The global increase in prevalence of noncommunicable diseases for the past decades (34) can be attributed, at least in part, to the low levels of physical activity undertaken by the majority of the general population (16). In light of this, a key aim of public health organizations is to increase population physical activity levels (20). Of the health markers that can be improved by physical activity, maximal aerobic capacity (V˙O2max) is consistently shown to be the strongest prognostic marker for future cardiovascular health and premature death in cross-sectional studies (38,56). Furthermore, longitudinal studies demonstrate that improvements in V˙O2max are associated with substantial reductions in all-cause and cardiovascular mortality during follow-up (9,43).
For the past two decades, relatively high volumes of moderate-intensity aerobic exercise (total time commitment ≥150 min·wk−1) have consistently been recommended for improving health markers (20). However, uptake of and adherence to these recommendations remains low in the general population (25), with lack of time identified as one of the main perceived barriers to becoming and remaining physically active (39,41,71). Therefore, the seminal finding by Burgomaster et al. (12) that a training protocol consisting of repeated brief all-out cycle sprints (i.e., Wingate sprints) is associated with aerobic adaptations has led to substantial interest in the use of (sub)maximal high-intensity interval training (HIIT) and supramaximal sprint interval training (SIT) as time-efficient alternative/adjunct exercise strategies for improving V˙O2max (21). The most commonly studied SIT protocol consists of four to seven repeated 30-s Wingate sprints, thus resulting in less than 4 min of high-intensity exercise per session (75). For the past few years, several meta-analyses have reported the efficacy of SIT in increasing V˙O2max (24,53,65,75). These have concluded that in healthy individuals, SIT improves V˙O2max to a similar (24) or greater extent (53) than traditional aerobic training, with greater benefits for individuals with lower pretraining V˙O2max (53,75).
Although these findings provide strong support for the effectiveness of SIT in improving V˙O2max, surprisingly few efforts have been made to identify “optimal” SIT protocols, e.g., protocols which will either provide the greatest increase in V˙O2max, or a set increase with the lowest total training volume or time commitment. Weston et al. (75) reported a likely small effect of increasing the intervention duration and a possibly moderate effect of increasing the work-to-rest ratio, but no studies have meta-analyzed or directly investigated the potential effects of the number of sprint repetitions in an SIT session. This parameter is particularly important as it has a large influence on the total duration of a training session, as well as the level of fatigue (44) and affective responses (19) experienced by the participant, thus influencing the likelihood of individuals taking up and adhering to a specific SIT intervention (26). As the main aim of investigating SIT protocols is generally to identify a time-efficient alternative to aerobic exercise, there is a need to identify the effect of this training parameter on the associated increase in V˙O2max. Recent evidence suggests that the positive effects of SIT on V˙O2max can be attained with fewer sprints (22,23,35,50), and therefore the aim of the present study was to perform a meta-analysis to provide estimates of the modifying effect of the number of sprint repetitions in SIT protocols on the increase in V˙O2max in untrained adult participants after training.
Literature search criteria and study selection
This study was undertaken in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines (54). We aimed to identify all studies that have examined pre- and posttraining V˙O2max after a period of at least 2 wk of training consisting of repeated (≥2) all-out Wingate cycle sprints or modifications thereof (e.g., studies using 10-, 15-, or 20-s all-out sprints instead of 30-s Wingate sprints). For this purpose, the electronic databases PubMed and Web of Science were searched for relevant available records up to May 1, 2016, using the 28 possible combinations of the independent variable search terms “Wingate,” “all-out,” “sprint,” and “interval training,” and the dependent variable search terms “fitness,” “aerobic capacity,” “aerobic power,” “V˙O2max,” “V˙O2peak,” “oxygen uptake,” and “oxygen consumption.” Relevant studies cited in recent meta-analyses were also used (24,53,65,75), as well as our own recent work (52). The following articles were excluded: 1) review articles/commentaries; 2) articles not written in English; 3) studies concerning patients, athletes, or participants with a mean baseline V˙O2max of >55 mL·kg−1·min−1 or a mean age <18 yr; 4) animal studies; 5) study trials in which SIT was combined with another intervention; and 6) SIT studies using noncycling exercise, intervals shorter than 10 s, or intervals that were not “all-out.” Two authors (NBJV and RSM) independently conducted the literature search and data extraction, and any discrepancies were resolved by consensus. The reviewers were not blinded to manuscript journals or authors. After removal of duplicate records, the titles and abstracts of all identified articles were screened for records that were clearly not relevant. These articles were omitted before assessing the full-text versions of the remaining articles for eligibility to be included in the meta-analysis. If more than one article reported data for the same experiment, duplicate data for these participants were only included once. The final data set included the results of 38 trials from 34 studies (Fig. 1).
