Gender differences in recreational and transport cycling: a cross-sectional mixed-methods comparison of cycling patterns, motivators, and constraints
© Heesch et al.; licensee BioMed Central Ltd. 2012
Received: 11 April 2012
Accepted: 4 September 2012
Published: 8 September 2012
Gender differences in cycling are well-documented. However, most analyses of gender differences make broad comparisons, with few studies modeling male and female cycling patterns separately for recreational and transport cycling. This modeling is important, in order to improve our efforts to promote cycling to women and men in countries like Australia with low rates of transport cycling. The main aim of this study was to examine gender differences in cycling patterns and in motivators and constraints to cycling, separately for recreational and transport cycling.
Adult members of a Queensland, Australia, community bicycling organization completed an online survey about their cycling patterns; cycling purposes; and personal, social and perceived environmental motivators and constraints (47% response rate). Closed and open-end questions were completed. Using the quantitative data, multivariable linear, logistic and ordinal regression models were used to examine associations between gender and cycling patterns, motivators and constraints. The qualitative data were thematically analyzed to expand upon the quantitative findings.
In this sample of 1862 bicyclists, men were more likely than women to cycle for recreation and for transport, and they cycled for longer. Most transport cycling was for commuting, with men more likely than women to commute by bicycle. Men were more likely to cycle on-road, and women off-road. However, most men and women did not prefer to cycle on-road without designed bicycle lanes, and qualitative data indicated a strong preference by men and women for bicycle-only off-road paths. Both genders reported personal factors (health and enjoyment related) as motivators for cycling, although women were more likely to agree that other personal, social and environmental factors were also motivating. The main constraints for both genders and both cycling purposes were perceived environmental factors related to traffic conditions, motorist aggression and safety. Women, however, reported more constraints, and were more likely to report as constraints other environmental factors and personal factors.
Differences found in men’s and women’s cycling patterns, motivators and constraints should be considered in efforts to promote cycling, particularly in efforts to increase cycling for transport.
Cycling offers health benefits, including improved cardio-respiratory fitness and decreased risk of all-cause and cardiovascular mortality . Commuter cycling is negatively associated with overweight and obesity  and may help employees meet physical activity recommendations of moderate- to vigorous-intensity physical activity for 30 minutes per day, 5 days per week . Active travel is also good for the environment as it can reduce traffic congestion, air and noise pollution, carbon emissions and fossil fuel consumption .
In Australia, only about 1% of daily trips are by bicycle, similar to the percentages seen in the US and the UK, but low compared with the 26% of daily trips reported for the Netherlands and 9-18% for some other European countries . However, cycling for recreation is the fourth most commonly-reported physical activity among Australian adults . The most recent data indicate that 17% of Australian adults cycled in the previous month but that most cyclists (62%) cycled only for recreation . Given that recreational cyclists already possess the motivation, equipment and skill, it has been argued, that in countries like Australia with low rates of transport cycling, recreational cyclists might comprise a useful target group for promoting cycling for transport .
Addressing gender differences in cycling and the reasons for these differences will be important for increasing transport cycling in countries such as the USA, UK and Australia. In Australia, not only do more men than women cycle in general , but even among cyclists, more men cycle for transport. In the state of Queensland, we have found that only 24% of transport cyclists are women . In Sydney, only 17% of bicycle commuting trips are by women and in Melbourne, only 25% are . Although these percentages are comparable to those in the US, where 24% of commuting trips are by women, they are much lower than in countries with established cycling cultures, such as the Netherlands and Germany, where women cycle at similar rates to men [5, 11].
Gender differences in transport cycling in Australia and other car-dependent countries reflect in part the different transportation patterns, needs, and purposes of men and women [12, 13]. For example, issues of safety, comfort and accessibility to destinations appear to be more important to women’s overall travel behavior than to men’s . This may partly explain the low transport cycling rates for women, as studies have found that women are more likely than men to report safety concerns as constraining their transport cycling . Gender differences may also be explained by the nature of a typical transport cycling journey in Australia. The average cycle commute trip length is high, 10 km in Queensland  and 11-15 km in Melbourne , generally higher than seen in Europe . Such trips may appeal to the most motivated, fit and sporty recreational cyclists, as the commute to work becomes an opportunity to improve fitness; however, the long distances may discourage other cyclists and women disproportionately so. International data indicate that women are more likely than men to trip chain as part of their commute, given their responsibilities for transporting children and other household members and to do the household shopping . These tasks require different cycling equipment and cycling style to those which are common in countries such as Australia .
Although gender differences are noted in travel patterns in general and in transport cycling specifically, studies have tended to make broad comparisons, and few studies have focused on modeling male and female cycling patterns separately [13, 17]. Given the low prevalence of transport cycling in countries like Australia, this modeling is difficult to achieve in studies of the general population as so few people report cycling. Studies which explicitly sample cyclists can provide valuable data on gender differences in cycling behavior. The primary aims of this study were to examine, in a population of current cyclists, gender differences in cycling patterns and in motivators and barriers to cycling, separately for recreational and transport cycling. A secondary aim was to explore possible overlaps in cycling patterns between recreational and transport cycling to better understand gender differences in cycling for different purposes. Most of the data collected to address our aims were quantitative; however, some qualitative data were gathered to expand the knowledge obtained from the quantitative findings.
