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. 2015 Oct 21;2:874–879. doi: 10.1016/j.pmedr.2015.10.001

Impacts of public transit improvements on ridership, and implications for physical activity, in a low-density Canadian city

Patricia A Collins a,⁎, Ajay Agarwal b
PMCID: PMC4721416  PMID: 26844163

Abstract

Public transit ridership offers valuable opportunities for modest amounts of daily physical activity (PA). Transit is a more feasible option for most Canadian commuters who live too far from work to walk or cycle, yet public transit usage in midsized Canadian cities has historically remained low due to inefficient transit service.

The objectives of this longitudinal study were threefold: to assess whether the introduction of express transit service in the low-density city of Kingston, Ontario, has translated to greater transit use among a targeted employee group; to document the characteristics of those employees that have shifted to transit; and to examine the PA levels of employees using transit compared to other commute modes.

An online survey was administered in October 2013 and October 2014 to all non-student employees at Queen's University. 1356 employees completed the survey in 2013, and 1123 in 2014; 656 of these employees completed the survey both years, constituting our longitudinal sample.

Year-round transit ridership increased from 5.5% in 2013 to 8.5% in 2014 (p < 0.001). Employees who shifted to transit had fewer household-level opportunities to drive to work and more positive attitudes toward transit. Transit commuters accrued an average of 80 minutes/week of commute-related PA, and 50 minutes/week more total PA than those that commuted entirely passively.

Kingston Transit's express service has stimulated an increase in transit ridership among one of their target employers, Queen's University. The findings from this study suggest that shifting to transit from entirely passive commuting can generate higher overall PA levels.

Keywords: Commute to work, Public transit, Physical activity, University employees, Kingston Ontario, Longitudinal study

Highlights

  • •

    Riding public transit to work offers opportunities for regular physical activity.

  • •

    Transit service in midsized Canadian cities often too inefficient to justify use.

  • •

    Few longitudinal studies of impacts of transit improvements on ridership.

  • •

    Introduction of express bus service led to significant increase in ridership.

  • •

    Transit riders reported accruing 50 minutes more activity per week than drivers.

Introduction

Commute mode and health

Within the field of public health, there is growing interest in promoting active commuting to increase daily physical activity levels among working-age populations (Butler et al., 2007, Shephard, 2008, Giles-Corti et al., 2010, PHAC, 2010, Bopp et al., 2011). This interest stems from mounting evidence that connects daily travel patterns to population health indicators, such as elevated obesity prevalence among those who commute passively (e.g., by private automobile) (Frank et al., 2004), and healthier body weights among active commuters (Gordon-Larsen et al., 2005). Active commuters also tend to be more satisfied with their daily commute (Páez and Whalen, 2010), making it a more attractive commute option for those who can choose it.

Health benefits of transit ridership

Despite established health benefits of active commuting, most Canadians do not live within close enough proximity to their place of work (i.e., within roughly 2 km for walking and 7 km for cycling (Larsen and El-Geneidy, 2010) to not rely on motorized transportation for at least part of the journey (Turcotte, 2011). In fact, over 70% of Canadians have been commuting by private automobile since 2006 (Statistics Canada, 2006, Statistics Canada, 2011a). However, there is growing recognition that riding public transit offers opportunities for active commuting, since the majority of transit trips involve walking at the beginning and end (Edwards, 2008, Lindström, 2008, Chaix et al., 2014). Indeed, cross-sectional studies have found that transit riders accrue more daily PA than those who commute by car (Besser and Dannenberg, 2005, Wener and Evans, 2007, Lachapelle and Frank, 2009). And, longitudinal research based in Salt Lake City, Utah, found that the introduction of light-rail transit (LRT) lead to increased total physical activity levels (Brown and Werner, 2007) and weight loss (Brown et al., 2015) among riders. Thus, promoting transit ridership may be a useful approach to increasing PA (as well as reducing traffic congestion and pollution), especially among the majority of Canadians who live too far from work for it to be feasible to use active modes for the entire journey.

