Due to the unknown effect of high-intensity exercise in sedentary older men, and to account for the effects of conditioning exercise, the study required 3 distinct measurement phases (A, B, and C) separated by 2 training blocks (1 and 2). Therefore, following randomization, INT undertook 6 weeks of supervised “preconditioning” exercise (training block 1), before undertaking a program of LfHIIT (training block 2), whereas CON remained inactive for the duration of the study. Participants were required to complete a minimum of 80% of training sessions to be included in the final data analysis. Figure 2 outlines a schematic of study design.
Calculation of sample power was based on previously published data regarding exercise-induced changes in Wingate PPO in younger cohorts after sprint interval training. This suggested an estimated effect size of 1.08, using an α of 0.05 and β of 0.8, and taking the asymmetric allocation into account resulted in a requirement of 23 participants in INT and 11 participants in CON. A priori power calculations were conducted using GPower V3.1, and 2:1 recruitment ratio was subsequently utilized to account for potential study accession within the intervention group.
2.2 Laboratory measures
On assessment Phases A, B, and C, participants arrived in the exercise physiology laboratory between the hours of 07.00 and 09.00 AM, after an overnight fast and having abstained from strenuous physical activity for a minimum of 5 days. Participants were reminded in the information sheet to maintain standardized conditions before each assessment point, which included arriving in a hydrated state (500 mL water 30–60 min before assessment), having abstained from caffeine and alcohol consumption for 36 hours.
2.3 Body composition
Since body composition is a known covariate of increasing PPO, it is important to assess such changes. Therefore, body composition was determined using standard methods and described elsewhere. Body fat assessments were performed with participants hydrated and wearing minimal clothing. Participants stood on a multifrequency bioelectrical impedance device (Tanita MC180MA, Tanita Corp, Tokyo, Japan), ensuring bare feet were in contact with electrodes on the foot plate. This assessed body mass and relative proportions of fat and lean tissue, which were assessed over a 20-minute period, to account for technical variation. The coefficient of variation (CV) for the measurement of body composition total body mass (TBM), fat-free mass (FFM), and fat mass (FM) in our laboratory is <2%.
2.4 Determination of static balance
Static balance was assessed barefoot, using a Footscan portable foot pressure plate and stability software (RS Scan Labs Ltd, Ipswich, England, UK), which has previously been shown to be a valid and reliable tool to measure stability. The footplate measured the total distance and area covered by an individual's center of pressure over a 20-second interval. Static measures of balance were included, standing on both feet (S B) and standing balanced on the dominant foot (S D) (Table 2).
2.5 Determination of peak power output
Both INT and CON participants were familiarized with the Herbert 6-second peak power test before commencing the study. This test was used to establish PPO at phases A, B, and C using a Wattbike Pro (Wattbike, Nottingham, UK) cycle ergometer employing a protocol detailed elsewhere. Briefly, each assessment of PPO was preceded with a 5-miuten warm-up on a Wattbike Pro set at a fixed resistance of (level 8, described as “heavy gearing”) and incorporated 2 brief cadence acceleration phases of approximately 3 seconds commencing after 90 and 180 seconds. The test employed a seated stationary start with dominant leg initiating the first down-stroke. The air braking resistance was set to level l0, and magnetic resistance set to level 1 (equating to 1045 W at 130 rpm and approximately 90–100 W increases for every further 5 rpm increase in cadence). After each cycle test, participants underwent 5 minutes of cool-down exercise on the Wattbike cycle, set at air brake resistance level 8. CV for the determination of PPO using this method in our laboratory is <1.6%, and we have previously demonstrated it to be a valid and reliable measure of PPO. PPO generated during phase B was used to establish the intensity of individual HIIT intervals during training block 2 (further detailed below).
2.6 Conditioning exercise (training block 1)
To prepare INT for the high-intensity exercise, this group underwent training block 1, which consisted of 6 weeks of personalized and supervised preconditioning exercise designed to progressively meet the American College of Sports Medicine (ACSM) guidelines of moderate-intensity cardiorespiratory exercise training consisting of ≥150 min per week (≥30 minutes/day on ≥5 days per week). This included with the familiarization of INT with Polar FT1 heart rate monitors (Polar Team System, Polar Electro Oy, Kempele, Finland), enabling the recording of exercise time, average and peak heart rate during exercise sessions. Progression of this conditioning exercise was achieved with systematic increments in weekly average heart rate reserve (HRR); week 1 to 2: 55% HRR; week 3 to 4: 60% HRR; week 5 to 6: 65% HRR, where the final 2 weeks incorporating short bursts of higher-intensity exercise into each session. Supervised exercise training modes provided options that included walking, walk/jogging, jogging, cycling, (flat terrain) cycling, (hill terrain), and adapted to suit the participants’ physical status and personal preference. Exercise compliance and heart rate data were recorded, and feedback on progress was administered to participants at the end of each exercise training session.