Sampling and study protocol
Adult cyclists residing in Queensland were administered an online survey to assess their attitudes, behaviors and cycling experiences. The sampling frame was the adult membership (aged ≥18 years) of Bicycle Queensland (BQ), a state-wide community organization that promotes recreational and transport cycling, organizes community bike rides for all levels of cycling ability and advocates for better cycling facilities and improved safety (see bq.edu.au). A small proportion of members are competitive cyclists. As found for Australian cyclists more broadly , most members cycle only for recreation, with less than half cycling for transport .
BQ sent email invitations, with a link to the survey, to the ‘primary members’ of member households, to encourage all adult BQ members of the household to participate. One week later, BQ sent reminder emails. To further encourage participation, respondents could enter into prize draws to win bicycle accessories and receive the study findings. This study was conducted with the approval of The University of Queensland Human Research Ethics Committee.
As reported elsewhere , 2085 of 4469 invited households responded (47% response rate). These households included 2356 individual respondents. Of these respondents, those who did not complete the survey (n = 189), indicated that they were not members of BQ (n = 245) or reported a residence outside Queensland (n = 62) were excluded from analysis, leaving data from 1862 respondents available for inclusion in this analysis.
Most questions were adapted from those used previously , although new demographic information questions were added to better characterize the sample and additional barriers were added to reflect the climate, topography and policies in Queensland.
Respondents completed standard demographic questions (sex, age, educational level, employment status, home postcode, body mass index) and details about their home environment, including the number of cars available for use, and the household composition. Home postcodes were used to determine socio-economic indexes for areas (SEIFA). This measure uses 2006 Census variables to assess the relative socio-economic advantage or disadvantage of Australian geographic areas , and for this study, respondents’ residential SEIFA. Areas are divided into deciles with higher deciles representing greater advantage. Using postal codes, respondents were also classified as living in a major city; inner regional area; or outer regional, rural or very rural area. Body mass index (BMI; kg/m2) was calculated from self-reported height without shoes and weight without clothes or shoes.
Respondents reported the length of time they had been cycling as an adult (weeks, months, years), their cycling frequency (5–7 days/week to never in the last year), and the purposes of their cycling (recreation [just for fun or exercise], competition, and/or transport [as a means of getting to and from places]).
Transport cycling behavior
Respondents reported whether they rode for transport in the previous week. Those who responded yes reported the number of bicycle trips taken for transport in the previous week (counting each single trip to a place as one trip and each return trip from a place as another trip), the total time spent cycling for transport in the previous week, and the destinations of these trips (work, university/vocational school/school, shops, recreational venues, friends/relatives). Respondents also described the bicycle routes they used in the last week and their route preferences given current traffic conditions and patterns. For these items, they selected one or more of three options: off-road or shared pedestrian/bike paths; designated on-road bike lanes, such as the bicycle awareness lanes painted green; and on the road (no bicycle lanes).
Recreational cycling behavior
Respondents reported whether they cycled for recreation in the previous week. Those who responded yes reported the number of recreational bicycle trips taken in the previous week and the total time spend cycling for recreation that week. They were instructed not to include any cycling reported already as transport cycling. Last, they reported the bicycle routes they used in the last week for recreational cycling and their route preferences, using the same response options included in the items asking about transport cycling routes used and preferred.
Motivating and constraining factors
In keeping with social-ecological models of behavioral determinants, respondents who had cycled for any purpose in the previous year were asked about personal, social and perceived environmental factors that were hypothesized to motivate or constrain cycling behavior, as identified in previous research . Respondents rated the importance of 18 factors in motivating them to cycle, using a 4-point scale (very important to not at all important). These were dichotomized as important (important and very important = 1) or not important (not at all important and slightly important = 0). Respondents were also asked whether 20 factors made it difficult for them to cycle more. Responses were on a 4-point scale (major constraint to not a constraint). These were dichotomized as a constraint (moderate and major constraints = 1) or not a constraint (minor constraint or not a constraint = 0). Last, respondents reported in an open-ended response format any other constraints or difficulties that deterred them from cycling in their local area.
The Active Australia physical activity questions were used to assess physical activity (PA) levels. Respondents reported time spent in the last week (in ≥ 10-minute sessions) walking (for recreation or exercise or to get to and from place to place), and in moderate- and vigorous-intensity leisure-time physical activities, and they were asked to include their cycling in their responses. Using standard procedures , a total score was calculated as the sum of the minutes spent in each PA multiplied by an assigned metabolic equivalent value (MET): walking = 3.0 METs; moderate-intensity PA = 4.0 METs; vigorous-intensity PA = 7.5 METs, to account for differences in intensity among the activities. A summary score of ≥600 MET minutes per week is equivalent to 150 minutes per week of moderate-intensity PA, the cut-off for meeting Australian PA guidelines . Thus, those reporting ≥600 MET minutes per week were considered to be meeting PA guidelines.
