 and 0.027, respectively, Dunnett's post hoc tests). On the plot for vigor, higher numbers on the y axis indicate increased levels of self-reported vigor. There was a main effect of carbohydrate treatment (ANOVA, P = 0.025): self-reported vigor was higher in the subjects who received carbohydrates than in those who received placebo. There was a linear orthogonal component associated with carbohydrate dose (ANOVA, P = 0.008). The results of one-way ANOVAs indicated that there were significant differences between the groups who received carbohydrates and the placebo group in self-reported vigor at the second and third administrations of the POMS (P = 0.008 and 0.045, respectively). Post hoc Dunnett's tests for the second and third administrations of the POMS indicated that the CHO6 group reported significantly more vigor than did the placebo group (P = 0.005 and 0.025, respectively).
For the Vigor subscale of the POMS, the overall ANOVA indicated that there was a significant main effect of treatment condition (P = 0.025): self-reported vigor was significantly higher in the groups who received carbohydrates than in the placebo group. There was also a significant linear component (P = 0.008) associated with carbohydrate dose. One-way ANOVAs for the between-group differences on the Vigor subscale at each test administration indicated that there were significant differences between the groups who received carbohydrates and the placebo group in self-reported vigor at the second and third administrations of the POMS (P = 0.008 and 0.045, respectively). Post hoc Dunnett's tests of the vigor data from the second and third administration of the POMS indicated that the CHO6 group reported significantly more vigor than did the placebo group (P = 0.005 and 0.025, respectively). There were no significant effects of the carbohydrate treatment on any of the other subscales of the POMS.
DISCUSSION
This double-blind study, conducted over 10 h, provided 6 isovolumic doses of a liquid carbohydrate beverage to the CHO6 and CHO12 groups for a total dose of 35.1 and 70.2 kJ/kg, respectively. A control group received a placebo beverage that was indistinguishable from the treatment beverage. All groups received equivalent fluid volumes based on individual body weight. The subjects consisted of a large sample of fit, young male volunteers. All subjects participated in an identical, scripted and monitored, sequence of activities, including sustained aerobic activities. The subjects' cognitive state was continuously monitored with the use of a unique ambulatory vigilance monitoring device and a standardized mood questionnaire.
The results from the vigilance task show that a key cognitive function associated with maintaining alertness was significantly improved by administration of supplemental carbohydrate. These effects were significantly dose-related, as confirmed by an orthogonal components test. Optimal cognitive (vigilance) performance was present in the CHO12 group, the worst was in the placebo group, and the CHO6 group was intermediate (Figure 2). For the CHO12 group, the effects of carbohydrates on vigilance were present throughout the study: during the march (a period of sustained moderate aerobic activity), during both runs (periods of intense aerobic activity), and during the 2 rest periods.
Over the course of the study day, as shown by the contrasts conducted to compare the march with subsequent activities, vigilance performance in the placebo group declined significantly at every time period (Table 2). However, the only period of significant reduction in vigilance in the CHO12 group was during the rest period, when subjects were napping. The CHO6 group had an intermediate level of decline in vigilance over the course of the day. This indicates that the energy depletion that was occurring in the placebo group resulted in degraded vigilance performance, which was partially mitigated by the administration of a 6% carbohydrate beverage and almost completely prevented by administration of a 12% carbohydrate beverage.
The effects of carbohydrates on confusion, as assessed by the POMS, were similar to the effects on vigilance. Confusion at the second and third administrations of the POMS was significantly less in the subjects who received carbohydrates than in those who received placebo (Figure 3). These effects were also dose-related, with the CHO12 group having the greatest improvement. Vigor, as assessed by the POMS, was significantly greater in the subjects who received carbohydrates than in those who received placebo. Overall, this study shows that supplemental energy, in the form of liquid carbohydrate, has substantial beneficial effects on cognitive states during periods of high energy use. Vigilance, measured continuously with the vigilance monitor, and 2 moods closely associated with vigilance, confusion and vigor, were affected in the same positive manner by carbohydrates at multiple time periods. The POMS Confusion and Vigor subscales are established indicators of poor cognitive performance that assess cognitive states closely related to alertness (30).
Many mechanisms could explain the observed effects of carbohydrate energy supplements on vigilance and mood during aerobic exercise and during the periods of the study when the subjects were recovering from physical activity. One mechanism is an increase in plasma glucose available to the brain and therefore a generalized increase in brain metabolic activity. During exercise and recovery, brain requirements for glucose increase while plasma glucose is decreasing (1,31). The additional carbohydrates provided may have acted directly on the brain to prevent a reduction in the synthesis of various metabolites and neurotransmitters and may therefore have protected the brain from the consequences of an energy deficit.
