In triathlon training, consistency is king. But what if that consistency was a culprit in your latest injury? As all too many of us know, like IT band syndrome, shin splints, and stress fractures often present themselves at the worst times and have been the bane of many great race preparations.

Consistent, repetitive motion with improper running form often causes these injuries. But according to new research out of the University of Florida, you probably don’t even know your form could use a tune-up – and your shoes might be the reason why.

The study, published in the journal , consisted of 710 runners from various backgrounds. After asking each runner if they were a heel striker, non-heel striker (mid-foot or forefoot strike) or they “didn’t know,” the researchers examined each runner’s gait with a high-tech slow-mo motion capture system and analyzed their past running injuries.

The results were abundantly clear. Those runners who “didn’t know” their gait pattern had, by far, the greatest likelihood of sustaining a running-related injury.

The main contributing factor to runners not knowing their foot strike, or how their feet were hitting the ground, was the heel-to-toe drop of their training shoes. A higher drop, as well as higher shoe weight, led to less accurate body awareness and a higher likelihood of injury.

Additionally, those runners who changed their shoe type in the past six months were more likely to sustain a running-related injury.

So if shoes are part of the problem, is the solution simply changing them out? Yes and no. Let’s look at the takeaways and how can you apply them to reduce your risk of injury.

Shoe Choice Matters

As the study highlights, a shoes with high heel-to-toe drop and greater weight contribute to less awareness of foot strike. Opting for a shoe that has a lower drop and weight is an effective way to become more engaged (literally) with the ground and how your foot is interacting at the impact, loading, and takeoff stages of your run gait. A healthy foot will feel the ground, fully load, then utilize its “free” stored energy to push you forward.

A more minimalistic shoe will let the foot function as it should. Further, a large heel-to-toe drop alters how the force of impact is distributed throughout the body. As shown in  on the effect of shoe drop on joint stress, a higher-drop results in much larger stress at the patellofemoral (knee) joint. Opting for a lower-drop shoe allows the body to distribute stress as it was designed to do, reducing excessive loading to individual joints.

Opting for trainers with a mild drop (4-6mm) and not too much “clunk” could be an easy way to become more aware of how you’re running and stay injury-free.

If you’ve been running in a high heel-toe drop shoe and dealing with injury, it might be worth trying a different shoe. Just remember, as with any change, to progress gradually into your new shoes to allow the body time to adapt. Start with one to two runs per week, and slowly progress over four to five weeks until you can wear your new shoes full time.

Self-Awareness Matters More  

Yes, the type of shoes you wear can be a culprit in running-related injury, especially if they blunt the signals your body needs for good running form. This study clearly shows that enhanced body awareness while running, particularly when it comes to foot strike, leads to lowered injury risk.

Becoming more cognizant of how your body is moving and how your foot interacts with the ground is a free way to decrease your risk of injury. Yes, it’s nice to listen to music or zone out with a podcast during a long run. However, it’s likely worth it to zone in to the task at hand now and then to ensure you’re moving well.

One helpful tip is to run in front of a mirror on a treadmill so you can watch yourself run in real time. It’s easy to adopt poor running mechanics without realizing it, especially when fatigue sets in. Unlike the friendly spectator yelling, “Looking good!” at mile 23 of the marathon, the mirror doesn’t lie.

The best part about working on your running form is that it will help you develop movement patterns that make you stronger instead of more likely to get injured. More importantly, it might even help you actually look good at mile 23!

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There’s tons of evidence, from hundreds of studies with hundreds of thousands of participants, showing that exercise is an effective tool to combat depression and other mental health issues like anxiety. These studies find that it’s at least as good as drugs or therapy, and perhaps . It’s now recommended in official guidelines around the world as a or treatment. Still, there’s an important caveat to consider: is all this evidence of a connection between exercise and mental health any good?

That’s the question debated in in Medicine & Science in Sports & Exercise, based on a symposium held at the annual meeting of the American College of Sports Medicine. Four researchers, led by Patrick O’Connor of the University of Georgia, sift and weigh the various lines of evidence. Their conclusion is mixed: yes, there’s a relationship between exercise and mental health, but its real-world applicability isn’t as clear as you might think.

The Observational Evidence on Exercise and Mental Health

O’Connor and his colleagues assess three main types of evidence. The first is observational studies, which measure levels of physical activity and mental health in large groups of people to see if they’re connected, and in some cases follow up over many years to see how those relationships evolve. The headline result here is pretty clear: people who are more physically active are less likely to suffer from depression and anxiety now and in the future.

Observational studies also suggest, albeit more weakly, that there’s a dose-response relationship between exercise and mental health: more is better. is enough to produce an effect, but higher amounts produce a bigger effect. It’s an open question, though, whether doing too much can actually hurt your mental health. Some studies, for example, have found links between overtraining in endurance athletes and symptoms of depression.

The big problem with observational studies is the question of causation. Are active people less likely to become depressed, or is it that people who are depressed are less likely to be active? To answer that, we need a different type of study.

The Evidence from Randomized Trials

The second line of evidence is from randomized control trials, or RCTs: tell one group of people to exercise, tell another group not to, and see if they fare differently. Overall, the evidence from RCTs lines up with the observational evidence: prescribing exercise improves or prevents the occurrence of depression and anxiety.

For example, here’s a graph from a 2024 meta-analysis of 218 RCTs with a total of over 14,000 participants, :

Dots that are farther to the left indicate how much a treatment aided depression compared to a control group. Notice that walking or jogging ranks slightly above cognitive behavioral therapy and far above SSRI drugs. That’s an encouraging picture.

The evidence still isn’t bulletproof, though. One problem is that it’s very difficult to avoid placebo effects. Participants who are randomized to exercise know that they’re exercising, and likely also know that it’s supposed to make them feel better. Conversely, those who sign up for an exercise-and-depression study and are assigned to not exercise will expect to get nothing from it. These expectations matter, especially when you’re looking at a difficult-to-measure outcome like mental health.

Another challenge is the timeframe. Exercise studies are time-consuming and expensive to run, so they seldom last more than six months. But a third of major depressive episodes spontaneously resolve within six months with no treatment, which is in part why FDA guidelines suggest that such trials should last two years, to ensure that results are real and durable.