All quantitative analyses were conducted with STATA/SE 10.1 (StataCorp, College Station, Texas). Missing data were imputed using the Hotdeck procedure that uses all other available data to impute a value for categorical variables. The survey (svy) command was used to account for clustering of respondents within households (StataCorp, 2007). Descriptive statistics were generated for all quantitative study variables. Logistic and linear regression modeling was used to examine whether gender was associated with the transport and recreational cycling behavior variables, after adjusting for other demographic characteristics and for cycling patterns. For examining associations between gender and non-normal variables (times spend in each type of cycling and in total PA) the same modeling was performed except ordered logistic regression was used with the outcome variable categorized into quintiles. Moreover, given apparent duplication of transport and recreational cycling trips reported by some transport cyclists, recreational cycling modeling was limited to the subgroup of respondents who reported no transport cycling in the previous week. Significance was set at p < 0.05.
Two authors (KCH, SS) analyzed the open-ended survey responses. The qualitative data collected on usage of, and preferences for, cycling paths were used to place participants into the respective usage and preference categories already defined in the survey (e.g., any description of cycling away from roads was coded into the existing off-road or shared pedestrian/bike paths category) and to better describe these categories. KCH and SS each independently coded these data into the quantitative categories, and then discussed discrepancies between their coding before reaching consensus. The data collected on cycling constraints were used to expand our understanding of the barriers to cycling beyond the categories included in the questionnaire. For the first step, KCH and SS independently reviewed the qualitative constraint data to identify major themes. Next, they used these themes to independently code the constraint data and to look for any gender differences. Discrepancies between coders were discussed in team meetings and consensus was used to determine the final themes. As the final step in the analyses of all the qualitative data, KH summarized the findings in consultation with SS.
Characteristics of the total sample and men and women separately (n = 1862), Queensland, Australia
% of total sample a
% of men a
% of women a
p = 0.0001
p = 0.021
No tertiary degree
Trade/apprenticeship or certificate/diploma
Postgraduate university degree
Live with adults and no children
Live with adults and children
No. of cars in household
p = 0.003
Full-time paid work
Part-time paid work
Retired or not in paid work
p = 0.18
Decile 10 (most advantaged)
Deciles 1-6 (most disadvantaged)
p = 0.10
Outer suburban or more remote
Normal (BMI <25)
Overweight (BMI 25- < 30)
Obese (BMI ≥ 30)
Years of cycling as an adult
5 - < 10
2 - < 5
0 - < 2
At least once/month
At least once in previous 3 months
At least once in the last year
Cycle purpose last week
Recreation and transport
Did not cycle last week
Total physical activity (mins/week)
p = 0.87
Not meeting guidelines
Transport cycling patterns
Gender differences in transport and recreation cycling patterns in the previous week: results of multivariable analysis a
% of men
% of women
Gender differences b
Transport cycling in sample (n = 1862)
Work or study
Transport cycling in the last week (n=827)
Cycle routes used
On-road designated cycle lane
Cycle routes preferred
On-road designated cycle lane
Recreational cycling in sample (n = 1862)
Recreational cycling in the last week (n=1318)
Cycle routes used
On-road designated cycle lane
Cycle routes preferred
On-road designated cycle lane
Most transport cyclists used a combination of cycle routes. Based on the qualitative data, we included within the ‘off-road’ category bush paths (e.g., through parks) and footpaths. Qualitative responses also indicated that some cyclists qualified their responses on usage or preference for ‘on-road’ (e.g., cycling ‘on road shoulders’ or ‘on quiet streets only’). Women were more likely to use off-road paths (p = 0.011) whereas men were more likely to cycle on-road (p = 0.045). However, few men or women preferred to cycle on the road, with women less likely than men to prefer cycling on the road (p = 0.020). Interestingly, more men and women were cycling off-road than would prefer to do so. This may be explained in part by qualitative data indicating that respondents perceived that most off-road paths were not direct routes to destinations. One woman reported, “The most direct route is along major motorways that do not have any cycle path option, so consequently I have to ride kilometers out of the way.” It may also reflect the observation by respondents that off-road travel typically required sharing congested paths with pedestrians and animals. Not surprising then, our qualitative findings indicated a preference by many transport cyclists for dedicated cycle-only paths separated from both motorists and pedestrians.
Recreational cycling patterns
More men than women cycled for recreation in the previous week (p = 0.003; Table 2). Among the 783 respondents who cycled for recreation but not for transport in the previous week, the time spent in recreational cycling was higher for the 553 men (proportional OR with males as referent = 0.64 [95%CI 0.47, 0.88]), with men spending a median of 279 mins (IQR 180, 420) and the 230 women, a median of 240 mins (IQR 180, 360). The men also took more recreational cycling trips than did the women (b = -.44 [95% CI = -0.68, -0.20]; p < 0.001]): the adjusted mean number of recreational cycling trips for men was 2.87 trips per week (95%CI 2.74, 3.01), and for women, 2.48 trips (95%CI 2.28, 2.64). As shown for transport cycling, for recreational cycling there were no gender differences in MET minutes of total PA (proportional OR with males as referent = 0.78 [95%CI 0.57, 1.08]), with a median MET minutes for men of 2760 [IQR 1725, 4140] and for women of 2880 [IQR 1710, 4230]). There was also no gender difference in the proportion of total PA from recreational cycling (proportional OR with males as referent = 0.73 [95%CI 0.52, 1.01]), with a median proportion of minutes from recreational cycling for men of 65.2% (IQR 40.0%, 87.5%) and for women of 52.7% (IQR 30.8%, 85.7%).
