Friday, May 28, 2021

Cadence lock: Why GPS watches have a hard time measuring heart rate during running

 Does your GPS watch report bizarre, dramatic spikes in heart rate in the middle of your run? I received a text message from a friend recently with this screenshot of his heart rate and elevation data from an easy run:

This was from a typical run on pretty mild to moderate hills. At first glance, you might think that running uphill triggered an abrupt increase in heart rate, but unless this coincided with an abrupt surge in speed, such a big spike in heart rate seems very strange.

Looking at this plot, it seems like one of two things is happening: either (a) my friend’s watch is seriously mistaken about his heart rate, or (b) my friend should see a cardiologist.  

Even though companies like Garmin or Apple or Fitbit keep their data processing algorithms pretty close to the chest,  my PhD research involves a lot of work with wearable technology, so I have a pretty solid understanding of what’s going on under the hood when a GPS watch is estimating things like running speed or heart rate.

I immediately noticed that the supposed “heart rate” being reported by the GPS watch in the screenshot above looked suspiciously similar to the range of values you’d see for cadence—around 165 to 185 steps per minute. So, I asked him to send me an overlay of his heart rate and his cadence (which is also measured by the watch). An, lo and behold—at halfway through the run, a near-perfect match! 

This phenomenon is something that’s been dubbed “cadence lock” in the running scene—sometimes, your watch seems to “lock onto” your cadence, confusing it with your heart rate. Why does this happen, and how can you fix it? To answer these questions, we’ll need a bit of background on wearable tech.

How do GPS watches measure your heart rate when you run?

Heart rate sensors on GPS watches are a relatively new innovation, but they rely on techniques that date to the mid-20th century. If you have one of these watches, you know they have a bright green LED on the wrist-facing side, like this: 

The watch above has three green LEDs, and one photosensor (the black square in the middle). This approach is called photoplethysmography, or PPG, and is the same technology used in pulse oximetry (which is used in hospital “finger clips” to track blood oxygenation.

Here’s the basic idea: the way the hemoglobin proteins in red blood cells absorb light is affected by whether or not they are currently carrying oxygen. Further, because blood vessels contract and expand along with the beating of your heart, the way certain wavelengths of light (such as green light!) are absorbed, or not, varies predictably as your heart beats.

Because each beat of your heart sends a wave of freshly oxygenated red blood cells rushing through your lungs and into your blood vessels, there is an ebb and flow to the amount of light absorbed by the tissue close to the surface of your wrist.

So, in theory, it should be possible to look at the rise and fall of the light absorption at the wrist to detect the heart rate. And indeed, most of the time this works just fine! The only problem is, in running, things get a bit messy.

Why is wrist-based heart rate so inaccurate during running?

Running causes problems for wrist-based optical heart rate monitors because it creates strong acceleration signals that interfere with the optical data coming into the watch. There’s a nice open-source dataset at PhysioNet that beautifully illustrates the problem. Check out the following plot: 

We’ve got three sources of data: a chest electrocardiogram (also known as an ECG) measuring the true contraction of the heart via electrical activity, an optical sensor at the wrist measuring the optical signal on the back of the wrist, and a wrist-worn accelerometer, which measures the motion of the wrist. The person in this plot is running at a pretty easy pace on a treadmill. A few things to notice:

  1. On the chest ECG (top panel), heart rate jumps out plain as day. This runner’s heart beats nine times in five seconds, meaning his or her heart rate is about 108 beats per minute during this five-second window.

  2. In the acceleration data at the wrist (middle panel), cadence jumps out pretty clearly as well. It’s a bit harder to see if (unlike me) you don’t look at this stuff all day long, but based on the repeating pattern of acceleration (which comes from the forward-backward swinging of the wrist and the up-down bouncing of the body), it’s pretty clear this runner takes about 11 steps in ten seconds, meaning his or her cadence is about 132 steps per minute.

  3. The optical data from the wrist (bottom panel) is pretty messy! 

You can probably start seeing where we’re going here. The problem that a GPS watch faces is trying to extract the heart rate signal from all the noise generated from your cadence. One way to get a handle on the difficulty of this problem is to take a look at the different frequencies present in each signal. That’s what the plot below is doing: 

For the engineers out there, this comes from a Fourier transform; if this means nothing to you, don’t worry about it. Notice the problem? The heart rate signal at the wrist is tiny compared to the noise from the motion of your wrist! Thus, it’s easy to see where “cadence lock” comes from: the watch locks onto the noise generated by the motion of your wrist, instead of the true signal generated by your heart.

