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Cycling Equity - Dr Rachel's Aldred

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Presentation - Newcastle - 12 December 2017
Organised by Newcastle Cycling Campaign

Veröffentlicht in: Umweltschutz
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Cycling Equity - Dr Rachel's Aldred

  1. 1. Cycling Equity (including new analysis of data from the Active People Survey with Anna Goodman) Rachel Aldred Reader in Transport University of Westminster rachelaldred.org @RachelAldred
  2. 2. What is cycling equity? And why does it matter? Source: Angus Maguire and the Center for Story-based Strategy, http://interactioninstitute.org/using-the4thbox-play-and-political-imagination/ Even when we do try and plan for cycling, are the tools we’re using exclusionary? Does it make sense to talk about ‘choosing’ to cycle in a hostile environment? I will argue we should be talking about removing barriers and redressing exclusion so that people of all backgrounds, ages, abilities etc. can benefit from cycling
  3. 3. The inclusive cycling approach – Cycling as a system or a service – What barriers have we created (physical, social, financial, etc.) that stop people participating in cycling? – Barriers may be general (affect some groups more than others) or specific – Need also to recognise not all cycling ‘counts’ Second pic: Cycling UK, https://www.cyclinguk.org/sites/default/file s/document/migrated/article/barrier4.jpg
  4. 4. Inequalities in cycling participation in England
  5. 5. Data used – Active People Survey (APS), a rolling national survey examining participation in sport and activity among adults in England. – Data on c. 500 people/year per local authority. – Anna Goodman and I carried out new analysis using four years of APS data from October 2011 to September 2015. – After excluding 4% of participants with missing data, this gave a total sample of 632,222 adults aged 16-99. – APS covers all cycling, and we can look at utility and recreational cycling separately.
  6. 6. Unadjusted results, all cycling in past 4 weeks – NB this 1st set of graphs refers to all cycling (utility and recreational – and there may be differences) – Unadjusted = not controlling for other factors – so differences between groups may be due to other underlying factors (e.g. lower participation at older ages may be connected to disability) – These inequalities are all culturally specific – for all of them, there are places where they don’t apply or the gaps shown are reversed
  7. 7. Gender 0% 5% 10% 15% 20% 25% Male Female Any cycling in last month Active People Survey data, analysis: Anna Goodman
  8. 8. Age 0% 5% 10% 15% 20% 25% 16-29 30-39 40-49 50-59 60-69 70+ Any cycling in last month Active People Survey data, analysis: Anna Goodman
  9. 9. Ethnicity 0% 2% 4% 6% 8% 10% 12% 14% 16% White Non-white Any cycling in last month Active People Survey data, analysis: Anna Goodman
  10. 10. Disability 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% Non-disabled Disabled Any cycling in last month Active People Survey data, analysis: Anna Goodman
  11. 11. Educational level 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% High Medium Low Educational level Any cycling in last month Active People Survey data, analysis: Anna Goodman
  12. 12. Car ownership 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% No car in household Car(s) in household Any cycling in last month Active People Survey data, analysis: Anna Goodman
  13. 13. Adjusted analysis, utility and leisure cycling
  14. 14. Gender 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Recreational cycling Utility cycling Rate ratios, adjusted for other characteristics Male Female Active People Survey data, analysis: Anna Goodman
  15. 15. Age 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Recreational cycling Utility cycling Rate ratios, adjusted for other characteristics 16-29 30-39 40-49 50-59 60-69 70+ Active People Survey data, analysis: Anna Goodman
  16. 16. Ethnicity 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Recreational cycling Utility cycling Rate ratios, adjusted for other characteristics White Non-white Active People Survey data, analysis: Anna Goodman
  17. 17. Educational level 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Recreational cycling Utility cycling Educational level Rate ratios, adjusted for other characteristics High Medium Low Active People Survey data, analysis: Anna Goodman
  18. 18. But for educational level, it’s not quite what it seems… – At national level, both recreational and utility cycling seems to decline with lower educational levels. – When looking within local authorities, this relationship remains for recreational cycling. – However, for utility cycling, this national result turned out to be driven by an ecological association, i.e. higher-cycling local authorities tended also to have more educated populations. – Within local authorities, there was no evidence that more educated people were more likely to cycle than less educated people. – Across 317 local authorities, average rate ratio for those with low/medium vs. high education was 1.06 (95%CI 0.99 - 1.13).
  19. 19. Car ownership 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Recreational cycling Utility cycling Rate ratio, adjusted for other characteristics Car(s) in household No car in household Active People Survey data, analysis: Anna Goodman
  20. 20. Are higher-cycling authorities more equal than lower-cycling authorities? – Yes for gender and age, for both leisure and utility cycling – Yes for disabled people’s participation in leisure cycling – E.g. where participation of everyone in cycling is twice as high, gap between group X and Y is smaller • NB this is cross-sectional not longitudinal…
  21. 21. Are higher-cycling authorities more equal than lower-cycling authorities? – Yes for gender and age, for both leisure and utility cycling – Yes for disabled people’s participation in leisure cycling – E.g. where participation of everyone in cycling is twice as high, gap between group X and Y is smaller • NB this is cross-sectional not longitudinal… – Otherwise no (participation of the group is higher where cycling is higher, but equality of representation isn’t higher) – E.g. where participation of everyone in cycling is twice as high, gap between group X and group Y is maintained