2.7 LfHIIT intervention (training block 2)
Training block 2 was based on a program of LfHIIT previously employed by our research group, which consisted of 1 LfHIIT session performed once every 5 days for 6 weeks (9 sessions). These sessions consisted of 5 minutes of warm up followed by 6 × 30-second sprints at 50% peak power on a cycle ergometer (Wattbike Pro, Nottingham, England, UK), each interspersed with 3-minute intervals of active recovery, which we have previously demonstrated to be feasible high-intensity protocol to achieve >90% HRR in a similarly aged cohort. The first 3 (3/9) LfHIIT sessions were used to familiarize the participants to high-intensity exercise, working at 40% of each participants’ peak power established during the 6-second peak power test at phase B. Subsequent sessions (6/9) were conducted at 50% of predefined PPO. This was the only exercise performed during this training block and preceded the final measurement phase (phase C). At each measurement phase, data were obtained 5 days after the last exercise session.
2.8 Statistical analysis
Data were analyzed using SPSS version 20.0. Q-Q plots were employed to confirm normal distribution of data. Training effects were compared using a 2 × 3 mixed design analysis of variance (ANOVA), comprising 3 within-group condition (phases A, B, and C) and 2 between-group conditions (INT and CON). Where significant interaction effects were evident, data were further investigated using post hoc pair-wise comparisons to identify within-group and between-group simple effects using a Bonferroni correction. An alpha value of P ≤ 0.05 was used to indicate statistical significance. Data are presented as mean ± standard deviation (SD); differences between conditions are reported as mean difference and 95% confidence intervals (95% CIs).
3.1 Study compliance and adverse events
No participants were lost to follow-up. Among the participants who enrolled to the study, 100% completed phases A, B, and C, and there were no adverse events recorded either during the conditioning exercise (training block 1) or during the LfHIIT (training block 2).
3.2 Peak power output
For absolute peak power, there was a significant main effect of phase (P < 0.01), but not for group (P > 0.05); however, there was a significant interaction (P < 0.01). There were no differences between groups for absolute power at phase A (699.1 ± 180.1 vs 655.1 ± 130.1 W for INT and CON, respectively) or phase B (phase B = 706.5 ± 173.8 vs 661.8 ± 139 W for INT and CON, respectively). However, there were differences between groups at phase C (831.1 ± 170.6 vs 657.3 ± 133.1 W for INT and CON, respectively). INT participants did not increase absolute power between phases A and B (P > 0.05), but improved significantly between phases B and C (P < 0.01; 95% CI 90.2–159.0). PPO remained unchanged in CON at all measurement phases (P > 0.05 for all comparisons; Fig. 3I).
For rPPO (W/kg), there was a significant main effect of phase (P < 0.01), but not group (P > 0.05), and there was a significant interaction effect (P < 0.01). There were no between-group differences at phase A (7.71 ± 1.81 vs 8.1 ± 1.7 W/kg for INT and CON, respectively) or phase B (8.1 ± 1.7 vs 8.2 ± 1.8 W/kg for INT and CON, respectively), but at phase C, INT had significantly greater relative PPO than CON (9.5 ± 1.83 vs 8.0 ± 1.5 W/kg for INT and CON, respectively; P < 0.05). Within groups, INT demonstrated no increase between phases A and B (P > 0.05), but had a significant increase between phases B and C (P < 0.01; 95% CI 1.053–1.832), whereas there were no changes in relative PPO for CON (P > 0.05 for all comparisons; Fig. 3II)
The rPPO relative to FFM (rPPOFFM) was used to as a marker for changes in muscle quality. There was a main effect for phase (P < 0.01), but not for group (P
< 0.05), and there was a significant interaction effect (P < 0.01). There were no differences between groups at phases A, B, or C (P > 0.05 for all comparisons). At phase C, there was a trend for a higher rPPOFFM in INT (12.2 ± 2.1 vs 10.53 ± 2.76 W/kgFFM; P = 0.07, 95% CI −3.514 to 0.167). Within groups, INT did not change between phases A and B (P > 0.05); however, there was a significant increase in INT between phases B and C (10.67 ± 2.3 vs12.2 ± 2.1 W/kgFFM; P < 0.001, 95% CI 0.943–2.117). There were no changes in rPPOFFM in CON (P > 0.05 for all comparisons; Fig. 3III).