Full articles were assessed for mean absolute pre- and posttraining V˙O2max. Absolute V˙O2max (L·min−1) was used rather than relative V˙O2max (mL·kg−1·min−1) as this provides an estimate of true changes in the ability to take up and use oxygen, independent of possible concomitant changes in body mass. Relative V˙O2max was used for the five studies for which absolute V˙O2max data were not available (8,42,48,57,68). Any data for V˙O2max obtained at intermediate time points during the intervention were excluded. The corresponding authors of articles without the required data were contacted by e-mail; authors from 23 studies were contacted (1,2,5,6,10–13,22,23,27,28,31,32,35,40,49,57,62–64,68,70,77), and we received raw data from 17 studies (5,10–13,22,23,27,28,31,40,49,57,62–64,77). Graph digitizer software (DigitizeIt, Braunschweig, Germany) was used to obtain the data from one study for which absolute pre- and posttraining V˙O2max data were only available in a figure (70). For trials with a no-exercise control group, the effect entered into the meta-analysis was intervention minus control. Data for aerobic exercise comparator groups were not included in the meta-analysis. The effect of training was expressed as a percentage change score. Percentage effects of SIT on V˙O2max were converted to factors (= 1 + effect/100), log transformed for the analysis, and then back transformed to percentages. Effects were weighted using percentage standard errors derived from exact P values, or from estimated errors of measurement as recommended by Weston et al. (75). Under the assumption that studies with similar test protocols and subject characteristics would have similar typical errors of measurement, the typical errors from these studies were averaged (via the weighted mean variance) and assigned to the studies that did not report an exact P value (1,2,6,35,46,68,70). The SE was then calculated via the relationship between typical error and SE (72). Finally, data for the following potential moderators were extracted for each study: participant characteristics (sex, age, body mass index, and baseline V˙O2max), training parameters (intervention duration, total number of training sessions, maximal number of sprint repetitions per training session, sprint duration, sprint/recovery ratio, and sprint resistance), and study type (controlled/uncontrolled; dummy variable).
To evaluate the extent of publication bias, a funnel plot of model residuals versus their corresponding standard errors was inspected for evidence of asymmetrical scatter (75). This approach takes into account any heterogeneity explained by the meta-regression, which is not accounted for in standard funnel plots of observed effects versus their standard errors. No evidence of asymmetrical scatter was apparent (Fig. 2).
A mixed effects meta-regression model was conducted using the “metafor” package in R (version 3.2.4, R Foundation for Statistical Computing, Vienna, Austria) (73). The overall effect of SIT on V˙O2max was evaluated using the mean values of the covariates. The modifying effects of covariates were evaluated as the difference between levels (e.g., male/female) for nominal variables. For numeric variables, effects were evaluated as the change in V˙O2max associated with a 2 SD change in the predictor (i.e., a typically low vs a typically high value ), or a practically relevant value (e.g., three additional SIT sessions would typically constitute an additional week of training). The random effects in the model specified a between-study SD, representing the typical difference in the true value of the effect in different study settings, plus a within-study random effect to account for within-study repeated measurements (a control treatment and/or more than one training treatment) (75). The SD was doubled before interpreting its magnitude with the scale used to interpret fixed effects (66), for the same reason that the magnitude of the effect of a linear covariate is evaluated with two SD of the covariate (33). We performed a sensitivity analysis to determine whether the inference relating to the modifying effect of maximum number of sprints was substantially altered when two potentially influential studies (with 12 and 15 maximum sprints, respectively [32,64]) were removed from the analysis.