As you might imagine, the problem of tracking your heart rate amid all this noise gets even nastier in two situations:

  1. When the wrist acceleration signal is very strong—which is what happens when you are running fast

  2. When your cadence gets close to your heart rate—which also happens when you are running fast

This, of course, is quite annoying for people who do heart rate-based training, since you’d normally be especially concerned with your heart rate during your workouts.

We might imagine some ways to attack this problem: use multiple optical sensors, try to somehow subtract the acceleration signal out of the optical signal, and so on. You can bet this is what companies like Apple, Garmin, and Fitbit try to do. But, given what we’ve seen above, it’s likely that even the best tricks won’t always work.

How to improve the accuracy of wrist heart rate measurements during running

First off, if knowing your heart rate is absolutely critical to your training, use a chest strap instead. That’s the best way to guarantee accurate readings. That being said, there are a few strategies you might use to improve the quality of wrist-based heart rate measurements.

For starters, strap your watch on tightly and make sure the sensor is clean. When the optical sensor is pressed against your skin, it will move around less when you run, and have a better chance at reading your heart rate accurately. 

Another trick you can try is holding your arm out in front of you for several seconds before checking your heart rate. The idea here is to reduce the acceleration on the wrist from the swinging motion of your arms. I suspect this will work less well than you’d think, because even when you don’t swing your arms when you run, they are still bouncing up and down quite a lot with respect to the ground (because your arm is attached to your torso).

An optical heart rate monitor that experiences less acceleration—for example, the kind that goes on your forearm or upper arm—will likely have an easier time detecting your true heart rate and not falling prey to cadence lock.

Still, as I mentioned above, even the upper arm experiences quite strong accelerations during fast running, so even an arm-based optical heart rate sensor is not likely to be a perfect solution for everyone.

Lastly, if your watch supports it, change the settings on your watch face to display your cadence on the same screen as your heart rate. If you check your heart rate and see it closely tracking your cadence, you’ll know that you’re experiencing cadence lock, and you should disregard what your watch says. 


There’s a lot more to say about whether heart rate training for runners is even a good idea in the first place (I for one am skeptical), and there’s also more to say about a range of other factors that can affect the accuracy of a wrist-worn heart rate monitor.

The bottom line is that you should keep your sensor clean, make sure your watch isn’t loose, and compare your recorded heart rate against your cadence. If they’re suddenly changing in lock-step, you know something is off, and you shouldn’t trust your wrist-based heart rate data.

Saturday, January 23, 2021

Blog update and podcast/media roundup

Well, it’s been a while! As you may have noticed, Running Writings hasn’t seen an update in quite a while. Perhaps for good reason—I’ve been working on my PhD in biomechanics at Indiana University's School of Public Health, which, as I’ve discovered, leaves very little time to spare.

Every time I think up an idea for a blog post (and I have had dozens!) I realize there’s one more dataset to analyze, one more paper to revise, one more grant to apply for, one more skill to learn. So, though RW hasn’t seen any updates, I haven’t dropped off the face of the earth, and I’ve been learning an incredible amount of new things about the science of running performance and running injuries. But all of that work keeps me very busy, and unfortunately I haven’t had much of a chance to share what I’ve been up to with the people who follow Running Writings. 

Plans for Running Writings

Rest assured, I still have big plans for bringing the science of running out into the real world, and Running Writings will continue to be a big part of that. One of the first steps forward is going to be overhauling the website itself—RW runs on Google Blogger, which is ancient and neglected. You may have noticed that I’ve had comments disabled for several months, as the site was being overrun by spam. Moving to a new hosting platform will help immensely on that front, and will also modernize the look and feel of the site. Look for a big overhaul sometime...“soon”? Early spring perhaps? There is some chance RW will be down temporarily, but I don't intend on deleting or moving any old content.

Once that’s done, I’m hoping to share some of the more useful tidbits of science that I’ve learned over the course of the last 3+ years as a PhD student studying this stuff every single day. They won’t necessarily be the long-format blog posts that I’ve written previously, but hopefully you’ll still find them useful.

