Humans elicit numerous metabolic adaptations in response to shifts in dietary macronutrient intake to reconcile substrate availability with energy expenditure (EE). During continuous submaximal endurance exercise (>3–4 h), exhaustion appears to be associated with depleted endogenous carbohydrate (CHO) stores (i.e., skeletal muscle (1) and hepatic (2) glycogen) and the inability to maintain the CHO oxidation rates exhibited during the early stages of exercise (1,3). As such, various dietary training strategies have been proposed to spare finite glycogen stores (~700 g) and to optimize competition fuelling (4). CHO loading and supplementation seem to be the most efficacious strategies for prolonging exercise capacity and improving endurance performance by maximizing glycogen content and preserving CHO oxidation rates throughout exercise (1,3,5). However, interest has persisted in chronic adaptation to low-CHO diets in an attempt to spare endogenous CHO stores by maximizing fat oxidation rates and increasing hepatic production of fatty acid-derived ketone bodies (KB) as an additional fuel source (6,7).
Very low-CHO, high-fat, ketogenic diets (KD) contrast typical recommendations for endurance athletes. These are typically characterized by CHO intake <50 g⋅d−1 and elevated circulating KB (primarily d-β-hydroxybutyrate (d-βHB)) concentrations >0.5 mmol⋅L−1 (7), although concentrations >0.2 mmol⋅L−1 may be accepted (8). The term keto-adaptation has been used to encompass the metabolic adaptations resulting from a KD, which include the following: 1) increased maximal fat oxidation (MFO) to >1 g⋅min−1 (9–11); 2) reduced blood glucose utilization (9); and 3) reduced muscle (9,12) and hepatic (12) glycogen utilization during exercise. The importance of KB to EE is uncertain; however, it is postulated as the defining feature differentiating adaptation to ketogenic versus nonketogenic, lower-CHO (~2.5 g CHO⋅kg−1⋅d−1 or <25% energy intake (EI)), higher-fat (LCHF) diets (i.e., fat-adaptation). It seems that a minimum of 3–4 wk is required to overcome the initial performance decrement associated with a KD (9,11), and despite a suggestion that several months is required to optimize keto-adaptation, the only studies having investigated athletes ingesting a KD for this duration did not examine performance (10,12) or failed to rigorously monitor dietary intake and training volume (13).
Recently, a 3-wk KD negated high-intensity exercise performance in a ~45-min time trial in elite race walkers (11). However, performance during prolonged, high-intensity events (<2–3 h) demands high rates of CHO, not fat, oxidation (4,5). As such, keto- (or fat-) adaptation is more likely to benefit submaximal exercise events lasting several hours, as the practically infinite fat stores become the preferred energetic substrate. A single study has investigated the effect of a KD on submaximal exercise capacity (62%–64% of maximal oxygen uptake (V˙O2max) (9). The researchers used a single-arm design, with the pretest acting as the CHO-diet trial and the posttest after 4 wk of ingesting a KD. Of the five trained cyclists, three improved and two impaired their time-to-exhaustion (TTE), resulting in no overall difference between dietary conditions (147 vs 151 min). However, there was the potential of an order, or training, effect, and the results were heavily skewed by the improvement of a single participant from 148 to 232 min. In addition, for the CHO-diet trial, participants commenced exercise after an overnight fast and abstained from CHO during exercise, which is incongruent with recommended performance nutrition strategies (5,14). Therefore, the study design favored the keto-adapted trial.
In the same study, the researchers stated the efficiency of substrate oxidation improved after keto-adaptation because of a similar oxygen uptake at the same absolute workload (9). Because the stoichiometry of fat compared with CHO oxidation requires more oxygen for combustion to generate an identical energy yield, it would have been expected that oxygen uptake increased after the KD if exercise efficiency was maintained. This increased oxygen cost of exercise after keto- or fat-adaptation may impair exercise efficiency during prolonged, high-intensity endurance exercise (11); however, the shift in oxygen uptake at submaximal intensities may simply be a reflection of substrate preference, not exercise efficiency (15). More appropriate measures of exercise efficiency may be the energy cost of exercise (15) and the discrepancy between measured and predicted oxygen uptake based on shifts in the RER (16,17). Although differences in these measures tend to be subtle, they may elicit significant effects on submaximal exercise capacity.
To our knowledge, no studies have investigated the effect of keto-adaptation on submaximal exercise capacity in trained endurance athletes using a randomized, repeated-measures, crossover design and acute fuelling strategies to polarize substrate availability and metabolism. In concordance, the aim of the present study was to examine the effect of a 31-d KD on submaximal endurance capacity, substrate utilization, and exercise efficiency.
This study was conducted during the maintenance training phase for all participants. Participants underwent two 31-d experimental conditions (KD or their habitual mixed diet (HD)) with a testing block immediately before and during the final 3 d of the intervention in a randomized (www.randomizer.org), counterbalanced, crossover design with a 14- to 21-d washout period between dietary interventions. A schematic overview of the study design is shown in the Supplemental Content (Figure, Supplemental Digital Content 1, Overview of study design, http://links.lww.com/MSS/B596).
