It is well established that performance in endurance sports (>90 min of moderate- to high-intensity exercise) is enhanced by strategies that increase the muscles’ endogenous (1) and exogenous (2) carbohydrate (CHO) use. For this reason, the traditional dietary guidelines for endurance athletes have encouraged a diet providing sustained high-CHO (HCHO) availability to support the quality of daily training, promote recovery and prepare optimally for competition (3). More recently, investigation of the cellular responses to training and nutrition interactions has identified that exercising under conditions of low-CHO availability amplifies the cascade of signaling events that underpin metabolic adaptation. Furthermore, low-CHO availability can delay the restoration of muscle glycogen, thus extending the period of enhanced cellular signaling (4). This work has enabled sports scientists and coaches to exploit the specificity of nutritional support for each workout, by integrating strategies of “train high” and “train low” into the athlete’s training program, both in an applied context (5) and in laboratory investigations (6). Of note, the deliberate periodization of CHO availability during a training block can enhance training responses, transferring to superior performance in subelite endurance athletes (6). However, similar evidence is not yet available in elite competitors (7). An alternate but somewhat contentious approach to nutrition for endurance athletes involves adopting a ketogenic low-CHO high-fat (LCHF) diet (8). Chronic adaptation to an LCHF diet alters the muscle to better use the body’s largest fuel source (fat) during exercise, rather than the limited glycogen stores, thereby achieving a sustained exposure to high plasma levels of ketone bodies (8). Although this scenario may be suitable for exercise conducted at moderate intensities (60%–70% of aerobic capacity), it may impair, rather than enhance, the performance of endurance events performed at higher intensities (7).
To date, interest in these different approaches to nutrition strategies for fuelling endurance exercise has focused on sports performance, with little consideration to the effect on the athlete’s health. However, factors such as the inflammatory response to exercise can be influenced by an athlete’s glycogen status, with concentrations of the inflammatory cytokine interleukin-6 (IL-6) highest when exercise is undertaken with low muscle glycogen stores (9). An increased IL-6 response signals the upregulation of hepatic glucose release to maintain blood glucose concentrations and sustain exercise intensity (9). However, IL-6 is also a key regulator of exercise-induced hepcidin activity (10), with peak levels of this hormone reported at 3–6 h postexercise (11). Hepcidin is the body’s primary iron-regulatory hormone, reacting in a homeostatic manner to keep iron stores within a healthy physiological range (12). Hepcidin governs the movement of iron through the only known iron export transporter, ferroportin. An increase in hepcidin levels internalizes ferroportin, consequently limiting the amount of iron that can be absorbed from the diet and recycled by macrophages (12). In response to exercise, inflammatory signals upregulate hepcidin activity, which likely results in a transient disruption to iron absorption. Over time, such a response may lower an athlete’s iron stores. Serum ferritin, a key marker of iron status, is an acute phase reactant that also increases in response to inflammation (13). Therefore, a decrease in iron status may be difficult to detect during periods of inflammation, and caution should be taken assessing iron status solely via serum ferritin assessment (14).
Given the link between increases in IL-6 and hepcidin activity, it is possible that manipulating CHO availability around exercise could influence postexercise iron metabolism. For instance, consuming a low-CHO diet for 24 h after a glycogen-depleting exercise task increases postexercise IL-6 and hepcidin levels more than an HCHO diet (15); however, the longer-term physiological implications of such a strategy are unknown. Therefore, periodically or chronically restricting CHO availability over several weeks, particularly during blocks of intensified training stress, may have undesirable implications for an athlete’s iron status. This is an important consideration because adequate iron stores are required for optimal adaptation to training, and low iron stores may contribute to poor health outcomes and impair athletic performance (16). Therefore, the aim of this study was to examine the inflammatory and hepcidin response in elite athletes, following three different approaches to CHO availability during a 3-wk block of intensified training.
Internationally competitive race walking athletes participated in this study (Table 1). All athletes met the International Association of Athletics Federations walk standard for a World Championship or Olympics, in either the 20- or the 50-km event. This investigation was the culmination of three separate training camps that occurred in November 2015 (n = 11 athletes), January 2016 (n = 19), and January 2017 (n = 28). Of note, 11 athletes participated in two of the three camps, and three athletes completed all three. During this study, four athletes were unable to complete the required training due to injury or illness, and another four athletes had unusually high serum ferritin levels (>300 μg·L−1) and were excluded from the analysis. Therefore, a total of 50 athlete data sets, representing 37 athletes (31 males and 6 females), from three separate but identically conducted training camps were available for analysis. The studies providing these data sets were approved by the Ethics Committee of the Australian Institute of Sport (approval nos. 20150802 and 20161201). Written informed consent was obtained from all athletes before study commencement.