Barriers to, and opportunities for, increasing transit ridership

In midsized Canadian cities (i.e., populations 100,000–500,000), public transit systems often struggle with low ridership due to low population densities that are not supportive of efficient transit services (Turcotte, 2011). Low-density developments often lead to inefficient bus routing and inconvenient scheduling, and a recent study based in a midsized US city found that these factors present significant barriers to transit ridership (Lawson et al., 2012). The challenges faced by transit systems in midsized cities are compounded by the tendency for midsized cities to have ample parking supply in their central business districts, and limited traffic congestion on major corridors during peak hours (Shoup, 2011).

Despite barriers to transit ridership in midsized cities, research suggests that improvements to transit services and programs that promote transit hold promise for encouraging people to shift to public transit for their daily commute (Shannon et al., 2006, Brown and Werner, 2007). Additionally, midsized cities across Canada are increasing efficiencies within their transit systems to increase ridership, and to make their municipalities more sustainable (AMO, 2008).

Knowledge gaps and study objectives

Much of the literature on the commute modes of working-age adults have been cross-sectional in nature (Evans et al., 2002, Pendola and Gen, 2007, Handy and Xing, 2011, Hansson et al., 2011, Feng and Boyle, 2013), which presents challenges with understanding the relationship between changes in the commute landscape, such as improvements to transit, and mode choice, and similarly, between mode choice and health. Additionally, most previous research on this topic has been conducted in large metropolitan areas, especially in the USA, where transit improvements are often for higher-order infrastructure such as subways, light-rail transit, and bus rapid transit (Wener et al., 2003, Evans and Wener, 2006, Brown and Werner, 2007, Frank et al., 2007, Kam et al., 2011, Lachapelle and Noland, 2012).

In midsized Canadian cities, like Kingston Ontario, transit improvements are typically more modest, such as the introduction of express routes. Yet, little is known about whether these modest improvements have the capacity to stimulate increased ridership, and whether the positive health outcomes associated with transit ridership that have been observed in larger cities are also observable in smaller cities. Thus, the objectives of this longitudinal study were threefold: to assess whether the introduction of express transit service in Kingston, Ontario, has stimulated greater transit use among a targeted employee group; to document the characteristics of those employees that have shifted to transit; and to examine the physical activity levels of employees using transit compared to other commute modes.

Study site context

The city of Kingston is located roughly equidistant between three major urban centers in Canada (i.e., Toronto, Montreal, and Ottawa) and is home to several large public institution employers (e.g., Royal Military College, Corrections Canada, St. Lawrence College, and Queen's University). Like most cities of its size in North America, Kingston Ontario is an automobile-centric city; the vast majority of households in Kingston commute by car (82%), with active modes accounting for 12% of commute mode share (9.6% walking, 2.4% cycling), and transit accounting for only 4% (SPCK&A, 2009). A major contributor toward Kingston's automobile dependency is its low population density. The city has a population of 123,363 and a population density of 273.4 people/km2 (Statistics Canada, 2011b). While Kingston is unsurprisingly less dense than Canada's large cities of Toronto (4150 people/ km2), Montreal (4520 people/ km2), and Vancouver (5250 people/km2), it is notably less dense than other cities of similar size. For instance, Burlington, Ontario, has a population of 176 k and density of 947 people/ km2, while Barrie Ontario has a population of 135 k and density of 1750 people/ km2.

To help reduce Kingstonians' heavy reliance on private automobiles, the City introduced a Transit Redevelopment Plan for 2011–2015 (Kingston, 2011). The plan centers on making critical improvements to the transit system to increase ridership, including the introduction of three new express transit routes that traverse the most common commuter routes in the city. The first of the three new express routes was introduced in September 2013, and the remaining two were introduced in May 2015 (Fig. 1). Providing more frequent service to Queen's University, situated within Kingston's downtown core, is identified as a top priority in the Plan. In support if the City's effort to promote transit ridership among Queen's employees, the university also introduced an employer-subsidized monthly transit pass in March 2014. These changes to the commuting landscape for Queen's employees offer a prime opportunity to evaluate their impacts on the commuting habits of this targeted employee group.