For TBM, there was no main effect for phase (P > 0.05), nor for group (P < 0.05), nor was there a significant interaction effect (P > 0.05). For lean body mass (LBM), there was a significant main effect for phase (P < 0.05), but not for group (P > 0.05), and a significant interaction between the 2 (P < 0.05). Between groups, there was no difference at any phase (P > 0.05 for all comparisons; phase A = 65.9 ± 6.7 kg vs 63.4 ± 6.9 kg; phase B = 66.1 ± 6.6 vs 63.7 ± 7.6 kg; phase C = 68.1 ± 7.5 vs 63.6 ± 7.3 kg for INT and CON, respectively) (Fig. 4I). Within groups, LBM did not change in INT between phases A and B (P > 0.05), but there was a significant increase between phases B and C (P < 0.05, 95% CI 0.545–3.512), whereas CON did not experience any changes in LBM between any phases (P > 0.05 for all comparisons) (Fig. 4II). Total body fat (TBF) demonstrated a significant main effect of phase (P < 0.01), but not group (P > 0.05), and a significant interaction between the phase and group (P < 0.05). Between groups, there were no significant differences at any phase (phase A = 23.9 ± 17.3 vs 19.8 ± 10.8 kg; phase B = 22.8 ± 17.6 vs 19.9 ± 11.6 kg; phase C = 20.8 ± 17.3 vs 19.3 ± 11.1 kg for INT and CON, respectively; P > 0.05 for all phases). Within groups, INT demonstrated significant decrease in TBF between phases A and B (P < 0.05, 95% CI 0.129–2.128), and between phases B and C (P < 0.05, 95% CI 0.392–3.551). CON experienced no change in TBF between any phase (P > 0.05 for all comparisons) (Fig. 4III).
3.4 Balance and flexibility
There was no main effect for phase (P > 0.05), group (P > 0.05), nor any interaction effects for any measures of static balance (Table 2).
The main finding of the present study is that 6 weeks of LfHIIT, subsequent to conditioning exercise, is a feasible and effective method to improve PPO and rPPO in otherwise healthy sedentary ageing men. A further finding was that neither standard conditioning, nor LfHIIT resulted in any improvement in measures of static balance that were assessed in this study. These findings have important implications for exercise prescription in older populations.
4.1 Standard conditioning exercise
In the present study, general conditioning (phase A) had no effect on PPO or rPPO in INT. Previously, low to moderate intensity training has been shown to improve PPO calculated from vertical jump height in similarly aged females; however, similar data in males are lacking. Indeed, the ACSM position statement relating to exercise for older individuals neglects to consider any effects of aerobic exercise training on measures of peak muscle power. Nevertheless, the present study failed to find any effect of moderate-intensity exercise on PPO in older males. This is likely attributable to the specificity of neuromuscular and metabolic adaptations of skeletal muscle in response to chronic exercise.
The most comprehensive data currently available on low volume HIIT is a recently published meta-analysis by Weston et al. However, as indicated by the authors, their results deal exclusively with younger adult participants, as there are no previously published data regarding the effects of low-volume HIIT on indices of muscular power or body composition in healthy older participants. Indeed, Weston et al identify that of those studies reporting PPO, the oldest cohort previously studied had a mean age of 32 years. Correspondingly, this study represents the oldest cohort to undertake a HIIT program, to date. Weston et al report the effect of low-volume HIIT on PPO in younger cohorts as being unclear, reporting a small average increase and wide CIs (1.8% ± 5%), meaning that in some cases, there was a negative effect of low-volume HIIT training interventions. This was calculated using the difference between control and intervention groups, with the small effect partly due to PPO improvements in control groups. Using the same calculation, the present study reports an overall effect on PPO that is an order of magnitude greater (26.5%) after LfHIIT, when comparing INT with CON, and a within-group increase of 17% for INT between phases B and C.
One potential explanation for the greater effect in the present study relates to participants’ age. Since normal ageing is associated with a progressive decline in PPO, it is likely that participants in the present study had a low PPO at baseline, and consequently had a much larger scope for improvement than studies of younger participants. Although further comparison with available literature is hindered, as this is the first RCT study using older participants, it does provide the first evidence that LfHIIT may be an age-specific training method to increase PPO.
