Eva Maria Støa

Maximal strength training improves running economy in distance runners.

PURPOSE The present study investigated the effect of maximal strength training on running economy (RE) at 70% of maximal oxygen consumption (V[spacing dot above]O2max) and time to exhaustion at maximal aerobic speed (MAS). Responses in one repetition maximum (1RM) and rate of force development (RFD) in half-squats, maximal oxygen consumption, RE, and time to exhaustion at MAS were examined. METHODS Seventeen well-trained (nine male and eight female) runners were randomly assigned into either an intervention or a control group. The intervention group (four males and four females) performed half-squats, four sets of four repetitions maximum, three times per week for 8 wk, as a supplement to their normal endurance training. The control group continued their normal endurance training during the same period. RESULTS The intervention manifested significant improvements in 1RM (33.2%), RFD (26.0%), RE (5.0%), and time to exhaustion at MAS (21.3%). No changes were found in V[spacing dot above]O2max or body weight. The control group exhibited no changes from pre to post values in any of the parameters. CONCLUSION Maximal strength training for 8 wk improved RE and increased time to exhaustion at MAS among well-trained, long-distance runners, without change in maximal oxygen uptake or body weight.

Physiological determinants of the cycling time trial.

Abstract Støren, Ø, Ulevåg, K, Larsen, MH, Støa, EM, and Helgerud, J. Physiological determinants of the cycling time trial. J Strength Cond Res 27(9): 2366–2373, 2013—The purpose of this study was to examine the physiological determinants of endurance cycling time trial (TT) performance in a heterogeneous group of competitive male road cyclists. About 15 male cyclists who had all competed in cycling the preceding season were tested for the anthropometric variables height, body weight, leg length, ankle circumference, and body fat percentage. They were also tested for maximal oxygen consumption (V[Combining Dot Above]O2max), lactate threshold (LT), metabolic cost of cycling (CC), peak power output and average power output during a 30-second Wingate test, 1 repetition maximum and peak power in half squats, and a TT test on an ergometer. Heart rate and cadence (rounds per minute, RPM) were continuously measured during all cycle tests. Pearson Bivariate correlation tests and single linear regression tests were performed to obtain correlation coefficients (r), effect size (F), standard error of estimate (SEE), and 95% confidence interval. The single variable that correlated best with TT performance was power output at LT (r = 0.86, p < 0.01). Standard error of estimate was 7.5%. Lactate threshold expressed in %V[Combining Dot Above]O2max did not correlate significantly with TT performance. An equation representing both aerobic and anaerobic endurance capacity TT(w) = 0.95 ([V[Combining Dot Above]O2max/CC] TT%V[Combining Dot Above]O2max) + 0.05 (Wingate average) correlated strongly with TT laboratory performance (r = 0.93, p < 0.01, SEE = 5.7%). None of the strength, power, or anthropometric variables correlated significantly with TT laboratory performance.

Percent Utilization of Oo2max at 5-km Competition Velocity Does Not Determine Time Performance at 5 km Among Elite Distance Runners

Støa, EM, Støren, Ø, Enoksen, E, and Ingjer, F. Percent utilization of &OV0312;o2max at 5-km competition velocity does not determine time performance at 5 km among elite distance runners. J Strength Cond Res 24(5): 1340-1345, 2010-The present study investigated to what extent maximum oxygen uptake (&OV0312;o2max) and fractional utilization (%&OV0312;o2max) in 5-km competition speed correlate with 5-km performance times among elite long distance runners. Eight elite long distance runners with 5-km performance times of 15.10 minutes ( ± 32 seconds) were tested for &OV0312;o2max during an incremental protocol and for %&OV0312;o2max during an 8-minute treadmill test at the velocity representing their 5-km seasonal best performance time. There was no correlation between fractional utilization and 5-km performance. The study showed no significant difference between &OV0312;o2max obtained during an incremental &OV0312;o2max test and %&OV0312;o2max when running for 8 minutes at the runners individual 5-km competition speed. The 5-km time was related to the runners &OV0312;o2max even in a homogenous high-level performance group. In conclusion, the present study found no relationship between fractional utilization and 5-km performance time. Training aiming to increase %&OV0312;o2max may thus be of little or no importance in performance enhancement for competitions lasting up to approximately 20 minutes.