The study protocols involved in these training camps have been described previously (7), and outcomes from three separate training camps have been combined to facilitate more comprehensive analysis. During this investigation, male and female athletes completed 3 wk of intensified training and testing while adhering to one of three dietary interventions: (i) an HCHO diet (n = 16), (ii) a periodized CHO (PCHO) availability (n = 17), or (iii) an LCHF diet (n = 17). Athletes were allocated into their dietary group by matching key characteristics (e.g., sex, age, training status, and personal best times) and accounting for dietary preference/nonacceptance of a diet. All camps were conducted at the Australian Institute of Sport with athletes living on site, undertaking all meals, and performing all training sessions under rigorous supervision. This process ensured a high level of dietary compliance throughout the study. As part of each training camp, athletes completed a baseline (Baseline) and postintervention (Adapt) testing session to evaluate the effect of each diet on the iron-regulatory response to exercise (see Fig. 1).
After the baseline testing session, athletes commenced their allocated dietary intervention and prescribed training programs for 3 wk. All diets were designed by accredited sports dietitians and prepared by professional chefs, and matched for total energy intake and an energy availability of ~40 kcal·kg fat-free mass−1·d−1. The HCHO intervention consisted of a daily intake of 8.0 g·kg−1 (females) and 8.5 g·kg−1 (males) body mass of CHO, with all training sessions performed with HCHO availability (17). The PCHO intervention consisted of the same daily CHO intake as HCHO diet, with differences attributed to the timing of CHO intake. Here, CHO was strategically periodized around key training sessions, achieved by a combination of overnight fasting and delayed postsession refueling (4,6). Finally, the LCHF intervention emulated a ketogenic diet, comprising 80% fat and restricted CHO intake to <50 g·d−1 (8,18). Full details of each dietary intervention are presented in Table 2. The methodology used to achieve strict dietary control has been detailed previously (19).
While adhering to their allocated dietary interventions, all athletes completed the same 3-wk block of periodized training that included race walking, resistance training, and cross-training (running, swimming, or cycling). Individual training load was prescribed throughout the study to accommodate training history and event preparation. Six key race walking training sessions each week were compulsory and monitored by the research team. All remaining sessions were self-recorded by athletes in a computerized daily training log.
During this investigation, athletes completed a standardized exercise session, involving a hybrid laboratory and field race walking protocol at Baseline and Adapt. For these sessions, athletes arrived to the laboratory at a standardized time, in an overnight fasted and rested state. While the subject was resting quietly in a supine position, an indwelling cannula was inserted into an antecubital vein and a venous blood sample collected (fasted). Cannulas were flushed with a 3-mL saline solution every ~30 min throughout the trial to keep the vein patent. Athletes then received a standardized breakfast providing 2 g·kg−1 body mass CHO. The exception here occurred during the Adapt test of the LCHF group, who consumed a high-fat isocaloric meal in accordance with their dietary guidelines. Athletes then provided a preexercise venous blood sample, which occurred either 105 min (camp 3) or 120 min (camps 1 and 2) postbreakfast.
At 2 h postmeal, athletes commenced a combined laboratory and field race walking protocol, which involved an evenly paced 19 and 25 km race walking session for female and male athletes, respectively. During this effort, lasting approximately 2 h, kilometers 0–1, 12–13, and 24–25 (camps 1 and 2) or kilometers 0–1, 6–7, 12–13, 18–19, and 24–25 (camp 3) were completed on a motorized treadmill. Athletes walked at their target speed (10–11 km·h−1 for females, 12–13 km·h−1 for males), as established previously during a graded exercise test (7). This speed corresponded approximately to the individual’s 50-km race walk pace and an exercise intensity of ~75% V˙O2max. The remaining distance was completed outdoors on a flat 5-km circuit with athletes unimpeded by vehicle or pedestrian traffic. Immediately postexercise, a third venous blood sample was drawn. Given the long protocol duration, a standardized recovery drink, in accordance with the athlete’s dietary allocation (0 or 1.5 g·kg−1 body mass CHO), was provided at 30 min postexercise to avoid hunger. Athletes abstained from any further food intake until a final blood sample was collected 3 h postexercise.