A sample size of 8–10 participants was established a priori based on previous investigations detecting physiological adaptations throughout a 2- to 4-wk dietary training intervention period (11,18,19). Participants were required to have been 1) habitually consuming a mixed diet for >12 months, 2) weight stable for >1 month, 3) running >50 km⋅wk−1, and 4) able to run a marathon in <3.5 h. Participants were excluded if they 1) had a history of fat- or keto-adaptation, 2) previously ingested ketone supplements, 3) were currently or recently injured, 4) experienced moderate-to-severe gastrointestinal symptoms or illness within the previous 4 wk, 5) had a history of irritable bowel syndrome, 6) habitually smoked, or 7) had been ingesting dietary supplements or medications known to effect performance within the previous 2 wk, with the exception of caffeine, protein, and CHO supplements. Ten eligible healthy, trained, male endurance athletes (two marathoners, five ultramarathoners, and three long-distance triathletes) volunteered to participate in the study. Participants were comprehensively screened by an experienced registered dietitian (RD) after their expression of interest. Participants were fully informed of the rationale of the study and possible risks of the experimental procedures before providing their written consent; however, they were not informed of the potential performance effects of a KD and were requested to refrain from personal investigation to prevent biasing their results. The study was approved by the Auckland University of Technology Ethics Committee (Auckland, New Zealand).
Metabolic and body composition testing (days −2 and 29)
Participants presented to the laboratory between 0600 and 0700 h having fasted from 2300 h the previous day and abstained from caffeine, alcohol, and strenuous exercise for the previous 24 h. Participants’ body mass (shorts only), height, and sum of 8 (Σ8) skinfolds were measured by an accredited anthropometrist (ISAK, level 1, skinfold coefficient of variation of 3.8%). To determine V˙O2max, maximal aerobic EE, MFO, and the relative intensity at which MFO occurs (Fatmax), participants performed a graded metabolic test to volitional exhaustion on a motorized treadmill (h/p/cosmos, Nußdorf, Germany). Participants ran for 3-min stages at 7.5, 9, 10.5, 12, 13.5, and 15 km⋅h−1 against a 1% gradient to simulate the energetic cost of level-gradient outdoor running (20). If RER ≥1.0 at 13.5 km⋅h−1, the 15-km⋅h−1 stage was excluded. Expired gas was collected and analyzed continuously using a computerized metabolic system with mixing chamber (Parvo Medics TrueOne 2400, Salt Lake City, UT), with the final 30 s of each stage averaged to calculate V˙O2 and V˙CO2. The second ventilatory threshold (VT2) was determined using the V-slope method (21). RPE (Borg 6–20 scale (22)) and heart rate (HR) using short-range telemetry (Garmin Fenix 3; Garmin, Kansas City, KS) were recorded during the final 30 s of each stage. After the completion of the final stage, treadmill speed was reduced to 11 km⋅h−1 and subsequently increased by 0.5 km⋅h−1 every 30 s until the attainment of volition exhaustion. V˙O2max was determined by averaging the highest 30-s period and accepted if there was at least a 30-s plateau in V˙O2 and one of the following two criteria: 1) RER >1.10 or 3) HR ± 10 bpm age-predicted maximum (220 − age). Simple regression equations were used to estimate the speed required to elicit 70% V˙O2max for the use in the run-to-exhaustion trial, until which participants were requested to refrain from strenuous exercise (~48 h).
Run-to-exhaustion trial (days 0 and 31)
Participants presented to the laboratory between 0600 and 0700 h having abstained from caffeine and alcohol for the previous 24 h. After the metabolic test on either day −2 or 29, participants were requested to ingest a high-CHO diet and consume adequate fluid to replicate their typical race preparation. Participants ingested a prescribed breakfast containing 2 g⋅kg−1 of CHO 90 min before arrival to replicate typical race-day nutrition. In the post-KD trial, participants continued ingesting a KD after the metabolic test and were prescribed an isoenergetic LCHF breakfast (<10 g CHO). Participants collected their first morning void to measure hydration status via urine specific gravity with a preexercise hypohydration threshold set at >1.025. Soon after arrival, an indwelling intravenous teflon catheter (18G; Terumo, Tokyo, Japan) was inserted into the antecubital vein for serial venous blood sampling. After 10 min of rest, body mass (shorts only), and venous and capillary blood samples were collected for determination of serum glucose, and blood d-βHB and lactate concentration. Participants then commenced running at the speed estimated to elicit 70% V˙O2max until volitional exhaustion (120–135 min after breakfast). Treadmill speed was matched during the prediet and postdiet trials. Participants were prescribed 4 mL⋅kg−1 of a 7.2% CHO-electrolyte drink (4:1 glucose-to-fructose ratio; Replace, Horleys, New Zealand) every 20 min, which was adjusted based on each participant’s tolerance and replicated in their postdiet trial. During the post-KD trial, participants received a combination of artificially sweetened fluids (electrolyte drink and cordial), water, and coconut oil (100% energy derived from fat; Blue Coconut Oil, Blue Coconut, New Zealand) at a rate reciprocating the fluid and energy ingested during the pre-KD trial. Expired gas was collected for 4–5 min every 30 min and at exhaustion, with the final 1 min averaged to calculate V˙O2 and V˙CO2, alongside RPE (22) and HR (Garmin Fenix 3; Garmin). Venous and capillary blood samples were collected at 60 and 120 min to determine serum glucose, and blood d-βHB and lactate concentration. The cannula was flushed with 3–4 mL of saline every 30 min to maintain patency. On attainment of volition exhaustion, treadmill speed was reduced to 4.4 km⋅h−1 for 2 min, then restored to the speed eliciting 70% V˙O2max until the participant indicated volitional exhaustion. This process was repeated, so at the third attainment of volitional exhaustion, the test was terminated. The walking time was excluded from the total TTE. This protocol has a lower coefficient of variation for measuring exercise capacity compared with traditional single exhaustion protocols (5.4%, 1.4%–9.6% (95% confidence intervals, or CI)) (23). Stimulatory aids (television, music, and conversation) were provided until the end of the first exhaustion phase to reduce boredom. Immediately after exercise cessation, venous and capillary blood samples were collected to determine serum glucose, and blood d-βHB and lactate concentration. Participants removed wet clothing and towel dried themselves before measuring their body mass. All trials were conducted by the same researcher, and standardized encouragement was provided. To ensure maximal effort in each trial, a substantial monetary incentive was awarded to the participant who accumulated the highest TTE after completion of the four trials. Participants were blinded to elapsed time during each trial and were not notified of their results until study completion. Participants were provided with 5 mL⋅kg−1 of water during the first hour of recovery, after which venous and capillary blood samples were collected to determine serum blood glucose and blood d-βHB concentration.
