We investigated one week of dietary microperiodization in elite female (n = 23) and male (n = 15) runners and race-walkers by examining the frequency of training sessions and recovery periods conducted with recommended carbohydrate (CHO) and protein availability. Food and training diaries were recorded in relation to HARD (intense or >90min sessions; KEY) versus RECOVERY days (other-than KEY sessions; EASY). The targets for amount and timing of CHO and protein around KEY sessions were based on current nutrition recommendations. Relative daily energy and CHO intake was significantly (p < .05) higher in males (224 ± 26 kJ/kg/d, 7.3 ± 1.4 g/kg/d CHO) than females (204 ± 29 kJ/kg/d, 6.2 ± 1.1 g/kg/d CHO) on HARD days. However, when adjusted for training volume (km), there was no sex-based difference in CHO intake daily (HARD: 0.42 ± 0.14 vs 0.39 ± 0.15 g/kg/km). Females appeared to periodize energy and protein intake with greater intakes on HARD training days (204 ± 29 vs 187 ± 35 kJ/kg/d, p = .004; 2.0 ± 0.3 vs 1.9 ± 0.3 g/kg/d protein, p = .013), while males did not periodize intakes. Females showed a pattern of periodization of postexercise CHO for KEY vs EASY (0.9 ± 0.4 vs 0.5 ± 0.3 g/kg; p < .05) while males had higher intakes but only modest periodization (1.3 ± 0.9 vs 1.0 ± 0.4; p = .32). There was only modest evidence from female athletes of systematic microperiodization of eating patterns to meet contemporary sports nutrition guidelines. While this pattern of periodization was absent in males, in general they consumed more energy and CHO daily and around training sessions compared with females. Elite endurance athletes do not seem to systematically follow the most recent sports nutrition guidelines of periodized nutrition.
Ida A. Heikura, Louise M. Burke, Antti A. Mero, Arja Leena Tuulia Uusitalo, and Trent Stellingwerff
Ida A. Heikura, Trent Stellingwerff, Antti A. Mero, Arja Leena Tuulia Uusitalo, and Louise M. Burke
Contemporary nutrition guidelines promote a variety of periodized and time-sensitive recommendations, but current information regarding the knowledge and practice of these strategies among world-class athletes is limited. The aim of this study was to investigate this theme by implementing a questionnaire on dietary periodization practices in national/international level female (n = 27) and male (n = 21) middle- and long-distance runners/race-walkers. The questionnaire aimed to gain information on between and within-day dietary choices, as well as timing of pre- and posttraining meals and practices of training with low or high carbohydrate (CHO) availability. Data are shown as percentage (%) of all athletes, with differences in responses between subgroups (sex or event) shown as Chi-square x2 when p < .05. Nearly two-thirds of all athletes reported that they aim to eat more food on, or after, hard training days. Most athletes said they focus on adequate fueling (96%) and adequate CHO and protein (PRO) recovery (87%) around key sessions. Twenty-six percent of athletes (11% of middle vs 42% of long-distance athletes [x2 (1, n = 46) = 4.308, p = .038, phi = 0.3])) reported to undertake training in the fasted state, while 11% said they periodically restrict CHO intake, with 30% ingesting CHO during training sessions. Our findings show that elite endurance athletes appear to execute pre- and post-key session nutrition recovery recommendations. However, very few athletes deliberately undertake some contemporary dietary periodization approaches, such as training in the fasted state or periodically restricting CHO intake. This study suggests mismatches between athlete practice and current and developing sports nutrition guidelines.
Marko T. Korhonen, Harri Suominen, Jukka T. Viitasalo, Tuomas Liikavainio, Markku Alen, and Antti A. Mero
Eighteen young (23 ± 4 yr) and 25 older (70 ± 4 yr) male sprinters were examined for ground reaction force (GRF) and temporal-spatial variables. The data were collected during maximum-speed phase, and variability and symmetry indices were calculated from a total of 8 steps. There was little variation (CV < 6%) in vertical and resultant GRF and kinematic variables, while impact loading had high variability (CV: 10–21%). Overall, the pattern of variability was similar in both groups. Yet, a small but significant age-related increase in CV was evident in horizontal GRFs. There was a variable-specific asymmetry between legs but it was not related to leg dominance. No age differences existed in the symmetry indices. Results indicate that only selected force platform variables are symmetric and repeatable enough so that their use for comparison purposes is appropriate. Data also suggest that aging may increase variability in certain biomechanical measures, whereas symmetry is not affected by age.