We used magnitude-based inferences to provide an interpretation of the real-world relevance of the outcomes. Uncertainty in effect estimates was expressed as ±90% confidence limits, and as the likelihood that the true value was beneficial, trivial, or harmful in relation to threshold values for benefit (improved fitness) and harm (reduced fitness) (32). The overall effect of SIT on V˙O2max was interpreted as a clinical outcome, whereby an effect was deemed unclear if the chance that the true value was beneficial was >25%, with odds of benefit relative to odds of harm (odds ratio) of <66. Modifying effects were evaluated mechanistically and deemed unclear if the likelihood that the true value was beneficial and harmful was both >5%. Otherwise, the effect was deemed clear and was qualified with a probabilistic term using the following scale: <0.5%, most unlikely; 0.5%–5%, very unlikely; 5%–25%, unlikely; 25%–75%, possible; 75%–95%, likely; 95%–99.5%, very likely; >99.5%, most likely. As robust anchors for the smallest worthwhile clinical and practical effects relating to V˙O2max were not available, standardized effect thresholds of 0.2, 0.6, and 1.2 SD were adopted for small, moderate, and large effects, respectively (75). Here, the SD related to the average between-subject variances for baseline V˙O2max; these corresponded to magnitude thresholds of 1.0%, 2.9%, and 5.8%.
Data available for the 34 studies and 38 trials included in the meta-analysis are shown in Table 1 and Figure 3. The meta-analysis indicated an overall likely large effect of an “average” SIT protocol on V˙O2max (mean ± 90% confidence limits percent increase in V˙O2max = 7.8% ± 4.0%; Table 2). A possibly small effect was evident for the modifying effect of the maximum number of sprint repetitions in a training session (−1.2% ± 0.8% decrease per two additional sprint repetitions; Fig. 4A). The percentage chances that the modifying effect was negative, trivial, or positive were calculated to be 62.7%, 37.3%, and 0.0%, respectively. There were possibly small effects of baseline V˙O2max (−1.5% ± 1.9% decrease per 10 mL·kg−1·min−1 higher baseline V˙O2max; Fig. 4B) and age (−1.1% ± 1.2% decrease per 7 yr increase; Fig. 4C). All other modifying effects (intervention duration, number of sessions, sprint duration, recovery time, sprint resistance, body mass index, sex, and study type) were unclear or trivial (Table 2). Unexplained variance between studies was 2.2% ± 0.8% (likely moderate). The inference relating to the effect of maximum number of sprint repetitions was not altered when the two studies with the highest number of sprint repetitions (32,64) were removed from the analysis (−1.0% ± 1.1%; possibly small decrease; chances that the modifying effect was negative, trivial, or positive of 51.6%, 48.2%, and 0.0%, respectively).
The main aim of the present meta-analysis was to examine the modifying effect of the number of sprint repetitions in an SIT session on the increase in V˙O2max after training. Using data from 34 training studies and 418 participants, we demonstrate that the improvement in V˙O2max with SIT is not attenuated with fewer sprint repetitions, and possibly even enhanced. Considering the low physical activity levels in the general population (25), and the fact that lack of time is consistently identified as one of the main perceived barriers to becoming and remaining physically active (39,41,71), this finding has implications for the design of practical SIT interventions for improving general health. SIT protocols have the potential to be the most time-efficient interventions that are associated with improvements in key health markers, but because of the need for recovery intervals after sprints, this potential can only truly be achieved if the number of sprint repetitions is low. Therefore, our observation that reducing the number of sprint repetitions will not attenuate the increase in V˙O2max associated with SIT, and in fact may possibly improve the effect, is an important novel finding.
Based predominantly on the results of studies investigating the dose–response relationship between regular aerobic exercise and improvements in health markers, it has generally been accepted that at a given exercise intensity, a greater volume of exercise training (in terms of training duration and frequency) is associated with greater improvements in V˙O2max (20). For example, in a clinical trial comparing low- or high-intensity aerobic training protocols with matched energy expenditure (Studies of a Targeted Risk Reduction Intervention through Defined Exercise I), the magnitude of change in V˙O2max was greater in the group exercising at a higher intensity (15). Although the volume of exercise used in HIIT and SIT protocols is generally reduced compared with aerobic exercise programs (11,47,63), the principle of a dose–response relationship has not been challenged in these studies directly; it is the interaction between training volume and intensity that is used to justify the lower volume. Thus, HIIT and SIT studies investigating the effects of protocols with a lower intensity or a shorter sprint duration tend to increase the number of sprint repetitions (45,69). Apart from two studies demonstrating that reducing sprint duration from 30 s to either 15 s (74) or 10 s (31) does not attenuate the improvement in V˙O2max with SIT, there have been no HIIT or SIT studies that have specifically investigated the dose–response relationship between volume of high-intensity exercise and the health outcomes. Our meta-analysis provides the first evidence that at “all-out” supramaximal exercise intensities the generally accepted positive association between volume of training and magnitude of training adaptations does not hold true. Thus, research into the health benefits of SIT should increase the focus on protocols with fewer sprints.