Dietary Intervention and Monitoring
Participants commenced their dietary allocation (KD or HD) immediately upon completion of their initial run-to-exhaustion trial (day 0), as theoretically the ability to restore depleted muscle and hepatic glycogen led to the rapid differentiation between the two dietary conditions. To ensure immediate and ongoing compliance to the KD, participants undertook a comprehensive education session with an RD after the metabolic test to provide sufficient preparation time. The education session included the following: 1) provision of a KD information booklet specifically developed for this study; 2) 3-d menu plan specific to the participant’s energy requirements, dietary preferences, and tolerances as determined by prior dietary review; 3) 7-d example menu plan for additional meal ideas; 4) extensive list of snack ideas; and 5) lifestyle, dining-out, shopping, cooking, and budgetary advice. To further support dietary compliance, participants were required to have daily contact with an RD, which included unlimited daily access (phone and e-mail). The prescribed KD contained ≤50 g·d−1 CHO, 15%–20% EI from protein, and 75%–80% EI from fat. Each participant was provided with coconut oil, extra virgin olive oil, LCHF cereal, and (for both dietary conditions) discounted fruit and vegetables. Participants were requested to refrain from alcohol and dietary supplement use for the duration of the study.
To monitor compliance to each dietary intervention, participants were trained in dietary reporting and provided an image-assisted (alongside a fiducial marker) weighed dietary record reported remotely in real-time to an RD via a mobile phone application (WhatsApp, Facebook, San Francisco, CA) for the 5 d preceding each run-to-exhaustion trial, a minimum of two nonconsecutive days between days 1–7, 8–14, and 15–21, and the morning of the trial to confirm the ingestion of the prescribed breakfast. Where underreporting was suspected, participants were required to provide a 24-h dietary recall or repeat the dietary report the subsequent day. Each dietary record was coded (FoodWorks Professional Edition, Version 8; Xyris Software, Queensland, Australia), with images validating the reported intakes, by an RD and checked for accuracy by a second RD. To help maintain energy balance, participants reported their morning body mass daily and were advised to prevent a >2% fluctuation. Verification of compliance to the KD was via daily self-measurement of urinary acetoacetate (AcAc) concentrations with a semiquantitative (color range) strip (Ketostix, Bayer) and capillary blood d-βHB concentrations on days 3, 7, 14, 21, and 28 before ingesting breakfast and exercising. Capillary blood d-βHB concentrations were also measured immediately before the post-KD metabolic test by the primary researcher. Images of the results were immediately sent to the primary researcher for quantification of ketosis. Color comparisons were made using the urinary AcAc strips in a subgroup (n = 4) of participants when ingesting an HD to dismiss the potential of false positives.
Participants designed their own 28-d training schedule and were asked to replicate this during each dietary adaptation period. This included a combination of running and cycling. Participants reported their resting morning HR and training data for each session, which included session duration (in minutes), average HR, and RPE. These variables were used to calculate Banister training impulse (TRIMP) and session RPE (24). Because the intervention was applied under free-living conditions, all other lifestyle choices were allowed to vary naturally.
Blood Sampling and Analysis
Venous blood samples were collected into 8-mL serum vacutainers (Becton Dickinson and Co, Franklin Lakes, NJ) with the participants seated in an upright position. Each serum vacutainer was left to clot for 30 min at room temperature before centrifugation at 1500g for 10 min at 4°C and separation into two 1.5-mL aliquots to be stored at −80°C before the analysis of glucose concentration (Cobas Modular P800 Analyser; Roche Diagnostics, Auckland, New Zealand). Capillary blood d-βHB (Freestyle Optium Neo; Abbott Diabetes Care, Victoria, Australia) and lactate (Lactate 2 Pro; Akray, Kyoto, Japan) concentration was measured from a fingertip blood sample using standardized techniques.
Calculation of Whole Body Rates of Substrate Oxidation and Energy Expenditure
Whole body rates of CHO oxidation, fat oxidation, and EE were calculated from steady-state V˙O2 and V˙CO2 using nonprotein RER values (25). During the KD trials, no corrections to the equations were implemented, as the oxidation of fat-derived KB does not alter the stoichiometry (25). To ascertain maximal aerobic EE (EEaero-max), V˙O2max was multiplied by 21.745 J⋅mL−1 O2, assuming that glucose was the only substrate oxidized (26). Fat oxidation rates obtained during the metabolic test were depicted graphically as a function of exercise intensity (% V˙O2max), and a third-order polynomial curve with intersection in (0,0) was constructed to determine MFO and Fatmax. A third-order polynomial curve with intersection was chosen based on the best-curve fit and with the assumption that if V˙O2 was zero, no fat oxidation would be observed.
