1.1. Inclusive bicycling

The increased investment in cycling and growth in bicycle mode share raises important questions about who is benefitting from these investments. Researchers and practitioners are increasingly recognizing that the benefits (e.g., access to opportunities) and burdens (e.g., traffic collisions) of transportation are inequitably distributed across population groups (Pereira, Schwanen and Banister, 2017). In Canadian cities, bicycling infrastructure, including bike share stations, is less prevalent in neighborhoods with lower socioeconomic status (Fuller and Winters, 2017; Hosford and Winters, 2018). In the US, some research suggests that areas with larger white and higher-income populations are afforded better access by bicycle to destinations such as healthcare facilities and grocery stores (Jahanshahi et al., 2021). Overall, this body of work collectively underscores that there is marked variability across cities in the patterns of both existing and new investments in bicycling infrastructure by area-level income and race (Braun, Rodriguez and Gordon-Larsen, 2019; Ferenchak and Marshall, 2021; Fuller and Winters, 2017). In response, many municipalities are incorporating equity-based goals, objectives, and project prioritization procedures into their transportation plans (Doran, El-Geneidy and Manaugh, 2021; Manaugh, Badami and El-Geneidy, 2015).

There are other important influences beyond infrastructure for cities to consider when creating an inclusive cycling culture. The availability of bicycling infrastructure can increase levels of cycling and reduce the risk of traffic collisions (Pucher, Dill and Handy, 2010), but infrastructure alone does not necessarily generate a diversity in the profile of people who bicycle (Lubitow and Miller, 2013). Cycling has been perceived by people of color as “something that white people do” (Briseño et al., 2019) and the construction of bicycling infrastructure can lead to fears of gentrification and displacement by low-income and racialized residents (Lubitow and Miller, 2013). This may lead to other groups feeling unfamiliar and uncomfortable with cycling, which can be compounded by the disproportionate vulnerability to traffic collisions and to harassment by police that Black, Indigenous, and people of color (BIPOC) and low-income residents can experience in public space (Agyeman and Doran, 2021). Indeed, research shows that Black and Latino Americans are up to 30% more likely than white Americans to die while cycling (Zimmerman et al., 2015). An inclusive cycling culture is required for populations facing structural disadvantages to fully benefit from investments in bicycling infrastructure.

Concurrent with this growing empirical evidence base on differences in bicycling behaviours across population groups, there has been a proliferation of scholarship concerned with the place of bicycling in wider debates around transport equity or mobility justice (Golub, 2016; Sheller, 2020). Current work that identifies differences in bicycling across population groups tends to engage more explicitly with transport justice and identify systemic and cultural changes to promote more equitable bicycling outcomes. For example, Martens and colleagues (Martens et al., 2016) discuss the role of cycling to promote wider social goals of inclusion as well as environmental quality, while Soliz (2021) explores how social movements can be integrated into bicycle planning in underserved areas.

1.2. Evidence on demographic trends in cycling

National data from North America and Western Europe do indeed show differences in bicycling mode share across sociodemographic groups. Women cycle far less than men in the US and Canada and, in the US, cycling rates among men increased more than women between 2001 and 2009 (Pucher, Buehler and Seinen, 2011). Gender differences in cycling rates may be due to women being more concerned by safety and security when cycling, as well as women’s disproportionately larger role in mobility of care (Pucher, Dill and Handy, 2010). Cycling rates have been found to steadily decline with age in the US and UK, but countries with higher cycling rates such as Germany and the Netherlands have seen bicycling mode share increase among groups over the age of 25 (Pucher and Buehler, 2008). The relationship between personal income and cycling is variable in studies from the US, UK, Germany, and the Netherlands (Heinen, van Wee and Maat, 2010; Parkin, Wardman and Page, 2007; Pucher and Buehler, 2008), although higher rates of cycling for utilitarian purposes have been found among low-income groups in Canada (Winters et al., 2007). In the US, white people have higher bicycle mode shares than those identifying as African American, Hispanic, or Asian, though cycling rates rose more among non-white groups between 2001 and 2009 (Pucher, Buehler and Seinen, 2011). Likewise, in England and Wales, electoral wards with a higher proportion of non-white residents have lower rates of bicycle commuting (Parkin, Wardman and Page, 2007). Geographic factors such as climate, topography, and land-use may also impact bicycle mode share (Heinen, van Wee and Maat, 2010).

In Canada, the demographics of who is cycling has not been documented nationally. This is in part due to the lack of a national household travel survey that would provide data on cycling for all types of trips. The Canadian Census (and 2011 National Household Survey (NHS)) provides data every five years on the main travel mode used for commuting. These data can provide some indication of who is cycling to work in Canada, and how the cycling population is changing over time.