Beyond these immediate updates, Modern Training and Physiology is somehow still selling at least one copy nearly every single day, which still blows me away. Somewhere collecting digital dust, I do have outlines for more long-format writing (and even more books) in the future. I’ll be revisiting those as I get closer to finishing my PhD. 

What am I researching these days anyways?

When I was applying to graduate school, I remember putting a clever line in my personal statement about “realizing I didn’t just want to write about running research - I wanted to become a running injury researcher myself.”  Well, I did it! I have a few research papers out, and am working on several more. Seeing something that you originally wrote in a coffee shop using Google Docs show up in a nicely formatted PDF in a real scientific journal is really something else. 

After a lot of voracious reading and some scatterbrained ideas presented at a few conferences, my research interests have settled on four broad topics: running injuries (big surprise there!), wearable technology, physical activity epidemiology, and advanced statistical methods for studying those first three topics. 

This fall, I passed my qualifying exam, which means I am All But Dissertation. So, just as soon as I can cook up a really brilliant PhD thesis, I’ll have my degree! No small matter, of course—especially considering the pandemic (any bets on how long until you can safely sit in a poorly-ventilated room five feet from someone running on a treadmill?). But, I do have some research ideas I’m pretty excited about; yes they involve several of the topics above, and no, unfortunately I can’t share any details yet! 

Podcasts and media appearances

One thing I can share is that the research I’ve done so far has led to some pretty cool opportunities already. In April, my advisor (Dr. Allison Gruber) and I appeared on the Mountain Land Running Podcast to talk about using wearable technology to monitor training loads

Pretty soon after, one of my studies got mentioned in a Runner’s World article about cross-training after injuries (original paper is here—in it, we used Fitbits to study what happens to a runner’s overall physical activity level when he or she gets hurt). Then, this winter, I got to chat about elite marathon training and the science of running injuries with Joe Sell on the Marathon Running Podcast. 

Joe’s podcast was especially fun, since we got to chat both about science and about elite training (especially Renato Canova’s marathon training methods)—since my research is so focused on injuries, I don’t get to do much with elite training these days. The previous episodes of the podcast, especially episode 6 with Nate Jenkins, are awesome, so it was incredibly fun to go on this podcast. 

Brought to you by readers like you

In an odd way, none of these things would have been possible without the readers of this blog. So, allow me to say “thank you!” to everyone who’s been reading RW over the last ten years! I wouldn’t have gotten my start in running injury research, and all of the great things that have come out of it, if this website hadn’t gotten any traction. Here’s to more running, more writing, and more Running Writings! 

Sunday, November 4, 2018

Can improving your 5k time increase your lifespan? A look at extreme aerobic fitness and longevity

During my PhD studies, I try to keep up with the broader scientific literature on the health effects of vigorous exercise (given that I do study running, after all). Just a few days ago, a fascinating new study caught my eye. It was published in JAMA Network Open by a team of researchers at the Cleveland Clinic in Ohio. The study explored the connection between aerobic fitness and longevity. In other words, do aerobically fit people live longer compared to out-of-shape people?

Background: Aerobic fitness and long-term health

For the general population, the answer to this question is a definitive yes, based on previous research. The real innovation of this study was that it specifically examined people with extremely high aerobic fitness. People in the top few percentiles of population-level aerobic fitness don’t get there by genetics alone. As any distance runner is well aware, becoming very fit requires a lot of intense and high-volume training. Some cardiologists have hypothesized that this kind of intense training is unhealthy. They point to research showing that biomarkers of heart damage increase after running a marathon, and other work showing a potential “U-shaped curve” for physical activity levels and cardiovascular disease risk.

The study details

The actual participants in this study were 122,000 men and women who underwent a standardized treadmill test of aerobic fitness. The treadmill test progressed as most do, starting at an easy walk and gradually increasing both the speed and the incline until the participant could not continue any longer. This final stage of the treadmill test was used to determine the person’s “peak METs,” or peak metabolic equivalent energy output.

The researchers tracked each study participant in the Social Security Death Index, which (for fraud prevention purposes) is a registry of all deaths of Americans who have social security numbers. By monitoring which patients showed up in the death index, and when, the researchers could determine who did and did not die during the course of the study.

