2Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
3Dartmouth Hitchcock Medical Center, Cardiovascular Medicine, Lebanon, NH
4Geisel School of Medicine at Dartmouth, Hanover, NH
Methods: We searched PubMed and SCOPUS for randomized trials published from 1992-2017 with a primary endpoint of endurance performance. We identified 407 citations which were examined against our inclusion criteria of randomization or crossover allocation to diet and for which a primary outcome was endurance performance.
Results: Twenty full text articles met our inclusion criteria and were included in the present review. In the days to weeks prior to testing, one trial of a high-fat diet versus carbohydrate improved performance, the others were neutral. There was no benefit of substituting protein for carbohydrate during this time period, but almond intake did result in ergogenic benefits. In the pre-event meal, fat only showed ergogenic benefits when combined with carbohydrate intake. A single study suggested that vegetable-derived nitrates did provide benefit. During endurance events, partial substitution of carbohydrates with protein had varying results on performance and should be further examined.
Conclusion: Carbohydrates remain the best fuel source both before and during events for overall endurance performance compared to other macronutrients, including water. Partial substitution of carbohydrate with fat and protein immediately before and during events warrants further investigation. Additional trials on nitrates and almond consumption are also needed.
Of the metabolic pathways that generate ATP to power muscular contraction, it is the oxidative pathways that are most relevant in endurance events. The energy substrates available for cellular respiration include muscle and liver glycogen, intramuscular lipid, triglycerides stored in adipose, and protein. Compared to free fatty acids, carbohydrate generates more ATP per unit of oxygen and thus provides greater gross exercise efficiency [4]. In addition, during endurance events, the onset of fatigue is closely correlated with depletion of muscle glycogen [5]. For these reasons, much of the research on sports nutrition in the hours and days prior to exercise has focused on carbohydrate loading to maximize liver and muscle glycogen stores. However, over the past decade, investigators have explored alternatives to this traditional approach. These alternatives include attempts to induce adaptive changes in intracellular transporters and enzymes to allow more lipolysis and more efficient use of free fatty acids during exercise. Other experiments have compared diets with an increased protein content and others have tested specific foods. Our conceptual view of the literature is shown in Table 1.
Time Relative to Endurance Event |
||||
|
Days to Weeks Prior |
Pre Event Meal |
During Event |
Immediately Post |
Carb vs Fat |
A |
E |
I |
M |
Carb vs Protein |
B |
F |
J |
N |
Carb vs Carb |
C |
G |
K |
O |
Specific Foods |
D |
H |
L |
P |
In SCOPUS, the following keywords were used (endurance exercise OR aerobic OR endurance performance) AND (performance OR recovery) AND (diet) AND (carbohydrate intake OR fat intake or protein intake) AND English [Language]. Additional publications were also retrieved from the authors’ files and the references of selected papers. A total of 348 articles from PubMed and 59 articles from SCOPUS resulted from the initial search.