Fig. 1.

Fig. 1

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Map of express transit routes in Kingston, Ontario (Kingston, 2011).

Methods

Methodology

This study involved an online survey administered at two points in time to the same population of non-student employees working at Queen's University in Kingston, Ontario. The survey captured information about commute patterns in general, and use of public transit in particular, among employees at Queen's University. Ethics approval was granted by the Queen's University General Research Ethics Board in September 2013 and September 2014, in advance of each survey round.

Sampling approach

Since improving transit service to Queen's University was identified as a top priority in the Kingston Transit Redevelopment Plan (Kingston, 2011), this study chose to focus on the impacts of transit improvements on the commute patterns of its employees. Queen's is the second largest employer in Kingston (KEDCO, 2014), is located in the city's grid-like downtown core, and is directly served by several public transit routes, including the city's first express transit route. Eligible employees were those living within the geographic area served by Kingston Transit (Fig. 1). This corresponded to postal codes with forward sortation areas of K7K, K7L, K7M, K7N, and K7P.

Survey design and administration

The survey contained primarily closed-ended questions, and took an average of 12 minutes to complete. In both years, information on respondents' commute attributes (including seasonal variations), their household attributes, and their attitudes toward public transit was captured. In 2014, additional questions about health status, physical activity levels, and activity limitations were included. To the extent possible, we incorporated questions from existing Statistics Canada surveys, including the General Social Survey for general questions about commuting (Bechard, 2011), the Canadian Community Health Survey for questions about general health status (Statistics Canada, 2012a), and the Canadian Survey on Disability for questions about activity limitations (Statistics Canada, 2012b). However, the many of the survey questions were specific to the study context and had to be newly developed. For instance, questions about commute mode were context-specific, given the diversity of ways that Queen's employees get to work (e.g., many employees park off-campus and walk for the remainder of the journey), and existing surveys (Bechard, 2011) do not capture these nuances that have important implications for the relationship between commute mode and health. Similarly, questions pertaining to the influence of the introduction of express transit in Kingston were context-specific. And, while survey instruments do exist that are designed to capture the amount and intensity of physical activity, such as the International Physical Activity (IPA) Questionnaire (Statistics Canada, 2012c), these survey modules tend to be quite lengthy and burdensome to respondents. Since we simply needed respondents to indicate the total amount of physical activity they engage in excluding time spent commuting, we decided to minimize respondent burden and capture this information through fewer questions that we designed using a similar format to those in the IPA. The researchers drew from well-established methodological sources to guide the development of new questions and the overall design of the survey (Salant and Dillman, 1994, Dillman et al., 2008).

The survey was administered online using the web-based platform FluidSurveys. To protect respondents' identities, the researchers partnered with Queen's University's Office of Institutional Research and Planning (OIRP), who took responsibility for identifying eligible employees, administering recruitment and follow-up emails, downloading the dataset once the survey was closed, and stripping the dataset of identifying information (e.g., names, email addresses). For the 2013 survey, initial recruitment emails were sent to the entire population of non-student employees at Queen's University (N = 3151), and 1356 completed the survey (response rate = 43.0%). For the 2014 survey, initial recruitment emails were sent to the same population of non-student employees (N = 3392), and 1123 completed the survey (response rate = 33.1%). Both surveys involved two reminder emails to non-respondents 2 weeks following the initial invitation. Of these samples, N = 656 completed the survey in both years, constituting our longitudinal sample, and the focus of this paper.

Statistical analysis

Cross-tabulations and chi-square statistics were generated for analyses of sample characteristics and changes in commute modes over time, and for tests of differences between employees that have versus have not shifted to public transit. Comparisons of physical activity levels by commute mode employed analysis of variance (ANOVA). A 95% level of confidence was the minimum threshold employed for all analyses.