The findings

As with previous research, the authors of this study found that people with better aerobic fitness, as measured by peak METs, were less likely to die, even after controlling for factors like age, sex, body mass, history of disease, smoking, and other potential confounding variables.

Most interestingly, the researchers found that there was no upper limit to the benefits of physical fitness. The healthiest group of people—in other words, those least likely to die from any cause—were those that the authors classified as having “extreme cardiorespiratory fitness.”

In the context of this study, the authors defined this as scoring in the top 2.3% of all performers for their age and sex. These extremely fit individuals were less likely to die compared to those who scored in the 75th-97.6th percentiles for aerobic fitness, to the tune of a 23% lower risk of death. This pales in comparison to the difference between the most and least fit people, though: Compared to the top 2.3%, those in the lowest 25% of aerobic fitness had five times the risk of death!

Can your 5k time predict your lifespan?

One thing I love doing is trying to translate research findings into something that’s more tangible and practical for people who aren’t clinical researchers. What does it really mean to have a “peak MET two standard deviations above the age and sex mean?

You may have seen the term “MET” before, at the gym on exercise equipment. It’s a standardized unit of energy expenditure, where 1.0 METs is the energy expenditure of sitting still in a chair.  METs are closely related to another unit of energy expenditure that you might be more familiar with, which is VO2.  One MET is equivalent to 3.5 ml of oxygen per kg of body mass. What this means is that if you know someone’s peak metabolic equivalent, you can easily figure out their VO2 max—all you have to do is multiply by 3.5.  So, it’s pretty easy to turn the cut-points for low, average, high, and elite aerobic fitness in this paper from MET thresholds into VO2 max thresholds.

Once we have VO2max, we’re in more familiar territory for runners. If you’ve read my book, Modern Training and Physiology, you know that your VO2 max is a very important predictor for your race performances. Now, coaches like me usually rail against VO2 max as the end-all-be-all of running performance, because VO2 max does not differentiate very well between someone whose 5k PR is 16:00 and someone whose 5k PR is 15:30. That being said, in this case, VO2 max is a pretty useful predictor of running performance, if we are talking about magnitudes like a 30:00 versus a 20:00 5k (or a 30:00 versus a DNF).

You might see where this is going. What I want to do is convert these fairly arcane public health measurements into something that’s understandable for the everyday person. What better way than a 5k time? If we convert the “elite” cutoffs in METs into VO2 max cutoffs, it’s easy to run these through a race time predictor and come up with a goal 5k time for “optimal longevity” (with some very serious caveats!). Let’s take a look at what those elite aerobic fitness cutoffs look like before we talk about the caveats.

After looking at these times, we can see the disconnect between what’s “elite” at the population level and what’s “elite” for a runner. A 21-year-old male who runs 18:25 for the 5k is certainly in good shape, but he’s still nearly four minutes shy of what he’d need to run to run at Division 3 Nationals in track—much less D2 or D1.  

In the context of health and longevity, this is a good thing: even “extreme cardiorespiratory fitness” is well within the reach of many (though certainly not all) people in the general population. One thing I should reiterate is that the longevity benefits of being in the “elite” fitness group are significant even after adjusting for things like smoking, body weight, and other things you might think could account for differences in fitness levels.

If these times seem out of reach for you, don't fret—the difference in survival between people of "high" and "elite" fitness was statistically significant, but very small compared to the differences between people who with "high" or "elite" fitness compared to those who were not fit. 

As the figure above shows, the biggest differences in longevity are clearly seen when comparing those whose fitness is poor to those who are at least above average, or better.

Not so fast: The caveats

Now, for some caveats. First, my VO2 max to 5k time conversion is a tiny bit hand-wavy. Once you get to high levels of running fitness, most of your improvements don’t come from better VO2 max; they come from improvements in running economy. That being said, I’m fairly confident that my converted times are in the right ballpark.

The more important caveats have to do with the nature of the causal relationship—or lack thereof—between high aerobic fitness and a long and healthy life. This study measured the fitness levels of healthy people, then followed them to see who died. Being extremely fit appeared to be a good predictor of avoiding death in the future. The key question is what biological mechanism is responsible for this association?