- randomized control trial and/or crossover design
- dietary intervention before and/or during endurance event
- endurance event was moderate-to-high intensity
- endurance performance (timed trials or duration) as primary endpoint
- primary endpoint results included in publication - published between 1992 and 2017
High Carbohydrate vs High Fat |
||||||||||
Trial |
N |
Sex |
Level |
Timing of Intervention |
Diet Label |
Macronutrient Distribution |
Primary Endpoint |
Result |
||
Carb |
Fat |
Protein |
||||||||
Helge 1998 |
15 |
M |
Untrained |
4 wks straight |
High carb |
65 |
20 |
15 |
TTE cycling |
No difference |
High Fat |
21 |
62 |
17 |
|||||||
Carey 2001 |
7 |
M |
Well trained competitive |
6 days prior to 1 day of Carb loading |
High Carb |
70 |
15 |
15 |
1 hour cycling TT after 4 hours of at 65% of VO2 max |
No difference |
High Fat |
16 |
69 |
15 |
|||||||
Lambert 2001 |
5 |
M |
Trained |
10 days prior to 3 days of Carb loading |
High Carb |
>65 |
<15 |
20 |
20 km cycling TT after 150 mins at 70% of VO2 max |
Slight reduction in time required to cover 20 km |
High Fat |
<15 |
>65 |
20 |
|||||||
Rowlands 2002 |
7 |
M |
Nationally competitive |
14 days straight |
High Carb |
70 |
16 |
14 |
100 km cycling TT after 45 mins of steady state exercise |
No difference |
High Fat |
15 |
66 |
20 |
|||||||
11.5 days prior to 2.5 days of Carb loading |
High Fat |
15 |
66 |
20 |
||||||
Fleming 2003 |
20 |
M |
Recreationally active |
6 wks straight (HF, mod protein) vs control |
High Carb |
59 |
25 |
15 |
Work output and max power in 45 min cycling test |
18% decrease in work output and 10% decrease in peak power in the HF, mod protein group |
High Fat; Mod Protein |
8 |
61 |
30 |
|||||||
Larson-Meyer 2008 |
21 |
M/F |
Endurance trained runners |
3 days prior to 1 day of "glycogen normalization" |
Low Fat |
75 |
10 |
15 |
10 km running time trial after 90 minute preload run at 62% of VO2 max. |
No difference in 10 km running times. |
Mod Fat |
50 |
35 |
15 |
|||||||
Couto 2014 |
19 |
M |
Physically active adolescents |
48 hours |
High Carb |
69 |
15 |
15 |
10 km time trial after 10 mins of running at 65% of VO2 max |
10 km times were shorter in high Carb versus high FAT. No difference in high Carb vs habitual. |
High Fat |
24 |
60 |
15 |
|||||||
Habitual |
56 |
27 |
16 |
|||||||
High Carb vs High Protein |
||||||||||
Macdermid 2006 |
7 |
- |
competitive trained |
7 days |
High Carb |
66 |
23 |
11 |
Long distance cycling time trial |
Times were significantly lower in the high carbodydrate group (126 mins vs 153 mins). |
High Protein |
44 |
26 |
30 |
|||||||
McLay 2007 |
9 |
F |
endurance athletes |
3 days |
High Carb |
47 |
35 |
17 |
16 km cycling time trial after 45 min preload ride |
No difference in time trial times |
Normal |
77 |
7 |
14 |
|||||||
Carbohydrate vs Carbohydrate |
||||||||||
Chen 2007 |
9 |
M |
endurance runners |
3 days |
high index/high load |
73 |
14 |
13 |
10 km running time trial after 1 hour preload run at 70% of VO2 max. |
No difference in the two high carb groups but the low index/low load group had faster 10 km run times than the high index/low load group. |
low index/low load |
73 |
14 |
13 |
|||||||
high index/low load |
30 |
49 |
21 |
|||||||
Specific Foods |
||||||||||
Yi 2014 |
10 |
Male |
trained cyclists and triatheletes |
4 weeks |
75 g/d almonds |
N/A |
N/A |
N/A |
Distance covered in 20 min time trial after 125 mins of steady state cycling |