Why Context Matters When Studying Exercise and Mental Health

The third and final body of evidence that O’Connor and his colleagues dig into is the contextual details. Exercise itself seems to matter, they write, but “who we play with, whether we have fun, whether we are cheered or booed, and whether we leave the experience feeling proud and accepted, or shamed and rejected also matters.”

For example, most of the research focuses on “leisure time physical activity,” meaning sports and fitness. But there are other types of physical activity: occupational (at work), transportation (active commuting), and domestic (chores around the house). Is there a difference between lifting weights in the gym and lifting lumber on a construction site? Between a walk in the park and a walk down the aisle of a warehouse?

One view of exercise’s brain benefits is that it’s all about neurotransmitters: getting the heart pumping produces endorphins and oxytocin and various other mood-altering chemicals. If that’s the case, then manual labor should be as powerful as sports, and working out alone in a dark basement should be just as good as meeting friends for a run on a sunny day. Both intuition and research suggest that this isn’t the case.

Instead, some of exercise’s apparent mental-health benefits are clearly contextual. Doing something that creates social connection and provides a feeling of accomplishment is probably helpful even if your heart rate doesn’t budge above its resting level. And conversely, an exercise program that leaves you feeling worse about yourself—think of the clichĂ© of old-school phys ed classes—might not help your mental health regardless of how much it boosts your VO2 max.

This is where the big research gaps are, according to O’Connor and his colleagues. It’s pretty clear at this point that exercise isn’t just correlated with mental health; it can change it. But the best ways to deploy it in the real world remains understudied. For now, the best advice is probably to follow your instincts. Don’t stress about what type of exercise you’re doing, how hard to push, or how long to go. For improving mental health, these variables seem to have surprisingly weak effects. Instead, focus on the big levers: whether you’re enjoying it, and whether you’ll do it again tomorrow.

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When , one of the first things she talked about in her post-race speech was period tracking.

“For this race, a lot of things were actually coming together,” she said in her finish-line interview after the win. “So for example, I was in the first half of my menstrual cycle, and I always told myself, once this happens on a world championship race day, this is the chance. I feel so much stronger than in the second [half].”

It’s not the first time Philipp called out her menstrual cycle as a factor in her triathlon success. After setting an Ironman record of 8:18:20 at Hamburg in 2022, period tracking was a “game changer” in optimizing her training and nutrition.

Does this mean all triathletes with a period should track their menstrual cycles with the same attention to detail as power meter data, nutritional intake, and sleep? Could period tracking really help athletes crack the code for a PR?

If you spend any time on social media, you probably assume the answer is “yes.” Women’s health and performance – specifically, as it pertains to hormones, is a hot topic right now. There’s no shortage of influencers and self-proclaimed experts offering advice on how to use period tracking to optimize athletic performance, but actual credentialed experts proffering detailed advice and protocols? Those are harder to come by. That’s because the science of period tracking for athletic performance is in its infancy, says Dr. Kelly McNulty, sports physiology researcher at Northumbria University and founder of .

It’s great that we’ve had this boom in menstrual cycle tracking,” says McNulty. “Menstrual cycle tracking is more common now, and it’s advocated for, especially within elite environments, as something athletes should be doing. There’s a tendency that everyone’s a female health expert now, but on the flip side of that, the science isn’t quite there yet. We don’t want to be giving bad advice off low-quality research.”

That’s not to say period tracking is a bad idea – only that athletes should beware of one-size-fits-all advice on how women perform during certain phases of the cycle. Let’s take a deeper look at how to make period tracking work for you, whether you’re just starting out in triathlon or an Ironman World Champion.

What the science says about period tracking for athletes

As Triathlete has written about before, . The major contributing factor to this dearth of information is a belief that it’s simply “too complicated” to study women – their monthly menstrual cycle and resulting hormonal fluctuations skew otherwise straightforward results. The lack of research on this topic means data collected on males is extrapolated to females, and female athletes usually train based on recommendations made for male athletes.

McNulty was part of a 2021 research team that reviewed more than 5,000 studies across six popular sport and exercise journals, , with as few as 6% of studies focusing exclusively on females.  that even fewer studies looked at women by life stage – a particularly “invisible” cohort is women going through midlife, perimenopause, and menopause. Simply put, the science on women isn’t that great, and though it is an area of increasing interest for researchers, McNulty says it will still be five to 10 years before there’s a robust body of high-quality research.

Still, McNulty warns, “Everybody’s an expert now. And so everyone’s coming out saying that they will tailor your training plan to your menstrual cycle, and it sounds too good to be true in a lot of ways. We don’t want to come in and tell people, ‘No, this is a bad idea,’ but we do feel really strongly about making sure that people know that if you’re paying for someone to do that, and they’re claiming they’re an expert, that nobody’s really fully an expert on that, except for the people who are currently doing the research – and even they don’t have all the answers.”

There are, of course, some already-published studies that indicate hormone fluctuations aren’t a complication; they’re actually key to understanding and optimizing athletic performance in women. Hormones like estrogen and progesterone rise and fall throughout a woman’s month-long menstrual cycle, influencing everything from how she performs in training or racing to how she recovers. have found hormones may affect ligament laxity, suggesting injury risk may increase at various stages of the cycle. There is also evidence that when hormones fluctuate, so too does a woman’s body’s ability to maintain proper hydration levels, metabolize nutrients, and regulate body temperature – unique factors critical to female athletic performance.

Should you avoid period-tracking apps for athletes?

These studies, plus a growing demand for women-specific health advice, have led to an influx of period-tracking apps for athletes, which help women monitor where they are in their monthly cycles. Some apps even recommend what kind of training to do (or avoid) and when.

Though such apps can be enlightening for female athletes looking for insights on their individual physiology, that there currently isn’t enough research to make standard recommendations related to period tracking and sport performance.

That doesn’t mean that period tracking is a waste of time; only that experts aren’t at the point to confidently say “on X day of the cycle, women are best off doing Y workout and recovering with Z food.” McNulty says the information period-tracking apps give is often generic, and given the variety in menstrual cycle experiences among women, the information presented might not always be suited to the specific athlete. Some with putting highly-sensitive health information into such apps.

