Socioeconomic inequalities in distance to and participation in a community-based running and walking activity: A longitudinal ecological study of parkrun 2010 to 2019

Objectives

To conduct a longitudinal ecological analysis of the distance to and participation in free weekly outdoor physical activity events (parkrun) in England from 2010 to 2019, and related socioeconomic and ethnic inequalities, to inform policies to support participation in physically active community events.

Methods

We calculate distance to the nearest parkrun event for each English Lower Layer Super Output Area (LSOA) each month from January 2010 to December 2019. We then report the trends in distance to and participation in parkrun by Index of Multiple Deprivation quintile. We also report trends in the Relative Index of Inequality (RII) by deprivation for participation and distance to nearest event. We go on to investigate trends in LSOA level determinants (e.g. deprivation and ethnic density) of parkrun participation between 2010 and 2019, using multivariable Poisson regression models.

Results

Mean distance to the nearest parkrun event decreased from 34.1 km in 2010, to 4.6 km in 2019. Throughout the period, parkrun events tended to be situated closer to deprived areas compared to less deprived areas. Participation rates increased superlinearly (greater than linear increase) from 2010 to 2013 before slowing to linear growth. Participation over the period exhibits a clear socioeconomic gradient, with people from deprived areas having consistently lower participation rates over the period. parkrun participation rates became more equal between 2010 and 2013 (RII improved from 189 to 39), before stabilising at an RII between 32.9 and 39.6 from 2014 to 2019. The results of the Poisson regression model validate this finding; the coefficients on IMD score initially increased from −0.050 in 2010 to −0.038 in 2013, and then remained relatively stable to 2019 (−0.035).

Conclusions

Over the past 10 years, geodesic distance to the nearest parkrun decreased from a mean of 34 km to 5 km. In 2010, there was equality between the least and most deprived areas but by 2017 the distance of the most deprived areas was 29% that of the least deprived. Participation was shown to have increased over the past 10 years which can be split into two distinct phases: from 2010 to 2013 participation increased super-linearly and inequality in participation fell dramatically; from 2013 to 2019 participation increased linearly, and inequality in participation remained stable. Despite parkrun's ambitions of creating inclusive events and engaging with deprived communities, the socioeconomic gradient in participation rates remained high and stable since 2013. Gaining a better understanding of the reasons why parkrun grew so quickly may be useful for other physical activity movements, while further analysis of the relatively lower participation rates in areas with higher socioeconomic deprivation is important for developing initiatives to encourage physical activity in these communities.

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Geographical access to & participation in parkrun in England improved every year from 2010 to 2019.

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However, the rate of improvement slowed down, especially after 2013.

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New events reduced distance to parkrun in high deprivation areas more than low deprivation areas.

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Socioeconomic inequalities in participation fell from 2010 to 2013 and stabilised after.

Multiple deprivation and geographic distance to community physical activity events - achieving equitable access to parkrun in England

Objectives

To evaluate geographic access to free weekly outdoor physical activity events (‘parkrun’) in England, with a particular focus on deprived communities, and to identify optimal locations for future events to further maximise access.

Study design

This study is a cross-sectional ecological analysis of the socio-economic disparities in geographic access to parkrun events in England in late 2018.

Methods

We combined geolocation data on all English Lower Layer Super Output Areas and parkrun events to calculate geodesic distances to the nearest event for more than 32,000 communities in England. We use this measure of geographic access to summarise the relationship between access and socio-economic deprivation, measured using the index of multiple deprivation. We then used geographic coordinates of public green spaces in England to conduct a simple location-allocation analysis to identify 200 locations for future event locations that would maximise access.

Results

In England, 69% of the population live within 5 km of one of the 465 parkrun events. There is a small negative correlation between distance and deprivation, indicating that access is slightly better in more socio-economically deprived areas. Setting up an additional 200 events in optimal locations would improve access: the average distance to the nearest parkrun event would improve by 1.22 km, from 4.65 km to 3.43 km, and approximately 82% of the English population would live within 5 km of a parkrun event.

