Stratified fitness training; The future of health and performance? Ciaran Keogh

In healthcare it is estimated that current treatments may only be designed to work approximately between 30 to 60 percent of patients on average. However, with advances in our understanding into human biology in health and disease, we come to understand on the one hand, the heterogeneity of disease conditions, and on the other hand, heterogeneity amongst human population in response to medicine based on their physiological makeup, which can be defined at the pharmacological level. The aim of stratified healthcare is to identify as early as possible which patients are more likely to respond to different treatments as early as possible, streamlining the delivery and effectiveness of treatment. A brief overview of stratified healthcare can be found here

The principles of fitness are often used to describe the various factors that need to be considered when planning any kind of fitness or strength training programme, overload, progression, specificity, reversibility, specificity and individualisation of training are 6 commonly used principles that guide training design. The principle of individualisation is one that is not always well understood or accounted for. Individualisation means that not everyone will respond in the same fashion to the same training stimulus, essentially this is stratified fitness programming, but what examples have we in the research of this principle in practice, both in occurrence and intervention.

The variability and individuality of fitness adaptions are clearly highlighted in a well known study by Hubal et al. 2005. In this study 500 participants completed a 12-week progressive resistance training routine consisting of bicep curls. Changes were assessed by means of cross-sectional area of the muscle training, i.e. did the muscle grow, how strong did the muscle become, did the maximum amount of weight the individuals could lift for 1 repetition (1RM) increase ? Initially, if we look at average increases of these measures, strength increased by 54% and size of the muscle increased by 19%, however if we look deeper into the numbers and assess the range of change that occurred we see that the change in strength varied from 0 to 250%, and the change in size varied from a decrease of -2% to an increase of 59%. The range of improvement and in some cases disimprovement across the 500 subjects is fascinating, the principle of individualisation is clearly in effect, despite the same stimulus being applied, the outcomes are vastly different. There is no doubting that structural, morphological and genetic differences amongst the 500 individuals contributed to the varied response. Much like the stratified approach to healthcare, profiling and identifying the response of individuals to specific stimuli can lead to a more targeted intervention in the beginning, thus maximising the training effect in participants of all levels.

The concept of individualisation is not a new one, but it could be argued that the implantation of this idea in sports performance may not be as common as it should. The challenge is identifying the likely response of an individual as early as possible. It is possible that in time our suitability to a training intervention may be dictated by a simple swab test that identifies some key genomes that will allow us to plan training based on these results, however at present over 200 genetic variations are potentially associated with physical performance phenotypes or training responsiveness and to date approximately 20 polymorphisms have been found to be specifically associated with elite athlete performance. While this area of research is promising, the number of genomes associated with performance is still quite large.  In a practical setting the improvement of jumping performance by using a stratified or individualised approach is well described in a study by Jimenez & Reyes (2017), the full paper is available here

All subjects in the three optimized training sub-groups (velocity-deficit, force-deficit, and well-balanced) increased their jumping performance with jump height improvement for all subjects, whereas the results were much more variable and unclear in the non-optimized group. The individualized training program specifically based on the force velocity imbalance (gap between the actual and optimal force velocity profiles of each individual) was more efficient at improving jumping performance than a traditional resistance training common to all subjects regardless of their force velocity imbalance.

It is proposed that quantifying force velocity imbalance on an individual basis could therefore help improve the effectiveness of training prescription by adjusting it to each athlete’s individual needs. In theory, this would lead to improved explosive performance through an effective change in the individual current force velocity profile toward the optimal value, either reducing the force velocity imbalance and or increasing the maximum power output (Samozino et al., 2014).

Through my own research in UL, I hope to establish more clarity in objectively identifying the motor types of athletes using non invasive methods, with the aim of maximising training interventions.

Ciaran Keogh round
Ciaran Keogh is a postgraduate researcher studying for his PhD in the department of Physical Education and Sport Sciences at the University of Limerick.  Contact Ciaran via email at or follow Ciaran on Twitter


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