• David Leith // MSc (Med) Exercise Science

Each to 'Their' Own! - Exploring individual Differences


What is food for one man may be bitter poison to others”. Man ‘hath’ long acknowledged the differences in individuals’ taste preferences. Indeed we all look slightly different, have our own idiosyncrasies and excel in different sporting codes – that 0.1% of genetic uniqueness – thus it should follow that our bodies have different ‘tastes’ and thrive on different stimuli. During recent decades, however, practitioners have often looked past the individual in prescribing training and nutrition programs – leading to sub-optimal results and frustration. There is increasing evidence that personalisation may be a more effective approach.

Remember your school sporting days: there was always that one kid who adapted quickly to any sport and made every first team, while others struggled to develop despite hours of training. Fast-forward to today and we see the same pattern: some show rapid gains in the gym or improved park run times, whilst others may be stuck in a permanent plateau despite similar training. This phenomenon has been well documented: large studies, such as the HERITAGE Family Study[2], have shown that there is considerable inter-individual variation in response to regular exercise training. This has been observed in parameters as diverse as HDL-cholesterol and VO2max - even when individuals of similar training status are exposed to the same volume of activity[1].

In previously sedentary males, Vollard et al (2009) investigated the relationship between changes in metabolism and aerobic capacity (VO2max) with aerobic performance (15 minute time-trial)[3]. After 6 weeks of supervised training (4x / week at 70% initial VO2max), participants exhibited substantial variation in training adaptations. VO2max response varied from a 2% decrease to a 30% improvement; however, the ‘low-responders’ in VO2max were not necessarily ‘low-responders’ in other parameters. Although ‘on average’ the participants improved both VO2max and performance, changes in these two parameters were not related; rather VO2max improved in concert with maximal ventilatory-capacity, and aerobic performance with sub-maximal metabolic changes. Without presenting these adaptations on an individual basis, the average effects would have obscured the independence of the physiological and biochemical parameters associated with aerobic capacity and performance. This shows the misinterpretations that may arise from reporting only main effects and group differences in scientific studies.

In a recent Finnish study[4], in which I was fortunate enough to work as a research intern, Vesterinen et al. (2015) investigated the factors that influence individual adaptation in recreational runners to 8-weeks of two variations of endurance training: high-volume (HVT) or high-intensity (HIT). On average, HIT but not HVT improved peak treadmill running speed (PTRS); however, within both groups there was substantial variation: -2.8% to +4.1% in HVT and 0 to +10.2% in HIT. Heart-rate variability (HRV), a measure of cardiac autonomic regulation that has been previously related to heterogeneity in endurance-training adaptation, was found to be a strong predictor of PTRS changes. Specifically: lower baseline high-frequency-power of HRV (HFP) predicted stronger improvements from HVT, whereas higher HFP predicted better responses from HIT. This provides support for HRV as a physiological tool to predict adaptations and better individualise endurance training.

Even in well-trained athletes, where potential for gains is far more marginal, the notion of individualisation is crucially important. A given training stimulus may affect athletes very differently, as has been shown for example, in caffeine supplementation[5], altitude training[6], as well as HIT studies[7]. In the latter study, 14 well-trained cyclists underwent a 4-week HIT program during which heart-rate-recovery (HRR) was measured after the standardised warm-up before each session. Cyclists were separated into two groups: those who exhibited a continuous HRR decline (HRRdecr) or increase (HRRincr) during the 4 weeks. Although both groups improved relative peak-power-output (PPO), the HRRincr cyclists had a significantly greater improvement in 40km time-trial (TT) power-output and tendency for a faster time. This study and Vesterinen et al. emphasise that different athletes respond better to different types of training. It is, therefore, crucial to tailor training programs at all levels to the needs of the individual.

Many elite sporting teams have adopted tools to monitor this individual variability during training periods and manage their athletes accordingly[8]. This is especially important in optimising the balance between training load and recovery to ensure athletes do not become over-fatigued, or ‘non-functionally over-reached’, since the latter may be detrimental to both performance and well-being8. Measures of both external (e.g. power, speed, GPS data) and internal (e.g. Rating of perceived exertion, heart-rate indices, self-reports / psychomotor skills) load are routinely employed to assess whether individual athletes are coping with the training load and adapting positively to the training program. Since the training loads required for adaptation vary for different athletes, individualising the monitoring process is crucial to ensure that the internal load experienced by each athlete is matched to what the coach prescribes.

So where does this leave us? I believe these examples highlight the need for both researchers and clinicians to recognise the ‘biochemical individuality’ of each person and the need to treat them as such. Individuals are more complex than what general training programs support, and we require thorough assessment to determine what interventions will suit us best. Practically speaking, it seems that the more you know about your client’s physiology the better, and a fair bit of experimentation may be required to decipher which training programs allow them to flourish!

1. Minich, D.M., & Bland, J.S. Personalised Lifestyle Medicine: Relevance for nutrition and lifestyle recommendations. The Scientific World Journal. 2013, (2013).

2. Bouchard, C., & Rankinen, T. Individual differences in response to regular physical activity. Med. Sci. Sports Exerc. 33, S446-51 (2001).

3. Vollaard, N.B.J., Constantin-Teodosiu, D., Fredriksson, K., Rooyackers, O., Jansson, E., Greenhaff, P.L., Timmons, J.A., and Sundberg, C.J. Systematic analysis of adaptations in aerobic capacity and submaximal energy metabolism provides a unique insight into determinants of human aerobic performance. J. Appl. Physiol. 106, 1479–1486 (2009).

4. Vesterinen, V., Häkkinen, K., Laine, T., Hynynen, E., Mikkola, J. and Nummela, A. Predictors of individual adaptation to high-volume or high-intensity endurance training in recreational endurance runners. Scan. J. Med. Sci. Sports. (2015).

5. Jenkins, N.T, Trilk, J.L., Singhal, A., O'Connor, P.J., Cureton, K.J. Ergogenic effects of low doses of caffeine on cycling performance. Int. J. Sport. Nutr. Exerc. Metab. 18(3), 328-42 (2008).

6. Chapman, R.F., Stray-Gundersen, J., Levine, B.D. Individual variation in response to altitude training. J. App. Physiol. 85 (4), 1448-1456 (1998).

7. Lamberts, R.P., Swart, J., Capostagno, B., Noakes, T.D., Lambert, M.I. Heart rate recovery as a guide to monitor fatigue and predict changes in performance parameters. Scand. J. Med. Sci. Sports. 20 (3): 449-57 (2010).

8. Halson, S.P. Monitoring Training Load to Understand Fatigue in Athletes. Sports Med. 44 (Suppl 2): S139–S147 (2014).

#Physiology #Genetics

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