As found for transport cyclists, most recreational cyclists used a combination of paths. Based on the qualitative data, the off-road category included bush paths (e.g., called dirt, bush, forest, park, fire, mountain bike tracks), rail trails, the beach, and footpaths. Female recreational cyclists were more likely to use off-road paths (p = 0.001) while their male counterparts were more likely to cycle on-road (p = 0.025) (Table 2). Moreover, women were less likely than men to prefer cycling on-road (p < 0.001), but more likely to prefer cycling off-road (p < 0.001). More recreational than transport cyclists preferred cycling on-road although cycling on-road was the least preferred option among both types of cyclists.
As found for transport cyclists, the qualitative data indicated that many recreational cyclists preferred designated bicycle paths away from both motor vehicle and pedestrian traffic. Those who cycled for recreation on bush paths, rail trails, or the beach said these were the preferred paths as well. Some who preferred on-road cycling quantified their response (e.g., ‘on road in slower traffic’, ‘on road with wide shoulders,’ ‘quiet sealed country roads’, ‘early morning quiet roads’).
Motivators for men and women to cycle, of total sample, transport-only cyclists, and recreation-only cyclists a
Respondents who cycled within the last year (n = 1849) b
Respondents who only cycled for transport in the last week (n = 292) b
Respondents who only cycled for recreation in the last week (n = 783) b
Improving / maintaining fitness
Fun and enjoyment
Relaxation / stress reduction
Building physical activity into my busy lifestyle
To get outside in the fresh air
It is a challenge
It is a low impact activity
Time out to myself
Other health reasons
It is something active I can do with other people
It is a convenient form of transportd
Concerns about the environmentd
Confidence in my cycling ability
It is a cheap form of transportd
Seeing other people cycling
Participating in a cycling event or program like Ride to Work Day
Encouragement from family, friends or work colleagues
Encouragement from supervisors or employerd
Top motivators for most male and female transport-only cyclists also included it being a convenient and cheap form of transport and having concerns about the environment, with women more likely than men to agree that cycling being a cheap form of transport and concerns about the environment were important motivators. For male and female recreation-only cyclists, the top motivators included the social aspect (something active I can do with other people), with the women were more likely to agree that this was a motivator.
Constraints on men’s and women’s cycling, of total sample, transport-only cyclists, and recreation-only cyclists a
Respondents who cycled within the last year (n = 1849)
Respondents who only cycled for transport in the last week (n = 292)
Respondents who only cycled for recreation in the last week (n = 783)
Gender differences b
Gender differences b
Gender differences b
Concerns about cycling in traffic
Aggression from motorists
Rainy or stormy weather
Lack of time
Lack of safe places to park or store my bicycle at places I would want to ride my bicycle to
Inhaling car fumes when cycling on the road
Lack of shower and changing facilities at places I would want to ride my bicycle to
Inability to put my bicycle on public transportation (buses, trains)
Decrease in daylight hours during winter months
Hot or humid weather
Living too far away from places I would want to ride my bike to
Illness, injury or health problems
The presence of hills
Lack of knowledge about local cycling routes
Cost of cycling (bicycles, accessories, clothing, rides)
Lack of fitness
Lack of confidence in bicycle maintenance, such as repairing a puncture
Lack of confidence in my cycling ability or skills
The qualitative data indicated that inadequate infrastructure was a major barrier for both men and women. Most importantly, respondents perceived that the infrastructure was unsafe for cycling. These data expand upon the quantitative findings that concern about cycling in traffic was the primary barrier for both men and women and for both recreational and transport cyclists, and the data support our findings about men’s and women’s cycle route preferences. One major infrastructural concern was the poor conditions of existing road and cycle paths. As one woman explained, “They just mark off a crappy, potholed gravel strewn section of the usual road and whack a picture of a bike on it and call it a bike lane.” Another woman explained that the city had “not really taken into account the way cycle traffic flows” in road design. As a consequence of the perceived inadequate cycling infrastructure, respondents reported that they encountered rough surfaces, uneven and little maintained road shoulders, and that “rural roads [that] are very third world with being narrow, pitted and cracked [with] loose verges.” The other major safety concern was that the infrastructure made interactions with motorists on-road and pedestrians and animals off-road unavoidable. Respondents reported concern with the narrowing of bicycle access over bridges and roundabouts, the lack of safe crossings for cyclists across heavy traffic, and, most mentioned, “disconnects between pathways.” Respondents in rural areas in particular described the “near lack” of on-road cycle paths or bicycle paths. Such concerns with the roads help explain the earlier finding that more men and women were cycling on the road than would prefer to do so. Sharing paths with pedestrians was also cited as a barrier as these paths were reported to be congested at certain times of day with pedestrians often not aware of other path users. This finding may in part explain why the quantitative data collected about cycling route preferences indicated that more cyclists were cycling off-road than would prefer to do so. Moreover, many respondents reported danger from animals. A few described attacks from dogs or issues with other animals (snakes, wild pigs, dingos) crossing paths or roads, making travel by bicycle unsafe. The main animal culprit however were magpies and other nesting birds that would attack cyclists venturing near their nests during early summer.