While women wait for the scientific community to endorse a substantial body of evidence, there are still things athletes can do, McNulty says: ”If you are a female athlete or a coach/practitioner supporting a female athlete, then I recommend that you dive into the research and learn all you can about the potential effects hormones can have on women’s physiology. But do this with a critical eye.”

McNulty also says women can develop their own “bespoke athlete guidelines,” where each athlete uses her own expertise of her own body to identify patterns in performance. “When you learn more about your own menstrual cycle – what symptoms you experience and how you perform, train, and recover on certain days – you can use your knowledge and understanding to determine what bits of the research might apply to you and which don’t. From there you can begin to tweak and adjust things to maximize or manage performance/training depending where you are in your cycle,” she says.

It’s in these individual experiences of the menstrual cycle – not the advice of an app – where the biggest insights lie. “Every woman is different, and the research is only the beginning from which we can build our individualized content from,” McNulty says. “But this only happens if we understand our bodies first.”

How to track your period as an athlete

Tracking the menstrual cycle can be as simple as circling a day on a paper calendar or marking an X in your smartphone on the first day of your menstrual flow, or period. The menstrual cycle is counted from the first day of one period up to the first day of your next period.

The average menstrual cycle is 28 days long, but each woman is different. Some women’s periods are so regular that they can predict the day and time that the next one will start. Other women experience menstrual cycles that vary in length. Medically, periods are considered “regular” if they usually come every 24 to 38 days.

That menstrual cycle is further divided into four phases:

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Earlier this month, the Journal of Applied Physiology published a paper with the title “Evidence on Sex Differences in Sports Performance.” Seems pretty straightforward, but of course it’s not. The gap between male and female athletes has become a major flashpoint in debates on whether transgender women and athletes with differences of sexual development, like the South African runner Caster Semenya, should be able to compete in women’s sports.

Three scientists—Michael Joyner of the Mayo Clinic, Sandra Hunter of the University of Michigan, and Jonathon Senefeld of the University of Illinois Urbana-Champaign—present a series of seven statements on the topic of sex differences in sport, along with the evidence to support them. Some of them seem obvious, others less so. Whatever your opinion on the debate, I think it’s worth considering each of these statements (which I’ll paraphrase) in turn, in order to understand what the current evidence says and where the gaps are. The full paper, including references, is free to read .

A note on terminology: the article deals with differences in sex rather than gender. Although it’s an oversimplification, I’ll use the terms male and female to refer to people with XY and XX chromosomes, respectively.

1. Males outperform females in events that depend on strength, speed, power, and endurance.

The evidence cited here is primarily performance data from sports like running, jumping, and weightlifting, where outcomes are easily measured. Among elite adults, the male-female gap is typically above 10 percent. The largest gaps are seen in sports that depend on explosive power, like high jump and long jump, where the gap approaches 20 percent. Field sports are harder to measure, but to the extent that they involve running and jumping and lifting, similar conclusions should apply.

Are these gaps biologically determined, or, , the result of social factors like the limited opportunities for women in sport? Elite performance data, on its own, can’t answer this question. But there’s no question that the gap exists, and is nearly universal. There may be some exceptions in activities like , where the determinants of performance are more complex. Overall, though, this statement should be uncontroversial.

2. This male-female gap shows up before puberty.

This seems like a significant claim, because it suggests that males may have a performance advantage that isn’t erased even if a transgender woman has undergone hormone therapy to lower testosterone levels. The evidence, once again, is primarily from performance data. Take a look at this graph of age-group track and field results for boys and girls between 7 and 18 years old:

Between the ages of 7 and 9, boys seem to be ahead, on average, by 4 to 5 percent. The gap narrows between the ages of 10 and 12, presumably as girls start puberty earlier than boys. After the age of 13, male puberty gets going and the gap widens rapidly.

So what gives 8-year-old boys an edge? As Joyner and his colleagues acknowledge, it’s once again hard to distinguish between biological and social factors. There is a possible hormonal explanation. We undergo a “minipuberty” during the first few months of life, with a temporary increase in sex hormones that is associated with a subsequent increase in muscle and decrease in fat accumulation in boys. But it’s also true that boys tend to spend more time running and jumping in unstructured play, and this may reflect gendered social expectations rather than sex differences.

Overall, the small gap in pre-puberty performance doesn’t seem like strong evidence of ineradicable differences between males and females. Instead, it’s the subsequent shape of that curve that, as we’ll see, turns out to be more significant.

3. The gap widens with puberty, along with changes in body structure and function.

In the graph above, male-female differences accelerate dramatically after the age of 13 and continue all the way to adulthood. Now it gets harder to attribute the changes to social factors, because there are a host of other changes that accompany puberty and are associated with sports performance: males see a greater increase in muscle, airway and lung size, heart size, oxygen-carrying capacity of the blood, and so on.

Perhaps the most obvious difference is height: by the age of 20, the average male is taller than 97 percent of women. Differences in lung size or hemoglobin levels are invisible to us; differences in muscle mass could conceivably be because boys are encouraged to work out more. But height? We see it all around us, and accept that it’s driven by biological sex differences.

4. The main driver of the male-female performance gap in adults is the surge in testosterone during male puberty.

Here’s when things get more contested. Where, you might ask, is the randomized controlled trial proving that males who go through puberty without testosterone are worse athletes, or that females who go through puberty with male levels of testosterone are better athletes? Such studies haven’t been done, for obvious practical and ethical reasons.

Joyner and his colleagues argue that we can instead piece together the evidence from studies showing links between testosterone levels and increased physical performance during puberty; the various studies in humans and animals showing testosterone’s effects on muscle, bone, and blood parameters; doping studies where volunteers took testosterone; and strong circumstantial hints like the graph above showing the widening performance gap during puberty. The evidence here isn’t perfect, but as a whole it’s convincing.

5. Body changes during female puberty can have negative effects on sports performance.

This is an angle I hadn’t thought much about. The discussion usually focuses on the advantages conferred on males by testosterone, but there are a distinct set of changes that females experience during puberty. For example, they accumulate more body fat; their growth plates fuse so they stop growing taller; they develop breasts, which can alter balance and movement patterns; their hips widen, which may increase injury risk; they experience hormonal fluctuations associated with the menstrual cycle that may (or may not!) affect performance; they may eventually miss training time during pregnancy and face increased injury risk when returning to training after childbirth.