Results

Respondent characteristics

Table 1 summarizes commute variable and socio-demographic characteristics of the longitudinal sample (N = 656). From 2013 to 2014, only one variable changed significantly; the number of respondents reporting having no children under 14 years of age increased from 70% in 2013 to 72% in 2014.

Table 1.

Characteristics of longitudinal sample, N = 656.

2013 Sample 2014 Sample
Commute variables Works 5 days/week 82% 81%
Flexible hours 44% 47%
Access to vehicle for commute 88% 88%
Permit to park at Queen's 38% 39%
Lives within 5 km of Queen's 45% 45%
Socio-demographic variables Female 66% 66%
50 + years of age 49% 52%
Household income < 90 k 35% 33%
No children < 14 years 70% 72%⁎
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⁎

Statistically significant at 99% confidence level.

Change in commute mode over time

Commute modes were assigned to one of five general categories. Exclusively passive commuters were those employees that drove their own vehicle or carpooled and parked, or were dropped off, on Queen's campus. Somewhat passive commuters were those that drove their own car, or carpooled with others, parked at a location off-campus, and walked to Queen's for the rest of the journey. Transit commuters took public transit for the journey to work, while Active commuters walked or bicycled for their commute. Finally, employees that did not employ the same commute mode year-round were classified as Varies by Season for the year-round commute category.

Table 2 summarizes the 2014 commute modes by season and year-round, along with the changes in commute modes since 2013. On a seasonal and year-round basis, the most common mode was exclusively passive. Transit was the only commute mode for which there was a statistically significant change since 2013, with a 3–4% increase in ridership across the seasons and on a year-round basis. Transit ridership was highest in the winter season, at 14% of mode share.

Table 2.

2014 commute modes, and percent change in mode since 2013, by season and year-round.

Fall
 Winter
 Spring
 Summer
 Year-round
% in 2014 % change since 2013 % in 2014 % change since 2013 % in 2014 % change since 2013 % in 2014 % change since 2013 % in 2014 % change since 2013
Exclusively passive 44.4 − 0.8 46.9 − 1 42.5 − 1 41.6 − 1.5 40.7 − 0.6
Somewhat passive 10.3 − 1.5 11.7 − 0.9 9.2 − 1.3 9.3 − 0.9 8.5 − 0.7
Transit 11.1 3.5⁎ 14.0 3.9⁎ 9.7 3.4⁎ 9.0 3.1⁎ 8.5 3.0⁎
Active 34.3 − 1.1 27.4 − 2 38.6 − 1 40.2 − 0.6 14.2 − 0.7
Varies by season 28.2 − 0.9
Total 100 0 100 0 100 0 100 0 100 0
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⁎

Statistically significant at 99% confidence level.

Characteristics of employees shifting to transit use

Employees that were shifters (i.e., those that did not commute by public transit in 2013 but shifted to riding transit in 2014; N = 23) were compared to non-shifters (i.e., non-transit riders in both 2013 and 2014; N = 591) on a range of variables (Table 3). Shifters were significantly more likely to be female and report a household income within the lower range for this sample. In terms of commute-related characteristics, shifters had significantly fewer opportunities to support driving to work (e.g., driver's license, car ownership, access to car for commute) and more opportunities to support taking transit (e.g., living near multiple bus stops, having a Kingston Transit pass). In terms of behaviors and attitudes toward transit, shifters responded more favorably to transit service improvements and the introduction of a subsidized bus pass through Queen's, and are more willing to spend at least 30 minutes on Kingston Transit to commute to work. Finally, in 2013, commute satisfaction was lower among shifters compared to non-shifters, whereas in 2014, there was no significant difference in commute satisfaction between shifters and non-shifters.

Table 3.

Characteristics of Queen's employees that shifted to commuting by public transit in 2014 compared to those that did not make the shift.

