Hiking Statistics Updated November 2026

Human Written & Fact Checked · Updated

100 Older Adult Hiking Statistics for 2026

An average hiker's age cannot tell you how common hiking is among older adults. Participation within an age group, the age profile of hikers and observations from a particular trail are different measures. This page keeps those distinctions visible before comparing the numbers.

The evidence covers Australian adult age bands, Swiss participation and footwear research, Japanese activity recall and a voluntary Appalachian Trail survey. Older age categories differ between sources, so the findings are not combined into a worldwide senior-hiking estimate. Younger groups appear as comparisons, not as observations about older people.

Headline figures

  • Australia: bushwalking participation among adults aged 65+ was 9.7% during July 2025–June 2026. (Australian Sports Commission, Oct 2026)
  • Australia: an estimated 467,359 adults aged 65+ participated in bushwalking during July 2025–June 2026. (Australian Sports Commission, Oct 2026)
  • Australia: bushwalking participation among adults aged 55–64 was 20.1% during July 2025–June 2026. (Australian Sports Commission, Oct 2026)
  • Australia: organised bushwalking participation among adults aged 65+ was 1.6% during July 2025–June 2026. (Australian Sports Commission, Oct 2026)
  • Switzerland, 2025 fieldwork: hiking participation among women aged 60–74: 59%. (BASPO / Swiss Sport Observatory, Aug 2026)
  • Switzerland, 2025 fieldwork: hiking participation among women aged 75+: 52%. (BASPO / Swiss Sport Observatory, Aug 2026)
  • Switzerland, 2025 fieldwork: hiking participation among men aged 60–74: 58%. (BASPO / Swiss Sport Observatory, Aug 2026)
  • Swiss resident hikers aged 15+ had a mean age of 52 years in the 2025 fieldwork. (BASPO / Swiss Sport Observatory, Aug 2026)
  • Among hikers observed on selected Swiss mountain paths in summer 2024, high hiking/mountain boots among those aged 65+: 68%. (BFU, Sep 2025)
  • Among hikers observed on selected Swiss mountain paths in summer 2024, running shoes among those aged 65+: 6%. (BFU, Sep 2025)
  • The oldest respondent in The Trek's self-selected 2025 Appalachian Trail survey was 73 years old. (The Trek, Dec 2025)
  • In Japan's March 2026 online survey, 6% of respondents aged 60–69 reported trekking or hiking during the preceding three years. (Cross Marketing, Mar 2026)

How common is bushwalking among Australians aged 65 and older?

Participation rates and estimated participant numbers describe different aspects of reach. AusPlay provides both for residents in the specified age band, which helps separate an activity's prevalence from the size of a regional population.

How do state and territory rates compare?

Regional rates describe annual bushwalking participation within the older population. They are not older adults' share of bushwalkers. The source uses weighted survey estimates, so close values should not become definitive rankings. Residence also does not establish where a walk took place. These observations do not explain participation differences.

What scale do eastern-state participant estimates suggest?

Participant estimates add population scale to the rate comparison. Each observation estimates people in the stated age band who reported participating, instead of trips, distances or trail visits. The workbook retains unrounded weighted estimates; whole-person rounding here should not imply census precision. A person who walked frequently remains a participant instead of contributing a new count for every outing. These residence-based estimates can describe potential audience size, but local trail management requires evidence about destinations and timing. A resident may have walked in another state, and a state's trails may also attract people who live elsewhere. Neither movement is identified by the participant count alone.

What do the remaining participant estimates show?

The remaining jurisdictions complete the geographic comparison for this age band. Smaller regional populations make the distinction between rate and number especially important. Sampling uncertainty remains relevant even when the source provides a precise-looking estimate. The table does not show whether participants walked independently, joined a group or used a particular type of trail. Nor does annual participation establish a regular weekly routine. These limits do not make the estimates unusable; they define the population question that the numbers can answer without inferring details the survey table does not supply.

How does the later-working-age comparison differ?

Age cut-offs should stay visible instead of being collapsed into a vague senior category. AusPlay's preceding age band provides context, while organised participation describes a narrower activity arrangement within each band.

What did participation look like in the preceding age band?

The preceding band uses the same question and period. Comparing it with the older band describes differences between populations at one point in time. It does not track the same people as they age. Cohort characteristics and sampling variation influence comparisons. These rates cannot predict an individual's participation after a birthday.

How many participants were estimated in that band?

