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By: Andrew Forrest - January 2026
After reviewing a wide range of research on walking, one theme keeps emerging: the evidence strongly supports the health benefits of walking, but it also comes with important limitations. Understanding these limitations helps us at Walks4all interpret results responsibly and avoid oversimplifying what the studies actually prove.
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A large proportion of walking research is observational (cohort studies, surveys, population datasets). These studies can show that people who walk more often tend to have better outcomes (such as lower disease risk), but they usually cannot prove that walking is the only reason for those outcomes. Even with statistical adjustments, there can be hidden differences between groups that are hard to measure fully.
This is why you'll often see scientific language such as 'associated with' rather than 'caused by'.
People who walk more may also be more likely to adopt other health-supporting habits.
For example, individuals who walk 5,000 steps per day might also:
So, if a study finds fewer health issues among those walking 5,000 steps than among those walking 2,000, the difference might not be solely due to walking. Researchers try to 'control for' these factors, but residual confounding (unmeasured or imperfectly measured factors) can remain.
A major challenge in walking research is that illness, pain, disability, depression, or fatigue can reduce walking. In such cases, it can look like 'low steps cause poor health', when in reality, poor health may cause low steps (or both may influence each other).
Good studies try to account for this (for example, by excluding participants with existing disease at baseline), but it's not always possible to completely remove this bias.
Walking isn't one single intervention.
Studies define 'walking' in many different ways:
Two people can both achieve '5,000 steps', but one may walk briskly uphill while another walks slowly on flat ground. That means step counts alone don't always capture intensity, and intensity can matter for outcomes such as fitness improvements, blood pressure, glucose control, and cardiovascular adaptations.
Even when step targets show benefits, many studies can't precisely tell us:
For example, a study might show positive outcomes at 5,000 steps daily, but it doesn't necessarily tell us whether 6,000 or 10,000 steps would have been more (or less) beneficial - or how that might vary across populations. Real-world responses to walking are highly individual.
Walking exposure is often measured in ways that introduce error:
Measurement error can obscure results, especially when studies aim to detect small differences (e.g., 500-1,000 steps/day between groups).
Some intervention studies run for weeks or a few months. That may be long enough to detect changes in surrogate markers (such as blood pressure, mood scores, fitness tests, and blood sugar), but it may not be long enough to confidently detect differences in long-term outcomes, such as heart attacks, dementia, or mortality.
Also, even when a walking programme works in a trial, real life is messier: motivation changes, injuries occur, the weather shifts, and routines break. Adherence is often a major limitation.
Participants in walking studies are often people who are:
That means results may be less representative of people with mobility limitations, chronic pain, severe fatigue, caregiving constraints, or unsafe walking environments.
Many studies focus on specific groups (a particular age range, gender mix, country, or health status). Results may not translate neatly to:
Even the same walking dose may yield different outcomes depending on stress levels, occupational activity, and daily lifestyle demands.
Like many fields, walking research can be affected by:
The strongest confidence comes not from a single study but from consistent findings across many studies, methods, and populations.
These limitations don't make walking research 'weak' or useless. They mean we should treat the evidence as scientists do: as a growing, improving body of work rather than a single definitive answer.
At Walks4all, we take a practical, evidence-informed approach:
Walking may not be the only factor behind the positive outcomes observed in studies, but the sheer consistency of findings across decades of research strongly suggests it plays a meaningful, and often central, role in supporting health and wellbeing.
Walking evidence usually comes from various study types, including observational studies, randomised controlled trials (RCTs), and meta-analyses/systematic reviews. Observational studies follow people in real life and can identify patterns (for example, that higher walking levels are associated with better health), but they often can't rule out confounding factors or prove cause-and-effect.
RCTs assign people to a walking programme (or a comparison group), making it easier to test whether walking itself drives change; however, RCTs are often shorter and smaller, and may not reflect long-term real-world behaviour. Meta-analyses and systematic reviews combine results from multiple studies to estimate overall trends and consistency, but their conclusions remain limited by the quality, measurement methods, and diversity of the studies included.
Not always. Many studies show that higher levels of walking are linked to better health outcomes, but that doesn't automatically prove that walking is the direct cause. Stronger evidence comes from well-designed trials and consistent results across many studies, but even then, results can vary depending on who is studied and how walking is measured.
Healthy-user bias is when people who walk more are also more likely to do other health-supporting things - such as eating better, sleeping more, smoking less, or managing stress more effectively. This can make walking look more powerful than it is on its own, because walking acts as a 'marker' of a generally healthier lifestyle.
Step targets are not one-size-fits-all. The 'best' number of steps can depend on age, baseline fitness, health conditions, mobility, intensity, and even how steps are accumulated (short bursts versus longer walks). Many studies also show that benefits may increase up to a point and then plateau, so more steps aren't always proportionally associated with 'more benefit' across all outcomes.
They can be useful, but accuracy varies. Different devices and algorithms count steps differently, and people don't always wear their trackers consistently. Phones may miss steps if left on a desk or in a bag, and some wearables may struggle with slower walking speeds, assistive devices, or certain gait patterns. This measurement noise can affect study findings.
Yes - but with caution and personalisation. Walking research often under-represents people with chronic pain, fatigue conditions, disability, or multiple health conditions, and 'average' results may not reflect an individual's safe starting point. The most practical approach is to use research as general guidance, then tailor the walking dose and progression to symptoms and mobility, and take medical advice before undertaking any new exercise program.
January 2026