Because of the relatively low number of studies examining the effects of SIT protocols with fewer than six sprint repetitions, the present meta-analysis was not powerful enough to make conclusions on the optimal number of all-out sprint repetitions. Only two studies have investigated the effects of an SIT protocol incorporating just two sprints (50,52). As one of these used the largest sample size of all the studies included in the review (n = 34 ), the mean 10% increase in V˙O2max observed with this protocol (termed reduced-exertion high-intensity interval training [REHIT]) appears to be robust. The greatest improvement in absolute V˙O2max (17%) was reported by Gillen et al. (22), who modified the original REHIT protocol to include a third sprint. However, the total duration of this intervention was 12 wk, whereas at an intermediate measurement point after 6 wk, the increase in V˙O2max was 12%, very similar to the 10% and 14% improvements observed with the original REHIT protocol (50,52). Although future studies should determine whether the magnitude of the response for V˙O2max is different between SIT protocols incorporating two to four sprints, the data presented in the present manuscript suggest that this difference will be small. If this is indeed the case, then several considerations support the use of the smallest number of sprints; that is, the two sprints used in the REHIT protocol. First, including a warm-up, recovery, and cooldown, this protocol has the potential to be the most time-efficient protocol. Furthermore, a drawback of the use of SIT as a public health intervention is the potential for high associated perceived exertion and negative affective responses (8,21). In this light, it is important to point out that the number of sprint repetitions has been shown to negatively affect both of these parameters (19,44). Therefore, effective SIT protocols with fewer sprint repetitions will likely offer the best chance of sedentary target populations taking up and adhering to an SIT intervention for improving health (18). With this in mind, the available evidence suggests that two sprints can be recommended as effective at improving the important health marker of V˙O2max. It could be argued that considering the apparent linear association between the number of sprint repetitions and the improvement in V˙O2max (Fig. 4A), a single sprint could be expected to produce similar improvements with a lower time commitment. However, we have recently performed the first study to investigate the effects of a single supramaximal sprint on V˙O2max and observed no significant increase compared with a no-exercise control condition in response to 4 wk of training with a sample size of n = 15 (67). Further studies are required to confirm whether supramaximal sprints only improve V˙O2max if they are repeated. Furthermore, in light of the fact that the majority of studies that have studied the effects of SIT protocols incorporating two or three sprint repetitions have used 20-s sprints rather than the more commonly used 30-s sprints (22,23,50,52), further studies are required to investigate the shortest sprint duration that can be used without attenuating the adaptations to V˙O2max.
Our present analysis does not provide an explanation for the possibly negative effect of reducing the maximal number of sprint repetitions on improvements in V˙O2max, but a discussion of possible mechanisms is warranted. The main limiting factor of V˙O2max is generally assumed to be maximal cardiac output, possibly through increased blood volume (7,55). To date, no studies have examined the effect of SIT on blood volume, but there is evidence in favor (17,74) and against (36) increases in blood volume in response to HIIT. Similarly, there is evidence in favor (3) and against (47) increased maximal cardiac output with SIT, with the latter finding suggesting that the adaptations to SIT for V˙O2max may be peripheral in origin. Indeed, several authors have proposed that improvements in V˙O2max with SIT are caused by improved skeletal muscle oxygen extraction because of increased mitochondrial density (22,36,57,65,77). Although it remains unclear whether the improvement in V˙O2max with SIT is due to central or peripheral adaptations, we propose that both increased blood volume and increased mitochondrial density could plausibly be explained by the rapid glycogen depletion associated with supramaximal exercise (51). First, maximal rates of glycogenolysis in the initial 15 s of a supramaximal sprint (58) are associated with the accumulation of metabolic derivatives, resulting in a hypertonic intramyocellular environment, influx of water, and a transient ~15%–20% drop in plasma volume within a time span of just a few minutes (51). This severe disturbance of circulatory homeostasis could be a stimulus for the body to increase blood volume in response to repeated SIT sessions. Second, glycogenolysis is associated with the release and activation of glycogen-bound 5′ AMP-activated protein kinase (59), which through downstream signaling pathways involving peroxisome proliferator-activated receptor gamma coactivator 1-alpha (a proposed master regulator of aerobic adaptations) could be a mechanism leading to increased mitochondrial density (30). Glycogen breakdown during repeated supramaximal sprints has been shown to be completely attenuated by the time of the third sprint (58), and it is therefore plausible, for both of these speculated mechanisms, that performing just two repeated supramaximal sprints is sufficient to “saturate” (i.e., maximally activate) the adaptive response. In other words, if either increased blood volume or mitochondrial density underpins the changes in V˙O2max with SIT, and if rapid glycogen breakdown regulates those adaptations, then no additional improvements would be expected if more than 2–3 sprints are performed in a training session.