The national and selected regional estimates describe the number of participants within the comparison band. The regional figures are included in the national estimate and should not be added to it. A larger participant estimate can reflect population size as well as a higher participation rate. These counts do not measure activity intensity, route difficulty or equipment spending. They do not count current trail users. The source reports annual participation, and the same person may choose very different outings during that period. Counting people distinguishes population reach from total activity.

What do the other counts and organised participation show?

The remaining counts complete the age-band geography. Organised participation adds a different question about activity arrangements, with its denominator still the relevant resident age group. An organised participation rate is not the share of existing bushwalkers who belong to a club. The source's broader participation measure also covers activity outside organised arrangements. These selected observations cannot identify which organisations people used, how often they attended, or whether the arrangement improved their experience. They describe patterns without assigning benefits.

How does Switzerland's age profile compare?

Swiss findings add a different activity definition and age structure. Hiking and mountain hiking are combined, and the survey separates rates within age groups from the demographic composition of the hiking population.

What do the remaining age and sex comparisons show?

The source reports participation separately for female and male age groups. These observations complement the selected older-group figures in the takeaways. An age-specific participation rate is not the same as the proportion of hikers in that age group. The Swiss bands differ from AusPlay's, so the displayed values do not support a directly age-standardised international comparison. Sex-specific patterns also cannot explain individual motivations or circumstances. They describe population differences; causal explanations require additional evidence.

What does the overall hiking profile add?

The overall profile puts the age comparisons alongside general participation, frequency and activity importance. These observations describe the broader resident or hiking population under their stated definitions. The reported change uses percentage points, not a relative percentage change. A central frequency measure cannot describe every participant's routine. The women's share identifies the composition of hikers, while hiking as a main sport addresses a different relationship with the activity. None of these measures establishes an older adult's individual fitness or recommended level of exertion. The source is used here for participation context instead of personalised health advice.

How do regional and holiday measures change the denominator?

Language-region participation and sports-holiday hiking concern different populations and situations. The holiday age profile is therefore not interchangeable with the profile of all everyday hikers. A holiday measure does not identify how often people walk near home. Similarly, a mean age describes a group's composition instead of the chance that a person of that age participates. The source's language regions describe residents, not the language of every destination visited. These boundaries matter when using national research to plan communication for older visitors to a particular trail or accommodation.

What footwear did the Swiss field study observe?

Equipment observations can describe a sample without proving why its members made their choices. BFU's age comparisons provide context for older hikers, but they do not establish the safety or suitability of a shoe category for an individual.

How did the older age groups' footwear differ?

  • Observed high hiking/mountain boots among age 50–64: 60%. (BFU, Sep 2025)
  • Observed low hiking/trekking/mountain shoes among age 50–64: 24%. (BFU, Sep 2025)
  • Observed low hiking/trekking/mountain shoes among age 65+: 25%. (BFU, Sep 2025)
  • Observed running shoes among age 50–64: 15%. (BFU, Sep 2025)
  • Observed other footwear among age 50–64: 1%. (BFU, Sep 2025)
  • Observed other footwear among age 65+: 1%. (BFU, Sep 2025)

The older age bands showed different distributions of observed footwear. The selected oldest-band findings in the takeaways come from the same table and field period. These are observations of hikers present during the study, not national ownership estimates. A person could own several kinds of footwear and choose differently on another route. Cross-sectional age differences also do not show an individual changing equipment over time. The study does not isolate terrain, conditions or personal preference as causes of the observed pattern. Rounded categories should not be interpreted as exact counts of people.

What did the younger comparisons show?

  • Observed high hiking/mountain boots among age 15–29: 56%. (BFU, Sep 2025)
  • Observed high hiking/mountain boots among age 30–49: 52%. (BFU, Sep 2025)
  • Observed low hiking/trekking/mountain shoes among age 15–29: 21%. (BFU, Sep 2025)
  • Observed low hiking/trekking/mountain shoes among age 30–49: 26%. (BFU, Sep 2025)
  • Observed running shoes among age 15–29: 21%. (BFU, Sep 2025)
  • Observed running shoes among age 30–49: 20%. (BFU, Sep 2025)
  • Observed other footwear among age 15–29: 2%. (BFU, Sep 2025)
  • Observed other footwear among age 30–49: 2%. (BFU, Sep 2025)

The younger bands provide comparison groups within the same field study. These observations include the sampled hikers across sexes, instead of a female-only or male-only age profile. The comparison preserves the original shoe categories and age boundaries. It does not measure correct fit, wear, grip or the way equipment was used. Consequently, a difference between age groups cannot be translated into a difference in accident risk. The table describes equipment present in the sample, not a test of hiking competence.

