by Dr. Reed Ferber, Ph.D. CAT(C)
One the biggest advancements in running injury research has been how to determine a “sub-group,” which is best defined as “a special group that is included within a more general group.” In this case, the general group consists of all recreational runners. For several years, our research has focused on ways to scientifically determine different sub-groups to inform injury prevention and treatment.
One of the most well researched sub-group topics is the difference between male and female runners. For example, it is widely accepted that female runners are two times more likely to experience patellofemoral pain (PFP or “runner’s knee”) and iliotibial (IT) band syndrome as compared to male runners. However, male runners are twice as likely to develop Achilles tendinopathy and plantar fasciitis. My group was the first to publish research on differences in running gait patterns between male and female recreational runners to help understand these different injury patterns. In turn, these advances have helped shape injury prevention and rehabilitation protocols.
Another sub-group can be defined based on the way a runner’s foot strikes the ground when it lands. Many studies have confirmed that 90 to 95% of runners demonstrate a rearfoot strike pattern (heel contacting the ground first) regardless of whether they are elite half marathoners or novice runners. However, about 5 to 10% of runners naturally run with a forefoot (toes contacting first) or a midfoot (entire foot at once) strike pattern. Research has also confirmed that when you run with a forefoot strike pattern, there is a significant shift in your biomechanical pattern as compared to a rearfoot strike pattern. Specifically, with a forefoot strike, there is increased loading at the foot and ankle joints, as compared to the knee, and a greater risk of Achilles tendinopathy and plantar fasciitis. So, if you have a forefoot strike and you were compared to a rearfoot striker, your gait pattern would be very different and specific considerations would be required to understand the root cause of your injury.
A new study from my group, in collaboration with researchers at the University of Jyväskylä in Finland, has revealed new insights into running sub-groups. We used a form of artificial intelligence, called unsupervised machine learning, to see if we could group 291 runners, average age of 39.5 years and an even split between men and women, into sub-groups based on their running mechanics. We hypothesized that the sub-groups would reflect the types of injuries the runners were experiencing. In other words, we thought that runners with knee injuries, such as PFP and IT band syndrome, would have similar mechanics and thus be grouped together. We also thought that the uninjured runners would mostly group together as well. We used a “hierarchical cluster analysis,” which is a way of dividing the runners into sub-groups based on shared running characteristics.
Overall, five sub-groups were identified; however, contrary to our initial hypothesis, runners with similar injuries (or no injury) did not cluster together. Instead, we found that different types of injuries, and healthy control subjects, were evenly distributed across the five sub-groups. From this, we drew two main conclusions. First, there is not a single protective gait pattern to avoid injury. Second, changes in an individual’s running pattern play a larger role in determining injury potential.
This means that there is no single “correct” way to run in order to prevent injuries. The way you run is simply the way you run—so embrace it! The most important factor to consider is whether or not you change the way you run – something our research has been pursuing for quite some time using wearable technology. Last issue, I introduced our “Citizen Scientist” program and how we’re collecting vast amounts of wearable sensor data to help advance and transform running research.
The more scientific data we collect, the more accurate and detailed we can be in answering critical questions and conducting research to help you. For future biomechanical “sub-typing” research studies, we’ll be focusing on those who run with the Garmin Running Dynamics Pod (RDP). If you’re a user of this device, please consider participating. To get involved, please visit the project website.