There’s no doubt that all these changes occur, and that they have the potential to influence performance. Whether they collectively make a significant contribution to the gap between male and female athletic performance is less clear. It’s worth considering, but I’d classify it as an open question for now.

6. Suppressing male testosterone levels after puberty only partly eliminates the male-female performance gap.

There’s a smattering of case studies and comparison studies to support this statement. A 2023 U.S. Air Force in Military Medicine, for example, tracked fitness test scores for nearly 400 transgender servicemembers for up to four years after they began hormone therapy. For transgender women, performance on some tests, like the 1.5-mile run, ended up corresponding to average female times by the fourth year of hormone therapy. But for other tests like push-ups, there were still differences.

Here’s how push-up scores evolved in transgender women over the course of four years of hormone therapy. The red band shows the range of male scores within one standard deviation of average; the blue band shows the corresponding women’s range. Scores are still higher than average even after four years.

One reason for the retained advantage is that some of the changes that occur during puberty are irreversible. Those who go through male puberty will, on average, be taller and have bigger lungs. They’ll lose muscle mass during hormone therapy, but still retain more than the female average. There’s also evidence for “muscle memory,” a phenomenon that makes it easier to build muscle if you’ve previously had it.

It’s worth noting that the significance of retained advantages will vary from sport to sport. Greater height and muscle mass matter a lot in sports like basketball and rugby; they may matter less in, say, marathon swimming.

7. Adding testosterone improves female performance, but doesn’t eliminate the male-female gap.

This claim is the mirror image of the previous one: transgender men improve various facets of sports performance after beginning hormone therapy, but they don’t gain the full ten percent. This supports the idea that testosterone matters for performance, but that timing also matters: it plays its most significant role during puberty.

These are the seven claims that Joyner and his co-authors make. Some are stronger than others. But even if you take them all at face value, they don’t tell you what the rules for transgender or intersex athletes should be. That involves a difficult balance between fairness and inclusion. Maybe the male-female differences discussed here are the most important consideration; maybe they’re outweighed by other factors. I don’t think there are any easy answers here, but any compromises we reach need to acknowledge that these differences exist and are persistent.

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Researchers in Germany recently published one of those studies that, now and then, make me question my core beliefs. I’m a supplement skeptic, but I try not to let that identity prevent me from assimilating new data. And if there’s one supplement whose possible benefits I’ve been on the fence about in recent years, it’s vitamin D.

The new study, , is part of a major initiative to improve the performance of German elite athletes. A research team led by Sebastian Hacker of Justus Liebig University in Giessen studied 474 athletes on German national teams in a range of sports including hockey, table tennis, and three-on-three basketball. They tested vitamin D levels and measured (among other outcomes) handgrip strength.

Here’s the money shot:

This graph shows handgrip strength as a function of 25(OH)D levels, which is how vitamin D status is assessed in the blood.  The two dashed lines indicate the thresholds between vitamin D deficiency (below 20 ng/mL), insufficiency (between 20 and 30 ng/mL), and sufficiency (above 30 ng/mL). There have been long debates on where these thresholds should be set, but that’s the current thinking. Note that you’ll sometimes see 25(OH)D levels expressed in nmol/L; to get to those units, multiply the values above by 2.5.

The key point: there’s a clear slope to the line. Higher levels of vitamin D are associated with stronger grip strength, which in turn has been associated with health, longevity, and (less clearly) athletic performance. For every 1 ng/mL increase in 25(OH)D, handgrip strength increases by 0.01 N/kg, which means that going from 20 to 30 ng/mL should boost your strength by about three percent.

The Case for Vitamin D Supplements as a Performance Aid

Vitamin D plays roles in a whole bunch of body systems, including bone health, immune function, and—perhaps most notably for athletes—muscle performance. If you’re truly deficient in vitamin D, there’s no doubt you should get your levels up. But the evidence in the “merely insufficient” range is less clear, even in this data. If you took all the values below 20 mg/mL out of the analysis, would there still be a relationship between vitamin and handgrip strength? It’s not clear.

This isn’t the first time researchers have shown a relationship between vitamin D and strength. In fact, pooled data from 28 studies with 5,700 participants and concluded that there’s a positive relationship between vitamin D levels and quadriceps strength. At least, that’s the headline result—but when you look closer, it’s less convincing. The positive relationship was for quad strength when contracting the muscle at a specific speed of 180 degrees per second. But there was no relationship at a slower speed of 60 degrees per second. Worse still, there was a negative correlation for maximal contractions against an immoveable force: higher vitamin D levels were associated with smaller max force.

In other words, we shouldn’t be too quick to assume the new German data is definitive. Instead, it’s another data point in an ongoing debate. Another review, , finds “mixed results” in studies on the relationship between vitamin D levels and muscle mass and strength.

Causation or Correlation?

Even if we eventually conclude that there is a positive relationship between vitamin D levels and strength, it doesn’t necessarily follow that we should all start popping vitamin D pills. First of all, there’s the possibility of reverse causation. People who are strong and healthy may choose to spend more time exercising outdoors, which in turn may produce higher vitamin D levels. That’s actually one of the strengths of the new German study: since all the subjects were elite athletes, we can assume that they have similar levels of general fitness and physical activity.

There may also be confounding factors. Back in 2019, șÚÁÏłÔčÏÍű contributing editor Rowan Jacobsen wrote a surprising article in which he argued that the benefits of sunlight extend beyond merely raising vitamin D levels, most notably in triggering the release of nitric oxide from your skin into your bloodstream. If that’s the case, then taking vitamin D supplements won’t necessarily fix whatever problems are associated with lack of sunshine.

What we really want are intervention studies, where we give extra vitamin D to people and see if they get stronger. And we don’t want subjects who already have sufficient levels of vitamin D, because they stand to benefit less; instead we want people with insufficient levels. That’s what , this one from Estonia, did.

The Estonian researchers took 28 volunteers with “insufficient” 25(OH)D levels in the low 20s mg/mL. Half of them got a placebo, and the other half took 8,000 IU per day of vitamin D, which eventually got their 25(OH)D levels up to a healthy 57 ng/mL. Both groups did 12 weeks of resistance training, but there were no discernible differences in their results, which were published in the journal Nutrients. Here are the gains in one-rep maximum for various exercises for the two groups:

In fact, the further you dig into the literature, the less convincing the data looks for vitamin D as an athletic supplement. For example, there was that found no significant benefit of vitamin D supplementation on muscle strength but a trend in the right direction. But even that weak finding was tainted by “key errors in the analytical approach,” according to : the true effect is close to zero.