The current study uses Canadian Census and NHS data to provide a nationwide portrait of: 1) how bicycle commute mode share varies by gender, race, income, and age in Canada; 2) how the demographics of bicycle commuters in Canada have (or have not) shifted over the 20-year period between 1996 and 2016; and 3) how bicycle commuting and bicycle commuter demographics vary across metropolitan regions in Canada. Our findings show social patterning, with more cycling by men, people who are white, and people with low incomes, and that patterns are persistent over the two-decade study period. This high-level portrait can provide an indication of the inclusiveness of bicycling in Canada. It allows practitioners to understand how Canada’s bicycling population is changing over time and can provide insight into where attention is needed to create more equitable bicycling systems.

3.1. Sociodemographic characteristics of people bicycle commuting

We report the 2016 rates of bicycle commuting amongst the Canadian population stratified by gender, race, income, and age, as well as differences between demographic subgroups in 2.

Table 2 shows the percentage of each demographic group that bicycles to work, and that the differences between each group and the reference category (women, visible minority, low-income, ages 15–24) is statistically significant. By mode share, men bicycled to work at almost double the rate of women in 2016 (1.9% versus 1.0%). Women slightly outnumbered men in Canada (50.9% of the population) and commuted almost as much (48% of total commuters are women) but only represent about a third of bicycle commuters. Thus, women are underrepresented in commuter bicycling in Canada. Similarly, those identifying as white or Indigenous regularly cycled to work at approximately twice the rate of visible minorities, and those living below the LICO cycled to work at double the rate of those who are not considered low-income. This is indicative of substantial discrepancies between white and non-white bicycle commuting patterns in Canada and a heavier reliance on bicycling by low-income commuters.

To assess how bicycle commute mode share varies across age groups we aggregated the main mode of commuting data into 10-year age categories (15–24, 25–34, 35–44, 45–54, 55–64, and 65+ pooled). Table 2 shows that bicycle commute mode share is lower in older age groups. The gap between mode shares is largest between the middle age categories, indicating that commuting to work by bicycle drops off for people in their late 20s and 30s.

3.2. Sociodemographic characteristics of people bicycle commuting over time

This section presents bicycle commuting rates by gender, race, income, and age for all census years between 1996 and 2016.

3.2.1. Gender

Figure 3 shows the Canada-wide bicycle commute mode share for men and women between 1996 and 2016. As in 2016, men have cycled to work at approximately double the rate as women across all census years analyzed. However, the proportion of women cycling to work has increased consistently each census year, from 0.7% in 1996 to 1.0% in 2016, whilst bicycle commute mode share for men is increasing variably and at a slower pace (from 1.7% in 1996 to 1.8% in 2016, peaking at 1.9% in 2006). Overall, women remain underrepresented as bicycle commuters in Canada, but the gap between men and women has narrowed over time.

Figure 3

Bicycle commute mode share in Canada by gender (Statistics Canada Journey to Work data, 1996–2016).

3.2.2. Race

The mode share of bicycle commuters over time in Canada are summarized by visible minority status in Figure 4. People who are visible minorities cycled to work at approximately half the rate of non-visible minority (white and Indigenous) commuters across all census years. Mode share is increasing over time, but slowly, for both groups (an approximately 0.1% increase for both between 1996 and 2016). These changes occurred as the visible minority population in Canada was growing substantially, almost doubling from 11.5% in 1996 to 21.6% in 2016. There appear to be major and continuing discrepancies in bicycle commuting by these racial groupings in Canada.

Figure 4

Bicycle commute mode share in Canada by visible minority status (Statistics Canada Journey to Work data, 1996–2016).

3.2.3. Income

The bicycle commute mode share of the Canadian populations living below and above the before-tax LICO are presented for the 20-year study period in Figure 5. Across all census years, people living with low incomes consistently cycled to work at much higher rates than those with higher incomes. Bicycle commuting is increasing at similar rates between 1996 and 2016 for both groups (2.2% to 2.8% for the low-income group and 1.1% to 1.4% for the rest of the population), though rates are increasing more consistently for the low-income group.

Figure 5

Bicycle commute mode share in Canada by low-income cut-off (LICO) status (Statistics Canada Journey to Work data, 1996–2016).

3.2.4. Age

Figure 6 highlights that younger people have a higher bicycle mode share across all census years. For age groups over 25 years, we see a pattern of bicycle commute mode shares generally increasing over time. However, in the youngest age group (15–24 years), we see declines over time. Thus, even as this younger population is cycling to work more than other age groups, over time, cohorts of young people are less likely to be cycling.

Figure 6

Bicycle commute mode share (%) in Canada by age group (Statistics Canada Journey to Work Data, 1996–2016).