Variable type Variable Shifters (N = 23) Non-shifters (N = 591) P-value
Socio-demographics Female 91% 66% 0.036
50 years of age or under 61% 51% 0.374
Has one or more children under 14 22% 28% 0.525
Household income < 90 k 73% 30% < 0.001
Commute characteristics Work hours are flexible 30% 47% 0.114
Has driver's license 82% 98% < 0.001
Has access to car for commute 65% 91% 0.001
Has a Kingston transit pass 83% 4% < 0.001
Has permit to park at Queen's, 2013 26% 41% 0.165
Has permit to park at Queen's, 2014 4% 42% < 0.001
Behaviors and attitudes KT express has increased KT use, 2013 21% 4% 0.001
KT express has increased KT use, 2014 52% 7% < 0.001
Bus pass has increased KT use 56% 4% < 0.001
Willing to spend > 30 mins on KT, 2013 35% 9% < 0.001
Willing to spend > 30 mins on KT, 2014 39% 3% < 0.001
Satisfied with commute, 2013 65% 82% 0.036
Satisfied with commute, 2014 78% 83% 0.573
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Comparisons of physical activity levels by commute mode

The third objective of this study was to examine the physical activity (PA) levels of Queen's employees who use transit compared to other commute modes, captured through self-reported numbers of minutes engaged in both commute-related and non-commute-related PA (Table 4).

Table 4.

Commute and non-commute physical activity levels by year-round commute mode.

Physical activity variable Entirely passive Somewhat passive Transit Active F P-value
Daily commute-related PA minutes N/A 20.7 ± 2.3 16.7 ± 1.4 29.3 ± 1.1 327.19 < 0.001
Weekly commute PA minutes N/A 98.4 ± 11.4 79.2 ± 6.4 140.3 ± 5.8 276.38 < 0.001
Weekly non-commute PA minutes 135.1 ± 7.8 141.4 ± 17.2 104.1 ± 13.4 157.2 ± 9.4 2.86 0.036
Weekly combined PA minutes 135.1 ± 7.8 237.4 ± 23.9 183.3 ± 15.5 296.3 ± 10.9 52.56 < 0.001
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Daily commute PA minutes were captured as follows. Active commuter respondents reported the average number of minutes they spend per day walking or cycling one-way to work. For transit commuters, respondents reported on the number of minutes they spend walking to the bus stop from their home and from the bus stop to their place of work at Queen's. For somewhat passive commuters, respondents reported on the number of minutes they spend walking from the place they typically park their car off-campus to their place of work at Queen's. Entirely Passive commuters were not attributed any minutes of commute-related PA. For each case, the one-way daily commute PA minutes were multiplied by two to capture both journeys.

To estimate weekly commute PA minutes, the daily commute PA minutes for each respondent was multiplied by the number of days per week they reported typically working at Queen's. For weekly non-commute PA minutes, respondents were asked to estimate the total number of minutes per week they typically spend engaged in PA, excluding any PA they accrue through their commute.

Analysis of variance revealed significant differences by commute mode for all assessments of PA minutes. Transit commuters accrued nearly 80 minutes of PA as a result of their commute by transit, over half of the 150 minutes of weekly PA recommended by the Canadian Society for Exercise Physiologists (CSEP) (CSEP, 2012). While transit commuters did not accrue as much combined weekly PA as somewhat passive commuters, they did accrue 50 minutes more combined weekly PA than entirely passive commuters.

Discussion

Examining transit shifting and shifters

The findings from this study revealed that the introduction of express transit service stimulated increased ridership among a longitudinal sample of Queen's University employees; a 3% increase in year-round transit ridership was observed, with the highest shift in ridership occurring in the winter. The increase in transit ridership may be partly attributable to changing household-level characteristics of the sample; the number of respondents reporting not having children under 14 increased significantly over time, suggesting fewer constraints on parents' commute habits, and thus greater opportunity to take public transit to work (Kim and Ulfarsson, 2008).