Of course, vitamin D’s merits as an athletic supplement are distinct from its potential for more general health purposes. Might it be that taking vitamin D supplements helps prevent cancer, heart disease, or type 2 diabetes; increases bone density; or reduces your risk of falls? No, no, no, no, and no, according to . More than 60 Mendelian randomization studies, which use genetic data to divide people into pseudo-randomized groups with high or low vitamin D levels, have generally found no difference in health outcomes.

Put it all together and the overall case for taking vitamin D supplements doesn’t look very compelling to me—assuming, that is, that you don’t have a genuine deficiency. Defining that threshold is the tricky part. Is it below 20 ng/mL, which health authorities consider deficient? Is it below 30 ng/mL which they label insufficient? Is it somewhere higher or lower or in between? I’m not sure, so for now I’ll hedge my bets: despite all my skepticism, I’m going to arrange to get my levels tested at my next doctor’s appointment.

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One of the funny little details in Eliud Kipchoge’s attempts to run a sub-two-hour-marathon was the electric pace cars. In Nike’s Breaking2 race in 2017, they used a Tesla. In the INEOS 1:59 Challenge, where Kipchoge actually broke the barrier, it was an Audi e-tron equipped with a specially built cruise control that was accurate to within less than a meter over the entire marathon distance. “There will be no emissions out of the back to upset any of the runners,” one of the INEOS engineers .

Was this just window-dressing, like the strips of aerodynamic tape that the Breaking2 runners pasted to their calves? Or does a bit of exhaust in the air actually slow you down? over the years have attempted to answer this question, but the results have been unclear, in part because it’s difficult to get accurate readings of air quality on the racecourse itself. But a new study from a research team at Brown University, led by Elvira Fleury and Joseph Braun, offers a more definitive answer: it matters.

The Problem with Particulate Matter

Fleury and Braun used a “spatiotemporal machine learning model” to produce detailed hyperlocal estimates of exactly how much fine particulate matter was in the air at each mile marker along the courses of nine major marathons in the U.S. for each year between 2003 and 2019. The model integrates readings from nearby air sensors with satellite data, weather, topography, and other inputs.

Fine particulate matter—also known as PM2.5 or, more familiarly, soot—refers to particles that are less than 2.5 microns in diameter, and is produced by internal combustion engines, forest fires, and other sources. It’s easy to inhale, and can cross from your lungs into your bloodstream, triggering inflammation and oxidative damage that raises the risk of heart disease, diabetes, and other conditions. When you’re running, you breathe more air than usual, and suck it in through your mouth, which bypasses the nasal filtration (i.e. hairs) that would otherwise catch some of the particles. This triggers a variety of problems, including constricting the blood vessels that supply your muscles with oxygen—bad news for a marathoner.

The machine learning model showed that PM2.5 levels varied widely from place to place and year to year. Levels in Boston and Chicago were as high as 20 micrograms per cubic meter in some years, and as low as 2 or 3 micrograms per cubic meter in others. Other courses like New York, Houston, and Los Angeles were in a similar range. The study, , combined this pollution data with 2.5 million finishing times, adjusting for other factors like heat and humidity.

How Does Air Pollution Affect Marathoners?

Before digging into the results, it’s worth pausing to consider what we’d expect to see. On a superficial level, there are two big trends to consider. The obvious one is that slower runners are out there longer, so we’d expect the total amount of time lost to increase with finishing time. The other one is that faster runners tend to breathe more heavily, so they suck in more particles per breath and lodge them more deeply in their respiratory systems—so we might, conversely, expect the effects to decrease with finishing time.

The most important question, though, is whether there are any effects at all. Overall, male marathoners at a given percentile finishing position were 32 seconds slower for each increase of 1 microgram per cubic meter in PM2.5 levels; female marathoners were 25 seconds slower. That may sound like a modest effect, but it seemingly suggests that average Chicago Marathon times in a low-pollution year like 2019 (~3 micrograms per cubic meter), might be around eight minutes faster than in a high-pollution year like 2011 (~20 micrograms per cubic meter). Even if that turns out to be an overestimate—I’ve taken the most extreme comparison I could find—it suggests that we’re talking about minutes rather than milliseconds.

Here’s how the effect varied depending on finishing position. The graphs below show finishing percentile on the horizontal axis, with first place on the left and last place on the right. The change in finishing time per microgram per cubic meter of PM2.5 is on the vertical axis. Graph A shows male finishers, graph B shows female finishers.

In both cases, the pattern is roughly the same. The fastest finishers have a relatively small effect; the median (which for most of the races tends to be between 4:00 and 5:00) and slightly-faster-than-median finishers have the biggest effect; and the slowest finishers have a smaller effect.

What explains this curve? It’s hard to know. It could be competition between the two factors I mentioned above: shorter exposure time protects the faster finishers, less heavy breathing protects the slower finishers, but runners in the middle get hammered. There are also lots of other possibilities. Maybe more well-trained runners are less affected by breathing discomfort. Maybe the anti-inflammatory effects of high aerobic fitness confer some protection from the negative effects of pollution. Maybe you actually adapt to polluted air if you train in it enough. There are glimmers of evidence for all these effects, but they remain speculative.

What These Air Pollution Findings Mean in Practice

The idea that air pollution hurts athletic performance certainly isn’t new—recall when U.S. athletes wore breathing masks to protect their lungs with they arrived in Beijing for the 2008 Olympics. What’s different here is that the effects are showing up even at very modest levels of air pollution. The for 24-hour exposure to PM2.5 is 35 micrograms per cubic meter, well above the levels seen in any of the races. The full-year standard was lowered last year from 12 to 9 micrograms per cubic meter. Of all the race-years analyzed, 61 percent of them were below this more rigid 9 micrograms per cubic meter standard—and yet these pollution levels still impacted race times.