For trials completed with HCHO availability, athletes were provided with a CHO solution before and at regular intervals throughout the exercise protocol. During exercise, this regimen resulted in a total CHO intake of ~60 g·h−1 (camps 1 and 2) or 70 g·h−1 (camp 3). The exception here occurred during the Adapt test, when the LCHF group had their CHO drinks substituted with a noncaloric electrolyte drink and consumed high-fat snacks to match the total energy consumed during the CHO-fuelled tests. Unrestricted water was provided to all athletes on course, with intakes recorded during the first trial and replicated during the Adapt trial.
For each participant, four blood samples per testing session were collected into 4-mL serum separator tubes (BD Vacutainer, Australia). Subsequently, samples were left to clot for 30 min before centrifugation at 2200g for 10 min. Serum was divided into 1-mL cyrotubes and stored at −80°C until batch analysis could be conducted. When athletes were fasted, an additional 2-mL K3EDTA tube was collected, and whole blood was immediately analyzed for hemoglobin and hematocrit by fluorescent flow cytometry on an XN-L 550 analyzer (Sysmex Corporation, Kobe, Japan). Serum iron and serum ferritin analysis were made on the fasted serum sample via a COBAS Integra 400 automated biochemistry analyzer (Roche Diagnostics, Switzerland). Concentrations of IL-6 were analyzed in duplicate on serum samples collected immediately pre- and postexercise using a commercially available ELISA (Quantikine HS; R&D Systems, Minneapolis, MN) on a BMG Labtech FLUOstar OPTIMA plate reader. The coefficient of variation for IL-6 determination was 5.9%.
Hepcidin-25 measurements were performed on serum obtained when athletes were fasted and at 3 h postexercise (www.hepcidinanalysis.com, Nijmegen, The Netherlands) using a combination of weak cation exchange chromatography and time-of-flight mass spectrometry (WCX-TOF MS) (20,21). An internal standard (synthetic hepcidin-24; custom-made Peptide International Inc.) was used for quantification (20,21). Peptide spectra were generated on a Microflex LT matrix-enhanced laser desorption/ionization TOF MS platform (Bruker Daltonics). Serum hepcidin-25 concentrations were expressed as nanomolars (nM). The lower limit of detection of this method is 0.5 nM. When values were below this limit, the lower limit of detection divided by the square root of 2 was used (22). The median reference level of serum hepcidin-25 (Dutch population) is 4.5 nM for men, 2.0 nM for premenopausal women, and 4.9 nM for postmenopausal women (www.hepcidinanalysis.com). The reference levels for the WCX-TOF MS method are derived from those obtained by an validated ELISA method (23), based on the regression line between the ELISA and the WCX-TOF MS results obtained from patients without hepcidin isoforms (20).
Dietary iron analysis
To estimate dietary iron intake, week 1 of each dietary intervention (which was constructed around a 7-d menu), for a 64-kg male, was analyzed using dietary analysis software (Food Works 8 Professional program; Xyris Software Australia Pty Ltd., Australia). Foods were categorized into heme (red meat, poultry, and fish) and nonheme iron sources (breads/cereals/grains, eggs, vegetables, fruits, nuts/seeds, and dairy) to determine the contribution of different foods to overall iron intake. A comprehensive breakdown of energy and macronutrients consumed as a part of each diet is presented in Table 2 and conformed closely to the study goals (19).
As no substantial differences were evident between HCHO and PCHO for any hematological variable and the same total CHO content was consumed daily, athletes adhering to these two diets were pooled into one group (CHO) for analysis. Differences in dietary iron intake between groups were analyzed using t-tests. Blood variables were analyzed with a general linear mixed model using the R package lme4 (24) to accommodate the unbalanced design and the repeated measurements (25). A random intercept for both athlete and camp was included to adjust for baseline levels and interindividual homogeneity, as well as different conditions between camps. All models were estimated using restricted maximum likelihood. Visual inspections of residual plots did not reveal any obvious deviations from homoscedasticity or normality. P values were obtained using type II Wald F tests with Kenward–Roger degrees of freedom as implemented in the R package car (26). Results are reported as mean estimates with a 95% confidence interval (CI). Initial models included all possible interactions, but nonsignificant interactions were dropped from the model for ease of interpretation. In the case of hepcidin-25, serum ferritin was included as a covariate in the model to account for the known influence of serum ferritin on the 3-h postexercise hepcidin response (27). In addition, effect sizes were calculated based on the classic Cohen’s d while accounting for study design by using the square root of the sum of all variance components in the denominator (28). The magnitude of change is presented as an x-fold change. To construct a 95% CI around the fold change, a bootstrapped CI based on 10,000 replications was calculated using the R package boot (29).