The easiest answer would be doing aerobic exercise. After all, there is a strong case to be made that very few, if any, 29-year-old women are going to be in sub-20 minute 5k shape without doing a good amount of aerobic exercise. But there are plenty of alternative mechanisms that could contribute too. What about genetic variation? Some people are born with a lot of what we call “talent,” the state of being highly aerobically fit even when they do not exercise. These same genetic traits which make someone a talented runner may also be responsible for different biological mechanisms that lead to a longer life: more flexible arteries, resistance to metabolic disease, etc.  Strong aerobic fitness might merely be an indicator of these traits, not the actual cause.

Now, the strongest circumstantial evidence still (in my opinion) supports the causal link between intense, high-volume training and a longer lifespan. At low, moderate, and moderately high doses, aerobic exercise is strongly protective against death. Moreover, alternative explanations, like the hypothetical genetic mechanisms I just laid out, would have to account for the fact that it is extremely rare, on the population level, for someone to reach these levels of “extreme cardiorespiratory fitness” with doing a solid amount of training.How many 45-year-old men are such fine genetic specimens that they can run a sub-20:00 5k fresh off the couch, compared to the number of 45-year-old men in sub-20 5k shape who train hard on a regular basis? 

Unanswered questions about fitness and lifespan

When we talk about the potential health effects of training too hard, we aren’t usually talking about a 40-year-old male who runs 19:25 in the 5k. Usually we are talking about ultramarathoners, sub-16 5k runners, Boston Marathon qualifiers, and other people who have a tendency to hammer out hundred-mile weeks and long multi-hour running sessions. If anyone is at risk of health problems from excessive exercise, it would be these extreme outliers. Because of the nature of distributions, you can be sure there are were a lot more 40-year-old men in 19:20 shape in this study than 40-year-old men in 16:20 shape, for example.

While these findings are promising, and suggest that more really is better when it comes to fitness and exercise, there’s still a need for research that focuses on those in the most extreme groups when it comes to exercise volume and intensity.  Fortunately, there is a longitudinal study happening right now on ultramarathoners that’s being run by Stanford University and UC Davis. It might take ten or 20 years before we get solid results from that study, though.

Finally, the question of causality still remains: If you take someone who does not have high aerobic fitness, and train them so they become aerobically fit, will they live longer? This question can only be definitively answered in a randomized controlled trial. Given the difficulty of following people for 20 or 30 years to observe mortality, testing this question directly might be impractical. Instead, it might be possible to correlate changes in aerobic fitness with changes in biological markers that we know are related to longevity—for example, if we hypothesize that lower arterial stiffness is one reason why extremely fit people live longer than those who are not fit, we could conduct a two or five-year clinical trial to see if an intense, high-volume aerobic training program would reduce arterial stiffness, compared to a lower-volume, lower-intensity aerobic training program.

As for me? I’m putting my chips on “better fitness = longer lifespan.” I’m turning 30 this year, so maybe I’ll hit the roads on my birthday, just to make sure I can still crank out a 19:05 5k.

Monday, June 25, 2018

How much slower did you run at the 2018 Boston Marathon because of the weather?

After this year’s incredibly windy and rainy Boston Marathon, I was curious to find out how much slower the race was. I’ve published analyses of courses and conditions in the past, such as with the infamously hot Grandma’s Marathon in 2016, and when I (correctly!) predicted that the new course for the Twin Cities Mile would be too slow to see a sub-four mile in 2015. However, in both of these cases, the environmental factors affecting race times were amenable to precise scientific study: the physiological effects of heat on running performance are well-known and can be examined in a controlled environment; ditto for the effects of elevation.  I’ve even got standardized formulas that I use when analyzing a road race course for my coaching clients that can accurately predict how fast or how slow each mile of a marathon will be, based on its elevation gain and drop.

With this year’s Boston Marathon, the situation was different. The reason for the slow performances was a combination of stiff, gusting wind, cold temperatures, and rain.  Even the elites kept warm running gear on for most or all of the race.  None of these things can be easily studied in a rigorous way, and even if they could, it’d be impossible to actually measure how “exposed” the athletes in the race were to these environmental factors as a function of time.