Greater distance covered in the almond group (21.9 vs 20.2 kms) |
isocaloric cookies |
N/A |
N/A |
N/A |
|||||||
Lis 2015 |
13 |
M/F |
endurance |
7 days |
Gluten free diet |
N/A |
N/A |
N/A |
Distance covered in 15 min time trial after 45 minute ride at 70% VO2 max |
No difference |
Gluten containing diet |
N/A |
N/A |
N/A |
High Fat vs High Carbohydrate vs (High Fat + Simple Carbohydrate) |
|||||||||||
Trial |
N |
Sex |
Level |
Timing of Intervention |
Diet Label |
Macronutrient Distribution |
Primary Endpoint |
Result |
|||
Total Carb |
Fat |
Protein |
|||||||||
Murakami 2012 |
8 |
M |
Collegiate long distance athletes |
4 hours prior to test after 3 days of Carb loading |
High Carb |
71 |
20 |
9 |
TTE on treadmill at 80% of VO2 max following 80 min preload run at 72% of VO2 max. |
TTE was significantly greater in the High FAT + maltodextrin group compared to the other two group |
|
High Fat |
30 |
55 |
15 |
||||||||
High Fat+ maltodextrin (410 kcals) |
30 |
55 |
15 |
||||||||
Carbohydrate vs Carbohydarte |
|||||||||||
Trial |
N |
Sex |
Level |
Timing of Intervention |
Diet Label |
Total Carb |
Dietary Fiber |
Soluble Fiber |
Primary Endpoint |
Result |
|
Kirwan 1998 |
6 |
F |
Recreationally active college women |
45 mins before endurance test |
Sweetened rolled oats |
75 g |
6.8 g |
2.3 g |
Time to exhaustion on cycle ergometry |
TTE was 16% greater in the SRO group than the control group. No difference between SOF and control. |
|
Mod Fiber |
75 g |
3.1 g |
1.6 g |
||||||||
Control (water) |
0 |
0 |
0 |
||||||||
Specific Foods |
|||||||||||
Trial |
N |
Sex |
Level |
Timing of Intervention |
Diet Label |
Total Carb |
Dietary Fiber |
Soluble Fiber |
Primary Endpoint |
Result |
|
Murphy 2012 |
11 |
M/F |
Recreationally fit; aged 18-55. |
75 mins before endurance test |
Nitrate (200 g of beetroot with > 500 mg of nitrates) |
N/A |
N/A |
N/A |
5 km treadmill run |
Time was statistically shorter in the beetroot group. This was limited to the final 1.8 kms. |
|
Control (isocaloric cranberry relish) |
N/A |
N/A |
N/A |
||||||||
Haakonssen 2014 |
32 |
F |
well trained cyclists |
2 hours prior to test |
3 servings of dairy (1350 mg Ca+) |
N/A |
N/A |
N/A |
Distance covered in 10 min time trial following 80 mins of exercise at 60% of VO2 max. |
No difference in performance |
|
isocaloric control |
N/A |
N/A |
N/A |
Siegler et al further examined partial protein substitutions by comparing CHO-only and CHO-PRO beverages to an isocaloric CHO-PRO-peptide beverage in 12 healthy men in a randomized crossover design [26]. No significant effect on timed trial or mean power output in a 5km time trial were observed between conditions. However, several metabolic conditions differed between conditions. RER was consistently higher in the CHO-PRO condition than the other conditions and mean heart rate was consistently lower in CHO condition compared to the others. Conversely, Cathcart et al did observe differences in endurance performance after randomizing 28 competitive mountain bikers to either CHOonly (control) supplements or CHO-PRO supplements [27]. Overall, those consuming the CHO-PRO supplement performed significantly faster than the placebo. However, it is difficult to attribute the enhancement specifically to protein as those in the CHO-PRO also consumed more calories on average during the race. Of note, this is the only experiment performed at very high ambient temperatures.