The effect of age on the v˙o2max response to high-intensity interval training

Purpose High-intensity interval training (HIIT) is documented to yield effective improvements in the cardiovascular system and be an excellent strategy for healthy aging. However, it is not determined how age may affect the training response of key components of aerobic endurance. Methods We recruited 72 males (mean ± SD, weight = 84.9 ± 12.9 kg, height = 180.4 ± 5.8 cm) and 22 females (weight = 76.0 ± 17.2 kg, height = 171.2 ± 6.7 cm) from 20 to 70+ yr with a training status typical for their age group and divided them into six decade cohorts. The participants followed supervised training with a targeted intensity of 90%–95% of maximal HR (HRmax) three times a week for 8 wk. Results After HIIT, all age groups increased (P < 0.001–P = 0.004) maximal oxygen consumption (V˙O2max) with 0.39 ± 0.20 (20–29 yr), 0.28 ± 0.21 (30–39 yr), 0.36 ± 0.08 (40–49 yr), 0.34 ± 0.27 (50–59 yr), 0.33 ± 0.23 (60–69 yr), and 0.34 ± 0.14 (70+ yr) L·min−1, respectively. These 9%–13% improvements were not significantly different between the age groups. In contrast to age, the percentage improvements after HIIT were inversely associated with baseline training status (r = 0.66, P < 0.001). HRmax was not altered within the respective age cohorts, but the two oldest cohorts exhibited a tendency (P = 0.07) to increase HRmax in contrast to a training-induced decrease in the younger cohorts. Conclusion In healthy individuals with an aerobic capacity typical for what is observed in the population, the training response is likely not affected by age in a short-term training intervention but may rather be affected by the initial training status. These findings imply that individuals across age all have a great potential for cardiovascular improvements, and that HIIT may be used as an excellent strategy for healthy aging.

Day to day variability in fat oxidation and the effect after only 1 day of change in diet composition

Indirect calorimetry is a common and noninvasive method to estimate rate of fat oxidation (FatOx) during exercise, and test-retest reliability should be considered when interpreting results. Diet also has an impact on FatOx. The aim of the present study was to investigate day to day variations in FatOx during moderate exercise given the same diet and 2 different isoenergetic diets. Nine healthy, moderately-trained females participated in the study. They performed 1 maximal oxygen uptake test and 4 FatOx tests. Habitual diets were recorded and repeated to assess day to day variability in FatOx. FatOx was also measured after 1 day of fat-rich (26.8% carbohydrates (CHO), 23.2% protein, 47.1% fat) and 1 day of CHO-rich diet (62.6% CHO, 20.1% protein, 12.4% fat). The reliability test revealed no differences in FatOx, respiratory exchange ratio (RER), oxygen uptake, carbon dioxide production, heart rate, blood lactate concentration, or blood glucose between the 2 habitual diet days. FatOx decreased after the CHO-rich diet compared with the habitual day 2 (from 0.42 ± 0.15 to 0.29 ± 0.13 g·min(-1), p < 0.05). No difference was found in FatOx between fat-rich diet and the 2 habitual diet days. FatOx was 31% lower (from 0.42 ± 0.14 to 0.29 ± 0.13 g·min(-1), p < 0.01) after the CHO-rich diet compared with the fat-rich diet. Using RER data to measure FatOx is a reliable method as long as the diet is strictly controlled. However, even a 1-day change in macronutrient composition will likely affect the FatOx results.

Response to comments on “High-intensity aerobic interval training improves aerobic fitness and HbA1c among persons diagnosed with type 2 diabetes”

Støren Ø, Helgerud J, Sæbø M, Støa EM, Bratland-Sanda S, Unhjem RJ, Hoff J, Wang E (2017) The effect of age on the V̇O2max response to high-intensity interval training. Med Sci Sports Exerc 49(1):78–85 Tomoyuki Kawada commented on our article “Effect of high-intensity aerobic exercise on aerobic fitness and HbA1c in patients with type 2 diabetes”. First of all, we have not stratified the effect of training intensity by age. The reasons for this are (1) the low number of participants in each age group, and (2) the adaptations to at least high-intensity aerobic interval training (HAIT) have recently been shown to be independent of age (Støren et al. 2017). Second, to select the level of intensity training in patients with T2D from the progress of T2D and lifestyle information, as suggested by Kawada, was not considered appropriate to answer the research problem in our study. On the contrary, we chose to match the two intensity groups by T2D progress, use of medications, etc. This was considered necessary to evaluate the adaptations to the two training regimes as correctly as possible. MIT may very well have an ability of improving aerobic fitness and

Response to comments on “Effect of high-intensity aerobic exercise on aerobic fitness and HbA1c in patients with type 2 diabetes”

50% between the two groups, which is more than we aimed for. This means that the MIT group exercised 173 min per week more than they used to, while the HAIT group only exercised 88 min per week more than they used to. Most important, there was a 93% difference in high aerobic intensity volume between the groups. This clearly expresses the difference between the two training groups. We thus do not agree that the interventions should need to differ more clearly. On the contrary, we aimed to perform two intervention training regimes matched for total work to differ in intensity but not differ in kilocalories spent. We agree that it would also be interesting to compare an even lower amount of HAIT with an even higher amount of MIT, but that was not the aim of the present study.