The comparison of shifters to non-shifters revealed some interesting patterns. Shifters to transit were much less likely to have a driver's license and access to a car to drive to work. This is an important and potentially promising finding, given emerging evidence on declining numbers of younger adults obtaining driver's licenses in Canada (Marzoughi, 2011). The findings also suggest that shifters made purposeful changes to their lives to support their use of transit to commute to work, by relinquishing their Queen's parking permits and by purchasing an employer-subsidized bus pass in 2014. These findings lend support to previous research that has found that workplace policies play important roles in promoting active commuting and employee health (Lachapelle and Frank, 2009, Brockman and Fox, 2011).

In both years, a significantly higher proportion of shifters reported being willing to spend more than 30 minutes on Kingston Transit to get to work, and that the introduction of express transit service increased their use of public transit. These findings suggest not only that shifters have a more positive attitude toward taking public transit, but also that they are amenable to changing their commute habits when services improve. What was particularly noteworthy, however, was that shifting to transit in 2014 led to an increase in commute satisfaction among shifters, suggesting that riding Kingston Transit does not produce dissatisfied commuters. This finding is promising, since research has shown that commute satisfaction is a key determinant of happiness and well-being (Olsson et al., 2013).

Physical activity implications of commute modes

Commute mode choice can dramatically impact the level of PA an individual accrues as part of the journey. Not surprisingly, active commuters in this study (i.e., those that walk or cycle for the entire journey) accrue the highest amount of daily (average 29 minutes) and weekly (average 140 minutes) commute PA minutes and approach the CSEP's recommended amount of PA through their commute habits alone (CSEP, 2012). Somewhat passive commuters (i.e., those that drive, park off-campus, and walk to Queen's campus for the remainder of the journey) also accrued a substantial amount of PA minutes through their commute, which is not surprising since these commuters likely adopt this behaviour in part to save money by not purchasing a Queen's parking permit, but also to incorporate exercise into their daily life. That transit commuters accrue 80 minutes of PA per week through their commute is particularly noteworthy, since it is likely that some of these commuters are opting for transit for reasons other than being physically active, and yet they are accruing more than half of the recommended 150 minutes per week of PA by riding transit.

When asked about non-commute weekly PA minutes, transit commuters reported the fewest number of minutes. Yet, when commute and non-commute PA minutes were combined, transit commuters accrued on average 50 minutes more per week than those that commute to Queen's by entirely passive modes. Thus, these findings corroborate the argument that incorporating physical activity into one's commute can be an effective approach to increasing overall PA levels (Shephard, 2008, Giles-Corti et al., 2010).

Policy implications and directions for future research

Given Kingston's low population density and the challenges that low density presents for creating efficient public transit service and encouraging ridership (Chen et al., 2008), the findings from this study are promising as they suggest that improvements in transit service even in low-density cities can generate the intended effects. Whether the increased ridership among Queen's employees, and among Kingstonians more generally, is actually meeting Kingston Transit's targets is unclear and warrants further investigation.

Given the potential physical activity benefits of shifting from passive commuting to commuting by transit, Kingston Transit could consider partnering with the local public health unit to launch education campaigns to promote transit use among the residents living within the outlying suburbs that are directly served by the express routes (e.g., comparing cost of monthly transit pass to parking permits, relating stop locations within neighbourhoods to number of potential minutes accrued in daily PA). Since several of Kingston's large employers are located at, or near, downtown, and along the express bus routes, such campaigns could result in mode shifts for employees of numerous organizations, and not simply for Queen's.

Non-shifters in this study are much more likely to have a permit to park at Queen's, suggesting this is a key barrier to shifting to transit. Since the cost of a permit to park on-campus is quite high ($90–120/month), once subscribed, it is difficult for the subscriber to justify making the switch to transit. The employer-subsidized bus pass program does appear to have helped stimulate transit use, since the vast majority of shifters did subscribe to this program. However, more work is needed by Queen's to ensure that its parking policies do not undermine the municipality's efforts to promote transit use.