In nonexercising animals, certain aspects of memory are enhanced when supplemental glucose is provided (32). In humans, glucose or treatments that increase plasma glucose enhance memory function (10,12,13). However, the effects of glucose or carbohydrates on vigilance and related functions in nonexercising humans have not been established (6). Both increased and decreased alertness and vigilance have been reported after carbohydrate administration in nonexercising subjects (11,14,15,24). The time of day, the macronutrient composition of meals, the test population characteristics, and the behavioral tests used may explain the differences between the studies (6,9,12,15,33). Of particular importance may be whether within-study comparisons are made across isoenergetic treatment groups. Studies that provide additional energy to some subjects should not be compared with those that examine differences in macronutrients while holding energy constant.
A critical factor determining the effects that carbohydrates have on alertness could be the energy status of the subject. In rested subjects who were fed a large lunch meal, increases in drowsiness were observed regardless of its composition (16). However, studies conducted on subjects who were tested in the morning, when energy stores are most depleted, suggest that a breakfast meal is critical for optimal cognitive performance (12,34). Our study resembles these breakfast studies in some respects, because although our subjects received breakfast, their energy expenditure was very high; thus, consumption of carbohydrates reversed an energy deficit. Children who exercise in the morning may be particularly susceptible to the adverse effects on cognitive function of skipping breakfast because they have less readily available energy stores than adults.
The increased alertness and responsiveness to stimuli that we observed could be the result of changes in a particular neurotransmitter system resulting from carbohydrate supplementation. For example, brain serotonin may be involved in regulating fatigue, particularly in exercising individuals (35,36). The role of serotonin in regulating alertness, sleep, and vigilance is controversial, and it has been reported to increase and decrease alertness, depending perhaps on the subtype of receptor affected (37,38). In resting subjects, carbohydrates increase peripheral tryptophan (7,8) and consequently brain serotonin, which is synthesized from tryptophan (39). When tryptophan is given to nonexercising individuals, it increases sleepiness (40,41). However, it has been reported that carbohydrates do not elevate plasma tryptophan in humans engaged in sustained exercise, and it has been hypothesized that carbohydrates will therefore have beneficial effects on centrally mediated fatigue (42). Tryptophan administration has also been reported to improve athletic performance (43) and to reduce pain sensitivity (40), suggesting that increased brain serotonin may be beneficial in exercising individuals. These issues will not be resolved until additional neurochemical studies are conducted in animals and studies that image brain serotonergic pathways during aerobic exercise are conducted in humans.
It has been suggested that the decreased muscle glycogen associated with sustained exercise and the subsequent degradation in physical performance may be responsible for increased accidents that occur during athletic activities such as downhill skiing (44). Although this is a viable hypothesis, it is also possible, on the basis of the results of the present study, that athletic accidents during periods when acute energy intake is not optimal occur because of impaired cognitive function. Decreased vigilance and increased confusion are not conducive to optimal physical performance in sports or other activities that require attention to difficult-to-detect stimuli and making critical decisions. The central fatigue hypothesis has typically been used to explain degradation in physical performance that cannot be accounted for by peripheral factors (45–47). Additional studies of the mechanisms responsible for the interactions between cognitive and peripheral factors during periods of moderate and high energy expenditure are necessary.
The present study suggests that supplementation with carbohydrates enables individuals to maintain optimal cognitive function when they are engaged in sustained physical activity. Individuals participating in many athletic activities and occupational duties, such as firefighting or construction, may benefit from the positive cognitive effects of carbohydrate supplementation. Other macronutrients that rapidly provide usable energy could also be beneficial under these conditions, provided that such macronutrients do not produce an imbalance in other key factors, such as amino acids, that are necessary for optimal brain function or produce adverse peripheral side effects.
Previously, it was not possible to continuously assess the cognitive function of individuals engaged in sustained high levels of physical activity, although anecdotal reports by athletes suggest that adverse changes in cognitive processing occur under such conditions. The availability of new technologies, such as the vigilance monitor used in this study, may permit a systematic evaluation of the effect of acute and chronic nutritional interventions on human cognitive function in naturalistic environments (21,22).
ACKNOWLEDGMENTS
Irwin Taub (deceased) and Teresa Skibiniski of the US Army Soldier and Biological Chemical Command, Natick, MA, designed and formulated the carbohydrate drinks, and their assistance was critical for the conduct of this study. We are grateful for the excellent assistance provided by Christopher Amendola, Cory Baker-Fulco, Specialist Nicholas DellaRocco, Julie D'Esposito, James Georgelis, Amy Marchetti, Susan McGraw, Sergeant DeAngelious Morrison, Phil Niro, Shivaun Roach, Karen Speckman, William Tharion, Sergeant Bryan Thorpe, and Staff Sergeant Roberta Worsham. In addition, we especially thank the members of 2nd Battalion, 75th Ranger Regiment, who volunteered for this study and participated in it with so much enthusiasm. We also acknowledge the exceptional support of their Commanders and other leaders.
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