Ida A. Heikura, Arja L.T. Uusitalo, Trent Stellingwerff, Dan Bergland, Antti A. Mero, and Louise M. Burke
We aimed to (a) report energy availability (EA), metabolic/reproductive function, bone mineral density, and injury/illness rates in national/world-class female and male distance athletes and (b) investigate the robustness of various diagnostic criteria from the Female Athlete Triad (Triad), Low Energy Availability in Females Questionnaire, and relative energy deficiency in sport (RED-S) tools to identify risks associated with low EA. Athletes were distinguished according to benchmarks of reproductive function (amenorrheic [n = 13] vs. eumenorrheic [n = 22], low [lowest quartile of reference range; n = 10] versus normal testosterone [n = 14]), and EA calculated from 7-day food and training diaries (< or >30 kcal·kg−1 fat-free mass·day−1). Sex hormones (p < .001), triiodothyronine (p < .05), and bone mineral density (females, p < .05) were significantly lower in amenorrheic (37%) and low testosterone (40%; 15.1 ± 3.0 nmol/L) athletes, and bone injuries were ∼4.5-fold more prevalent in amenorrheic (effect size = 0.85, large) and low testosterone (effect size = 0.52, moderate) groups compared with others. Categorization of females and males using Triad or RED-S tools revealed that higher risk groups had significantly lower triiodothyronine (female and male Triad and RED-S: p < .05) and higher number of all-time fractures (male Triad: p < .001; male RED-S and female Triad: p < .01) as well as nonsignificant but markedly (up to 10-fold) higher number of training days lost to bone injuries during the preceding year. Based on the cross-sectional analysis, current reproductive function (questionnaires/blood hormone concentrations) appears to provide a more objective and accurate marker of optimal energy for health than the more error-prone and time-consuming dietary and training estimation of EA. This study also offers novel findings that athlete health is associated with EA indices.
Ida A. Heikura, Louise M. Burke, Dan Bergland, Arja L.T. Uusitalo, Antti A. Mero, and Trent Stellingwerff
Purpose: The authors investigated the effects of sex, energy availability (EA), and health status on the change in hemoglobin mass (ΔHbmass) in elite endurance athletes over ∼3–4 wk of live-high–train-high altitude training in Flagstaff, AZ (2135 m; n = 27 women; n = 21 men; 27% 2016 Olympians). Methods: Precamp and postcamp Hbmass (optimized carbon monoxide rebreathing method) and iron status were measured, EA was estimated via food and training logs, and a Low Energy Availability in Females Questionnaire (LEAFQ) and a general injury/illness questionnaire were completed. Hypoxic exposure (h) was calculated with low (<500 h), moderate (500–600 h), and high (>600 h) groupings. Results: Absolute and relative percentage ΔHbmass was significantly greater in women (6.2% [4.0%], P < .001) than men (3.2% [3.3%], P = .008). %ΔHbmass showed a dose–response with hypoxic exposure (3.1% [3.8%] vs 4.9% [3.8%] vs 6.8% [3.7%], P = .013). Hbmasspre was significantly higher in eumenorrheic vs amenorrheic women (12.2 [1.0] vs 11.3 [0.5] g/kg, P = .004). Although statistically underpowered, %ΔHbmass was significantly less in sick (n = 4, −0.5% [0.4%]) vs healthy (n = 44, 5.4% [3.8%], P < .001) athletes. There were no significant correlations between self-reported iron intake, sex hormones, or EA on Hbmass outcomes. However, there was a trend for a negative correlation between LEAFQ score and %ΔHbmass (r = −.353, P = .07). Conclusions: The findings confirm the importance of baseline Hbmass and exposure to hypoxia on increases in Hbmass during altitude training, while emphasizing the importance of athlete health and indices of EA on an optimal baseline Hbmass and hematological response to hypoxia.
Johanna K. Ihalainen, Oona Kettunen, Kerry McGawley, Guro Strøm Solli, Anthony C. Hackney, Antti A. Mero, and Heikki Kyröläinen
Purpose: To determine body composition, energy availability, training load, and menstrual status in young elite endurance running athletes (ATH) over 1 year, and in a secondary analysis, to investigate how these factors differ between nonrunning controls (CON), and amenorrheic (AME) and eumenorrheic (EUM) ATH. Correlations to injury, illness, and performance were also examined. Methods: Altogether 13 ATH and 8 CON completed the Low Energy Availability in Females Questionnaire. Anthropometric, energy intake, and peak oxygen uptake assessments were made at 4 time points throughout the year: at baseline post competition season, post general preparation, post specific preparation, and post competition season the following year. Logs of physical activity, menstrual cycle, illness, and injury were kept by all participants. Performance was defined using the highest International Association of Athletics Federations points prior to and after the study. Results: ATH had significantly lower body mass (P < .008), fat percentage (P < .001), and body mass index (P < .027) compared with CON, while energy availability did not differ between ATH and CON. The Low Energy Availability in Females Questionnaire score was higher in ATH than in CON (P < .028), and 8 ATH (vs zero CON) were AME. The AME had significantly more injury days (P < .041) and ran less (P < .046) than EUM, while total annual running distance was positively related to changes in performance in ATH (r < .62, P < .043, n < 11). Conclusions: More than half of this group of runners was AME, and they were injured more and ran less than their EUM counterparts. Furthermore, only the EUM runners increased their performance over the course of the year.