Similarly, there are other differences with previous investigations that merit discussion. In particular, the present study used a low-frequency and low-volume HIIT model as opposed to previous investigations that have utilized a low exercise volume per session, but have maintained the traditional frequency of 3 sessions per week. This is of particular importance as other variables within the present study are comparable with previous investigations using low-volume HIIT. These include variables such as intensity, effort duration, total effort per session, work-rest ratio, and number of efforts per session. Consequently, the large improvements in PPO and rPPO in INT in the present study are even more surprising, given the use of both similarly low session volumes, and reduced training frequency (once every 5 days giving a mean frequency of 1.4 sessions/wk), which was less than half that of previous investigations. Correspondingly, the improvements in INT were in response to a total of 27 minutes of HIIT exercise across the 6-week period.
We have previously reported that when compared with their younger counterparts, older participants require longer recovery periods after a single bout of HIIT, with PPO recovery occurring within 5 days. Consequently, it appears that in older participants, allowing full recovery between bouts may facilitate muscle adaptation to HIIT and should be considered when programming training or LfHIIT protocols for older participants. It is evident from the present study that reducing exercise frequency in older cohorts is not detrimental to improvements in muscle power. It seems likely that the extended recovery between bouts allows for more complete recovery and adaptation (a process that may be slower in older individuals), and can prevent accumulated fatigue that might occur should training sessions be programmed too frequently.
The vast majority of studies investigating muscle power in ageing participants have used resistance exercise, high-speed power movements (normally adapted from traditional resistance exercises), or a combination thereof. Whereas high-velocity movements are widely considered to be more effective than high-load, low-velocity resistance exercise for improving muscle power, comparisons with the present study are difficult since the outcome measures used in individual studies are specific to their training intervention, with the consequence that the utility of comparing relative efficacy becomes questionable. For example, Sayers and Gibson report an approximate 3.5-fold improvement over control subjects in PPO generated against a resistance of 40% of participants leg press 1 repetition maximum (1RM). Given the mechanical and metabolic differences between a single expression of power during a leg press versus 30 seconds of high-intensity cycling, it is difficult to conclude the superiority of one intervention over another.
During initial conditioning, INT underwent a small reduction in body fat in the absence of any change to LBM. However, after LfHIIT, the reduction in body fat accelerated with a concomitant increase in LBM. Increased daily energy expenditure during general conditioning is the most likely explanation for the small reduction in body fat during that phase. The effectiveness of moderate-intensity exercise to reduce body fat in sedentary individuals has been previously reported and further substantiated by the present data. The mechanism behind a reduction in body fat after LfHIIT is unclear. As outlined above, the total high-intensity exercise time during that phase of the study was 27 minutes over 6 weeks (this increases to a total of 4.5 hours of exercise when recovery, warm-up, and cool-down periods were included). It would appear unlikely that reductions in body fat were mediated by increased calorie expenditure. One unexplored avenue is that HIIT participants may self-select higher levels of physical activity out-with the HIIT intervention which has been demonstrated in adolescents, but remains to be examined in adult and ageing populations. There are numerous reports of HIIT training resulting in reductions in TBM, TBF, and total visceral adipose tissue. The mechanisms underpinning reductions in body fat after HIIT are poorly understood, but have been postulated as being related to improved exertional, postexercise, and resting fat oxidation, and/or appetite suppression. The relative change in TBF in the present study (8.8% between phase B and phase C) is similar to changes reported in other HIIT studies, utilizing greater frequencies than is the case here.[24,25] The present study extends these results in 2 ways. First, by demonstrating that the effect is similarly evident in previously sedentary, but otherwise healthy ageing men. And secondly, by demonstrating that the effect persists despite low weekly exercise frequency and low total exercise volume.