All athletes adhered to their allocated diets, and the desired differences in dietary fat and CHO consumption were achieved (7,19). Dietary iron intakes are summarized in Table 3. Substantial differences in iron intake between diets were evident (t = −1.92, P = 0.05), with the CHO-rich diets providing a greater daily iron intake (17.8 ± 4.5 mg·d−1) as compared with LCHF (13.7 ± 2.1 mg·d−1). Heme iron sources, including red meat, poultry, and fish, contributed a similar absolute proportion of iron to all diets (CHO 1.7 ± 0.6 mg·d−1, LCHF 1.8 ± 1.2 mg·d−1; t = 0.80, P = 0.90); however, nonheme iron provision differed substantially between diets (CHO 16.1 ± 4.4 mg·d−1, LCHF 11.9 ± 1.6 mg·d−1; t = −2.26, P = 0.03). The CHO groups consumed a large proportion of iron from foods such as breads, cereals, and grains (49%) compared with the LCHF group (7%), whose major iron source was from nuts and seeds (LCHF 26%, CHO 1%).
Substantial differences in iron stores were evident after 3 wk of training and dietary intervention (see Table 4). The decrease in resting serum ferritin from Baseline to Adapt was significantly different between dietary treatments (F 1,59 = 5.63, P = 0.021), with a small and moderate 23% and 37% decrease evident after 3 wk of dietary manipulation in the LCHF and CHO groups, respectively. Reductions to resting serum iron were also present in the Adapt trial in both groups (F 1,60 = 14.78, P < 0.001); however, the magnitude was similar between dietary interventions (F 1,60 = 0.03, P = 0.854), with small decreases evident in both the CHO (16%) and the LCHF (20%) groups. The increase in hemoglobin (F 1,60 = 16.1, P < 0.001) and hematocrit (F 1,59 = 13.1, P < 0.001) was greater in LCHF during the Adapt trial.
A substantial increase in IL-6 occurred across the ~2-h exercise bout during both Baseline and Adapt trials (F 1,150 = 343.14, P < 0.001), with an attenuated postexercise IL-6 response observed after 3 wk of training and dietary intervention in both groups compared with Baseline (F 1,150 = 4.36, P = 0.038) (see Fig. 2A). Furthermore, significant differences were evident between dietary interventions (F 1,75 = 4.75, P = 0.033), with a greater postexercise IL-6 response in LCHF during the Adapt trial (13.6-fold increase; 95% CI: 7.1–21.4) when compared with CHO (7.6-fold increase; 5.5–10.2).
Hepcidin-25 consistently increased from pre- to 3 h postexercise during both Baseline and Adapt trials (F 1,157 = 178.18, P < 0.001) (see Fig. 2B), with the increase greater at Baseline than after 3 wk of training and dietary intervention in both groups (F 1,157 = 11.34, P < 0.001). Although no significant differences between dietary interventions were evident (F 1,157 = 2.55, P = 0.112), CI values indicate 3 h postexercise hepcidin-25 concentrations were lower in the Adapt trial (4.8-fold increase; 2.4–8.5) compared with Baseline (7.1-fold increase; 4.2–11.5) in CHO (β = 4.3, −6.6 to 2.0). By contrast, only trivial differences in the 3-h postexercise hepcidin response were evident between Baseline (4.3-fold increase; 2.0–8.3) and Adapt trials (6.3-fold increase; 3.5–10.4) for LCHF. Finally, serum ferritin was a significant variable in the hepcidin model (F 1,54 = 57.46, P < 0.001), demonstrating that higher preexercise values were consistently associated with a larger hepcidin response 3 h postexercise.
This study is the first to examine issues of iron metabolism in athletes adhering to an LCHF diet. The iron content of a ketogenic LCHF diet was lower than that of CHO-rich menus, resulting from the removal of grains and cereals (including fortified manufactured foods) that typically contribute to a substantial source of nonheme iron to Western diets. Furthermore, 3 wk of adaptation to a ketogenic LCHF diet by elite race walkers resulted in a greater postexercise IL-6 and hepcidin response compared with athletes consuming a CHO-rich diet. However, despite favorable changes to iron-regulatory markers and an increased dietary iron intake, the greatest decrement to serum ferritin occurred in athletes consuming a CHO-rich diet.