In this sample of Queensland, Australia cyclists, both recreational and transport cycling was predominately undertaken by highly educated, full-time employed, middle-aged men and for recreation. This finding supports other Australian data showing that most cycling is by middle-aged men and for recreation  and is consistent with data from Melbourne and from other car-dependent countries showing women cycle less for transport [11, 12, 15, 17, 22–25] and for recreation . In contrast, in countries with high rates of cycling, cycling rates are similar between men and women [5, 11].
The gender difference in transport cycling was due to men’s greater likelihood of commuter cycling. In contrast, in the Netherlands, a high cycling country, women are just as likely to cycle to work as men . Our findings may reflect women’s lower willingness to cycle the relatively long commuting distances in Australia, with constraints such as climate and weather factors, poor fitness levels, and lack of confidence in bicycle maintenance and in their own cycling skills compounding travel distance for women. Men’s and women’s low and similar rates of cycling to non-work destinations have also been found in Melbourne  and likely reflect the bicycle infrastructure in Australia, which supports longer work commutes from suburbs to urban centers . The low rates may also reflect the key motivation for men and women to cycle, fitness, which may encourage some cyclists to take advantage of opportunities for long bicycle trips to work, but discourage their taking shorter trips for other purposes. In contrast, a study in Minnesota (US) found that women are more likely than men to cycle for non-commute trips . In Tokyo, where men and women report high rates of weekly cycling, women are only half as likely as men to bicycle to work but are more likely to cycle for non-commute trips . Thus, the focus in Australian capital cities on providing commuter cycling routes into city centers, while neglecting cycling infrastructure in suburban areas, may be constraining transport cycling in general, and women’s participation in transport cycling in particular.
Our study showed that, on average, both male and female transport and recreational cyclists are exceeding physical activity guidelines , with the average time spent cycling for either purpose exceeding 200 minutes per week. Likewise, findings from a national Australian survey indicate that cyclists accumulate over 200 minutes of physical activity per week . Thus, Australian cyclists are an active subgroup compared with the general Australian population, 57% of whom are meeting physical activity guidelines . In contrast, when transport cycling is socially inclusive, as in many high-cycling countries, population subgroups that often have low levels of physical activity (e.g., women) are more likely to achieve adequate levels of physical activity [30–34].
As found in the state of Victoria  and in cities in Canada  and the US [17, 35, 36], men and women in this study preferred cycling routes separated from motorists. Our study adds that on-road routes were even less preferred for transport cycling than recreational cycling by both men and women, possibly because recreational cyclists can choose the day and time of their cycling and thus can ride when roads are quieter, whereas transport cyclists may have less choice, particularly for commuting to work.
This study also adds to what we know about motivators and constraints to cycling in Australia. As in other Australian states [15, 37, 38] and elsewhere [3, 22, 24], top motivators for cycling were related to health, fitness and enjoyment. These were important motivators for men and women and for transport and recreational cyclists, although women tended to perceive other factors to be motivating as well. Motivators for transport cycling also included perceptions about the cost and convenience of bicycle travel, and about the environment, which have been documented previously [15, 22, 24, 37–39]. Our study adds that these factors are more motivating to women than to men. In contrast, in high-cycling countries such as the Netherlands, cycling is more commonly seen as an appealing, convenient and safe alternative to car travel in urban areas by men and women, with the health and exercise benefits more incidental than deliberative .
Whereas in countries with good bicycling infrastructure most barriers tend to be personal [3, 40], infrastructure and other environmental barriers were clearly important constraints in our sample. The key constraints were related to traffic conditions, motorist aggression, and safety, consistent with barriers reported for other Australian cities [15, 37, 41, 42] and in studies from the UK and US [22, 24, 43–46], as is the finding that safety is more of a concern for women than men. Findings that personal, social, and policy factors constrained cycling also support previous literature [15, 22, 24, 25, 47, 48]. Our study further showed that women perceived more constraints, and some differences were noted between female transport-only and recreation-only cyclists that reflect cycling purpose, most notably, that traffic and transport factors were important constraints to more female transport-only cyclists and weather and climate factors were important constraints to more female recreation-only cyclists.
Strengths and limitations of the study should be considered. Strengths included the mixed method design, unusual for survey studies; the relatively large sample, which allowed for a detailed examination of gender differences in two types of cycling; and the inclusion of a large number of potential correlates, for statistical control of socio-demographic variables that have not been previously examined in studies of gender differences in cycling [12, 15] but that are known correlates of physical activity . The major limitation was the sampling from a cycling community group, which may have resulted in a sample of respondents who were more experienced and motivated cyclists than other samples of cyclists and thus may have exhibited different cycling behaviors, motivators and barriers from those of other cyclists. Comparisons with Australian data on cyclists  indicate that our findings are biased towards middle-aged adults and slightly biased toward men. The sample characteristics do reflect that in Australia, cycling is predominantly undertaken by middle-aged men , and the sample included a good cross-section of different types of riders. Our sample also tended to be of relatively high socio-economic status, which supports travel data from elsewhere [50–52] that suggest a socio-economic gradient in transport cycling in Australian and other car-dependent English-speaking countries. It should also be noted that our response rate of 47% is low but excellent for an online survey  and is comparable or better than response rates found for some recent large population-based studies in Australia [7, 54, 55]. Other limitations include the reliance on cross-sectional self-report data that only captured cycling patterns, behaviors and perceptions at one point in time and were subject to recall bias.