In contrast to its effects on fat mass, the effect of HIIT on lean body mass has not been extensively investigated. Combined endurance and HIIT training has previously been shown to increase thigh cross-sectional area over 16 weeks in middle-aged diabetic men. More recently, Gillen et al[28,29] demonstrated increases in FFM in the leg and gynoid regions of overweight young females after 6 weeks of low-volume HIIT performed 3 times per week. In the present study, muscle hypertrophy was not directly measured, but clearly cannot be ruled out as a contributor to increased LBM. Similarly, although not measured in this study, exercise-induced changes to male sex hormones may have indirectly influenced PPO through interactions with muscle hypertrophy/function. However, the tenet for this phenomenon is not well described in the ageing male literature,[31,32] and the latest evidence introduces the potential for a significant role of insulin-like growth factor in the exercise response in ageing men. Nonetheless, increases in muscle mass in this study would have the additional benefit of increasing resting metabolic rate, which may also explain the accelerated reduction in TBF after LfHIIT. Nevertheless, whatever the basis for increased LBM, the present study builds on previous work by demonstrating that in older cohorts, increases in LBM are possible, and can occur despite low exercise frequency and volumes.
In addition to adverse changes in muscle mass and body composition, ageing is also associated with decrements in muscle quality (defined as force production per unit of muscle). Although not investigated directly in the present study, PPO relative to FFM (rPPOFFM) may be used as a surrogate, though imperfect measure of muscle quality. In the present study, LfHIIT resulted in significant increases in rPPOFFM in INT. This suggests that along with the increases in FFM, LfHIIT may also improve muscle quality. These changes, when viewed alongside with the increases in PPO, the small decreases in TBF, the low time requirements, and the high levels of adherence, suggests LfHIIT may be a potent tool for improving measures predictive of future frailty in older sedentary populations. Our use of rPPOFFM as a surrogate marker for muscle quality is not without significant limitations, though our findings suggest that this is an avenue for further study. As such, the 56–65 yrs cohort in this study are good candidates for high intensity training. Whereas undoubtedly aged, this demographic, frequently termed “the young old” typically have many years of minimally diminished functional capacity remaining and are less likely to have a mobility limiting disorders. In the absence of epidemiological evidence for HIIT to improve “lifespan,” or indeed, long-term health outcomes in previously sedentary ageing cohorts, this study provides preliminary evidence for LfHIIT to induce short-term improvements in muscle power. With careful exercise prescription, LfHIIT-induced improvements in muscle power could potentially be carried through into older age, thus positively impacting the exercisers’ “health-span.” With this in mind, replication of the present findings and longer-term follow-up studies in male and female cohorts are strongly encouraged.
Neither conditioning exercise nor LfHIIT was effective at improving indices of balance in INT. Previous investigations have reported that power training can improve balance in older participants.[1,35] The reasons for the lack of effect of either training regimen in the present study may be due to a number of factors. Most previous studies have used functional movements using weighted vests or high-velocity movements adapted from traditional resistance training exercises. In contrast, stationary cycle ergometry includes 5 points of contact with a stable ergometer, and thus requires less corrective stability than other forms of high-velocity exercise. It is possible that stationary cycle ergometry is sufficiently stable and effectively limits improvements in balance. Alternatively, others have reported no detrimental effects on balance in older participants who have maintained moderate physical activity (regular walking) after retirement. Given that the age and static balance results of the present cohort were similar to those reported by Melzer et al, it is equally possible that our participants had no significant balance impairment, and thus any training effects may be minimal. In addition, it may be that the static balance test utilized in the study was insufficiently challenging to identify improvements after the training program. Consequently, future work in similar populations may wish to employ more challenging assessments of participants balance.
4.4 Study limitations
The present study has some important limitations that should be noted. One concerns the proximity (11 days) of the conditioning exercise (training block 1) to the LfHIIT intervention (training block 2), which makes it impossible to rule out the contribution of conditioning exercise to the overall effect on INT after LfHIIT. However, given the randomized controlled design and the lack of difference between groups at phase B, the difference in PPO evident at phase C is almost certainly due to the LfHIIT intervention. As the effects of high-intensity exercise are unstudied in older cohorts, the inclusion of the conditioning exercise during phase A was deemed a prudent means of gradually introducing the previously inactive INT cohort to the rigors of high-intensity training. This decision appears justified as there was complete adherence to the LfHIIT after conditioning. Similarly, the ACSM has recently indicated that conditioning training should be employed before undertaking high-intensity interval training.
In conclusion, the novel findings of the present study are that LfHIIT is both feasible and effective as a training modality to increase lower limb muscle power in sedentary ageing men. However, when performed using stationary cycle ergometry, it does not improve balance in otherwise healthy sedentary ageing males. This study provides strong supporting evidence for the inclusion of LfHIIT when prescribing exercise to improve lower-limb power in ageing cohorts.
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Keywords:Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.
ageing; dynapenia; low-frequency high-intensity interval training; muscle quality; sarcopenia