To compare exercise efficiency between the pre- and post-KD conditions, calculations were adapted from previously published sources (25) to predict V˙O2 based on shifts in RER with unchanged efficiency (see the equation hereinafter). The derivation of this equation can be referred to in the Supplemental Content (Supplemental Digital Content 2, Derivation of the equation to calculate predicted oxygen uptake, http://links.lww.com/MSS/B597). Discrepancies between predicted and measured V˙O2 were used to quantify unaccounted oxygen uptake (i.e., oxygen uptake that cannot be explained by shifts in RER alone).
Predicted VO2 = ([0:55 × Pre-KD VCO2] + [4.471 × Pre-KD VO2]) / ([0.55 × Post-KD RER] + 4.471) Energy conversion: 1 kcal = 4.18 kJ
All data are expressed as mean (±SD) unless otherwise stated. The mean differences (Δ; ±90% confidence limits (CL)) between interventions and preintervention to postintervention are also expressed. Data were checked for normal distribution using the Shapiro–Wilk tests, and where appropriate, statistical analysis was performed on the logarithmic transformation of the data. For cardiorespiratory data, values were averaged for each hour and only used in analysis if n = 100% for all preintervention and postintervention trials. For urinary AcAc concentrations, weekly values were averaged for each participant. A three-way (diet–adaptation–intensity/time for cardiorespiratory and metabolic variables) or two-way (diet–adaptation for exercise capacity and body composition variables or adaptation–intensity/time for predicted vs measured oxygen uptake) repeated-measures ANOVA was performed, and if Mauchly’s test of sphericity was violated, adjustments to the degrees of freedom were made for the ANOVA using Greenhouse–Geisser ε (IBM SPSS Statistics software, version 21; IBM Corp). Where a significant effect was observed, post hoc analysis was conducted using Holm–Bonferroni adjustments for multiple comparisons. Within-group changes from preintervention to postintervention were examined using adjusted Student’s paired t-tests for dependent variables. Significance level was accepted at an α of P < 0.05. To interpret the magnitude of effect and to identify trends within nonsignificant data, Cohen d effect sizes (±90% CL) were estimated using a purpose-built spreadsheet (27), with ES thresholds set at <0.2, >0.2, >0.6, >1.2, >2.0, and >4.0 for trivial, small, moderate, large, very large, and extremely large effects, respectively. If the 90% CL overlapped 0, the magnitude of effect was deemed unclear.
Two participants were excluded during the study because of poor dietary reporting, poor dietary compliance to the KD, and low training load, thus giving a sample size of n = 8 (two marathoners, four ultramarathoners, and two long-distance triathletes; age, 29.6 ± 5.1 yr; body mass, 73.1 ± 6.9 kg; height, 1.81 ± 0.05 m; BMI, 22.4 ± 1.7 kg⋅m−2; V˙O2max, 59.4 ± 5.2 mL⋅kg−1⋅min−1; hours training per week, 10.4 ± 1.6 h; years training, 9.0 ± 3.5 yr).
Dietary and Training Compliance
There was no diet–adaptation interaction for body mass (P = 0.083); however, main effects for diet (P = 0.011) and adaptation (P < 0.001) were observed. Body mass was lower in the KD compared with HD (P < 0.002) and post- compared to pre-adaptation (P = 0.015). There was a significant diet–adaptation interaction for Σ8 skinfolds (P = 0.05), with a significant moderate reduction at post- compared with pre-KD (Δ = −5.2 ± 2.7 mm; P = 0.028; d = −0.60 ± 0.35). There was no difference for preintervention dietary macronutrient and EI between groups (all, P > 0.05; d = unclear or trivial; data not shown). Dietary intake during each intervention is summarized in Table 1. There was no difference in daily EI between diets (P = 0.49; d = 0.35 ± 0.92). Protein intake did not differ between diets (P = 0.99, d = 0.01 ± 1.08). However, in the KD compared with HD, there was a significant large reduction in CHO intake (Δ = −302 ± 49 g⋅d−1; P < 0.001; d = −3.44 ± 0.64) and a significant extremely large increase in fat intake (Δ = 152 ± 35 g⋅d−1; P < 0.001; d = 4.57 ± 1.20). Urinary AcAc and capillary blood d-βHB concentrations are summarized in the Supplemental Content (Figs. A and B, Supplemental Digital Content 3, Ketone body concentrations during keto adaptation, http://links.lww.com/MSS/B598). During the KD, all participants demonstrated positive urinary ketones by day 3 and for 95.5% of participant days. For blood d-βHB, all participants had elevated concentrations of ≥0.3 mmol⋅L−1 by day 3 and ≥0.5 mmol⋅L−1 by day 7. Participants demonstrated blood d-βHB concentrations ≥0.5 mmol⋅L−1 on 87.5% of participant days from day 3 onward. Training load did not differ between diets as determined by total TRIMP (P = 0.39; d = 0.25 ± 0.51) and total session RPE (P = 0.59; d = −0.17 ± 0.56), which is summarized in the Supplemental Content (Table, Supplemental Digital Content 4, Summary of accumulated training load during the 31-d adaptation periods, http://links.lww.com/MSS/B599). However, there was a trend toward a small increase in total running TRIMP during the KD compared with HD (Δ = 279 ± 220; P = 0.08; d = 0.27 ± 0.25), despite total running distance not differing (253.7 ± 112.8 vs 249.7 ± 104.9 km; P = 0.71; d = 0.03 ± 0.16).