In the current study, elite race walkers had a substantially greater IL-6 response to a standardized 2-h bout of exercise after 3 wk of adherence to an LCHF diet than a similar group of athletes who consumed a CHO-rich diet. It has been well documented that low muscle glycogen status is associated with increased IL-6 production from contracting skeletal muscle (9,30). In these situations, IL-6 upregulates hepatic glucose production in a homeostatic-like manner to maintain blood glucose concentrations throughout prolonged exercise (9). Although muscle glycogen stores were not directly measured in the current study, we assume that after 3 wk of strict CHO restriction, glycogen stores were likely at least partially depleted. Therefore, we suggest that the likely greater decrement to muscle glycogen stores resulting from adherence to an LCHF diet was the signal for an increased postexercise IL-6 response, in an attempt to sustain blood glucose concentrations, thus providing a fuel source to sustain exercise intensity.
The role of IL-6, however, extends beyond that of hepatic glucose regulation, also being a key regulator of hepcidin activity (10), particularly during the acute postexercise recovery period (16). Given the greater postexercise increase in IL-6 levels evident after adaptation to the LCHF diet, it seems logical that 3 wk of strict CHO restriction might also amplify the hepcidin-25 response to exercise. However, the influence of dietary manipulation on hepcidin activity was less conclusive, with a modest attenuation of hepcidin-25 levels after 3 h of recovery from a standardized exercise session in the group who had consumed a CHO-rich diet, while no clear change was evident in the LCHF group between Baseline and Adapt. Alterations to hepcidin activity are physiologically important because increases in this hormone leads to the internalization of ferroportin, inhibiting iron absorption from the gut and recycling from macrophages (12). The attenuated IL-6 response from consumption of a CHO-rich diet may have positively influenced hepcidin activity, resulting in favorable alterations in iron regulation during the postexercise period.
Factors other than inflammation are also known to influence hepcidin concentrations (31), with an athlete’s resting serum ferritin status a major determinant of the 3-h postexercise hepcidin response (27). Athletes who are iron depleted (serum ferritin <30 μg·L−1) exhibit a suppressed postexercise hepcidin response compared with athletes with either suboptimal (serum ferritin 30–50 μg·L−1) or healthy (serum ferritin >50 μg·L−1) iron stores (27). Such a response is interpreted to be a homeostatic outcome to encourage iron absorption and transport when stores are low overriding the inflammatory stimulus for an increase in hepcidin postexercise, thereby encouraging the absorption of iron from the gut. In the current study, the LCHF group had substantially greater resting serum ferritin levels during the Adapt trial than the CHO group, which in part may explain the greater hepcidin response evident in this group. Furthermore, this pattern of response is supported by data showing that resting serum ferritin was a significant variable in our hepcidin-25 modeling approach, with higher serum ferritin values associated with a greater hepcidin-25 response. However, it should be noted that athletes in a previous study (27) with a range of serum ferritin values similar to the present cohort (30–100 μg·L−1) produced a similar postexercise hepcidin response. Therefore, it is likely that the differences in hepcidin expression evident here occurred as a function of both an altered postexercise IL-6 response induced by dietary manipulation and via disparities in serum ferritin stores between groups after 3 wk of dietary intervention.
Another consideration is the type and total iron content present in the dietary treatments investigated. Absolute heme iron intake was similar between all diets, given the deliberate attempt to match protein intake across dietary conditions. It is well known that the heme form of dietary iron shows superior bioavailability, with absorption rates of approximately 5%–35% from a single meal compared with 2%–20% from nonheme sources (32). Differences in total iron intake between groups came from a greater proportion of nonheme iron sources in the CHO group. These foods included breakfast cereals fortified with iron, breads, and whole grains, all of which are CHO-rich foods eliminated from the LCHF diet. Although nuts and seeds contributed nonheme iron to the LCHF diet, quantities were not substantial enough to match intakes from the CHO-rich diets. Finally, all diets provided iron intakes that were well above the recommended daily intake (RDI) of 8 mg·d−1 for males (33). However, given the large decrements in iron stores across the 3-wk training period in all dietary treatments, the adequacy of the iron RDI for elite athletes during periods of intensified training is an area for further exploration by clinicians and dietitians.
