Variability in exercise physiology: Can capturing intra-individual variation help better understand true inter-individual responses?

High-intensity interval training (HIT), in a variety of forms, is today one of the most effective means of improving cardiorespiratory and metabolic function and, in turn, the physical performance of athletes. HIT involves repeated short-to-long bouts of rather high-intensity exercise interspersed with recovery periods. For team and racquet sport players, the inclusion of sprints and all-out efforts into HIT programmes has also been shown to be an effective practice. It is believed that an optimal stimulus to elicit both maximal cardiovascular and peripheral adaptations is one where athletes spend at least several minutes per session in their 'red zone,' which generally means reaching at least 90% of their maximal oxygen uptake (VO2max). While use of HIT is not the only approach to improve physiological parameters and performance, there has been a growth in interest by the sport science community for characterizing training protocols that allow athletes to maintain long periods of time above 90% of VO2max (T@VO2max). In addition to T@VO2max, other physiological variables should also be considered to fully characterize the training stimulus when programming HIT, including cardiovascular work, anaerobic glycolytic energy contribution and acute neuromuscular load and musculoskeletal strain. Prescription for HIT consists of the manipulation of up to nine variables, which include the work interval intensity and duration, relief interval intensity and duration, exercise modality, number of repetitions, number of series, as well as the between-series recovery duration and intensity. The manipulation of any of these variables can affect the acute physiological responses to HIT. This article is Part I of a subsequent II-part review and will discuss the different aspects of HIT programming, from work/relief interval manipulation to the selection of exercise mode, using different examples of training cycles from different sports, with continued reference to T@VO2max and cardiovascular responses. Additional programming and periodization considerations will also be discussed with respect to other variables such as anaerobic glycolytic system contribution (as inferred from blood lactate accumulation), neuromuscular load and musculoskeletal strain (Part II).

The purpose of this review was to address the question of interindividual variation in responsiveness to regular exercise training and to define the contributions of age, sex, race, and pretraining phenotype level to this variability. A literature review was conducted of the studies reporting interindividual variation in responsiveness to standardized and controlled exercise-training programs, and included an analysis of the contribution of age, sex, race, and initial phenotype values to the heterogeneity in VO(2max), high-density lipoprotein (HDL)-C and submaximal exercise, heart rate (HR), and systolic blood pressure (SBP) training responses in subjects from the HERITAGE Family Study. Several studies have shown marked individual differences in responsiveness to exercise training. For example, VO(2max) responses to standardized training programs have ranged from almost no gain up to 100% increase in large groups of sedentary individuals. A similar pattern of heterogeneity has been observed for other phenotypes. Data from the HERITAGE Family Study show that age, sex, and race have little impact on interindividual differences in training responses. On the other hand, the initial level of a phenotype is a major determinant of training response for some traits, such as submaximal exercise heart rate and blood pressure (BP) but has only a minor effect on others (e.g., VO(2max), HDL-C). The contribution of familial factors (shared environment and genetic factors) is supported by data on significant familial aggregation of training response phenotypes. There is strong evidence for considerable heterogeneity in the responsiveness to regular physical activity. Age, sex, and ethnic origin are not major determinants of human responses to regular physical activity, whereas the pretraining level of a phenotype has a considerable impact in some cases. Familial factors also contribute significantly to variability in training response.

The response to an exercise intervention is often described in general terms, with the assumption that the group average represents a typical response for most individuals. In reality, however, it is more common for individuals to show a wide range of responses to an intervention rather than a similar response. This phenomenon of 'high responders' and 'low responders' following a standardized training intervention may provide helpful insights into mechanisms of training adaptation and methods of training prescription. Therefore, the aim of this review was to discuss factors associated with inter-individual variation in response to standardized, endurance-type training. It is well-known that genetic influences make an important contribution to individual variation in certain training responses. The association between genotype and training response has often been supported using heritability estimates; however, recent studies have been able to link variation in some training responses to specific single nucleotide polymorphisms. It would appear that hereditary influences are often expressed through hereditary influences on the pre-training phenotype, with some parameters showing a hereditary influence in the pre-training phenotype but not in the subsequent training response. In most cases, the pre-training phenotype appears to predict only a small amount of variation in the subsequent training response of that phenotype. However, the relationship between pre-training autonomic activity and subsequent maximal oxygen uptake response appears to show relatively stronger predictive potential. Individual variation in response to standardized training that cannot be explained by genetic influences may be related to the characteristics of the training program or lifestyle factors. Although standardized programs usually involve training prescribed by relative intensity and duration, some methods of relative exercise intensity prescription may be more successful in creating an equivalent homeostatic stress between individuals than other methods. Individual variation in the homeostatic stress associated with each training session would result in individuals experiencing a different exercise 'stimulus' and contribute to individual variation in the adaptive responses incurred over the course of the training program. Furthermore, recovery between the sessions of a standardized training program may vary amongst individuals due to factors such as training status, sleep, psychological stress, and habitual physical activity. If there is an imbalance between overall stress and recovery, some individuals may develop fatigue and even maladaptation, contributing to variation in pre-post training responses. There is some evidence that training response can be modulated by the timing and composition of dietary intake, and hence nutritional factors could also potentially contribute to individual variation in training responses. Finally, a certain amount of individual variation in responses may also be attributed to measurement error, a factor that should be accounted for wherever possible in future studies. In conclusion, there are several factors that could contribute to individual variation in response to standardized training. However, more studies are required to help clarify and quantify the role of these factors. Future studies addressing such topics may aid in the early prediction of high or low training responses and provide further insight into the mechanisms of training adaptation.