3.3. Geographic variations in bicycle commute mode share

Bicycling policy and infrastructure decisions in Canada are most often made at the municipal level. Even within municipalities, the provision of bicycling infrastructure and factors such as topography vary by neighborhood. The promotion of bicycling, attitudes towards bicycling, as well as other environmental factors such as climate, is thus highly localized (Heinen, van Wee and Maat, 2010). The census/NHS PUMF can only be disaggregated to the CMA level, which often includes multiple municipalities but can provide an indication of how levels of bicycle commuting vary by region. Bicycle commute mode share for select CMAs available in the PUMF Census data are presented in Figure 7.

Figure 7

Bicycle commute mode share for the two largest census metropolitan areas in each Canadian province (Statistics Canada Journey to Work data, 1996–2016).

Victoria, British Columbia consistently had at least triple the bicycle commute mode share of the other CMAs. The mode share in Victoria also rose considerably, from 5.0% in 1996 to 6.4% in 2016. The three most populous CMAs (Toronto, Vancouver, and Montréal) have all seen substantial increases in bicycle commute mode share over the two decades, although Toronto’s mode share remains among the lowest.

A disaggregated exploration of bicycle commute mode share by geography reveals regional variability in some of the above results presented in Section 3.2 (Table 3). The grey cells indicate geographical areas where specific equity-deserving groups may be commuting by bicycle more, relatively speaking, although ratios should be taken in context of the absolute mode shares (e.g., higher ratio between groups are more likely in areas with low absolute mode shares). There were no CMAs where women’s bicycle commute mode share was equal to or greater than those by men. Men consistently commuted by bike at 1.5–2 times the rate of women across the country, and as high as 6 times higher in Oshawa, a suburban municipality with limited bicycling infrastructure. The two areas with the tightest gender split (ratio of 1.3) were Moncton – Saint John, and Kelowna – Abbotsford. Across most cities, people who are classified as visible minorities had lower bicycle mode shares than non-visible minorities, with the exception of Sherbrooke – Trois-Rivières and Windsor (where visible minorities had higher mode share), and Oshawa (where cycling was low overall, but equal across race). An interesting contrast is that in areas outside the larger CMAs, people who are visible minorities commute by bicycle at higher rates (1.5%) than those who are not visible minorities (0.5%). Finally, the data show a consistent trend that low-income groups had higher bicycle commute mode shares than the rest of the population in all CMAs except Calgary, Alberta. The relatively higher rates of commuter cycling for both visible minority groups and low-incomes outside of the larger CMAs (e.g., in smaller, more car-centric CMAs, and outside urban areas) may be indicative of constraints in transportation alternatives leading to these groups facing structural disadvantage to commute by bicycle, rather than a choice between a set of transportation alternatives that more affluent and white populations may have.

4.1. Gender

Our analysis found that men commute by bicycle at approximately twice the rate of women in Canada, but rates of bicycle commuting are increasing faster for women than men. The overarching gap is consistent with previous research which has found that in western countries where bicycle mode share is low overall, men cycle more than women (Heinen, van Wee and Maat, 2010). Women in Canada cycle at similar rates to the UK (29% of bicycle trips are taken by women) and at higher rates than in the US (25%) and Australia (21%) (Pucher and Buehler, 2008). The consistently lower bicycle mode share for women is indicative of widely studied barriers to cycling and cultural limitations that some women face while cycling in North America, including an enhanced fear of violence and harassment in public space relative to men, lower confidence in mixed-traffic conditions, expectations of appearance when arriving at workplaces, and childcare responsibilities (Lubitow, 2017). Studies have shown that women have stronger preferences than men for bicycling infrastructure with physical separation from motor vehicles (Garrard, Rose and Lo, 2007; Twaddle, Hall and Bracic, 2010). The increasing bicycle mode share for women may indicate slight shifts towards gender equality in cycling in Canada.

4.2. Race

We found that Canadians who Statistics Canada identifies as ‘visible minorities’ cycle to work at approximately half the rate of white and Indigenous people, and both groups have shown increasing mode share at similar rates. Pucher et al. (2011) similarly found that cycling rates are twice as high amongst white populations in the US, as compared to Hispanic and African American groups, although cycling rates were increasing in non-white demographics but not amongst white demographics. In England, utilitarian cycling rates among non-white individuals are approximately 60% the rates of white individuals, and recreational rates are only 50% (Goodman and Aldred, 2018). These differences are also found in countries where the overall prevalence is high, such as the Netherlands, where ethnic minorities bicycle less (Fishman, Böcker and Helbich, 2015).