Cardiorespiratory variables, perceived exertion, and substrate oxidation during the metabolic test
A summary of the outcomes from the metabolic tests can be viewed in the Supplemental Content (Table, Supplemental Digital Content 5, Summary of metabolic variables and perceived exertion during the metabolic test, http://links.lww.com/MSS/B600; Figs. A–D, Supplemental Digital Content 6, Summary of oxygen uptake and exercise efficiency during the metabolic test, http://links.lww.com/MSS/B601). For the post-KD test, blood d-βHB concentration was 0.94 ± 0.45 mmol⋅L−1 on arrival to the laboratory. There were no diet–adaptation interactions or main effects for V˙O2max, EEaero-max, VT2, or HRmax (all, P > 0.05; all d = trivial or unclear). However, there were diet–adaptation interaction for vV˙O2max (P = 0.01), with a significant moderate reduction in the post- compared with pre-KD test (Δ = −1.0 ± 0.8 km⋅h−1; P = 0.025; d = −0.92 ± 0.52). There were no interactions or main effects for HR or RPE (all, P > 0.05). A significant diet–adaptation–intensity interaction was observed for absolute V˙O2 (P = 0.003), with a small nonsignificant increase at 12 km⋅h−1 (Δ = 0.13 ± 0.11 L⋅min−1; P = 0.22; d = 0.34 ± 0.31) and a significant moderate increase at 13.5 km⋅h−1 (Δ = 0.29 ± 0.10 L⋅min−1; P = 0.011; d = 0.66 ± 0.27) in the post- compared with pre-KD test. Relative to body mass, there was a significant diet–adaptation–intensity interaction for V˙O2 (P = 0.011), with a trend toward a moderate increase at 12 km⋅h−1 (Δ = 2.7 ± 1.5 mL⋅kg−1⋅min−1; P = 0.082; d = 0.70 ± 0.47) and a significant large increase at 13.5 km⋅h−1 (Δ = 5.0 ± 1.6 mL⋅kg−1⋅min−1; P = 0.009; d = 1.30 ± 0.52) during the post- compared with pre-KD test.
There were significant diet–adaptation interactions for RER during the metabolic test (P = 0.001) and RER at V˙O2max (P = 0.004). In the post- compared with pre-KD test, there was a significant reduction in RER across all intensities (P < 0.001) and a very large reduction in RER at V˙O2max (Δ = −0.14 ± 0.04; P = 0.002; d = −2.84 ± 1.07). No differences were observed between the pre- and post-HD tests for RER (all, P > 0.05). There were significant diet–adaptation interactions for MFO and FATmax (all, P < 0.001), with a significant extremely large increase in MFO (0.57 ± 0.10 vs 1.12 ± 0.10 g⋅min−1; P < 0.001; d = 4.95 ± 1.07) and FATmax (43% ± 5% vs 70% ± 4% V˙O2max; P < 0.001; d = 5.05 ± 0.82) in the post- compared with pre-KD test, whereas the HD intervention had no effect on MFO (0.57 ± 0.11 vs 0.60 ± 0.12 g⋅min−1; P = 0.43; d = 0.20 ± 0.25) or FATmax (45% ± 7% vs 44% ± 3% V˙O2max; P = 0.42; d = −0.18 ± 0.39). All participants exhibited MFO rates >1.0 g⋅min−1 and FATmax >65% V˙O2max in the post-KD test.
Exercise efficiency during the metabolic test
In the post-KD test, there was a significant adaptation–intensity interaction for predicted compared with measured V˙O2 (P < 0.001), with a significant large increase in measured V˙O2 at 13.5 km⋅h−1 (Δ = 4.4 ± 1.6 mL⋅kg−1⋅min−1; P = 0.01, d = 1.25 ± 0.53; Fig. C, Supplemental Digital Content 6, Summary of oxygen uptake and exercise efficiency during the metabolic test, http://links.lww.com/MSS/B601). The shift in RER from the pre- to post-KD trial explained 14% ± 8% of the increase in V˙O2 at 13.5 km⋅h−1. Furthermore, there were significant diet–adaptation–intensity interactions for absolute EE (P < 0.001) and EE relative to body mass (P = 0.011). There was a significant small increase in absolute EE at 13.5 km⋅h−1 (Δ = 5.1 ± 2.2 kJ⋅min−1; P = 0.026; d = 0.56 ± 0.28) and, when relative to body mass, a small nonsignificant increase at 12 km⋅h−1 (Δ = 0.02 ± 0.02 kJ⋅kg−1⋅min−1; P = 0.18; d = 0.56 ± 0.47), and a significant moderate increase at 13.5 km⋅h−1 (Δ = 0.04 ± 0.02 kJ⋅kg−1⋅min−1; P = 0.018; d = 1.14 ± 0.73) in the post- compared with pre-KD test.
Environmental and dietary conditions during the run-to-exhaustion trial
Trials were performed within standard laboratory conditions of 17°C ± 1°C and 45% ± 3% humidity. There was no difference in running speed between the HD and KD trials (12.9 ± 0.7 vs 12.9 ± 0.8 km⋅h−1, P = 0.89), and all participants commenced each trial with urine-specific gravity values <1.025. The exercise-induced reduction in body mass did not differ between trials (all, P > 0.05, all d = trivial or unclear; Table 2). Macronutrient compositions of the pre-HD and post-HD trial meals were identical (148 ± 14 g CHO, 7 ± 1 g fat, and 23 ± 4 g protein) and similar to the pre-KD trial meal (146 ± 14 g CHO, 7 ± 1 g fat, and 23 ± 4 g protein). However, CHO and fat contents were lower and higher, respectively, in the post- compared with pre-KD trial meal (8 ± 1 g CHO and 67 ± 6 g fat), whereas protein content was similar (26 ± 6 g). There was no difference in CHO ingestion rate during the pre-HD, post-HD, and pre-KD trials (55.7 ± 6.0, 53.4 ± 2.8, and 55.3 ± 8.4 g⋅h−1, respectively; all P > 0.05; all d = trivial or unclear). Coconut oil was ingested during the post-KD trial at a rate identical to the EI in the pre-KD trial (26.0 ± 4.0 g⋅h−1).
