Understanding Inputs and Outputs
People often confuse outputs for inputs in the health and performance space, don't be one of them
Image from here
The Body is a Complex System, I will spare readers the lesson in ‘systems theory’ but in essence this means any one input causes a number of changes and results from those changes. Similarly different inputs may causes different changes but similar results ie physiology is bit of a ‘black box’ between input and output/result.
This is important because in health and performance, we are increasingly seeing a misunderstanding (at least in my opinion) between inputs and outputs. At times, it is even worse, and we are seeing an emphasis on intermediaries which are being misunderstood as outputs.
Let me explain.
IF we concede that it’s hard to understand EXACTLY what happens as a result of our inputs, BUT that we can control those AND we can measure outputs, then we can evaluate our inputs as drivers of our outputs (perhaps not linearly but none the less). The natural next step then, would be to control and refine inputs based on changes in the outputs rather than focussing on the outputs… Sounds eerily familiar to being ‘processed focussed’ rather than ‘outcome focussed’ right?
Time for some examples:
VO2Max
Perhaps one of the hottest topics in both health and performance at the moment. All endurance athletes want a high VO2Max and increasingly in the longevity space this is being recognised an important indicator of function and longevity.
On the surface this sounds pretty reasonable and to be honest, it is. There is a ‘but’ though. VO2Max is ASSOCIATED with longevity and endurance performance, NOT causative (Eliud Kipchoge for instance, did not have the highest VO2Max of the runners tested in the original breaking 2 project). This is because in both cases, VO2Max, the maximal amount of oxygen you can use, is an indicator of adaptations, an intermediary, NOT the outcome per se. The outcomes in these cases being a highly functioning cardiovascular system helping drive longevity and contributing to endurance performance. We could, in fact, be even more concrete and say that the outcomes are actually longevity and running faster over a marathon in the example used. If VO2Max was the outcome, we wouldn’t race, we’d give this mob all the medals and go home.
Why this is important is because your VO2Max is a very reasonable way to track your progress or test your physiology, but as Goodhart’s law states: “when a measure becomes the goal it ceases to be a good measure.” That is to say, the goal in the case of athletes and longevity (or general health) focussed individuals is a lifestyle that promotes the changes that allow you to have a high VO2Max, not the VO2Max itself.
Performance
Heart Rate
I often see athletes looking at heart rate as an outcome they are aiming for. Be it that they want a lower heart rate for the same output or something else. This makes some intrinsic sense given heart rate adapts to changes in cardiovascular fitness, with increased stroke volume (blood pumped out by a single beat of the heart) being one adaptation to endurance training, which in turn means heart rate is lower. However, as mentioned above, if heart rate was an outcome we cared about we’d give out medals for it, not run the race and we would see a bunch of people taking beta blockers (drugs that lower heart rate) instead of EPO.
The point here is not that heart rate isn’t useful, in fact it is very useful to understand what the specific external load (speed, distance etc) you are imposing on the body is doing to the body. The body’s response to the this load (measure by heart rate for example) is what is called internal load. The challenge is many factors impact internal load, for example, nutrition & hydration status, climate, illness etc. So as an output, heart rate is very noisy data and ultimately on competition day, we don’t actually care what your heart rate is (or isn’t), we care about the external work done.
Again, this is not to say there’s no value in heart rate, or that it shouldn’t be tracked, it is to say that it should not be the goal we are optimising for. Remember Goodhart’s law: “when a measure becomes the goal, it ceases to be a good measure”. The best way to have a low heart rate is to take drugs that blunt heart rate - these do not enhance performance unless you’re a shooter and need to slow heart rate to shoot between beats or similar.
Power to Weight Ratio
As I discussed briefly in this article, people in all realms of life are quite concerned about improving body composition (see also below), in the realm of performance this is often to help improve power to weight ratio. The thought being; if I can be lighter then I will be faster because my power will stay the same or decrease proportionately less. This makes an absolute tonne of sense if you can control the specifics of this well ie your loss of weight/mass is all fat or mostly fat AND there are no other issues for example hormonal, psychological etc. Unfortunately, in my experience this is more often the exception than the rule.
Again, the body is a complex system.
Also focussing on weight makes no sense, when the outcome you are looking for is an improvement in power to weight ratio. In fact, power to weight may not make so much sense either - your goal should ultimately be to cross the line in the least possible time, or some other outcome like number of pullups etc.
So, we are back to not looking at a surrogate or intermediary and trying to focus solely on inputs, which then drive the desired outcomes, which we use to evaluate the inputs efficacy. In this case: train well, recover well and eat well (which may include not eating as many helpings of desert, or at least ensuring you get enough protein and fiber first!). This will then allow the body to self organise and drive the optimal power to weight ratio, which may be at a higher bodyweight than you think. As a personal example, I am currently around 8kg (17.6lbs) heavier than I was when I ran middle distance as a teenager. My 1km time is almost identical and every other time is significantly better; weight is non-linear with performance.