  22. 22. Why? – For all under-represented groups, likely to be a combination of general and specific barriers – E.g. disability: obstacles and cost Price £4525.00 Source: http://www.ashfieldspecialneeds.co.uk/s ide-by-side-tandem-fun2go.html
  23. 23. Newcastle & Gateshead – 13.9% and 9.2% respectively did any cycling in the past month – But how equally is this distributed?
  24. 24. Newcastle & Gateshead #1 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Older people Women Non-white Disabled Lower educational level Relative risk, any past-month cycling (utility or recreational) Gateshead Newcastle upon Tyne
  25. 25. Newcastle & Gateshead #2 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Older people Women Non-white Disabled Lower educational level Relative risk, any past-month utility cycling Gateshead Newcastle upon Tyne
  26. 26. Making cycling equal
  27. 27. Explaining inequalities – Important not to assume these are fixed/natural – even where they also exist in higher-cycling English local authorities – Generally other examples where inequalities do not exist, or relationships are reversed (and assumptions can change dramatically – I found papers from 80s and 90s assuming non-white and lower income Britons naturally cycled more)
  28. 28. E.g. gender and age in the Netherlands Source: DfT (2016) National Propensity to Cycle Tool Stage 1 Report, Appendix 8 https://www.gov.uk/government/publications/national-propensity-to-cycle-first-phase-development- study . NTS (England) analysis by Anna Goodman.
  29. 29. Ethnicity and cycling – In USA: non-white people and immigrants more likely to cycle to work (and cycling increasing faster among those groups) – In Netherlands, some disparities but much less than in England • BME people in the Netherlands make 22.8% of their trips by cycle, compared to 27.9% for white Dutch people. – May be more cycling to PT among non-white Dutch people (Fishman 2015) – raises issue of ‘invisible cyclists’
  30. 30. Explaining inequalities – general & specific issues – Even higher-cycling English local authorities are far from perfect – problems found elsewhere may exist there too, excluding some groups disproportionately from cycling – E.g. infrastructure is rarely good enough anywhere in England for young children to cycle alone, as in the Netherlands – But also we’ve barely started identifying and addressing specific barriers – some created by policy e.g. building only for commuter trips does little for retired people
  31. 31. Paradigm Shift – Individualisation of cycling – traditionally seen as a personal choice ‘some people’ weren’t making – Led to a lack of attention to how people from different groups are excluded from cycling – Instead need to focus on how different communities and groups are structurally excluded, both directly and indirectly, by planning, enforcement, infrastructure, attitudes, etc. – Parallels with direct, indirect discrimination
  32. 32. Direct & indirect discrimination: gender and risk – Traffic safety is a major barrier for men and (even more so) women – But safety from sexual harassment is under-researched Here are just a few of the women's stories, because there are many, many more. "It happens a lot, but this one particular time I was waiting at a traffic light and a group of men in a van were once all yelling at me as it was summer and I was wearing a short dress - that was one of the classic 'I wish my face was your saddle' times... It makes me feel so uncomfortable and is also really embarrassing in front of all of the other drivers." – Joanna Source: http://www.huffingtonpost.co.uk/entry/female- cyclists-sexism_uk_573eeabfe4b00006e9ae8248
  33. 33. Language, imagery - and policy! - matters ‘It remains relatively unusual for disabled people’s cycling to be considered within broader [London] transport strategy documents’ 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Cycle Taxis Car Demand responsive transport Pedestrians Unspecified Public transport London Borough Transport Strategies mentioning disabled people as users of different modes Source: https://www.sciencedirect.com/science/article/pii/S2214140517301615
  34. 34. Language, imagery - and policy! - matters – ‘It remains relatively unusual for disabled people’s cycling to be considered within broader [London] transport strategy documents […] – By contrast it was more usual for cycling strategies to at least mention disabled people as cyclists or potential cyclists. However, discussion of policies that might increase disabled people’s participation in cycling was often limited to general aspirations or references to leisure cycling clubs and training. Few images showed non-standard cycles of the kind that might be used by some disabled cyclists.’ Source: https://www.sciencedirect.com/science/article/pii/S2214140517301615
  35. 35. The first step is getting beyond imagining the ‘cyclist’ is this guy… but there’s still a lot to do even then.
  36. 36. Bike routes are obstructed Not enough protection from motor traffic Design and imagery is not inclusive Unsuitable (or no) bike parking Inequitable distribution of bike routes and services Discrimination and harassment Some people can’t afford the bikes they need Bike routes slow and indirect Interconnected barriers that keep cycling low and/or exclude specific groups
  37. 37. Don’t expect overnight changes… but inclusive planning will make a difference.
  38. 38. No one likes hostile traffic environments, but women even less so than men 0 500 1000 1500 2000 2500 3000 3500 Women's preferences are stronger No differences found Source: systematic review by Aldred et al 2017, Transport Reviews, http://www.tandfonline.com/doi/full/10.1080/01441647.2016.1200156
  39. 39. Protected lane study showed higher female participation (not equal, but positive change). Source: Aldred, R. and Dales, J. Journal of Transport and Health, http://www.sciencedirect.com/science/article/pii/S2214140516303978 0% 10% 20% 30% 40% 50% 60% 70% 80% Female 60+ Non-sporty clothing No specialist clothing Royal College Street observational study Control Protected
  40. 40. Cycling Equity (including new analysis of data from the Active People Survey with Anna Goodman) Rachel Aldred Reader in Transport University of Westminster rachelaldred.org @RachelAldred

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