The Science Behind Lactate Threshold Tests

Nate and I were recently guests on the VeloNews Fast Talk podcast during which we talked about how research has influenced training and racing (check back later for when it goes live!).  Even after the podcast ended, I’ve still been thinking of the many ways science has helped athletes improve performance.  The lactate threshold test is a great example that we unfortunately didn’t have time to cover during the podcast.  Luckily for you readers though, I’ve got time to cover it now.   

There are all kinds of protocols for a lactate threshold test but the basics are pretty straight forward.  An athlete starts at a relatively easy pace and then the intensity increases every 4-5 minutes until they can no longer maintain the exercise intensity (protocols commonly differ in the magnitude the workload changes for each stage and sometimes also in stage lengths).  During the last minute of each stage, a small amount of blood is taken and levels of lactate are measured. 

The key metrics from the test (lactate and power output) are then graphed resulting in something like this:

LT curve.png

Early in the graph, we see lactate levels remaining relatively stable (as is the case in this example, sometimes we also see a slight decrease in lactate as the athlete settles into the test).  Past a certain workload though, lactate levels begin to increase exponentially.  The primary goal with training is to shift the graph to the right so that you extend the workloads during which lactate levels remain low. 

A number of ideas exist regarding how to train so that you move the graph to the right.  One idea is to train at the intensity just before lactate begins to increase.  For the graph above, this individual would therefore train in the ~270W range.  Others suggest training at a higher intensity beyond the initial inflection.  One answer likely does not fit everyone so it’s important to experiment and find what works best for you. 

It’s also important to realize not every graph will look the same. Here is another example:

LT2.png

The differences here might not be quite as obvious.  One difference is that early in the test the lactate levels slightly increase instead of staying flat.  Although the increase is not dramatic, these levels would suggest the athlete should focus on their aerobic endurance base (those traditional endurance miles).  Building up that endurance ability will flatten out the earlier section of the graph and help with overall performance. 

Another difference between the graphs is the peak lactate levels.  In the first example, the athlete gets to ~7.5 mmol/L while in the second example, the athlete gets to ~11 mmol/L.  Some of these differences can be attributed to variability between athletes (and in some cases differences between protocols).  However, if an athlete is unable to reach their typical peak levels, this can indicate fatigue and a need to take some extra rest. 

One thing I have yet to touch on so far is the actual threshold for each athlete.  One reason for this is that there are many (many, many, many…) ways to define the threshold from a lactate threshold test.  Some common definitions include: power at 4mmol/L (in the first example that would equate to ~345W), power at 1mmol/L above baseline (~310W), and power at the first inflection point (~280W). Many of these definitions depend on what you are trying to predict – in other words, the length of the event.  The definition you use though, is not as important as keeping your definition consistent when repeating tests and looking at performance improvements (we won’t judge if you pick the definition that gives you the highest value…). 

The lactate threshold test is one of the great tools for measuring fitness and helps to highlight weaknesses that need to be trained.  While a field test (e.g. 20-minute test) is easy enough to do, visiting the exercise science lab provides you with that little bit more physiological knowledge. And as any G.I. Joe fan will tell you, knowing is half the battle [to maximizing your performance gains].  Thanks for reading!