On the great philosophical question of why bad things (i.e. injuries) happen to good people (i.e. runners who obey the ten percent rule), the sages are divided. Some say it鈥檚 because we haven鈥檛 yet figured out precisely which form flaw, muscle imbalance, or training error triggers a given injury. Others say that the problem runs deeper鈥攖hat we need a comprehensive causal framework that links together training and life stresses, the resulting biomechanical loads applied to different parts of the body, and the ever-changing capacity of each joint and tissue to absorb those loads.
In in the International Journal of Sports Physical Therapy, running injury experts of the University of British Columbia and of the University of Montana advance that latter perspective. For example, they point out, simple rules about training load are doomed to failure because increasing the stress on a tissue like a tendon by just ten percent will cause it to fail . That鈥檚 one reason that the addition of speedwork so often triggers problems even if you鈥檙e not running any farther than usual. You can鈥檛 prevent an injury unless you understand the sequence of events that鈥檚 likely to cause it.
But drawing that web of causal arrows remains a tall order鈥攁 point illustrated nicely by , this one on Western States ultramarathoners. A team led by , a sports medicine doctor and researcher at Stanford University, studied 123 runners (83 men, 40 women) who ran the 100-mile race in 2018 and 2019, publishing the results in the Clinical Journal of Sports Medicine. Their goal: to explore the components of the female and athlete triads, including the risk of stress fractures and other bone stress injuries, in ultramarathoners.
In women, the athlete triad refers to 鈥渢he combination of low energy availability, menstrual irregularities, and low bone mineral density (BMD).鈥 In men, low levels of sex hormones such as testosterone substitute for menstrual irregularities. It鈥檚 a subset of the broader condition known as .
In theory, the causal arrow here is pretty straightforward. If you don鈥檛 eat enough, either overall or during the periods of the day when you need it most to support your training, you鈥檒l end up with lower levels of sex hormones. That鈥檚 what triggers the warning sign of irregular or absent periods. And over time, it can lead to lower bone mineral density, which in turn leaves you vulnerable to stress fractures, even at training loads you might previously have been able to handle. There鈥檚 good evidence for every step of this chain.
Based on a self-reported questionnaire (sample question: 鈥淎re you trying to change your body weight or body composition to improve your performance?鈥), lots of the Western States runners appeared to be at risk of disordered eating: 62.5 percent of the women and 44.5 percent of the men. Quite a few (16.7 and 30.1 percent, respectively) had low bone density, defined as a less than -1. Many (37.5 and 20.5 percent) had a history of stress fractures, which matches data from other studies of hardcore runners. Add in a few other variables like low body mass and irregular periods, and you can calculate a cumulative triad risk score, which identified 61.1 percent of women and 29.2 percent of men as being at moderate risk for bone stress injuries and 5.6 percent of each as high risk.
In a sense, this is a nice illustration of Napier and Willy鈥檚 point. If you zero in on a single risk factor like bone mineral density, you鈥檙e not going to get a very useful gauge of injury risk. Relatively few of the women had low BMD, but lots had stress fractures; for men, it was the opposite. Hormone levels, measured using 鈥檚 blood testing battery, were similarly ambiguous. In women, there did seem to be a link between low levels of testosterone and estradiol and low bone mineral density. The same pattern didn鈥檛 show up in men, though.
If you broaden the causal diagram, as with the cumulative triad risk score, you get a more meaningful assessment of injury risk. In , for example, every one-point increase in the cumulative risk score for male athletes (which doesn鈥檛 even include any direct assessment of hormones, since there鈥檚 no simple proxy like menstrual dysfunction for men) produced a 57 percent increase in the risk of a subsequent stress fracture. For women, it鈥檚 : a diagnosis of moderate risk doubles your chances of a stress fracture, and high risk quadruples it.
That鈥檚 still just one part of Napier and Willy鈥檚 grand plan, though. Napier co-authored (with Karrie Hamstra-Wright of the University of Illinois at Chicago and Kellie Huxel Bliven of A.T. Still University) that describes a 鈥渉olistic approach鈥 to bone stress injuries, suggesting that 鈥渁thletes have their own cumulative risk profile that influences their capacity to withstand specific training loads.鈥 Here they鈥檙e no longer talking only about triad risk factors: instead they鈥檙e summing up of non-modifiable (sex, race, age, genetics, alignment, prior injury鈥) and modifiable (strength, fatigue, flexibility, biomechanics, stress, recovery, nutrition鈥) intrinsic factors, as well as extrinsic factors like footwear, training surface, and training load.
There鈥檚 no equation for this hypothetical super-calculation of injury risk鈥攜et. In a sense, this is simply an attempt to mathematically describe what already goes on inside the head of a good clinician when he or she is assessing an athlete. The big question is whether the equation鈥攐r, more likely, a future machine-learning algorithm鈥攚ill ever be able to combine all those inputs and produce injury advice that鈥檚 meaningfully better than, say, the ten percent rule plus . Only time, and a lot of painstaking research, will tell.
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