Functional high‐intensity training: A HIT to improve insulin sensitivity in type 2 diabetes
Bibliographic record
Abstract
The paper by Fealy et al. (2018) in this issue of Experimental Physiology sheds new light on the potential for brief, vigorous exercise to improve insulin sensitivity and other indices of cardiometabolic health in overweight and obese individuals with type 2 diabetes. Thirteen men and women, aged 53 ± 7 years, performed a functional high-intensity training programme consisting of aerobic and resistance exercises. Participants completed a total of 18 training sessions over 6 weeks at an established Crossfit™ gym under the supervision of a certified coach. Each workout entailed a distinct combination of calisthenics, gymnastics, weightlifting and other ‘cardio’ exercises, such as rowing. The sessions ranged from 8 to 20 min in duration, including a warm-up and cool-down, and the main high-intensity phase elicited a heart rate >85% of maximum. Insulin sensitivity, determined using oral glucose tolerance tests performed before the intervention and ≥24 h after the final exercise session, improved after training. The programme also reduced fat mass, diastolic blood pressure, blood lipids (triglyceride and very low-density lipoprotein cholesterol) and metabolic syndrome z-score, and increased basal fat oxidation and plasma adiponectin. Training compliance was >95%, and no injuries or adverse events were reported. The timely report by Fealy et al. (2018) will no doubt stimulate additional research on the potential for practical, time-efficient exercise protocols to enhance health-related markers in deconditioned individuals and people with cardiometabolic diseases. The findings demonstrate the feasibility and efficacy of functional high-intensity training in a small group of carefully screened participants under controlled conditions. The subjects were non-smokers with no contraindications for elevated levels of physical activity, based on a detailed medical history and completion of an exercise stress test with 12-lead ECG before participation. The new results build on data from other small, proof-of-concept studies that have revealed the potential for high-intensity interval training (HIIT) to improve indices of glycaemic control in a time-efficient manner in people with type 2 diabetes (Little et al., 2011). Larger, longer and more comprehensive randomized controlled studies are warranted to advance our understanding of the effectiveness of brief, intense exercise training and how it compares with traditional physical activity recommendations advocated by public health agencies. Adherence to current guidelines are poor, with ‘lack of time’ being a key barrier cited to regular participation in physical activity. At the same time, there are legitimate safety concerns regarding the appropriateness of high-intensity exercise in certain circumstances and conditions. The risk of acute myocardial infarction and sudden cardiac death is known to be increased after vigorous activity in susceptible individuals, which emphasizes the need for appropriate medical prescreening (Thompson et al., 2007). The relative risk should not be overstated, however, as evidenced by a recent comprehensive review that concluded: ‘mounting clinical evidence supports HIIT as a safe therapy for the majority of individuals with elevated cardiometabolic risk’ (Cassidy, Thoma, Houghton, & Trenell, 2017). A resurgence of scientific interest over the past decade into the potential for brief, vigorous exercise to improve cardiometabolic health has been accompanied by increased attention from fitness enthusiasts. For the past 5 years, HIIT and body weight training have ranked among the top fitness trends worldwide in an annual survey by the American College of Sports Medicine. The functional high-intensity training programme used by Fealy et al. (2018) effectively integrated both trends, and the resultant method is particularly appealing because of its versatility. Variations of the protocol can be done almost anywhere, with minimal need for specialized equipment. In addition to benefiting people with type 2 diabetes, the training method could be effective for the prevention and management of other lifestyle-induced cardiometabolic diseases and inactivity-related disorders. Crossfit™ and other workout programmes of a similar style have proved extremely popular, but translational studies are warranted to establish the effectiveness of functional high-intensity training scientifically in the ‘real world’. Some dismiss the method outright owing to the high degree of motivation and volitional effort required to perform such training. Such criticism tends to ignore the reality that fewer than one-quarter of adults meet current physical activity guidelines, and there is an obvious need for practical, time-efficient substitutes that broaden the available options from which to choose. The determinants of physical activity behaviour are complex, but emerging data support the viability of brief, vigorous exercise as an alternative to traditional forms of training from a psychological perspective (Stork, Banfield, Gibala, & Martin Ginis, 2017).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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; a candidate call from one teacher head, not a consensus.
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".