Our findings provide evidence of a substantial overlap between recreational and transport cycling in Australia. Namely, almost all transport-only cyclists, both male and female, reported that fitness improvement or maintenance was their main motivation for transport cycling; these cyclists were primarily cycling only to a destination (work) far enough away from home to allow for fitness training; and both transport and recreational cyclists were highly physically active, with participation in either type of cycling making a substantial contribution to physical activity levels. We conclude that promoting transport cycling, particularly commuting cycling, to recreational cyclists, may increase cycling for transport, but most likely among men and the most athletic. With literature from the transport field indicating women choose their transport mode based on safety and accessibility , adoption of transport cycling by women will require conversion in Australian society to a transport cycling culture, one in which there is a strong commitment to prioritizing transport cycling over car travel for short daily trips; providing bicycle infrastructure and end of trip facilities to support short, safe and direct trips; and promoting everyday cycling in city and suburban neighborhoods. The findings from this study support prior work  that suggests that a strategy of creating system-wide networks of designated bicycle paths will assist in achieving higher levels of more socially-inclusive transport cycling. Our findings also suggest differences in men’s and women’s cycling patterns, motivators and constraints that should be considered in efforts to promote cycling. In summary, the establishment of cycling as a convenient, safe and enjoyable form of transport for a wide range of trip purposes in multiple settings is likely to increase the bicycle mode share of transport, and, in particular, encourage more women to go along for the ride.
Dr. Heesch was supported by a NHMRC program grant in physical activity and health (ID#301200) at The University of Queensland, School of Human Movement Studies. Dr. Sahlqvist was supported by funds from the Engineering and Physical Sciences Research Committee at the Medical Research Council, Epidemiology Unit. The authors wish to thank the Bicycle Queensland staff for their assistance with development of the questionnaire and study design, recruitment of their members, and collection of incentives for the prize draws. We would like to give a special thank you to those Bicycle Queensland members who took the time to complete the online survey for this study.
- Oja P, Titze S, Bauman A, de Geus B, Krenn P, Reger-Nash B, Kohlberger T: Health benefits of cycling: a systematic review. Scand J Med Sci Sports. 2011, 21 (4): 496-509. 10.1111/j.1600-0838.2011.01299.x.View ArticleGoogle Scholar
- Wen LM, Rissel C: Inverse associations between cycling to work, public transport, and overweight and obesity: findings from a population based study in Australia. Prev Med. 2008, 46 (1): 29-32. 10.1016/j.ypmed.2007.08.009.View ArticleGoogle Scholar
- Engbers LH, Hendriksen IJ: Characteristics of a population of commuter cyclists in the Netherlands: perceived barriers and facilitators in the personal, social and physical environment. Int J Behav Nutr Phys Act. 2010, 7: 89-10.1186/1479-5868-7-89.View ArticleGoogle Scholar
- Woodcock J, Banister D, Edwards P, Prentice AM, Roberts I: Energy and health 3 - energy and transport. Lancet. 2007, 370 (9592): 1078-1088. 10.1016/S0140-6736(07)61254-9.View ArticleGoogle Scholar
- Pucher J, Buehler R, Bassett DR, Dannenberg AL: Walking and cycling to health: a comparative analysis of city, state, and international data. Am J Public Health. 2010, 100 (10): 1986-1992. 10.2105/AJPH.2009.189324.View ArticleGoogle Scholar
- Australian Sports Commission: Participation in Exercise, Recreation, and Sport. 2010, Canberra: Annual Report 2010Google Scholar
- Munro C, Sinclair KM: Australian Cycling Participation 2011. 2011, Sydney: Ausroads LtdGoogle Scholar
- Park H, Lee YJ, Shin HC, Sohn K: Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist. Transportation. 2011, 38 (2): 305-319. 10.1007/s11116-010-9299-4.View ArticleGoogle Scholar
- Sahlqvist S, Heesch KC: Characteristics of utility cyclists in Australia: an examination of the associations between individual, social and environmental factors and utility cycling. J Phys Act Health. 2012, 9: 818-828.Google Scholar
- Garrard J, Handy S, Dill J: Women and cycling. City Cycling. Edited by: Pucher J, Buehler R. 2012, MIT Press, Cambridge, USAGoogle Scholar