Instead, I chose to use a statistical approach.  The Boston Marathon is run on the same course every year, so previous years can be used as a control.  I chose to use the results from three years of fairly good weather at the Boston Marathon: 2016, 2014, and 2013.  The temperature at the finish line when the men’s winner crossed the line was between 64 and 61 degrees F for all three of these years, and the weather was amenable to good performance. In contrast, 2017 was too hot for optimal marathon performance, and 2015 was rainy and windy as well.  I sampled the finish time for the 10th, 20th, 50th, 100th, 150th, 200th, 250th, 500th, and 1000th place finishers in each of these years, for both men and women, and compared these to the finish times for the same places for men and women in 2018.

It looked like an exponential decay curve best-describes the trends: the slower you ran, the less-affected your time was by the weather.  The actual data points are in black in the figure above; the exponential decay function that I fitted to the data is shown in color.  These plots allow you to quickly figure out how much slower you ran at Boston this year, compared to an equivalent performance on the same course in ideal conditions.

What about the race winners? Or, Why does the model cut off below 2:30 and 3:00?

Put simply, the statistical model collapses for times below these thresholds.  There just aren’t enough people who run this fast to get a consistent sample of the expected finish for a 2:20 marathon at Boston for men, or a 2:50 for women.  Truly elite performances start to get affected by things like the depth of the field and the tactics of how the race played out, so I didn’t want to extrapolate the model beyond its capabilities.

Why were slower runners not affected as severely by the weather?

From a purely physics-based perspective, this makes sense: air resistance is proportional to the square of your velocity, so a faster runner is going to be affected to a much greater extent by a stiff headwind. Slower runners may have had the benefit of more “shielding” from runners around them, leading to less of an effective headwind. The temperature in Boston also climbed steadily throughout the day, so slower runners had the benefit of warmer temperatures later in the race.

Why were women more severely affected by the weather?

I think this has to do with the temperature.  Women, as a whole, tend to be much smaller than men of an equivalent marathon time.  Picture a few male three hour marathoners that you know, and compare them to a few female three hour marathoners.  The women tend to be vastly smaller in terms of body mass and height.  One consequence is that they have much more surface area (i.e. skin area) relative to their body mass.  This is great if it's hot out, because you can radiate away heat much more effectively.  But when it's cold, the same effect works against you: your body temperature drops far faster in cold conditions because you lose so much heat.  This same effect may also explain why faster runners were more severely affected: they tend to be smaller than slower runners.

Better late than never right? Hopefully you found this little statistical exercise useful, and best of luck at your next marathon!

Saturday, April 7, 2018

What causes metatarsal stress fracture in runners, and how can you prevent it? Research-backed solutions

 Do you have a sharp, aching pain on the top of your foot when you run? If so, it might be a metatarsal stress fracture. The metatarsals are perhaps the most elegant bones in your lower body.

The five long, slender bones extend from your midfoot to your toe joints, and despite their small size, must handle a tremendous amount of stress when you run. As a result, the metatarsal bones are a common location for stress fracture in runners.

If you have pain on the top of your foot or pain in your forefoot, you’ll want to read on. We’ll dig into the scientific research on who gets metatarsal stress fractures, why they happen, how to prevent them, and how you can return to running as quickly as possible.

The basics: Metatarsal anatomy and symptoms of stress fracture

You have five metatarsal bones in your foot. Each one corresponds to a toe, and they are numbered, by convention, starting from the inside. So your first metatarsal corresponds to your big toe, and your fifth metatarsal corresponds to your pinky toe.

When you run, the metatarsals act like a lever, helping you to catapult your body forward by using your forefoot as a base of support. They’re a critical part of allowing your body to use your calf muscles and Achilles tendon to store and generate power when you run. This is why the metatarsals are longer and thicker than their upper-body analogy, the metacarpals on the hand.

Sunday, March 25, 2018

A long overdue update on Running Writings!

Hello to all readers! You’ve no doubt noticed an embarrassing lack of content on Running Writings in the last year or so, so I’m here to provide a brief update.  I’ve been surprised and pleased by the fact that despite this, RunningWritings continues to be quite popular in search results, and I’m still contacted rather frequently by runners around the world with questions and insights on training and injury. Sometime in the last year or so, RunningWritings hit two million views! To top it off, Modern Training and Physiology—which is coming up on its fifth anniversary of publication!—is perennially popular on

You will be happy to know that RunningWritings is not retired, and I do still have projects in the works.  Last spring, I accepted an offer to pursue a PhD in biomechanics through Indiana University. As a result, I’ve been pretty busy over the last year! The good news is that I now have access to an incredible array of technology through the Indiana University Biomechanics Lab to study running mechanics and running injuries.  Since my program is a part of Indiana University’s School of Public Health, I’m also able to apply the tools of epidemiology to ask bigger questions about what affects your risk for running injuries and even how we might be able to prevent them.