These findings support the common belief that utilitarian cyclists are primarily white (Agyeman and Doran, 2021; Lubitow, 2017). The “not visible minority” population in our analysis comprised both Indigenous people and white populations, consistent with historical Statistics Canada classifications, although the absolute number of Indigenous people bicycle commuting is small, relative to white cyclists (~8,300 and 220,000, respectively, in 2016). Evidence suggests that racialized populations are facing pervasive barriers to cycling in western countries. For example, many barriers in the US are because of systemic racism, such as fears of police and other violence, harassment, and microaggressions through other road users’ behavior when navigating public space, commonly referred to as “Biking While Black” (Barajas 2021; Lubitow, 2017). In England, lower cycling rates amongst non-white people have been attributed to cultural associations of cycling with low social status and infantilism, preferences for more modest clothing, and low coverage of cycling in Black media (Steinbach et al., 2011). Low cycling rates may also be related to lower bicycling infrastructure investment in neighborhoods with higher proportions of racialized residents, a pattern seen in some North American cities but not others (Flanagan, Lachapelle and El-Geneidy, 2016).

4.3. Income

We identified a significantly higher bicycle commute mode share among the low-income population compared to the rest of the population, with the difference in mode share between the two groups remaining relatively consistent between 1996 and 2016. Analysis of other national datasets from western countries have not identified such a discrepancy in cycling rates across income groups. Pucher and Buehler (2008) found that cycling rates are similar across income groups in the US, the UK, Germany, the Netherlands, and Denmark. This result is based on bicycling trips of all purposes, but other studies have found that recreational bicycling is more prevalent among higher-income groups (Heinen, van Wee and Maat, 2010). Within the Canadian context, Winters et al. (2007) used the national Canadian Community Health Survey to identify an inverse relationship between household incomes and utilitarian bicycling (work, school, or errands). The high cycling rates amongst the low-income population found in this analysis therefore may be due to low-income commuters’ higher reliance on bicycling as a lower-cost transportation alternative, whereas those with higher incomes may choose to bicycle when there are comfortable conditions (e.g., high-quality bicycling infrastructure, favorable weather) (Pucher, Buehler and Seinen, 2011). Those with higher incomes are more likely to own a car and are generally better able to spend more money on transportation, allowing them more travel alternatives to choose other than bicycling if conditions are unsafe or uncomfortable (Heinen, van Wee and Maat, 2010). Thus, these Canadian results combined with the other research on the prominence of recreational bicycling among higher-income groups may point to a division in bicycling trip purposes along socioeconomic lines, where mid- to high-income earners bicycle for leisure or as a choice among several transportation options, whereas low-income earners bicycle out of necessity for a low-cost transportation alternative (Pucher, Buehler and Seinen, 2011).

4.4. Age

While we see expected patterns of decreasing bicycling within increasing age groups, we importantly see a pattern of increasing commuter bicycling within each age group. The one exception is the youngest age group analyzed (15–24 years), which appears to have lower rates of bicycling in more recent census years, though their mode shares remain higher than older age groups. Our results generally reflect findings from the US and UK that bicycling rates decline as age groups increase, with a sharp decrease between the teenage years and 20s (Pucher and Buehler, 2008). It is commonly assumed that decreasing bicycling rates with age are due to declining physical ability, but research has indicated that cultural factors and infrastructure preferences among older adults are also at play (Aldred, Woodcock and Goodman, 2016). The perception of a typical cyclist being young and athletic can feel exclusionary to older adults (Lubitow, 2017). Older adults are often more constrained by their stronger preferences for bicycling infrastructure with physical separation from motor vehicle traffic (Van Cauwenberg et al., 2019). A contributing factor to the rapid decrease in bicycle commute mode share between the 15–24 and 35–44 age groups may be experiencing a major life event, such as changing jobs, relationship changes, moving, and increasing caregiving responsibilities (Chatterjee, Sherwin and Jain, 2013).

4.5. Intersections of sociodemographic characteristics

There is a need to advance intersectional perspectives in cycling research and practice (Lam, 2022). Structural forces compound and interact such that individuals’ intersecting spatial and social identities face unique barriers; travel behavior cannot be fully explained by a single aspect of one’s identity. For example, if the journey-to-work data are further stratified by age and gender, we see that the 2016 bicycle commute mode share for racialized women is only 0.6%, half the rate of all women (1.2%) and racialized men (1.1%). Stratifying bicycle commute mode share by gender and income shows that bicycle mode share for low-income women is 2.2% compared to 1.0% women who are not low-income, and 3.6% for low-income men compared to 1.8% for men who are not low-income. Efforts towards equitable bicycling in Canada must consider the intersecting barriers and constraints to bicycling that people might experience based on overlapping systems of oppression, as well as explore whether people are bicycling as a choice or because there are limited alternative transportation options available. The Canadian Census PUMFs are well-suited for surfacing differences in bicycle commute mode share as they provide individual records from which the user can generate custom crosstabs across sociodemographic characteristics and commuting behavior. Future research can capitalize on this opportunity that the PUMFs provide and complement this data qualitative analysis to surface reasons for why these differences are occurring.