Area variation in recreational cycling in Melbourne: a compositional or contextual effect?

Kamphuis, Carlijn B. M.; Giskes, Katrina; Kavanagh, Anne; Thornton, Lukar; Thomas, Lyndal; Lenthe, Frank J. van; Mackenbach, Johan P.; Turrell, Gavin

doi:10.1136/jech.2007.067116

Cited by 41 publications

(32 citation statements)

References 27 publications

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“…This lack of effect of objective built environment characteristics differs from findings by previous studies, which found objective built environment variables to be a significant contributor to socioeconomic inequalities in walking in leisure time [35], cycling in leisure time [36], and overall physical activity [37, 38]. However, the abovementioned studies again focused mostly on ‘micro’ built environment variables like aesthetics [36], the accessibility of physical activity-facilities (including parks, but also sport centers and youth clubs [37, 38]), and the presence of walking paths [35], whereas the present study used ‘macro’ characteristics such as density, land use pattern and overall accessibility measures. One possible explanation of these differences could be that ‘micro’ characteristics are more likely to be improved in the wealthier, better-organized neighborhoods of higher-educated residents (e.g.…”

Section: Discussioncontrasting

confidence: 99%

The role of the built environment in explaining educational inequalities in walking and cycling among adults in the Netherlands

et al. 2017

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BackgroundThis study examined whether characteristics of the residential built environment (i.e. population density, level of mixed land use, connectivity, accessibility of facilities, accessibility of green) contributed to educational inequalities in walking and cycling among adults.MethodsData from participants (32–82 years) of the 2011 survey of the Dutch population-based GLOBE study were used (N = 2375). Highest attained educational level (independent variable) and walking for transport, cycling for transport, walking in leisure time and cycling in leisure time (dependent variables) were self-reported in the survey. GIS-systems were used to obtain spatial data on residential built environment characteristics. A four-step mediation-based analysis with log-linear regression models was used to examine to contribution of the residential built environment to educational inequalities in walking and cycling.ResultsAs compared to the lowest educational group, the highest educational group was more likely to cycle for transport (RR 1.13, 95% CI 1.04–1.23), walk in leisure time (RR 1.12, 95% CI 1.04–1.21), and cycle in leisure time (RR 1.12, 95% CI 1.03–1.22). Objective built environment characteristics were related to these outcomes, but contributed minimally to educational inequalities in walking and cycling. On the other hand, compared to the lowest educational group, the highest educational group was less likely to walk for transport (RR 0.91, 95% CI 0.82–1.01), which could partly be attributed to differences in the built environment.ConclusionThis study found that objective built environment characteristics contributed minimally to educational inequalities in walking and cycling in the Netherlands.Electronic supplementary materialThe online version of this article (doi:10.1186/s12942-017-0083-y) contains supplementary material, which is available to authorized users.

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Section: Discussioncontrasting

confidence: 99%

The role of the built environment in explaining educational inequalities in walking and cycling among adults in the Netherlands

et al. 2017

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“…In countries with low modal shares such as the UK and Australia, evidence suggests that recent modest growth in cycling has tended to occur disproportionately amongst socioeconomically advantaged groups (Goodman, 2013, Kamphuis et al, 2008, Sahlqvist and Heesch, 2012, Steinbach et al, 2011. Evidence from Melbourne seems to confirm this finding.…”

Section: Introductionsupporting

confidence: 72%

The link between socioeconomic position, access to cycling infrastructure and cycling participation rates: An ecological study in Melbourne, Australia

Pistoll

Goodman

2014

Journal of Transport & Health

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Objective: Promoting cycling has moved up the policy agenda in recent years, but debate still exists surrounding the role played by socioeconomic barriers to participation in low cycling countries. This ecological study aimed to examine whether there are systematic socioeconomic disparities in access to cycling infrastructure and investment in Melbourne, Australia. Methods:We used Geographic Information System (GIS) techniques to measure the density of on-road, off-road and informal cycling routes in 58 neighbourhoods of inner Melbourne. We examined whether small-area socioeconomic indicators were associated with the density of these three types of cycling infrastructure or with local government spending on cycling. We additionally examined how small-area socio-economic position and infrastructure density were associated with the prevalence of cycling to work in the 2011 census. Results:The density of on-and off-road cycling infrastructure was positively associated with cycle modal share (both p<0.0001), and there was no evidence that the strength of this association differed between the two infrastructure types. The density of informal routes was not associated with cycling to work. There was no evidence that small-area socioeconomic position was systematically associated with the presence of on-road or quiet roads cycling infrastructure or with levels of investment. Levels of off-road infrastructure were somewhat higher in richer areas (r=0.32, p=0.02), although much of this was located in parkland and may have a predominant recreational function. Conclusion:In Melbourne, cycling infrastructure is positively correlated with cycle prevalence and is generally distributed equitably with respect to area-level socioeconomic position. In part this reflects the high levels of cycling infrastructure and spending in some relatively disadvantaged areas. Further studies that seek to understand the drivers behind successful policies in these areas may provide lessons for other areas, and aid our understanding of the complex relationships between cycling infrastructure, cycling behavior and socioeconomic position.

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“…Retail and service density (Cervero and Duncan 2003), and urban location (Stinson and Bhat 2004) all relate to the average separation between residences and potential destinations, suggesting that distance plays an important role in explaining transportation bicycle use. Land use patterns and bicycle infrastructure are also associated with recreational bicycle (Kamphuis et al 2008). Traffic conditions are tied to bicycle ownership (Beck and Immers 1994) and bicycle commuting (Deakin 1985;Parkin et al 2008), while bicyclefriendly design correlates with bicycling commuting and with recreational bicycling (Cervero and Duncan 2003;Kamphuis et al 2008).…”

Section: Conceptual Basis and Literature Reviewmentioning

confidence: 97%

“…Land use patterns and bicycle infrastructure are also associated with recreational bicycle (Kamphuis et al 2008). Traffic conditions are tied to bicycle ownership (Beck and Immers 1994) and bicycle commuting (Deakin 1985;Parkin et al 2008), while bicyclefriendly design correlates with bicycling commuting and with recreational bicycling (Cervero and Duncan 2003;Kamphuis et al 2008). Features of the natural environment, e.g.…”

Section: Conceptual Basis and Literature Reviewmentioning

confidence: 97%

Factors associated with bicycle ownership and use: a study of six small U.S. cities

2010

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Area variation in recreational cycling in Melbourne: a compositional or contextual effect?

Abstract: Creating supportive environments with respect to safety and aesthetic area characteristics may decrease between-area differences and area deprivation inequalities in recreational cycling, respectively.

Cited by 41 publications

References 27 publications

The role of the built environment in explaining educational inequalities in walking and cycling among adults in the Netherlands

The role of the built environment in explaining educational inequalities in walking and cycling among adults in the Netherlands

The link between socioeconomic position, access to cycling infrastructure and cycling participation rates: An ecological study in Melbourne, Australia

Factors associated with bicycle ownership and use: a study of six small U.S. cities

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