Health
Body Composition
I use this example and terminology intentionally, it is by far one of the greatest obsessions of the western world and I HOPE, that people who do care about it have managed to step beyond pure scale weight (body mass) as a surrogate for body composition. This is not going to digress into a discussion around the flaws of the scale, but suffice to say if that’s all you’re using to evaluate body composition you need more data points (and this article) badly.
People tend to focus on the scale as a means to understand body composition and at best it is crude but at worst it’s misleading. Ideal body composition (in the majority of endeavours) is low visceral fat (fat around your organs which is dangerous to health), high bone mineral density, good muscle muscle mass (this is intentionally vague but there’s not much merit in low muscle mass unless you’re a jockey and even then it’s debatable) and limited subcutaneous fat (the fat most people see and care about).
If one was to focus on the scale alone, most would optimise for lighter, to try minimise subcutaneous fat and would end up sacrificing things like muscle mass and probably drinking water.
Ideally, instead of focussing on the scale or even the DEXA scan (a better way to measure body composition), one would focus on the inputs that drive this outcome. These being: diet, exercise, sleep and stress management (sounds familiar right?)
Sleep Stages
Enter orthosomnia (the pathology of worry excessively about sleep tracker data - yes it’s a thing, check the references below). This is not to say all those concerned with better sleep have a problem with that pursuit or that using a sleep tracker is an issue. However, there is a good amount of data (again, see the below references for some examples) suggesting sleep tracker data isn’t perfect when it comes to sleep stages, so I wouldn’t worry too much about the individual sleep stages your favourite wearable spits out. That said, IF there’s a huge change, it probably reflects some signal, rather than pure noise (for more on this, see this article).
But I digress… This is an article on inputs and outputs and when it comes to sleep stages those are certainly the output. You can’t really control them much and to think your body isn’t doing its best to optimise them given your needs is a little naive. So, again, get the inputs right via sleep hygiene. Ensure your room is cool, dark and quiet, no alcohol or late day stimulants (like caffeine) and have a digital sunset and wind down routine. From there you can looks at things like avoiding late meals, sunlight exposure during the day, exercise. The further into things like supplements, mattresses etc. You get the point, big rocks first, focus on the inputs to create the good sleep (one of which is not being anxious about getting good sleep - real meta I know).
The key to the essence of this article is that you should be crystal clear on your goal outcomes and track these meticulously. To aid in this, you may have intermediaries or surrogates, these may well be helpful to fill in detail into the picture, but they are not the goal. Optimise your inputs and spend energy there, understand the impact of differing inputs in part via the intermediaries, and evaluate outcomes.
References:
Clausen JSR, Marott JL, Holtermann A, Gyntelberg F, Jensen MT. Midlife Cardiorespiratory Fitness and the Long-Term Risk of Mortality: 46 Years of Follow-Up. J Am Coll Cardiol. 2018 Aug 28;72(9):987-995. doi: 10.1016/j.jacc.2018.06.045. PMID: 30139444.
Laukkanen JA, Zaccardi F, Khan H, Kurl S, Jae SY, Rauramaa R. Long-term Change in Cardiorespiratory Fitness and All-Cause Mortality: A Population-Based Follow-up Study. Mayo Clin Proc. 2016 Sep;91(9):1183-8. doi: 10.1016/j.mayocp.2016.05.014. Epub 2016 Jul 18. PMID: 27444976.
Jones AM, Kirby BS, Clark IE, Rice HM, Fulkerson E, Wylie LJ, Wilkerson DP, Vanhatalo A, Wilkins BW. Physiological demands of running at 2-hour marathon race pace. J Appl Physiol (1985). 2021 Feb 1;130(2):369-379. doi: 10.1152/japplphysiol.00647.2020. Epub 2020 Nov 5. PMID: 33151776.
Baron KG, Abbott S, Jao N, Manalo N, Mullen R. Orthosomnia: are some patients taking the quantified self too far? J Clin Sleep Med. 2017;13(2):351–354.
Jahrami H, Trabelsi K, Vitiello MV, BaHammam AS. The Tale of Orthosomnia: I Am so Good at Sleeping that I Can Do It with My Eyes Closed and My Fitness Tracker on Me. Nat Sci Sleep. 2023 Jan 21;15:13-15. doi: 10.2147/NSS.S402694. PMID: 36713639; PMCID: PMC9875581.
Lee T, Cho Y, Cha KS, Jung J, Cho J, Kim H, Kim D, Hong J, Lee D, Keum M, Kushida CA, Yoon IY, Kim JW. Accuracy of 11 Wearable, Nearable, and Airable Consumer Sleep Trackers: Prospective Multicenter Validation Study. JMIR Mhealth Uhealth. 2023 Nov 2;11:e50983. doi: 10.2196/50983. PMID: 37917155; PMCID: PMC10654909.
de Zambotti M, Rosas L, Colrain IM, Baker FC. The Sleep of the Ring: Comparison of the ŌURA Sleep Tracker Against Polysomnography. Behav Sleep Med. 2019 Mar-Apr;17(2):124-136. doi: 10.1080/15402002.2017.1300587. Epub 2017 Mar 21. PMID: 28323455; PMCID: PMC6095823.