Low-altitude intervals improved altitude runners' 5,000 m times

For runners who live at altitude, hard interval sessions can feel like arguing with a vacuum cleaner. This study tested whether doing those hard sessions lower down might help trained runners improve 5,000 m performance.

Reference: Fentaw et al. Comparative effects of high-intensity interval training at low and moderate altitudes on 5,000-m performance and perceptual responses: A randomized controlled trial. Journal of Exercise Science & Fitness (2026) DOI: 10.1016/j.jesf.2026.200460.

Study snapshot

A quick, practical summary for runners and coaches.

Quick answer

This 8-week randomized controlled trialThe “gold standard” approach for determining whether a treatment has a causal effect on an outcome of interest. In such a study, a sample of people representing the population of interest is randomised to receive the treatment or a no-treatment control, and the outcome of interest is measured before and after exposure to the treatment and the control. studied 42 trained runners living at moderate altitude. High-intensity intervals improved 5,000 m performance, with a slightly larger improvement when the intervals were done at lower altitude. The main caution is that the study was small and very altitude-specific.

Key takeaways

  • High-intensity interval training improved 5,000 m performance in trained altitude-based runners.
  • The low-altitude interval group improved slightly more than the moderate-altitude interval group.
  • The findings are most useful for runners and coaches who already train at altitude.

How confident should we be?

Evidence confidence: Moderate

The randomizedRandomization means assigning people to different parts of a study (e.g., groups in a randomised controlled trial) by chance, not by choice. This helps make the groups similar at the start and reduces bias, so any differences you see are more likely due to the treatment, not background differences. In a crossover study, randomization usually decides the order in which each person gets the treatments (for example, Treatment A first then B, or B first then A). This way, order effects—like learning, fatigue, or simple time passing—are less likely to skew the results. design and real running-performance test are useful. But the study was small, short, and specific to trained runners living at moderate altitude.

Bottom line

For trained runners who live at moderate altitude, doing some hard interval sessions lower down may be worth considering. For most sea-level marathon, trail, and ultra runners, this is more of a useful coaching idea than a direct instruction: do the hardest sessions where you can execute them properly.

Read the deep dive below for a practical interpretation, actionable decisions, my thoughts, my Rating of Perceived scientific Enjoyment, the study details, full results, strengths, and limitations.

Running science research reviews for endurance runners

The deep dive

The details behind the headline result, including the practical meaning, full findings, limitations, and my interpretation.

Practical meaning

What does this research mean for runners and coaches?

This study is mainly about altitude-based 5,000 m runners, not all endurance athletes.

The researchers tested whether runners who live at moderate altitude might benefit from doing high-intensity intervals at a lower altitude, where oxygen availability is better. The results suggest that both altitude-based interval approaches helped, but the lower-altitude approach produced a slightly bigger performance improvement.

That practical interpretation is plausible. It is not the same as saying every runner should travel lower for workouts. The study tested a narrow setup: trained runners, 5,000 m performance, and 8 weeks of structured intervals.

For runners

If you live at moderate altitude, the study suggests that doing some key interval sessions at lower altitude could help you run those sessions under less altitude-related strain. That may be useful if your goal is shorter-distance performance, such as 5,000 m racing.

For sea-level runners, marathon runners, trail runners, and ultra runners, the findings are much less direct. The study did not test marathon performance, trail performance, ultra running, long-term durabilityDurability is a measure of how “durable” your physiological performance metrics are during prolonged fatigue-inducing exercise. I.e., can you still produce your maximal power at the end of a hard 2 hour run?, injury risk, or race outcomes outside a 5,000 m track test.

For coaches

The study supports a simple coaching principle: the setting of a workout can change the quality of the workout. If a runner lives high and struggles to hit the intended pace in hard sessions, moving some key interval work lower down might be sensible.

But the logistics matter. Travel, stress, sleep, terrain, and recovery can all gobble up the benefit. The intervention only makes sense if the runner can train lower without making the whole plan messier.

Practical decision

Should runners change anything?

Maybe. Lower-altitude interval sessions may be worth testing if you already live at moderate altitude and can use them without adding much travel stress.

Consider this if

  • You live at moderate altitude.
  • You are training for 5,000 m or a similar shorter-distance event.
  • You can reach lower altitude without adding much travel stress.
  • Your hard sessions are limited by the altitude rather than by fitness, pacing, or poor recovery.

Do not overreact if

  • You train mostly at sea level.
  • You are mainly focused on marathon, trail, or ultra performance.
  • Lower-altitude sessions would add travel fatigue.
  • Your current interval sessions are already going well.

A sensible next step

If you are an altitude-based runner, treat lower-altitude interval sessions as a possible training experiment, not a guaranteed upgrade. Track your interval pace, effort, recovery, and race-specific progress across several weeks.