- Pucher J, Buehler R: Making cycling irresistible: lessons from the Netherlands, Denmark and Germany. Transpt Rev. 2008, 28 (4): 495-528. 10.1080/01441640701806612.View ArticleGoogle Scholar
- Twaddle H, Hall F, Bracic B: Latent bicycle commuting demand and effects of gender on commuter cycling and accident rates. Transp Res Rec. 2010, 2190: 28-36. 10.3141/2190-04.View ArticleGoogle Scholar
- Meloni I, Bez M, Spissu E: Activity-based model of women's activity-travel patterns. Transp Res Rec. 2009, 2125: 26-35. 10.3141/2125-04.View ArticleGoogle Scholar
- Schintler L, Root A, Button K: Women's travel patterns and the environment - an agenda for research. Transp Res Rec. 2000, 1726: 33-40. 10.3141/1726-05.View ArticleGoogle Scholar
- Garrard J, Crawford S, Hakman N: Revolutions for Women: Increasing Women's Participation in Cycling for Recreation and Transport. 2006, Melbourne: Deakin UniversityGoogle Scholar
- van Wee B, Rietveld P, Meurs H: Is average daily travel time expenditure constant? In search of explanations for an increase in average travel time. J Transp Geogr. 2006, 14: 109-122. 10.1016/j.jtrangeo.2005.06.003.View ArticleGoogle Scholar
- Krizek KJ, Johnson PJ, Tilahun N: Gender differences in bicycling behavior and facility preferences. In Research on Women's Issues in Transportation, Conference Proceedings 35, Volume 2: Technical Papers. 2004, Washington, DC: Transportation Research Board, 31-40.Google Scholar
- Heesch KC, Garrard J, Sahlqvist S: Incidence, severity and correlates of bicycling injuries in a sample of cyclists in Queensland, Australia. Accid Anal Prev. 2011, 43 (6): 2085-2092. 10.1016/j.aap.2011.05.031.View ArticleGoogle Scholar
- Australian Bureau of Statistics: 2033.0.55.001 - Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA). 2008, Australia: Australia - data only, 2006Google Scholar
- Brown WJ, Bauman AE: Comparison of estimates of population levels of physical activity using two measures. Aust N Z J Public Health. 2000, 24 (5): 520-525. 10.1111/j.1467-842X.2000.tb00503.x.View ArticleGoogle Scholar
- Australian Government Department of Health and Aged Care: An Active Way to Better Health: National Physical Activity Guidelines for Adults. 1999, Australian Government Publishing Service, CanberraGoogle Scholar
- Bopp M, Kaczynski AT, Besenyi G: Active commuting influences among adults. Prev Med. 2012, 54: 237-241. 10.1016/j.ypmed.2012.01.016.View ArticleGoogle Scholar
- Garrard J, Rose G, Lo SK: Promoting transportation cycling for women: the role of bicycle infrastructure. Prev Med. 2008, 46 (1): 55-59. 10.1016/j.ypmed.2007.07.010.View ArticleGoogle Scholar
- Gatersleben B, Appleton KM: Contemplating cycling to work: Attitudes and perceptions in different stages of change. Transp Res Part A-Policy Prac. 2007, 41 (4): 302-312. 10.1016/j.tra.2006.09.002.View ArticleGoogle Scholar
- Winters M, Friesen MC, Koehoorn M, Teschke K: Utilitarian bicycling: a multilevel analysis of climate and personal influences. Am J Prev Med. 2007, 32 (1): 52-58. 10.1016/j.amepre.2006.08.027.View ArticleGoogle Scholar
- Kamphuis CB, Giskes K, Kavanagh AM, Thornton LE, Thomas LR, van Lenthe FJ, Mackenbach JP, Turrell G: Area variation in recreational cycling in Melbourne: a compositional or contextual effect?. J Epidemiol Community Health. 2008, 62 (10): 890-898. 10.1136/jech.2007.067116.View ArticleGoogle Scholar
- State of Queensland (Department of Transport and Main Roads): Queensland Cycle Strategy 2011-2021. 2011, Fortitude Valley, Queensland: State of QueenslandGoogle Scholar
- Japan Ministry of Land: Infrastructure, Transport and Tourism: Tokyo Person Trip Survey 2008. 2008, Tokyo: Government of JapanGoogle Scholar
- Armstrong T, Bauman A, Davies J: Physical Activity Patterns of Australian Adults. Results of the 1999 National Physical Activity Survey. Catalogue Number CVD 10. 2000, Canberra: Australian Institute of Health and WelfareGoogle Scholar
- Andersen LB, Schnohr P, Schroll M, Hein HO: All-cause mortality associated with physical activity during leisure time, work, sports, and cycling to work. Arch Intern Med. 2000, 160: 1621-1628. 10.1001/archinte.160.11.1621.View ArticleGoogle Scholar
- Matthews CE, Jurj AL, Shu XO, Li HL, Yang G, Li Q, et al: Influence of exercise, walking, cycling, and overall nonexercise physical activity on mortality in Chinese women. Am J Epidemiol. 2007, 165: 1343-1350. 10.1093/aje/kwm088.View ArticleGoogle Scholar
- Barnett TA, Gauvin L, Craig CL, Katzmarzyk PT: Distinct trajectories of leisure time physical activity and predictors of trajectory class membership: a 22 year cohort study. Int J Behav Nutr Phys Act. 2008, 5: 57-10.1186/1479-5868-5-57.View ArticleGoogle Scholar