One takeaway, then, is that if you’re going for a big marathon PR and you have a private pace car guiding you, it might be worth going electric. More generally, add air quality to the long list of factors to consider in choosing a race or evaluating a performance after the fact. If you set your PR at Boston in 2004, or Chicago in 2011, or Philadelphia pretty much any year before 2015, your coulda-shoulda-woulda time just got a few minutes faster.

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In the summer of 1991, Mical Garcia was 19 years old, taking classes at a cosmetology school in the farm town of Manteca, California, when she got an alarming call from her stepdad in Las Vegas. Her mother had run off. He came home from work to find her possessions gone, and a note explaining that she’d been leading a double life and did not want to be contacted.

Mical, who helps people pronounce her name by saying “like ‘me call you,’” was surprised but not overly concerned at the time. Her mother, Linda Sue Anderson, was carefree and a bit wild. “We’d play that song ‘Delta Dawn’ really loud, sing at the top of our lungs even though we didn’t have great voices, and dance,” Mical told me recently. Her mom once took her to see the Vegas crooner Engelbert Humperdinck in concert. Linda was beautiful, always had her long blond hair done, her nails and makeup just so. “She was never a Betty Crocker stay-at-home mom.”

The flip side was mood swings, which Mical, who is now a nurse, thinks could have been diagnosed as bipolar disorder. Linda would lock herself in her room, leaving Mical to babysit her sister, Dulcenea, and her brother, Ethan, who everyone called Petey. “I was in first or second grade, and I was cooking for them. My dad was traveling. She wouldn’t open the door.” Other times Linda, who worked as a travel agent, would disappear for days.

The family moved around a lot. When their parents divorced, they were living near Lake Tahoe. Their father won full custody and took the family to Manteca. Linda remarried and settled in Nevada. Her new husband was a pit boss at Caesars Palace with a degree from Stanford University. “He worshipped the ground she walked on,” Mical said. “I never heard they were having problems.”

So when Linda ran off, the Garcia children figured she’d come back eventually—just like she always had.

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One of the big debates in endurance sports these days is about “training intensity distribution,” which is a fancy term for how much of your training time you spend going easy, medium, or hard. The dominant paradigm is the polarized distribution, which calls for a lot of easy running, a little bit of hard running, and not much in the middle. But there are various other viewpoints, including the currently fashionable Norwegian training, which puts a heavy emphasis on medium efforts.

One way of exploring which training distribution is best is to look at the training diaries of the best endurance athletes in the world. That’s how the concept of polarized training was born, and it’s why Norwegian training is rising in popularity. Of course, this isn’t as reliable as a randomized trial. Maybe most elite athletes train in a certain way because it’s popular, not because it’s objectively better than the alternatives. And even if we figure out the best way for elites to train, it’s not clear that those insights will apply to the rest of us.

Another option to assess training intensity is to look at how the unwashed masses train: to sift through reams of data looking for the patterns and variables that predict the best race performances. That’s the approach taken in , from a group of researchers led by Daniel Muniz-Pumares of the University of Hertfordshire and Barry Smyth of University College Dublin. They analyzed 16 weeks of training data leading up to a marathon for 120,000 runners who recorded their training in Strava.

To Run Faster, Run More

Before delving into the nitty-gritty of training intensity distributions, we should start with the elephant in the training room. By far the best predictor of marathon time was how many miles a runner racked up. The researchers divided their sample into half-hour finishing groups: the fastest group was the sub-2:30 marathoners, the slowest group was those between 6:00 and 6:30.

On average, the runners accumulated 28 miles per week over the 16 weeks prior to their goal race. But there were big differences. Sub-2:30 runners ran 67 miles per week, about three times as much as those running slower than 4:30 and 60 percent more than even the sub-3:00 runners. Here’s the weekly mileage (in kilometers, on the vertical axis) as a function of marathon finishing time (in minutes, on the horizontal axis):

This is the men’s data; the women’s data show essentially the same pattern. The four different lines show the average mileage during four different four-week blocks before the race. There are some slight differences—mileage is highest five to eight weeks before the race, for example—but the overall pattern is the same throughout: faster runners run more.

What the Training Intensity Distribution Reveals

You could be forgiven for thinking that this is painfully obvious. But what’s interesting is how the faster runners ran more. They didn’t just scale up their training proportionally compared to the slower runners. Instead, the difference was almost exclusively in how much easy running they did.

You can divide the accumulated training into three zones loosely corresponding to easy, threshold, and interval or race pace. (I won’t belabor the details of how they crunched the training data or defined the zone boundaries, but it’s based on calculating each runner’s critical speed using the approach I described in this article.)

When you break out the different training zones, you find that runners of all levels, from sub-2:30 all the way through 6:30 marathoners, did virtually identical amounts of hard zone 3 training. They also did very similar amounts of zone 2 threshold training. There’s a slight trend toward the faster runners doing a bit more, but it’s barely noticeable. All the variation—remember, there’s a threefold difference in total training volume—is packed into easy zone 1 running.

The graph below is a little busy (it once again breaks out the results into four-week blocks, even though the trends in each block are similar). The key point is that the red lines (zone 3) are flat, meaning that all the different pace groups accumulated similar amounts of hard running time. The orange lines (zone 2) are nearly flat. But the green lines curve sharply upward on the left side of the graph, showing that the faster runners do more easy running.

So It’s Polarized Training for the Win?

That depends on what you mean by “polarized.” There’s a fairly convoluted debate (which I summed up here) on the meaning of the term, but there are two key elements. One is the idea that most of your running should be easy. That’s often summed up (as in the title of ) as 80-20 running: around 80 percent of your running should be easy, with the other 20 percent medium or hard. Muniz-Pumares’s new results support this view.

The second element is the idea that you should avoid medium intensities, since they’re too slow to give you the benefits of interval training but too hard to recover from if you’re trying to run big miles. That is where the name “polarized” originally comes from, since most of your training is supposed to cluster at the extremes of easy or hard. But the new data doesn’t back this claim up: very few of the runners, whether fast or slow, were doing truly polarized training.

What the runners were doing instead is called pyramidal training. Classic polarized training might involve an 80:5:15 breakdown of easy, medium, and hard. Pyramidal training, instead, might be 80:15:5. Instead of avoiding the middle zone, you do a moderate amount. In practice, though, the distinction between polarized and pyramidal is hazier than it seems. Previous research has found that the exact same training plan might look either polarized or pyramidal depending on whether you calculate the intensity distribution using running speed, heart rate, or even the intended effort.