TIP: Never make any major changes to your training or lifestyle habits based on the findings of one study, especially if the study is small or provides low-quality evidenceA low quality of evidence means that, in general, studies in this field have several limitations. This could be due to inconsistency in effects between studies, a large range of effect sizes between studies, and/or a high risk of bias (caused by inappropriate controls, a small number of studies, small numbers of participants, poor/absent randomisation processes, missing data, inappropriate methods/statistics). When the quality of evidence is low, there is more doubt and less confidence in the overall effect of an intervention, and future studies could easily change overall conclusions. The best way to improve the quality of evidence is for scientists to conduct large, well-controlled, high-quality randomised controlled trials.. Check whether other trials confirm the findings. If there is a meta-analysisA meta-analysis quantifies the overall effect size of a treatment by compiling effect sizes from all known studies of that treatment. on the topic, look at the effect sizeA standardised measure of the magnitude of an effect of an intervention. Unlike p-values, effect sizes show the size of the effect and how meaningful it might be. Common effect size measures include standardised mean difference (SMD), Cohen’s d, Hedges’ g, eta-squared, and correlation coefficients., the variability between studies, and the quality of evidenceCertainty of evidence tells us how confident we are that the published results accurately reflect the true effect. It’s based on factors like study design, risk of bias, consistency, directness, precision, and publication bias. High certainty means that the current evidence is so strong and consistent that future studies are unlikely to change conclusions. Whereas, low certainty means more doubt and less confidence, and that future studies could easily change current conclusions..

Expert interpretation

My thoughts

Running science from Thomas Solomon at Veohtu

This is a useful study, but it lives in a fairly narrow lane.

The researchers asked a practical question, used trained runners, and measured actual 5,000 m performance. That is much better than only measuring a lab marker and then declaring victory with a flourish. Real running tests deserve a polite nod.

The findings also make sense. Hard running at moderate altitude is harder because oxygen availability is lower. Moving hard sessions lower down may let runners execute the work better, feel a little less cooked, and race a little faster over 5,000 m. In this study, the low-altitude interval group improved by about 20 seconds, while the moderate-altitude interval group improved by about 17 seconds. That is not earth-shattering, but for a trained 5,000 m runner, it is not nothing either.

But the small sample keeps my excitement wearing a sensible length of running shorts. There were only 14 runners in each group. The study lasted 8 weeks. And some important reporting details were not available (e.g., info on blindingBlinding is when people in a study don’t know which treatment they’re getting. It stops expectations or beliefs (from patients or researchers) from skewing the results. “Single-blind” means participants don’t know; “double-blind” means participants and researchers don’t know; “triple-blind” means that the participants, researchers, and data analysts are kept in the dark. The goal is simple: fair tests and trustworthy findings. prodedures, allocation concealmentAllocation concealment is the step that hides the next treatment assignment before a patient enters a trial. It prevents staff from guessing or peeking, so they can’t steer patients to one group or another. It happens at enrollment, before blinding, and guards against selection bias., and whether the sample sizeN is how many participants or observations are analyzed. A bigger N usually means more precise estimates and more power (ability to detect a true effect). A smaller N results in a study that is less likely to detect a true effect (false negative/type II error) and is more likely to report false positives (type I error). Of course, a badly designed study is still bad even if it has a big N. was chosen using a power calculationA power calculation is a way to figure out how many people or data points you need in a study so you can reliably spot a real effect if it exists. It balances four things: the size of the effect you care about, how much random variation there is, how strict you are about false alarms, and how likely you want to be to detect the effect. In plain terms: it helps you avoid running a study that’s too small to be useful or so big that it wastes time and money.).

So, yes, the study is useful for altitude-based runners and coaches. No, it should not make every runner start hunting for a lower-altitude track. The sensible message is quieter: if altitude is stopping you from doing your hardest sessions well, training lower for those sessions may help. But is the magic in the altitude, or simply in better execution of hard work? Probably the second one, though the mountains do enjoy being mysterious.

My Rating of Perceived scientific Enjoyment

owlRPsE: 6/10

I experienced moderate scientific enjoyment because the study had a useful randomized design and a meaningful running-performance outcome, but the small sample, short duration, narrow setting, and limited reporting detail kept my scientific Spidey senses from getting jazzy.

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Read on for further details about the paper.

Research question

What did the researchers ask?

The authors aimed to compare whether high-intensity interval training performed at low altitude or moderate altitude affected pacing and perceived effort during a 5,000 m race in trained runners who lived at moderate altitude.

In plain English, the question was: if runners live high, do they perform better after doing their hardest sessions lower down?

Study design

What type of study was this?

This study was a randomized controlled trial.

A randomized controlled trial can test whether an intervention caused a change under the study conditions. That is useful here because the researchers assigned the runners to different training approaches.

But this study does not answer every altitude-training question. It cannot tell us whether the same approach works for sea-level runners, marathon runners, trail runners, ultra runners, or runners training across a full season.

Participants

Who took part?

The study included 42 trained runners who lived at moderate altitude.

The group included 23 male runners and 19 female runners. The runners were assigned to 3 groups, with 14 runners in each group.