Conclusion

Over two-thirds of the English population live within 5 km of a parkrun event, and contrary to our expectation, we find that geographic access is slightly better for those living in more deprived communities. Creating additional events may improve geographic access, but effective strategies will still be needed to increase engagement in new and existing events by those living in socio-economically deprived areas.

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Parkrun in a grass-roots movement that organises free weekly 5 km running and walking events.

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In England, the median distance to the nearest parkrun event was 3.4 km; 69% of the population lived within 5 km of an event.

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Access showed no negative socio-economic gradient. In fact, people in deprived communities had better geographic access.

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Sport England provided funding to set up 200 new events. We identified optimal locations, to further maximise public access.

An improvement index to quantify the evolution of performance in running

Improvements in track and field sports have been attributed to factors such as population increase, drugs and new technologies, but previous research has found it difficult to distinguish the contributions from specific influences. Here it is shown how this is possible by means of a performance improvement index based on useful work done combined with modelling of the annual top 25 performances. The index was set to 100 in 1948 and showed that, by 2012, it had increased in running events to between 110.5 and 146.7 (men's 100 m and marathon). Underlying global effects accounted for the majority of all improvements (16.2 to 46.7) with smaller influences attributable to an influx of African runners (3.6 to 9.3), and a 4-year oscillation that arose from staging of the Olympic Games (±0.2 to ±0.6). Performance decreased with the introduction of compulsory random drug testing (-0.9 to -3.9) the World Anti-Doping Agency (WADA; -0.5 to -2.5) and fully automated timing (-0.6 to -2.5). Changes in elite sporting performance since the 1890s are attributable to societal changes caused by the industrial revolution and globalisation superimposed on millennia of human evolution.

The impact of technology on sporting performance in Olympic sports

To assess the effect of technology on sport, the performance statistics for four disciplines were analysed: the 100-m sprint, pole vault, javelin, and cycling. The concept of a performance improvement index was developed to allow comparison between athletes and between sports with a higher index indicating a greater improvement in the sport. The following performance improvement indices were found: 100-m sprint, 24% over 108 years; pole vault, 86% over 94 years; javelin, 95% over 76 years; 4-km individual pursuit, 35% over 32 years; one-hour cycling record, 221% over 111 years. Around 4% of the index for the sprint was attributed to tighter, aerodynamic clothing, suggesting that general athletic improvement in sprint-type events has been around 20%. Technological developments in simple equipment such as the pole vault or javelin were seen to affect the index by around 30%, while the index associated with aerodynamic improvements in the one-hour record was around 100%. It is concluded that the performance improvement index could be extended to amateur as well as elite sport where distance or time is used as a measure of performance.

The dynamic impact characteristics of tennis balls with tennis rackets

The dynamic properties of six types of tennis balls were measured using a force platform and high-speed digital video images of ball impacts on rigidly clamped tennis rackets. It was found that the coefficient of restitution reduced with velocity for impacts on a rigid surface or with a rigidly clamped tennis racket. Pressurized balls had the highest coefficient of restitution, which decreased by 20% when punctured. Pressureless balls had a coefficient of restitution approaching that of a punctured ball at high speeds. The dynamic stiffness of the ball or the ball-racket system increased with velocity and pressurized balls had the highest stiffness, which decreased by 35% when punctured. The characteristics of pressureless balls were shown to be similar to those of punctured balls at high velocity and it was found that lowering the string tension produced a smaller range of stiffness or coefficient of restitution. It was hypothesized that players might consider high ball stiffness to imply a high coefficient of restitution. Plots of coefficient of restitution versus stiffness confirmed the relationship and it was found that, generally, pressurized balls had a higher coefficient of restitution and stiffness than pressureless balls. The players might perceive these parameters through a combination of sound, vibration and perception of ball speed off the racket.