Carbohydrate vs Protein |
|||||||||
Trial |
N |
Sex |
Level |
Timing of Intervention |
Type of Fuel |
Diet Label |
Nutrient Composition |
Primary Endpoint |
Result |
Osterberg |
13 |
M |
trained |
4 weeks |
Beverage |
CHO |
6% (glucose, fructose, sucrose) |
TT and power output to complete 7kj/kg of work |
No significant differences |
CHO-PRO |
7.5% (glucose, fructose, sucrose) vs 1.6% (whey) |
||||||||
Placebo |
noncaloric beverage |
||||||||
Hansen |
18 |
M |
trained; competitive |
6 days |
Beverage |
CHO |
1.2g/kg/h |
5-min power output TT |
No significant differences |
CHO-PRO |
1g/kg/h; 0.2g/kg/h |
||||||||
Siegler |
12 |
M |
untrained, healthy individuals |
2 months |
Beverage |
CHO |
67 g/hr (maltodextrin) |
5 km TT and power output |
No significant differences |
CHO-PRO |
53.1g/hr; 13.6g/hr (whey) |
||||||||
CHO-PRO-PEP |
53.1g/hr; 11.0g/hr; 2.4g/hr (marine-based) |
||||||||
Cathcart |
28 |
M/F |
trained |
8 days |
Food (Liquid and Solid) |
CHO-PRO |
Liquid: 72g CHO, 18g whey PRO |
TT of 8-day mountain bike race |
TT faster in CHO-PRO compared to CHO-only |
Placebo |
Liquid: 76g CHO |
While fat adaptation may have beneficial metabolic effects, these societies points out several benefits specific to carbohydrates, including its higher availability of ATP per unit of oxygen for mitochondria [5]. In terms of dietary intake guidelines, they recommend specifying CHO, PRO, and energy needs based on kilogram of body weight given the wide range of body size amongst competitive athletes. In addition, they recommends providing the timing of each nutrient should be specific to the sport rather than general daily goals.
In terms of daily CHO consumption during the training season, current recommendations include 6-10g/kg/day of CHO for those lasting 1-3 hours and 8-12g/kg/day for those lasting longer than 4 hours. During the events, the American College of Sports Medicine (ACSM) recommends 30-60g/hour of CHO for events lasting 1.5-2h and up to 90g/hour of CHO for those lasting 2.5-3 hours.
The quality of carbohydrate may also influence performance. Specifically, a high carbohydrate diet with a low glycemic load [15]. Unlike the glycemic index, a low glycemic load takes into account the quantity of the carbohydrate, which may prove more helpful in assessing carbohydrate quality.
Following a high-protein diet compared to high-carbohydrate diet had either a neutral [14] or negative [13] effect on timed trials compared to a high carbohydrate diets. Interestingly, athletes who supplemented with almonds exercised longer than those supplemented with isocaloric cookies, despite the lower carbohydrate content of the almonds [16]. Given the rising popularity of the Paleo diet, which favors high protein intake and lower carbohydrate intake, this food-based study is particularly timely. Further research should examine the potential benefits that may be specific to almonds or other nuts, such as the fatty acid profile. In general, given the wide range of study duration among these studies, additional RCTs are warranted to better elucidate the effect of high protein diets on endurance performance.
While nitrates from beetroots show promise for performance enhancement [21], additional studies with larger sample sizes are needed to address nitrates’ possible benefit, especially considering the rise in the consumer market of beetroot juice. Conversely, despite dairy’s growing popularity as a recovery food, calcium from dairy sources showed no benefit in performance when consumed immediately before an event [22].
The rise of a wide-range of diet trends amongst athletes, from the Paleo diet to the vegan diet, further emphasizes the call for future trials to investigate the relationship between macronutrient quality and endurance performance. In a preliminary report from a recent international study examining the prevalence of plantbased runners, it is estimated that 21% and 35% of runners currently ascribe to a vegetarian and vegan diet, respectively [32]. However, only one study in this review examined the effects of a specific protein source (almonds). Most studies only accounted for the quantity of the protein. Considering the contrasting nutritional composition between animal and plant-based protein, particularly in terms of iron, studies should at least differentiate between these two protein sources when analyzing the nutrient composition of meals. Studies may also benefit from accounting for the specific foods consumed within each of these categories.
The generalizability of these results is limited given the nature of the articles included in this review. The trials discussed in this review only examined endurance events related to cycling or running. In addition, most studies investigated men under the age of 50, indicating a strong gender and age bias. In addition, small sample size of these studies, which ranged from 5 - 32 participants. Finally, it is likely that not all relevant papers were included in this review as the literature search was not strictly systematic in its methodology.
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