The bottom line, from my perspective, is that it’s not worth getting too wound up about the specific nomenclature. This data supports the idea of doing lots of easy running and modest amounts of medium or hard running. It doesn’t support the idea of avoiding the medium zone. Whether you call that polarized or pyramidal is up to you.

What’s Lost in Translation

As I noted at the top, this isn’t a randomized trial. We know that faster runners did more easy running than slower runners. We don’t know if doing more easy running would have turned the slower runners into faster runners. But even if it did, that assumes that the slower runners have the time or desire to run more—and that’s by no means a safe bet.

The fundamental assumption for elites is that their training is primarily limited by what their bodies can handle. Polarized (or pyramidal) training is supposed to be effective because it’s an optimal way of racking up the greatest possible combination of training volume and intensity. To max out what your body can handle in a given week, aim for that 80-20 split.

Meanwhile, out in the real world, the key question isn’t how much my body can handle. It’s how much training I can squeeze in before work or between picking up the kids and making dinner or whatever. The 3:30 marathoners are putting in about four hours of training per week. It’s not hard to believe that adding an extra hour or two of easy running on top of what they’re already doing would make them faster.

The trickier—but also more relevant—question is how to make them faster on four hours of training per week. Switching to an 80-20 split would actually mean doing less total mileage, because they would be replacing a big chunk of their medium or hard running with easy running. Sure, they would recover more quickly from each training session. But would they really end up going faster?

This is an open question, and I don’t think there’s any firm answer at this point. But my takeaway from all this is that we should think carefully about what constraints we’re imposing or accepting on our training. If time is really the issue, then spending more of that precious time running hard might make sense for you. But if “I don’t have time” is just another way of saying “I don’t want to,” or if you’ve been held back by the fatigue and injuries that often accompany hard training, then it’s worth considering doing more easy running. It’s the easiest and least risky type of training—and in this analysis, at least, it’s the one weird trick that distinguishes faster marathoners from slower ones.

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Thanks to a wonky hamstring and some bad oysters, I’m currently coming back from a training hiatus of nearly a month. It’s an unfamiliar and somewhat unsettling feeling. So I have a lot of sympathy for Romuald Lepers, a French physiologist and dedicated triathlete who, in the name of science, agreed to take 12 weeks completely off training in 2022.

With the help of his colleagues, Lepers underwent a whole bunch of tests immediately after competing in the Swimrun World Championships in Sweden that fall. After 12 weeks of sloth, he repeated the tests. Then he resumed training and, 12 weeks later, repeated them a third time. The data is presented in a pair of papers in and , offering a detailed look at exactly what happens when you lose then regain fitness, and raising a surprising and tantalizing possibility: maybe a long training break is actually good for you.

Two Theories of Aging

runs a lab at the University of Bourgogne in Dijon, and is one of the world experts on masters athletes, which typically refers to athletes over the age of 40. He’s also an accomplished triathlete. In his younger days, he placed in the top 150 at the Ironman World Championship in Kona. At the time of the study, he was 53, training 10 to 12 hours per week, and still consistently placing near the front of his age category in Ironman 70.3 races.

Over the course of more than three decades, he trained very consistently, never missing more than two weeks of training at a time. So he decided to run an experiment on himself to fill a gap in the literature. There have been various “detraining” studies over the years that measure the loss of fitness when you stop training. A classic 1984 paper, for example, saw a 16 percent reduction in VO2 max after 12 weeks; and this analysis estimated how much a training break of a week or more will affect your marathon time. But there’s very little data on older athletes.

There’s an important debate about fitness loss in older people. We know that it happens, and we know roughly how quickly it happens—on average, at least. Starting in your 30s, you’ll typically lose 0.5 to 1 percent of your VO2 max every year; you’ll also lose muscle mass at a similar rate. One view is that this happens gradually and inexorably. The other view, sometimes referred to as “,” is that we decline at a much slower rate, but every once in a while we have mini-catastrophes—a prolonged bout of flu, a broken hip, a period of intense work or family stress during which we abandon all exercise habits—that lead to a sharp drop. Even if we resume normal training after one of these blips, we never quite make it back to our previous level, so these interruptions contribute disproportionately to our advancing decrepitude.

When you’re 20, you can take 12 weeks off and then, with a bunch of hard work, get right back to where you started. Lepers’s case study offers a test of whether the same is true in your 50s, or whether the body’s adaptive potential is so blunted that some of the losses become permanent.

What Happened After a 12-Week Training Break

The Frontiers in Physiology paper focuses on Leper’s changing fitness. Most notably, his VO2 max, as measured in a treadmill running test, dropped by 10.9 percent. In a similar test on an exercise bike, it dropped by 9.1 percent. That’s a big drop, equivalent to about 15 years of normal aging, but it’s on the low end compared to previous detraining studies. The penalty for time off in your 50s doesn’t seem to be any worse than in your 20s.

When he started training again, there was a surprise. After 12 weeks, his VO2 max didn’t just recover; it was better than when he started. In the running test, it was 4 percent higher than baseline; in the cycling test, it was 6 percent higher. There’s some inherent variability in VO2 max testing (and in all physiological testing, for that matter), but the fact that the same pattern showed up in the running and cycling tests suggests that the effect is real.

For a guy who’s been training and competing at a high level almost continuously for three decades, that’s an unexpected result. There are a couple of possible explanations. One is that his body composition changed. VO2 max is expressed relative to your body weight, so losing weight can create the illusion that you got fitter without changing your oxygen-processing abilities.

That’s not what happened here, though. His body did change: he initially gained 5.5 pounds of fat and lost 4.6 pounds of muscle. Then, after retraining, he lost 9.0 pounds of fat and regained 2.4 pounds of muscle. That meant his body fat went from 10.1 percent to 13.3 percent to 8.4 percent, with a net loss of 5.7 pounds by the end of the experiment. This explains some of the change in VO2 max, but not all of it: his overall oxygen-processing capacity still improved, independent of his weight.

