Added: Mikayla Seiber - Date: 15.01.2022 23:21 - Views: 18689 - Clicks: 5569
Metrics Alternative female with bike. 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.
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 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 deed 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. Cycling offers health benefits, including improved cardio-respiratory fitness and decreased risk of all-cause and cardiovascular mortality [ 1 ].
Commuter cycling is negatively associated with overweight and obesity [ 2 ] and may help employees meet physical activity recommendations of moderate- to vigorous-intensity physical activity for 30 minutes per day, 5 days per week [ 3 ]. Active travel is also good for the environment as it can reduce traffic congestion, air and noise pollution, carbon emissions and fossil fuel consumption [ 4 ].
However, cycling for recreation is the fourth most commonly-reported physical activity among Australian adults [ 6 ]. Given that recreational cyclists already possess the motivation, equipment and skill, it has been argued, that in countries like Australia with low rates Alternative female with bike transport cycling, recreational cyclists might comprise a useful target group for promoting cycling for transport [ 8 ]. 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 [ 7 ], but even among cyclists, more men cycle for transport. 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 [ 1213 ]. 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 [ 15 ].
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 [ 9 ] and km in Melbourne [ 15 ], generally higher than seen in Europe [ 16 ]. 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 [ 12 ]. These tasks require different cycling equipment and cycling style to those which are common in countries such as Australia [ 10 ]. 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 [ 1317 ].
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. Adult cyclists residing Alternative female with bike Queensland were administered an online survey to assess their attitudes, behaviors and Alternative female with bike experiences. A small proportion of members are competitive cyclists.
As found for Australian cyclists more broadly [ 7 ], most members cycle only for recreation, with Alternative female with bike than half cycling for transport [ 9 ]. One week later, BQ sent reminder s. To further encourage participation, respondents could enter into prize draws to win bicycle accessories and receive the study findings. These households included individual respondents. Most questions were adapted from those used ly [ 15 ], 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 of cars available for use, and the household composition. 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. Respondents reported whether they rode for transport in the week.
Respondents also described the bicycle routes they used in the last week and their route preferences given current traffic conditions and patterns. Respondents reported whether they cycled for recreation in the week. Those who responded yes reported the of recreational bicycle trips taken in the 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.
In keeping with social-ecological models of behavioral determinants, respondents who had cycled for any purpose in the year were asked about personal, social and perceived environmental factors that were hypothesized to motivate or constrain cycling behavior, as identified in research [ 15 ]. Respondents rated the importance of 18 factors in motivating them to cycle, using a 4-point scale very important to not at all important. 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. 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. 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 for clustering of respondents within households StataCorp, 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 week.
The qualitative data collected on usage of, and preferences for, cycling paths were used to place participants into the respective usage and preference already defined in the survey e. KCH and SS each independently coded these data into the quantitativeand 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 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. Compared with men, women tended to be ificantly younger, more educated, less likely to be living with children, living in a household with one car, working part-time and of a normal weight Table 1.
The main purpose of cycling for both men and women was for recreation. Few men and women reported to cycle for transport only; instead, those who cycled for transport also tended to cycle for recreation. Most men and women were meeting PA guidelines. Most transport cyclists used a combination of cycle routes. 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.
Not surprising then, our qualitative findings indicated a preference by many transport cyclists for dedicated cycle-only paths separated from both motorists and pedestrians. 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.Alternative female with bike
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