Submaximal Exercise Capacity
There were no diet–adaptation interactions or main effects for TTE (P = 0.557) or distance-to-exhaustion (DTE; P = 0.508; Fig. 1A and B). Furthermore, there was no difference in mean change between diets for TTE (P = 0.56; d = 0.25 ± 0.60) or DTE (P = 0.51; d = 0.26 ± 0.60). The range within the 90% CI for TTE and DTE increased approximately twofold in the post- compared with pre-KD trial, whereas there was a reduction from the pre- to post-HD trial ([pre-HD, 112–263 min vs post-HD, 211–252 min and pre-KD, 223–254 min vs post-KD, 188–250 min] and [pre-HD, 45.8–56.4 km vs post-HD, 45.7–53.7 km and pre-KD, 47.8–54.6 km vs post-KD, 40.5–53.1 km]).
d-βHB, glucose, and lactate concentration during the run-to-exhaustion trial
There was a significant diet–adaptation–time interaction for blood d-βHB concentration (P < 0.001), with significant large to extremely large increases in the post- compared with pre-KD trial for all time points (all, P < 0.05; Fig. 2A). No differences in blood d-βHB concentration were observed between the pre- and post-HD trials (all, P > 0.05; all, d = trivial or unclear). There was a significant diet–adaptation–time interaction for serum glucose concentration (P = 0.032); however, post hoc analysis could only locate a moderate nonsignificant increase at preexercise (P = 0.21, d = 0.92 ± 0.62) and a moderate nonsignificant reduction at 2-h exercise (P = 0.49, d = −0.93 ± 0.82) in the post- compared with pre-KD trial (Fig. 2B). Serum glucose concentration was elevated from 1-h exercise to 1-h postexhaustion compared with preexercise in all trials (all, P < 0.05), except for the post-KD trial, for which only exhibited an increase from preexercise to 1-h exercise (P = 0.005). There was no diet–adaptation–time interaction for blood lactate concentration (P = 0.061). However, there was a significant effect for time (P = 0.03), with blood lactate concentrations lower at 2-h exercise compared with exhaustion (P = 0.02; Fig. 2C).
Substrate oxidation during the run-to-exhaustion trial
There was a significant diet–adaptation interaction for the rate and percentage contribution to total EE of CHO and fat oxidation (all, P < 0.001; Fig. 3A–D). CHO oxidation was ~2.5-fold higher in the pre- compared with post-KD trial, and fat oxidation was ~3.5-fold higher in the post- compared with pre-KD trial (all, P < 0.001). In the post-KD trial, fat oxidation rates ranged between 0.88 and 1.51 g⋅min−1. There were no differences in substrate oxidation between the pre- and post-HD trials (all, P > 0.05; all, d = trivial or unclear).
Cardiorespiratory variables and perceived exertion during the run-to-exhaustion trial
Table 2 and Figure 4A–D provide a summary of the cardiorespiratory variables and perceived exertion data during the run-to-exhaustion trials. There was a significant diet–adaptation–time interaction for absolute V˙O2 (P < 0.001), with significant small increases in the post- compared with pre-KD trial during the first (P = 0.025; d = 0.46 ± 0.26) and second hours (P = 0.016; d = 0.48 ± 0.23; Table 2). These effects increased when accounting for body mass, resulting in significant moderate increases in V˙O2 occurring during the first (P = 0.009; d = 0.83 ± 0.37) and second hours (P = 0.005; d = 0.84 ± 0.23) and a significant small increase at exhaustion (P = 0.046; d = 0.50 ± 0.39; Fig. 4A). No effects were observed between the pre- and post-HD trials for absolute and relative V˙O2 (all, P > 0.05; all, d = trivial or unclear). Despite a significant diet–adaptation–time interaction for exercise intensity relative to V˙O2max, post hoc analysis could not locate specific differences between trials (all, P > 0.05; all, d = trivial or unclear; Fig. 4B). There was a significant diet–adaptation interaction for HR (P = 0.011), with an increase in the post- compared with pre-KD trial (P < 0.001; Table 2). HR did not differ between the pre- and post-HD trials (P = 0.85).
Exercise efficiency during the run-to-exhaustion trial
In the post-KD trial, there was a significant adaptation–time interaction for predicted compared with measured V˙O2 (P = 0.001; Fig. 4A), with trends for small increases in measured V˙O2 during the first hour (Δ = 2.2 ± 1.4 mL⋅kg−1⋅min−1; P = 0.06; d = 0.46 ± 0.33) and second hours (Δ = 2.2 ± 1.2 mL⋅kg−1⋅min−1; P = 0.06; d = 0.48 ± 0.30). The shift in RER from the pre- to post-KD trial explained 55% ± 32% of the increase in V˙O2 during the first 2 h. There was a significant diet–adaptation–time interaction for absolute EE (P = 0.001), with trends for small increases the first hour (Δ = 3.0 ± 2.0 kJ⋅min−1; P = 0.076; d = 0.33 ± 0.25) and second hours (Δ = 3.1 ± 1.7 kJ⋅min−1; P = 0.056; d = 0.36 ± 0.23) in the post- compared with pre-KD trial (Table 2). When accounting for body mass, there was also a significant diet–adaptation–time interaction (P < 0.001), with significant moderately higher rates of EE during the first hour (Δ = 0.06 ± 0.03 kJ⋅kg−1⋅min−1; P = 0.022; d = 0.65 ± 0.36) and second hours (Δ = 0.06 ± 0.02 kJ⋅kg−1⋅min−1; P = 0.014; d = 0.67 ± 0.31) in the post- compared with pre-KD trial (Fig. 4A). Despite a significant diet–adaptation–time interaction for the intensity relative to EEaero-max (P = 0.001), post hoc analysis could not locate specific differences between trials (all, P > 0.05; Fig. 4D).