The other possibility is that something changed within his muscles to make them more responsive to training. The second paper, in JCSM Communications, explores this possibility. Lepers underwent muscle biopsies at each stage of the experiment to measure the metabolic properties of his muscles. Detraining ramped up fast-twitch muscle activity and ramped down markers of mitochondrial function and aerobic capacity. Retraining mostly reversed the changes, and in some cases resulted in better-than-baseline muscle properties.

The details of what’s going on inside the muscles are fairly complex, and Lepers cautions that we shouldn’t read too much into a single case report. (That goes for all the findings; we have no idea if he’s just a freak.) But it’s interesting that the two sets of results seem to line up: the microscopic properties of his muscle and macroscopic fitness measures like VO2 max both declined with detraining then bounced back to be better than before with retraining.

So Should We All Take a 12-Week Training Break?

When I asked Lepers this question, he raised a couple of interesting points. One is that the psychology of taking such a long break went better than expected. He kept busy with work, ate normally, and didn’t stress because he knew that retraining would be a fun challenge. Crucially, he knew that once the 12 weeks were up he’d be able to start training again. That’s very different from, say, missing three months with a lingering injury where you’re never quite sure if it’s going to go away.

He also noted that many of his masters friends used to take long end-of-season breaks of a month or more when they were younger. But the older they get, the shorter and less frequent their breaks have become, presumably because they’re afraid that whatever fitness they lose they’ll never get back. If there’s one big headline finding from Leper’s self-experiment, it’s that this isn’t true, or at least wasn’t for him. That should help other masters athletes be a little less paranoid about the dangers of an occasional training break.

We can’t really claim, on the basis of a single case report, that taking 12 weeks off will enable you to break through and reach new levels of fitness. But even if you don’t return better than before, the idea that you can get back to your previous level is very reassuring. Over the years, I’ve found that I enjoy being fit, but what I really love is getting fit: the sensation of steady progress when week after week your times are dropping and your workouts are getting better. That feeling is increasingly hard to come by when you’ve been training for a long time. The best part of training breaks, from my perspective, isn’t vegging out on the sofa during the break; it’s getting back on the horse.

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For the past decade or so, sports scientists have been obsessed with the benefits of heat training. The extra stress of heat triggers various adaptations that help you handle hot conditions, like more sweating. Some of these adaptations, like increased blood volume, may even give you a boost when competing in cooler conditions. As a result, many top athletes now incorporate elaborate heat protocols into their training.

What if the opposite is also true? At in Montreal last month, a physiologist named Dominique Gagnon presented new data suggesting that cold training might offer some unique metabolic benefits that translate into enhanced health and endurance performance. It’s just a hypothesis at this point, based on a decade’s worth of incremental research. But as we head into the darkest, coldest months of the year, it’s kind of nice to think that our winter training might pack an extra punch.

Gagnon is a Canadian who recently moved from Laurentian University, in northern Ontario, to Finland’s University of JyvĂ€skylĂ€, three hours north of Helsinki. He knows cold, in other words. At the annual Canadian Society for Exercise Physiology conference, he presented comparing the training effects of working out in either warm (77 degrees Fahrenheit) or cool (32 degrees) conditions. The goal was to figure out whether training in the cold would boost levels, which is one of the key adaptations that underlies aerobic fitness.

What’s So Great About Cold?

Gagnon’s research on exercise in the cold goes back over a decade. Back in 2013, for example, he published showing that cold-weather exercise relies on a different fuel mix than warmer conditions, burning more fat and less carbohydrate. He suspects that this is because when you’re exercising in comfortable temperatures, there’s actually some local overheating in the muscles themselves.

Human metabolism is only about 25 percent efficient—comparable to the internal combustion engine in your car—so three-quarters of the energy in your food is released as heat in the muscles. That means that the temperature inside your muscles can be high even when the rest of you is cool. The advantage of exercising in the cold, then, is that it prevents your muscle cells from overheating and enables them to keep burning more fat for aerobic energy, which relies on the mitochondria in your muscles. In the long run, that should boost mitochondria levels and train your body to become more efficient aerobically.

There are various other hints supporting this view. Researchers at the University of Nebraska at Omaha, for example, that exercise in the cold produced a bigger spike in the cellular signals that tell the body to produce more mitochondria, though the difference wasn’t statistically significant. And have shown that they get a bigger fitness boost from exercise when the air is mildly cold.

The New Findings on Cold Training

In Gagnon’s new study, 34 volunteers trained three times a week for seven weeks, doing interval workouts on an exercise bike. Before and after the training period, they had muscle biopsies, which involve removing a small chunk of muscle from the leg, in order to analyse how much mitochondria was present. Sure enough, the group that trained in 32-degree air had a significantly greater increase in several different markers of mitochondrial content. Gagnon is still analyzing the VO2 max data, but initial signs are that those training in the cold were more likely to see a significant increase.

Those are encouraging findings. But even if the results (which have not yet been peer-reviewed) hold up, the next big question is whether this approach is practical. How cold do you have to be? Gagnon’s subjects performed their cold training in the equivalent of shorts and a T-shirt, which is less than I would typically wear at that temperature, but not totally unreasonable. Would the effects be nullified if you wore a long-sleeve shirt and tights? Gagnon’s not sure yet—but he emphasized that the goal isn’t to be cold, with measurably lower muscle and body temperature. Instead, it’s to avoid letting your muscles get too hot.

At this point, it’s worth flashing back to some findings I wrote about earlier this year. Stephen Cheung and his colleagues at Brock University in Canada showed that getting superficially cold, with no drop in core temperature, reduced time to exhaustion in a cycling test by about 30 percent. That involved sitting in a 32-degree room with a light breeze for half an hour before the subjects even started cycling. Staying in the room for longer, so that their core temperature actually dropped by a degree, reduced endurance by another 30 to 40 percent. This is not what Gagnon is aiming for.

Instead, the goal of cold training seems to be to let yourself get just cool enough that your muscles don’t overheat. Where that threshold is remains to be determined, and the results will need to be replicated before anyone takes them seriously. Gagnon is in discussions with the Finnish military, which has lots of personnel engaging in physical activity in perennially cold conditions, about further studies. Maybe it will turn out to be the next big thing in endurance training. Or maybe not. To be totally honest, I normally wouldn’t write about such preliminary results—but the idea that it might be true will help get me through some cold training runs this winter.

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