Apart from this hypothesis, it is also possible that increasing the number of sprint repetitions will result in “pacing” strategies that affect the “all-out” nature of the sprints (e.g., reduction of peak and mean power output in initial sprints), or that accumulated fatigue may reduce the effectiveness of later sprints. Furthermore, the fact that increasing the number of sprint repetitions does not enhance the improvement in V˙O2max with SIT provides strong evidence against a role for the magnitude of the acute effects of supramaximal sprints on oxygen transfer, energy turnover, or total energy use, as part of the stimulus for improving V˙O2max with SIT, because for each of these factors the stimulus should be greater with more sprint repetitions.
Several limitations to the present meta-analysis should be noted. First, to be of use as a practical intervention for preventing and/or treating inactivity-related chronic disease, SIT interventions should also be effective at improving for example insulin sensitivity and glycemic control, blood pressure, blood lipid profile, and body composition. Therefore, one limitation is that only V˙O2max was included as an outcome measure in the present analysis. However, insufficient data for a meta-analysis are available for the effects of SIT on blood pressure (14,23,76), blood lipid profile (4,76), and body composition (69,76), but the effect of SIT on insulin sensitivity and glycemic control has received more attention (4,22,23,50,52,60,76). However, the methods used to assess the effects of SIT on these parameters have varied, with different studies using oral glucose tolerance tests (4,50,52,76), intravenous glucose tolerance tests (22), euglycemic hyperinsulinemic clamps (60), or continuous glucose monitoring (23). This means that a meta-analysis of the effects of the number of sprint repetitions in an SIT protocol on insulin sensitivity and glycemic control is also currently not feasible. Nonetheless, the improvements in insulin sensitivity and glycemic control observed to date with SIT protocols incorporating two (50) or three sprints (22,23) are encouraging.
Second, because of the number of available SIT studies, the power of our meta-analysis is insufficient to conclude with certainty that the modifying effect of the number of sprint repetitions is negative; i.e., it remains possible that in reality performing more sprints will result in the same improvements in V˙O2max (a chance of approximately 1 in 3). However, this is not of major importance to the significance of our findings: even “no effect” of the number of sprint repetitions would lead to the logical conclusion that performing SIT protocols with more than 2 or 3 sprints is unnecessary for improving V˙O2max in sedentary individuals. On the basis of the present analysis, the chance that in reality the effect of performing more sprints is positive was calculated as 0.0%.
A final limitation of our meta-analysis is that only SIT interventions using all-out intensities were included. Optimizing time-efficient interventions aimed at improving general health requires consideration of various parameters, and exercise intensity is undoubtedly one of the key parameters affecting the effectiveness of HIIT and SIT protocols. However, because of the large range of intensities used in SIT and HIIT protocols (~80%–350% of V˙O2max), we felt it was important to attempt to “control” for this variable in the present analysis by including only studies that used “all-out” cycling exercise. Nonetheless, there is a clear need for studies examining the effect of the number of sprint repetitions at lower exercise intensities; for example, in HIIT studies.
In conclusion, in the present meta-analysis, we demonstrate that SIT is possibly more effective at improving V˙O2max if fewer sprint repetitions are performed in a training session. Considering the proclaimed aim of SIT to provide a time-efficient alternative/adjunct to high-volume moderate-intensity aerobic exercise, this finding has important implications for the design of practical SIT interventions. We put forward that SIT research should move away from further characterizing the commonly used 4–7 × 30-s Wingate protocol and toward establishing acceptable and effective protocols. This will require more studies to examine the modifying effects of a range of training parameters (including number of sprint repetitions, sprint duration, sprint intensity, and training frequency) on adaptations to key health markers, as well as exercise enjoyment and acceptability, perceived exertion, and the potential to cause negative affective responses.
The authors thank Professor Will Hopkins for helpful advice during the preparation of the manuscript. No sources of funding were used to assist in the preparation of this review. The authors have no conflicts of interest to declare. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
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