Exercise capacity and lactate accumulation based on RER at V˙O2max
Comparisons for exercise capacity and blood lactate concentrations were made between pre- and post-KD trials based on RER at V˙O2max (<1.0 (n = 4) and >1.0 (n = 4)). In the group with RER <1.0 at V˙O2max, TTE significantly declined from pre- to post-KD (237 ± 31 min vs 174 ± 24 min; P = 0.04; d = 1.49 ± 1.04). In contrast, for the group with RER >1.0 at V˙O2max, there was no effect of the KD on TTE (241 ± 27 min vs 265 ± 21 min; P = 0.15; d = 0.67 ± 0.83). Using an unadjusted Student’s unpaired t-test, there was a large significant reduction for mean change in TTE from prediet to postdiet in the group with RER <1.0 compared with >1.0 at V˙O2max (−63 ± 38 min vs 24 ± 21 min; P = 0.009, d = 1.22 ± 0.86). Furthermore, using an unadjusted Student’s unpaired t-test for each time point, the group with RER <1.0 at V˙O2max exhibited a significant large increase in the difference for mean lactate concentration at exhaustion from prediet to postdiet compared with the group with RER >1.0 at V˙O2max (P = 0.015, d = 1.45 ± 0.86). These TTE and lactate data are presented in the Supplemental Content (Figs. A–B, Supplemental Digital Content 7, Time-to-exhaustion and blood lactate concentration based on RER at V˙O2max in the post-KD trial, http://links.lww.com/MSS/B602). There were no differences in exercise intensity relative to VT2, V˙O2max, or vV˙O2max, or rates of substrate oxidation or blood d-βHB and serum glucose concentrations between the two groups (data not shown).
The present study investigated the effect of a 31-d KD on submaximal exercise capacity in endurance-trained runners. We provide novel findings regarding exercise efficiency related to oxygen uptake and EE. We found that 1) a 31-d KD preserved mean submaximal exercise capacity without the requirement of CHO restoration or supplementation, 2) exercise efficiency was impaired at intensities above 70% V˙O2max as evidenced by oxygen uptake that could not be explained by shifts in RER alone and increases energy expenditure shifts in RER alone, 3) RER at V˙O2max may have implications as a performance surrogate after keto-adaptation, and 4) keto-adaptation increased submaximal endurance variability as evidenced by a twofold increase in the 90% CI for TTE and DTE in the post- compared with pre-KD trial, which coincided with reduced endurance capacity in five of eight runners, indicating a meaningful risk of an endurance decrement at an individual level.
The aim of the dietary interventions was to polarize metabolic states, as it has been suggested that increased fat oxidation rates and blood d-βHB concentrations after keto-adaptation can overcome the necessity of acute CHO fuelling strategies during continuous exercise lasting for several hours (7). Because we could not replicate previous studies by providing meals, snacks, and fluid to participants during the adaptation period (9,11), we implemented a novel approach to measure and verify prescribed dietary intakes. This included an image-assisted (alongside a fiducial marker) weighed dietary record for 40% of the dietary adaptation days to reduce the potential of underreporting and misreporting (28), coding errors, and daily dietary variation (29). When combined with urinary AcAc (daily) and blood d-βHB (days 3, 7, 14, 21, and 28 and post-KD tests) measures, we can confirm that all participants were extremely compliant to the KD. Although the HD was lower in CHO compared with recommendations for moderate training loads (4.6 g⋅kg⋅d−1 vs 5–7 g⋅kg⋅d−1) (5), this difference is negligible and did not seem to affect training adaptation or exercise capacity. Moreover, studies using intensified training protocols during dietary adaptation periods, such as the aforementioned investigation of keto-adaptation in elite race walkers (11), may limit direct comparison to the present study because of interferences from a training response.
Acute fuelling strategies before and during the run-to-exhaustion trials would have, in part, compensated for suboptimal CHO intakes in the days prior. This required participants to ingest either a high- or low-CHO meal 2 h before the run-to-exhaustion trials and either CHO or fat while running according to the trial allocation. Arguably, the rate of CHO intake in our study (~55 g⋅h−1) was below recommendations for optimal performance of these durations (~90 g⋅h−1) (14). Nevertheless, 55 g⋅h−1 is comparable to recent publications of real-world dietary behaviors in ultraendurance athletes (30), with even small rates of CHO supplementation (i.e., 10 g⋅h−1) providing a performance benefit (14). In turn, fat oxidation was ~4-fold lower and CHO oxidation ~2.5-fold higher in the high-CHO trials compared with keto-adapted trial. This was likely underpinned by a combination of 1) elevated muscle (31) and hepatic glycogen content (32), 2) elevated blood glucose uptake into the muscle (33), 3) maintenance of blood glucose concentration (3), and 4) reduction in hepatic glycogen utilization (2). However, if CHO was acutely ingested in the post-KD trial, this would oppose adaptations to the KD and suppress hepatic ketogenesis, thus compromising rates of fat oxidation and ketolysis (8).
