Intermittent exercise and insulin sensitivity in older individuals—It's a <scp>HIIT</scp>
Bibliographic record
Abstract
The paper by Søgaard et al1 in this issue of Acta Physiologica sheds new light on the potential for high-intensity interval training (HIIT) to improve insulin sensitivity and other indices of cardiometabolic health in older individuals. While interval training has been practised by high-level athletes for more than a century, the last decade in particular has seen a resurgence of interest in the method as a means to enhance health in a wide range of individuals. Renewed scientific inquiry has been accompanied by increased attention from fitness enthusiasts, as evidenced by the fact that HIIT was again recently named the top fitness trend worldwide in an annual survey by the American College of Sports Medicine. Interest in HIIT is partly due to the potential for intermittent exercise to elicit physiological adaptations similar to traditional endurance training despite a reduced total exercise volume and time commitment.2 Relatively few studies, however, have examined the effect of low-volume HIIT protocols in older individuals. The terminology used to describe interval training can be confusing and is worth noting here. While there is no universal definition, HIIT is typically defined as relatively intense bouts of intermittent exercise that elicit ≥80% of maximal heart rate.3 It can be distinguished from a more intense form—sprint interval training (SIT)— in which bouts are performed in an “all-out” manner or the absolute intensity exceeds the workload required to elicit maximal oxygen uptake (VO2max).3 Even this relatively simple classification scheme can be problematic; to wit, the training workload used in the study by Søgaard et al exceeded VO2max, but the protocol was characterized as HIIT. More than a semantic point, this issue speaks to the lack of consistent terminology used in interval training studies. It also highlights the challenge associated with translating interval training research into practice, that is, what is the most appropriate way to characterize various training protocols? The use of perceived exertion ratings may be a pragmatic and effective strategy in this regard, and interval training researchers are encouraged to include and report such measurements. The study by Søgaard et al1 was completed on 22 sedentary, overweight and obese men and women (n=11 each) with a mean age of ~63 years and body mass index of ~31 kg/m2. Participants performed 16-18 sessions of supervised interval training over 6 weeks, plus an additional 1-2 sessions to maintain the training effect over a series of post-training measurements. Aside from a lead-in phase during which individual training loads were determined, most sessions involved five 1-minute intervals of stationary cycling at an intensity that elicited ~96%-98% of maximal heart rate. Absolute workloads were adjusted periodically to maintain the training stimulus, which corresponded to ~130% of the peak workload achieved during a baseline VO2max test (~145W and ~200W for the women and men, respectively). Participants performed a 2-minute warm-up at 50W, and the intervals were separated by 1.5 minutes of rest or light cycling at 25W, for a total time commitment of 13 minutes per training session or ~40 minutes per week. Whole body insulin sensitivity, determined prior to the intervention and 48-72 hours after the final training session using the hyperinsulinaemic-euglycemic clamp technique, improved after training. The response tended to be greater in men but there was no sex-specific difference. HbA1c was reduced after training in men only, and beta-cell function was seemingly unaffected, as there were no changes in fasting plasma glucose or insulin, and the insulin secretion rate and glucose excursion during oral and intravenous glucose tolerance tests were unchanged. Blood pressure and body weight did not change, but per cent body fat, visceral fat mass and android and gynoid fat distribution were lower after training. The duration of training can affect the change in at least some of these parameters, and a recent systematic review and meta-analyses concluded that ≥12 weeks of HIIT improves cardiometabolic risk factors including waist circumference, per cent body fat, resting heart rate, systolic blood pressure and diastolic blood pressure in overweight/obese populations.4 Only a few studies have employed the gold standard hyperinsulinaemic-euglycemic clamp technique to examine the effect of interval training on insulin sensitivity, and the study by Søgaard et al is only the second report in older individuals. The findings build on a recent investigation by Robinson et al (2017) that showed 12 weeks of HIIT improved insulin sensitivity in a small group of older men and women with a mean age of 71 years (n=9; body mass index ~27).5 The training intervention in the latter study involved 3 days per week of interval-based cycling (involving repeated 4-minute intervals at >90% of maximum) and 2 days per week of treadmill walking, with each session requiring a total of 40-60 minutes including warm-up and cooldown and recovery periods. The work of Søgaard et al1 is noteworthy as it shows insulin sensitivity can be improved in older individuals using a shorter training intervention and much lower total exercise volume and time commitment. The findings are consistent with the concept of an intensity-duration trade-off and supported by evidence showing that a relatively small volume of intense exercise can elicit physiological remodelling comparable to a large volume of lower intensity exercise2 While Søgaard et al1 did not address in detail the potential mechanistic basis for the improved insulin sensitivity, biopsy samples revealed an increased skeletal muscle protein content of GLUT4, glycogen synthase and hexokinase after training. Søgaard et al1 also demonstrate that low-volume interval training is an effective means to improve cardiorespiratory fitness in older individuals, as objectively measured by VO2max. This finding is consistent with a robust body of evidence that shows HIIT may serve as a time-efficient substitute or complement to commonly recommended moderate-intensity continuous training for improving cardiometabolic health.4 The ~6% improvement in VO2max in the study by Søgaard et al1 compares with a ~10% increase in VO2max reported in a large group (n=136) of sedentary men and women aged 18-53 years after a similar “5x1” interval training protocol performed three times per week for 6 weeks.6 The relative improvement in cardiorespiratory fitness was not different between men and women in either study, but the work of Phillips et al6 highlights the considerable interindividual variability in training responses. It is worth remembering that intermittent exercise need not be particularly intense to elicit health benefits, although a higher total volume of exercise is required. This is evidenced by the work of Karstoft et al7 who studied the effects of free-living interval walking training in overweight and obese individuals with type 2 diabetes (mean age ~60 years). Four months of interval walking, involving 1 hour per day, 5 days per week, was found to be superior to energy expenditure-matched continuous walking for improving cardiorespiratory fitness, body composition and glycemic control assessed by continuous glucose monitoring. The interval protocol was more effective even though it involved only slight variations in intensity that corresponded to ~69% and ~63% of maximal heart rate, respectively, during alternating 3-minute periods of “fast” and “slow” walking. Numerous other studies have demonstrated the feasibility and effectiveness of interval walking training for improving fitness in older individuals, but the protocols typically involve a minimal training time commitment of at least several hours per week. Søgaard et al1 demonstrate the efficacy of a time-efficient interval training protocol to improve insulin sensitivity and cardiorespiratory fitness in older individuals. The intervention was reported to be well tolerated by all participants, and there were no dropouts due to adverse effects of the training. Larger, longer and more comprehensive studies are warranted to advance our understanding of the effectiveness of brief, intense interval training and how it compares to traditional aerobic training as reflected in public health guidelines. In this regard, Generation 100 (https://www.ntnu.edu/cerg/generation100) will be the first randomized controlled trial to determine the effect of exercise training on morbidity and mortality in the elderly, and it will specifically explore the relationship between exercise intensity and health benefits. The effectiveness of interval training in the “real world” remains the subject of considerable debate, and while the determinants of physical activity behaviour are obviously complex, emerging data support the viability of interval exercise as an alternative to continuous exercise from a psychological perspective.8 I have no conflict to declare.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".