Me, markered up in the IU Biomechanics Lab!
 I’ve also submitted a number of findings to scientific conferences, and soon, to scientific publications.  As these are accepted and published, I’ll be providing summaries on my blog about what these findings mean for regular runners. I’m doing my best to make enough time to share what I’ve learned here on my website. Finally, I’m currently working on another major injury article (this one will be on metatarsal stress fractures; my tibial stress fracture article is still one of the most popular I’ve ever written!).  I’m shooting to get this next article up by mid-April, so keep your eyes open!

After publishing another big injury article, the next major project is to revamp the design of Running Writings.  This website is over seven years old now, and the Blogger platform is showing its age: the layout does not look very good on mobile platforms, and the ads are not very relevant.  Further, many of you have no doubt noticed the spam comments on many of my articles, which I don’t have the time to remove. Sometime in the next few months, I’m aiming to re-launch RunningWritings with a website design that’s better than ever.  You might even see some new features alongside as I move to a platform with greater flexibility. I’m going to be moving away from the ad content you see now and towards a revenue model that’s more fitting with what the fans of this website (including myself) want to see.  But don’t worry—all the content will always be free. After the website overhaul, any articles you’ve bookmarked should still remain at the same URL as before.  Preserving article comments may be more difficult—I’ll do my best, but no promises.

Following the big website overall, I should have more time to dedicate to reviving regular content, like training analysis and the Brief Thoughts series.  Who knows, I might even bring back the YouTube channel!

Thanks in no small part to the readers of this blog, my running journey has taken me to some pretty incredible places—and right now, that’s the ability to study the causes of running injuries for my doctoral degree.  While Running Writings can’t be my top priority while I’m working on my PhD, I’m just as excited as you to put out some new content.

Wednesday, April 12, 2017

Low ferritin and iron deficiency anemia in distance runners: A scientific guide for athletes and coaches

Low iron can slow your performance on the track and on the roads

When I see a runner getting fatigued early on in workouts or struggling mightily in races for no good reason, there's one potential cause I always consider first: low iron.

Iron deficiency is a significantly underdiagnosed problem in distance runners. Low levels of hemoglobin in the blood, or low levels of the iron storage protein ferritin, can have a profoundly negative impact on your ability to have successful workouts and races.

Hemoglobin is the main building block for red blood cells, which carry oxygen from your lungs to your muscles. If you don't have enough hemoglobin, you can't make enough red blood cells, and as a result, your distance running performance will suffer. Furthermore, research and practical coaching experience suggests that low ferritin levels can cause poor performance, even when hemoglobin levels are normal.

We'll take a close look at the science behind low iron and distance running performance, then analyze the best ways to treat and prevent iron deficiency in runners.

The biology of iron and red blood cells

One red blood cell contains millions of hemoglobin proteins
One red blood cell contains millions of hemoglobin proteins
Hemoglobin is an essential part of your body's oxygen delivery system. It's a protein with four iron atoms at its core, and these iron atoms are what grant red blood cells their ability to transport oxygen (as well as give them their red color).

Because red blood cells must be replaced fairly frequently, your body keeps extra iron on-hand in a storage protein called ferritin. Your body's iron reserves are mostly locked up in ferritin, which can be called upon when needed to synthesize hemoglobin for new red blood cells, or other proteins and enzymes in your body that also require iron.  Low ferritin by itself is termed iron deficiency.

As you might guess, when ferritin levels in the body are inadequate, hemoglobin synthesis slows down and your body can't produce as many red blood cells. Abnormally low hemoglobin levels is a condition termed anemia, and when the cause is low iron, this is iron deficiency anemia.

The prevalence of iron deficiency and anemia in distance runners

According to research from the Centers for Disease Control and Prevention, between 9 and 11% of teenage and adult women are iron deficient, while only 1% of teenage and adult men are iron deficient.1 In this context, "iron deficient" means serum ferritin levels below the standard lab reference ranges for the general population (typically 12 ng/mL). As we'll soon see, these ranges need to be increased for endurance athletes.