To investigate exercise efficiency after keto-adaptation, we estimated oxygen uptake that could not be explained by shifts in RER from pre- to post-KD conditions, assuming no change to EE. At lower intensities (particularly <60% V˙O2max), the shift in RER could fully explain the increase in oxygen uptake. This coincides with a previous study demonstrating similar oxygen uptake at 62%–64% V˙O2max (9), which suggested that keto-adaptation improved exercise efficiency at lower intensities. Nevertheless, we found that RER could only account for 14% of the increase in oxygen uptake at 13.5 km⋅h−1 during the metabolic test (~77% V˙O2max when keto-adapted) and 55% of the increase in oxygen uptake during the first 2 h of the run-to-exhaustion trial (~72% V˙O2max when keto-adapted). These effects likely underpinned the increase in EE observed between the pre- and post-KD trials and have previously been demonstrated in sedentary individuals (16), but were thought to be abrogated by endurance training (17). However, we demonstrate that this effect persists with keto-adaptation regardless of training status. The unaccounted oxygen uptake may be due to elevated fatty acid–activated transcription factor peroxisome proliferator–activated receptor α. In addition to peroxisome proliferator–activated receptor α’s upregulation of fat oxidative genes, it also regulates the expression of mitochondrial uncoupling proteins (34). Nevertheless, the effect of a ketogenic or LCHF diet on mitochondrial uncoupling in human skeletal muscle is unclear (16,17,35); therefore, this remains speculative.
Our findings also indicate that keto-adaptation impairs high-intensity, endurance performance. Similar to previous studies (9,11), CHO oxidation was truncated at near maximal exercise intensities after keto-adaptation, which manifested as a throttling of RER at V˙O2max. This may be due to an attenuation of glycogenolysis and pyruvate dehydrogenase activity (36) and could have underpinned the 1-km⋅h−1 reduction in velocity at V˙O2max. Furthermore, RPE was nonsignificantly higher at >65% V˙O2max during the metabolic test after keto-adaptation, which is in line with an earlier study investigating a 3-wk KD intervention in elite race walkers (11). However, during the submaximal run-to-exhaustion, RPE did not differ, despite HR being 7–9 bpm higher. This could be due to increased sympathetic nervous system activity (37), with potential neural effects after keto-adaptation compensating for the increase in metabolic stress. However, a decrement in high-intensity exercise performance does not necessarily negate ultraendurance performance. Therefore, with anecdotal reports of (ultra-) endurance athletes successfully employing LCHF diets and improved performance (18,19) or exercise capacity (9) in select individuals, including in the present study, further research remains warranted to understand the individual response to LCHF and KD for athletes competing at submaximal exercise intensities.
A potential surrogate to identify the individual response to keto-adaptation is RER at V˙O2max. In the present study, when RER was >1.0 compared with <1.0 (n = 4) at V˙O2max (n = 4) after keto-adaptation, between-diet comparisons of mean change from prediet to postdiet demonstrated a higher endurance capacity and lower lactate concentration at exhaustion. This response occurred despite no difference in exercise intensity relative to VT2, V˙O2max and vV˙O2max. It is important to note, however, that 3- to 5-min stages during a graded exercise test may not be reflective of steady-state pulmonary V˙CO2, particularly at high intensities, which can overestimate RER (38). Although corrective models have been proposed, these have not been validated but do highlight a potential limitation of the current analysis. Nonetheless, a reduction in RER at V˙O2max is associated with impaired high-intensity performance because of a reduction in maximal CHO utilization (9,11); with the present findings also suggesting a relationship with endurance capacity at submaximal intensities.
Differences in endurance capacity between groups with RER <1.0 compared with >1.0 at V˙O2max were also unrelated to rates of fat oxidation and serum glucose and blood d-βHB concentrations. Because MFO can increase to >1 g⋅min−1 within 3 d of adaptation to an LCHF diet (39) and blood KB concentrations increase rapidly (hours to days) in response to low-CHO availability (e.g., starvation and exhaustive exercise and a KD) (8), they are unreliable markers for optimal keto-adaptation. Potentially, differences in endurance capacity were due to lower rates of lactate oxidation (40) and gluconeogenesis via lactate (12) in the group with RER <1.0, thus resulting in the accumulation of blood lactate. Lactate production may also be higher because of increased shuttling of pyruvate to lactate dehydrogenase because of the inhibition in pyruvate dehydrogenase activity (36). Elevated blood lactate concentrations at submaximal exercise intensities also appear in endurance athletes self-reporting chronic (>8 months) keto-adaptation (10,12); therefore, it is uncertain whether this impairment in CHO metabolism resolves or persists with long-term adherence to a KD.
In conclusion, these findings demonstrate that 31 d of keto-adaptation can preserve mean submaximal exercise capacity. However, exercise efficiency was impaired, endurance variability increased, and there was a greater risk of an endurance decrement at an individual level after keto-adaptation. Moreover, the suggestion that longer adaptation periods to a KD are necessary to enhance endurance performance is currently unsubstantiated, although shifts in RER at V˙O2max may provide a time-course adaptation or performance surrogate to monitor such changes.
The study was designed by D. S., F. M., A. B., and D. D.; data were collected by D. S.; data interpretation and manuscript preparation were undertaken by D. S., F. M., A. B., E. M., and D. D. All authors approved the final version of the article. The authors would like to thank the participants for their commitment, humor, and cooperation. The authors declare no conflict of interest. Publication funding was received from The University of Auckland, Faculty of Medical Health Science Internal Sources. The results of the present study do not constitute endorsement by the American College of Sports Medicine. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.
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