Adequate iron stores are crucial in allowing athletes to adapt appropriately to training stimuli, which ultimately, may influence athletic performance (34). The large reduction to serum ferritin concentrations is not an uncommon finding after prolonged periods of strenuous (35) or specialized (e.g., altitude exposure) training (36). This effect may be attributed to the incorporation of iron into new tissues and cells induced by adaptation to training, as well as exercise-associated avenues of iron loss, including hemolysis, hematuria, gastrointestinal bleeding, and the iron content of sweat (16). The decrease in serum ferritin across the intervention period was substantially greater in the CHO group (37%) than the LCHF group (23%). This outcome is difficult to explain, as with the greater iron content of the CHO-rich diets and the more favorable inflammatory and hepcidin responses to exercise, we expected athletes would have maintained better iron status over the training camp in comparison to the LCHF group.
There are several possible explanations for the divergent findings in iron status. First, we postulate that a reduction in serum ferritin represents a positive change in functional iron status (i.e., a movement of stores toward new tissue synthesis or iron-related processes) rather than a simple drain of iron stores. The CHO group may have experienced greater adaptation to training and, hence, required a greater draw on their available iron stores to support adaptive processes, including increased erythropoiesis, DNA synthesis, and iron-dependent oxidative enzyme production (37). Although this is a self-limiting scenario (if there are insufficient iron stores to contribute to the increased stimulus for iron-requiring activities), there are other situations in which a successful response to an increase in training stress involves the net use, rather than preservation of iron stores. For example, a positive outcome of altitude training (increase in hemoglobin mass) is associated with a reduction in ferritin concentrations (38). Thus, the greater reduction to serum ferritin in athletes adhering to CHO-rich diets in the current study may represent an adaptive response to the training performed. Indeed, we noted that the performance trials associated with this study showed a substantially greater improvement in 10-km race performance with CHO-supported training (HCHO +6.6%, PCHO +5.4%) than the LCHF group (−1.6%) (7). Despite this suggestion, an increase to hemoglobin and hematocrit was evident in LCHF during Adapt. Such an outcome does not appear to support the prospect of greater adaptation in CHO; however, the biological variation of these markers should be considered. Within- and between-subject coefficient of variation for both of these markers is estimated to be ~2.8% and ~6.5%, respectively (39), which is attributed to the measurement being highly dependent on plasma volume changes (40), and therefore not appropriate for determining training adaptation. As such, the small changes to hemoglobin and hematocrit seen here are unlikely to be clinically meaningful and, for both markers, fall within the biological variation of the tests. Therefore, without directly quantifying changes in adaptation via an assessment of hemoglobin mass (as opposed to concentration), these conclusions remain speculative, and further research is required.
Second, it is known that ferritin is an acute phase protein, elevated in response to inflammation as part of a physiological cascade to restore homeostasis (13). As such, during periods of inflammation serum, ferritin may not accurately represent iron status (14). Given a schedule involving twice daily sessions and prolonged training sessions (30–40 km) at least weekly, it is possible that the resting serum ferritin concentrations in the LCHF group were artificially inflated during the Adapt trial as a result of low-level chronic inflammation. Specific testing of this theory is required to support the disassociation of serum ferritin concentrations from iron status in this scenario, and future studies should incorporate a more comprehensive panel of inflammatory markers, including C-reactive protein, IL-10, IL-1ra, and tumor necrosis factor-α.
In summary, alterations to the iron regulatory response to exercise were evident after 3 wk of adherence to an LCHF diet. Although elite athletes who chronically trained and acutely exercised with HCHO availability experienced an attenuated postexercise IL-6 response, and an attenuation (relative to LCHF) of the 3-h postexercise hepcidin expression, those who were adapted to an LCHF diet and exercised with low-CHO availability did not present with the same outcomes. Furthermore, the LCHF diet was associated with a lower total intake of dietary iron given the removal of CHO-rich foods that typically provide a substantial contribution of nonheme iron in the Western diet. Lower serum ferritin after 3 wk of training with HCHO intake might reflect a larger, more adaptive hematological response to training; however, further investigation is required before a full understanding of the effect of a ketogenic diet on iron status and iron metabolism can be achieved. Athletes adhering to an LCHF diet should routinely monitor their iron status in combination with markers of inflammation, to determine changes to iron availability. In athletes with an increased risk of iron deficiency, including those with suboptimal ferritin stores, endurance competitors, females, and vegetarians, iron supplementation may be appropriate to offset the low dietary iron and maintain adequate iron stores.
The authors thank all the athletes involved in this study for their commitment and dedication across the training camp. They also thank the larger Project Supernova team involved in the implementation of this study. This study was funded by a program grant from the Australian Catholic University Research Fund and a grant from the Australian Institute of Sport’s High Performance Sport Research Fund. The authors declare no conflict of interest. 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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