Running and Class

One of the anomalies about running is that despite the fact that it’s one of most accessible and cheap sports to be involved in, it’s disproportionately dominated by members of the middle-class. There’s plenty of evidence from all kinds of sources, including the massive Active People Survey by Sport England, to show that runners tend to have higher incomes and levels of education than participants in almost any other mainstream sport.

A few months ago I put together this table to show where running ranks amongst a range of sports in terms of its relative popularity with people in ‘high’ and ‘low’ status occupations (as per the National Socio-Economic Classification model).

To explain the figures: If a sport gets a score of 2 on the ranking that would mean it is twice as popular with the high status group as it is with the low status group. Or, if a sport gets 0.5 then the likelihood of a high status person participating in the sport is half that of a low status person. A sport scoring 1 is equally attractive to people of both groups.



Participation Rate Ratio

1 Tennis 3.89
2 Squash 3.00
3 Keep-fit classes 2.43
4 Golf 2.42
5 Mountaineering 2.40
6 Running 2.28
7 Road Cycling 2.25
8 Swimming – outdoor 2.09
9 Athletics – Track & Field 2.08
10 Aerobics 2.05
11 Badminton – indoor 1.87
12 Hockey 1.67
13 Swimming – indoor 1.60
14 Netball 1.53
15 Fitness & conditioning 1.50
16 Gym 1.49
17 Table tennis 1.29
18 Boxing 1.20
19 Karate 1.06
20 Equestrian 1.05
21 Bowls 1.03
22 Shooting 1.00
23 Cricket 0.97
24 Football 0.94
25 Rugby union – 15-a-side 0.73
26 Tenpin Bowling 0.71
27 Basketball 0.63
28 Snooker 0.60
29 Pool 0.56
30 Angling 0.54
31 Darts 0.40

[EDIT: A reader asked me what skiing would score in this table. Looking at people who ski at all (rather than once per week participation, which is the criteria for inclusion above) it would score 4.8, topping the table.]

Running, then, occupies a place just behind mountaineering and golf on the social scale, two sports which require significant financial outlays and are traditionally regarded very much as preserves of the middle-class. We can also see that running is the leading member of a cluster of individual outdoor racing and fitness sports – the others being cycling and wild swimming – that sit as a group on our socioeconomic hierarchy.

In this article I’m going to unpick this a little further, both by looking at the differing influences of income and education (two key factors underpinning understandings of social class) on running participation, and by unpacking that broad category of ‘Running’ into its different forms. As we will see, a similar hierarchy to the one shown above between sports also exists within the sport of running itself, with different forms attracting participants of significantly different backgrounds.

Unpacking Running

Anyone with more than a passing interest in running will know that the catch-all term ‘running’ covers a wide range of forms with significant differences in practices and appeal.

Track athletics, for instance, is a very different sport to fell-running. Ultra-marathon is a world apart from mud races. Multi-day adventure races have little in common with parkrun – save for running itself.

So perhaps, like the sports in the table above, different forms of running also attract different participant bases. Perhaps there’s a social hierarchy within running. In order to explore this we need first to unpack running into several different sub-sports we can compare.

The data from the Big Running Survey allows us to do this in a systematic way. Because each respondent listed the forms of racing they were involved in, we can look at groups of runners participating in different forms of the sport and see how they compare in terms of the socioeconomic factors of education level and income.

In this article we will look at how participants in the following forms of running vary in terms of their socioeconomic status:

  • Road racing (up to half marathon)
  • Fell-racing
  • Track racing
  • Ultra marathon
  • Obstacle course racing (OCR)


The chart below shows the mean personal income rank for each type of runner.

But first, a caveat: Because most of the runners in the data I have collected participate in more than one form of running (for example they have competed in both fell and road races in the last year) we have to bear in mind that the distinctions between different forms of running we observe may be watered down somewhat.The same runners appearing across more than one category will naturally make those categories more similar than they would be if we were looking at runners who only participate in one form of the sport.

So we need to interpret the figures carefully, and bear in mind that the differences we see below are probably smaller than what they might be if we compared ‘purists’ from each version of each sport.

Mean income rank by forms of running

Red line: Mean personal income in the UK

We can see that for all of the forms the mean income rank is between 2 and 3, which equates to between about £18,000 and £25,000. This makes sense in that this range includes the mean salary for the UK. Within this range though, there is a significant variation between forms, even without accounting for the number of people participating in multiple forms of running.

Ultra distance and fell-running lead the way, with road runners not far behind. There’s a significant gap back to OCR participants, and, on the lowest average income, track athletes.

However, these differences can be in part explained when we look back at the demographics of these different sports. In an earlier post we saw that different forms of running attracted men and women in different proportions. This is also true when it comes to age.