The article did not provide enough detail on age, full training history, injury status, or health status.

Methods

What did the researchers do?

Who? 42 trained altitude-based runners
What? High-intensity intervals at 1,220 m or 2,850 m
How long? 8 weeks

The researchers assigned the runners to 1 of 3 groups.

The first group completed high-intensity interval training at about 2,850 m. The second group completed the same type of interval training at about 1,220 m. The third group acted as a control group at about 2,850 m.

The intervention lasted 8 weeks. The 2 interval groups completed 2 high-intensity sessions each week. Each session included 4 intervals lasting 4 minutes, run at the speed linked with maximum oxygen uptakeVO2max is the maximal rate of oxygen consumption your body can achieve during exercise. It is a measure of cardiorespiratory fitness and indicates the size of your engine, i.e., your maximal aerobic power, which contributes to endurance performance.. The runners recovered for 3 minutes between intervals at a lower intensity.

Before and after the intervention, the runners completed a 5,000 m race on a 400 m track at about 2,850 m. The researchers recorded race time, speed during each 1,000 m segment, and rating of perceived exertionRating of perceived exertion (RPE) is a simple way to score how hard exercise feels to you, not to a machine. You pick a number on a scale (often 1–10), where low numbers mean “this feels easy” and high numbers mean “I’m really pushing it.” It blends how heavy your breathing is, how tired your muscles feel, and how much effort you think you’re putting in., which means how hard the effort felt.

Main findings

What did the study find?

Low-altitude intervals About 20 seconds faster
Moderate-altitude intervals About 17 seconds faster
Perceived effort Lower after interval training

Both interval groups improved their 5,000 m race time.

The low-altitude interval group improved by about 20 seconds. The moderate-altitude interval group improved by about 17 seconds. Both improvements were statistically significantEvidence that a result is unlikely to be due to chance under a “no effect” model (or null hypothesis). Statistical significance is often judged by a p-value below 0.05 to flag that “something” is going on, but not how big or important that “something” is. One statistically significant result doesn’t mean proof; replication is needed. And, a statistically significant result doesn’t necessarily indicate clinical significance..

The low-altitude group showed the slightly larger improvement. In plain English, this suggests that lower-altitude interval sessions may have helped the runners get a little more from the hard training, at least under these specific conditions.

The pacing analysis suggested differences between groups across race segments, especially early and late in the race. The researchers reported group differences in the first and fifth kilometer and group-by-time differences across all kilometer segments. That is interesting, but it is also detailed pacing analysis from a small study, so I would not hang the entire coaching plan on it.

The runners in the interval groups also reported lower perceived effort than the control group, with greater changes in the low-altitude interval group. That suggests the runners were not just faster; the effort may also have felt a little more manageable.

The authors concluded that high-intensity interval training at both altitudes improved 5,000 m performance and perceived effort, with greater benefits after low-altitude training.

What helps my confidence in the findings?

The strengths

  • The study used a randomized design.
  • The study included trained runners, not only recreationally active adults.
  • The researchers measured a real 5,000 m running performance outcome.
  • The intervention was practical: 2 interval sessions each week for 8 weeks.
  • The study included both male and female runners.

What limits my confidence in the findings?

The limitations

  • The study was small, with only 14 runners in each group.
  • The intervention lasted only 8 weeks.
  • The findings apply mainly to trained runners living at moderate altitude.
  • Several reporting details were not available, including info on blindingBlinding is when people in a study don’t know which treatment they’re getting. It stops expectations or beliefs (from patients or researchers) from skewing the results. “Single-blind” means participants don’t know; “double-blind” means participants and researchers don’t know; “triple-blind” means that the participants, researchers, and data analysts are kept in the dark. The goal is simple: fair tests and trustworthy findings., allocation concealmentAllocation concealment is the step that hides the next treatment assignment before a patient enters a trial. It prevents staff from guessing or peeking, so they can’t steer patients to one group or another. It happens at enrollment, before blinding, and guards against selection bias., adherence, and whether the sample size (N)N is how many participants or observations are analyzed. A bigger N usually means more precise estimates and more power (ability to detect a true effect). A smaller N results in a study that is less likely to detect a true effect (false negative/type II error) and is more likely to report false positives (type I error). Of course, a badly designed study is still bad even if it has a big N. was chosen using a power calculationA power calculation is a way to figure out how many people or data points you need in a study so you can reliably spot a real effect if it exists. It balances four things: the size of the effect you care about, how much random variation there is, how strict you are about false alarms, and how likely you want to be to detect the effect. In plain terms: it helps you avoid running a study that’s too small to be useful or so big that it wastes time and money..

Funding and conflicts

Who funded the study?

Debark University funded the work as PhD research under the Ethiopia Ministry of Education.

The authors declared that they had no conflicts of interestA conflict of interest happens when a person or group has a personal, financial, or professional interest that could influence their judgment. It does not always mean they did something wrong. But it can create bias or make others question whether the decision or result is fully fair and trustworthy..

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