What did the sex comparisons show across the sample?

  • Observed high hiking/mountain boots among men: 58%. (BFU, Sep 2025)
  • Observed high hiking/mountain boots among women: 58%. (BFU, Sep 2025)
  • Observed low hiking/trekking/mountain shoes among men: 26%. (BFU, Sep 2025)
  • Observed low hiking/trekking/mountain shoes among women: 23%. (BFU, Sep 2025)
  • Observed running shoes among men: 15%. (BFU, Sep 2025)
  • Observed running shoes among women: 16%. (BFU, Sep 2025)
  • Observed other footwear among men: 1%. (BFU, Sep 2025)
  • Observed other footwear among women: 2%. (BFU, Sep 2025)

The same study also reported observed footwear by sex. These are comparisons across the sampled sex groups and are not specifically estimates for older men or older women. The source does not provide an age-by-sex breakdown in this selected table. Combining separate age and sex percentages would therefore invent a subgroup estimate. Keeping the comparisons distinct avoids that error. The observations remain useful as a description of the study population, with no implied causal effect of a particular shoe type.

What can other age-based surveys tell us?

Activity recall and a long-distance survey provide useful contrasts, but their age boundaries are not interchangeable. Japan's selected study stops below the oldest age band in AusPlay, while a reader survey reflects the people who chose to respond.

How did Japanese trekking participation vary by age?

  • Three-year trekking/hiking participation among age20–29: 2%. (Cross Marketing, Mar 2026)
  • Three-year trekking/hiking participation among age30–39: 2%. (Cross Marketing, Mar 2026)
  • Three-year trekking/hiking participation among age40–49: 4%. (Cross Marketing, Mar 2026)
  • Three-year trekking/hiking participation among age50–59: 4%. (Cross Marketing, Mar 2026)

The Japanese online study reports trekking and hiking over a multiyear recall period. The oldest available band appears in the takeaways, with the younger comparisons below. The study's age limit means it cannot describe participation among people older than its sampled range. Its recall period also differs from annual Australian or Swiss participation. Activities can overlap, so the trekking category should not be added to other outdoor sports as if each respondent appeared only once. These are rounded participation estimates, not destination counts or measures of route difficulty. They answer a bounded population question instead of establishing an international ranking.

How did the mountain-climbing and trail-running category compare?

  • Three-year mountain climbing/trail running participation among age20–29: 5%. (Cross Marketing, Mar 2026)
  • Three-year mountain climbing/trail running participation among age30–39: 4%. (Cross Marketing, Mar 2026)
  • Three-year mountain climbing/trail running participation among age40–49: 6%. (Cross Marketing, Mar 2026)
  • Three-year mountain climbing/trail running participation among age50–59: 4%. (Cross Marketing, Mar 2026)
  • Three-year mountain climbing/trail running participation among age60–69: 5%. (Cross Marketing, Mar 2026)

A separate category combines mountain climbing and trail running. Its age profile is retained separately because it does not measure exactly the same activity as trekking and hiking. The combined wording prevents the figures from identifying either activity on its own. A respondent could also have participated in the trekking category, so the two profiles are not mutually exclusive groups. The source's online sample and recall period remain important limitations. These comparisons describe the research instrument's categories and should not be converted into a claim about how demanding a particular age group's outings were.

What did the Appalachian Trail survey's age profile show?

  • Survey respondents: mean age 44 years. (The Trek, Dec 2025)
  • Survey respondents: median age 37 years. (The Trek, Dec 2025)
  • Survey respondents: modal age 26 years. (The Trek, Dec 2025)
  • Survey respondents: youngest age 12 years. (The Trek, Dec 2025)

The voluntary long-distance survey reports several summaries of respondents' ages. Its oldest reported age appears in the takeaways; the other summaries below describe different features of the distribution. A mean, median and mode need not coincide. The sample includes different journey outcomes and does not establish the age distribution of all trail visitors. An age extreme also cannot show how likely someone of that age is to attempt or complete a hike. These observations demonstrate the range within the respondent group, while the voluntary recruitment limits population inference. The figures are descriptive instead of a fitness assessment or a suggested age limit.

Glossary

Methodology and sources

Every figure on this page comes from the organisation that produced it: regulators, statistics offices, public bodies, research institutes, and companies reporting their own data or surveys. Each one links to the original report or dataset and carries its release date. Survey results keep their population and fieldwork period, and financial figures keep the measure the producer used. Figures from different producers are not added together or ranked against each other. The page is reviewed monthly and updated when a producer releases newer data.