Ultra and fell running both attract more than their fair share of men, and of older runners. Both of these variables are associated with higher incomes. OCRs are associated with younger runners and are more popular with women. Track distances are very much the domain of the young. So perhaps this explains these differences. Let’s see what happens when we take gender out of the mix. We’ll just look at male runners in the next chart:


Surprisingly, looking only at male runners appears to have increased the variation. Another change is that fell-runners have dropped below road runners, with OCR runners snapping at their heels.

The change in ordering is probably because there were few women ‘dragging down’ the mean income rank of the fell-runners group compared to, say, road running, which has a much higher level of participation from women.

Let’s look at the same chart, but for female runners:


The most striking thing here is how similar the income scores are for all kinds of female runner, aside from track athletes. There’s almost no variation – so little that it may just come down to chance.

This is interesting. There appears to be a distinct economic hierarchy amongst male runners, but not amongst females. Let’s see if the same is true in terms of their education levels.


These are the mean ‘highest level of education achieved’ ranks for all runners:


There is significant variation between the forms of running in terms of the average education level of their participants, with ultra runners tending to be the highest educated and OCR competitors the least. Here there is less of an issue with gender skewing the results, as the men and women in the survey had similar average education levels. But that’s not to say splitting this down by gender won’t reveal differences in the distribution of education ranks. Let’s see.

Male runners:


Clearly if we look at male runners in isolation they present a different distribution to the mixed gender chart. Track athletes overtake road runners in mean education level, and fell-runners catch up with ultras.

And for female runners:


This more closely matches the overall chart, with the exception of the especially low level of mean education for female track runners in this sample. The similarity between the female chart and the overall chart is explained by the fact that there were more women in the survey sample than men by about a 3:2 ratio.

We can see that the amount of variation between the means is not significantly different for men and women. There’s about 0.5 rank points between the lowest and highest educated male groups, and for women the spread is about 0.4.

Map of the Social Space of Running

It’s worth remembering that at the start of this post we saw that running in general is very much a middle-class sport in terms of its participant base. So the variations within it can be seen as variations within middle-class taste, with different sub-groups preferring different forms of running.

To visualise this we can create a social map of running tastes with the data we examined above. The map is structured by income and education.

the social space of running

The orange lines indicate the sample means for income and education rank.

The chat shows us that within the (rather middle-class) population of runners there are some distinctions in terms of the relationship between different forms of the sport and the social status of those participating in them.

Road races up to half marathon sit at the centre, probably because this kind of racing attracts the widest range – and largest number – of participants. As a result participating in road running is the least socially distinctive form of the sport.

Fell and ultra racing share a quadrant of the map, attracting people of higher economic and educational status than average. However, we’ve seen that for men the mean income for fell-runners is significantly lower than sample average.

OCR and track racers occupy the low status quadrant, with lower than average income and education (compared to other runners, not necessarily to society in general). For track racers this can be explained in part by their relative youth.

Why the differences?

That’s it as far as this whistle-stop description of the social space of running is concerned, but we have yet to address the question of why different forms of running attract different social groups. This is a difficult question that means looking at the history and culture of the different forms of the sport, as well as issues such as access, geography and the demands of the different types of running.

In the next post I will start to unpick these distinctions, looking at each form of running in turn, attempting to explain how they have come about.

4 thoughts on “Running and Class

  1. Albert Kort

    Very interesting results. Confirms my thoughts about running and the people who participate. The higher the income, the more education, the longer distances they run.
    1. I suppose by ‘ultra’ is meant marathon and longer?
    2. The research is limited to the UK. Is there any research done in other countries?

    • Neil Baxter Post author

      HI Albert, so sorry for the slow response. My comments settings were set up wrongly and I didn’t get notified of your comment.

      Thanks very much for your thoughts. In answer to your questions:

      1) Yes, ultra generally refers to any race longer than 26.2 miles.
      2) There are lots of studies around running in various European countries and the US, though not focusing on quite the same areas or going to the same level of detail as my research. FOr European countries the book Running Across Europe provides a good and recent overview:

  2. Catherine

    This is just my own theory but OCR events do have a military conatation and those that go into the forces do tend to be more from a working class background. Not sure about the track events but maybe it’s because it’s a standard event that takes place in all schools and many carry on after leaving school.

    • Neil Baxter Post author

      Hi Catherine,

      Sorry for the delay responding – I got my comment settings in a muddle and hadn’t received a notification of your post.

      I’m not sure about the OCRs, but I’ve recently been talking to people involved in orienteering, and there’s definitely a large element of ex-military involved in that. Perhaps it’s similar for OCRs… something to look into!

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