- Berrigan D, Troiano RP, McNeel T, Disogra C, Ballard-Barbash R: Active transportation increases adherence to activity recommendations. Am J Prev Med. 2006, 31: 210-216. 10.1016/j.amepre.2006.04.007.View ArticleGoogle Scholar
- van Lenthe FJ, Brug J, Mackenbach JP: Neighbourhood inequalities in physical inactivity: the role of neighbourhood attractiveness, proximity to local facilities and safety in the Netherlands. Soc Sci Med. 2005, 60: 763-775. 10.1016/j.socscimed.2004.06.013.View ArticleGoogle Scholar
- Akar G, Clifton KJ: Influence of individual perceptions and bicycle infrastructure on decision to bike. Transp Res Rec. 2009, 165-172. 2140Google Scholar
- Dill J: Bicycling for transportation and health: the role of infrastructure. J Public Health Policy. 2009, 30 (Suppl 1): S95-S110.View ArticleGoogle Scholar
- Bonham J, Koth B: Universities and the cycling culture. Transp Res Part D - Transp Environ. 2010, 15 (2): 94-102. 10.1016/j.trd.2009.09.006.View ArticleGoogle Scholar
- McManus A, Smith J, McManus J, MacDonald E, Williams M: Evaluation of an alternative transport initiative in Perth, Western Australia, 2000-04. Health Promot J Austr. 2005, 16 (3): 184-188.Google Scholar
- The National Heart Foundation, Cycling Promotion Fund: Riding a Bike for Transport. 2011 Survey Findings. 2011Google Scholar
- de Geus B, De Bourdeaudhuij I, Jannes C, Meeusen R: Psychosocial and environmental factors associated with cycling for transport among a working population. Health Educ Res. 2008, 23: 697-708.View ArticleGoogle Scholar
- Daley A, Macarthur C, Stokes-Lampard H, McManus R, Wilson S, Mutrie N: Exercise participation, body mass index, and health-related quality of life in women of menopausal age. Br J Gen Pract. 2007, 57 (535): 130-135.Google Scholar
- O'Connor JP, Brown TD: Riding with the sharks: serious leisure cyclist's perceptions of sharing the road with motorists. J Sci Med Sports. 2010, 13 (1): 53-58. 10.1016/j.jsams.2008.11.003.View ArticleGoogle Scholar
- Basford L, Reid S, Lester T, Thomson J, Tolmie A: Drivers' Perceptions of Cyclists, TRL549. 2002, Berkshire, UK: TRL LimitedGoogle Scholar
- Christmas S, Helman S, Buttress S, Newman C, Hutchins R: Cycling, Safety and Sharing the Road: Qualitative Research with Cyclists and Other Road Users. 2010, London: Department of TransportGoogle Scholar
- Emond CR, Tang W, Handy SL: Explaining gender difference in bicycling behavior. Transp Res Rec. 2009, 16-25. 2125Google Scholar
- Sibley A: Women's Cycling Survey: Analysis of Results. 2010, WI: Association of Pedestrian and Bicycle ProfessionalsGoogle Scholar
- Daley M, Rissel C, Lloyd B: All dressed up and nowhere to go? A qualitative research study of the barriers and enablers to cycling in inner Sydney. Road Transp Res. 2007, 16 (4): 42-52.Google Scholar
- Titze S, Stronegger WJ, Janschitz S, Oja P: Environmental, social, and personal correlates of cycling for transportation in a student population. J Phys Act Health. 2007, 4 (1): 66-79.Google Scholar
- Trost SG, Owen N, Bauman AE, Sallis JF, Brown W: Correlates of adults' participation in physical activity: review and update. Med Sci Sport Exerc. 2002, 34: 1996-2001. 10.1097/00005768-200212000-00020.View ArticleGoogle Scholar
- Merom D, van der Ploeg HP, Corpuz G, Bauman AE: Public health perspectives on household travel surveys active travel between 1997 and 2007. Am J Prev Med. 2010, 39 (2): 113-121. 10.1016/j.amepre.2010.04.007.View ArticleGoogle Scholar
- Ltd BCP: Walking and Cycling: Census Analysis. 2008, Melbourne: Bartley Consulting Pty LtdGoogle Scholar
- Buehler R, Pucher J, Merom D, Bauman A: Active travel in Germany and the U.S. Contributions of daily walking and cycling to physical activity. Am J Prev Med. 2011, 41: 241-250. 10.1016/j.amepre.2011.04.012.View ArticleGoogle Scholar
- Manfreda KL, Bosniak M, Berzelak J, Haas I, Vehovar V: Web surveys versus other survey modes - A meta-analysis comparing response rates. Int J Mark Res. 2008, 50 (1): 79-104.Google Scholar
- Gebel K, Bauman A, Owen N, Foster S, Giles-Corti B: The Heart Foundation's Physical Activity Advisory Committee: The Built Environment and Walking. 2008, Canberra: National Heart Foundation of AustraliaGoogle Scholar
- Mummery WK, Lauder W, Schofield G, Caperchione C: Associations between physical inactivity and a measure of social capital in a sample of Queensland adults. J Sci Med Sport. 2008, 11 (3): 308-315. 10.1016/j.jsams.2007.06.002.View ArticleGoogle Scholar
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