Limitations

There are a few limitations of this study that are worth noting. First, individuals that were particularly interested in the topic of commuting, and in particular those that shifted to transit and wanted to report on their experiences, may have been more likely to complete the survey. If this happened, then the proportion of shifters in the longitudinal sample could be overestimated. This potential for bias was minimized by presenting the survey as one about commute modes and health. It is more likely that transit ridership statistics were underestimated, since the sample possessed a few characteristics that are associated with lower prevalence of transit use, namely living within close proximity to work, being older, and having higher household incomes.

Physical activity levels were determined based on self-reported estimates of number of minutes spent engaged in PA, for both commuting and non-commuting purposes. While the accuracy of these estimates is limited, there is no reason to believe that the level of inaccuracy varies by commute mode, and as such, would have little bearing on the PA analysis. We assumed that the mode of respondents' commutes back home would be the same as their commutes to work (e.g., taking transit to work and back home, walking to work and back home), and that within a given season, respondents would use the same commute mode for every day that they commute to Queen's. Given these assumptions, we multiplied the commute-related PA minutes by two (to capture commute-related PA for the journey home), as well as by the number of days in a typical week that they go to work (to capture commute-related PA for the week). Since these assumptions may not be correct, our estimates of PA may be biased. Such limitations are typical when attempting to capture PA data from self-administered surveys and can only be overcome (often with much smaller samples) through more objective yet invasive and costly instruments, such as accelerometers. Finally, PA minutes were only captured in 2014, which precluded analyses of changes in PA over time. This same survey will be administered again in 2015, ensuring these analyses can be performed.

Conclusions

This study examined changes in commute patterns over time among employees at a large employer in a low-density Canadian city, following the introduction of express transit service. Differences in physical activity levels by commute mode were also examined, to assess the potential for health improvement if one shifted from exclusively passive commuting to commuting by transit. Most notably, there was statistically significant increase transit use from 2013 to 2014, in every season and year-round, suggesting that the City's improvements to transit service are having their intended effects on one of their priority populations. Compared to non-shifters, transit ‘shifters’ had fewer household-level opportunities to drive to work and were more amenable to transit-supportive programs and services. And, when compared by commute mode, transit riders accrue more weekly physical activity minutes than exclusively passive commuters. Taken together, these findings suggest that investments in public transit, even in low-density cities like Kingston Ontario, can reduce reliance on automobiles and promote health.

Conflict of Interest

The authors declare that there are no conflicts of interests.

Acknowledgments

This research received internal grant funding from Queen's University. The authors would also like to acknowledge staff at the Office of Institutional Research and Planning at Queen's for their assistance in administering the survey and preparing the data for analysis.

Contributor Information

Patricia A. Collins, Email: patricia.collins@queensu.ca.

Ajay Agarwal, Email: ajay.agarwal@queensu.ca.

References

  1. AMO . Association of Municipalities of Ontario (report prepared by the Blackstone Corporation); Toronto, ON: 2008. A Sustainability Planning Toolkit for Municipalities in Ontario. [Google Scholar]
  2. Bechard M. Statistics Canada; S. a. A. S. Division, Ottawa, ON: 2011. General Social Survey Cycle 24: Time-Stress and Well-Being. [Google Scholar]
  3. Besser L.M., Dannenberg A.L. Walking to public transit: steps to help meet physical activity recommendations. Am. J. Prev. Med. 2005;29(4):273–280. doi: 10.1016/j.amepre.2005.06.010. [DOI] [PubMed] [Google Scholar]
  4. Bopp M., Kaczynski A.T., Wittman P. The relationship of eco-friendly attitudes with walking and biking to work. J. Public Health Manag. Pract. 2011;17(5):E9–E17. doi: 10.1097/PHH.0b013e31821138de. [DOI] [PubMed] [Google Scholar]
  5. Brockman R., Fox K.R. Physical activity by stealth? The potential health benefits of a workplace transport plan. Public Health. 2011;125(4):210–216. doi: 10.1016/j.puhe.2011.01.005. [DOI] [PubMed] [Google Scholar]
  6. Brown B.B., Werner C.M. A new rail stop: tracking moderate physical activity bouts and ridership. Am. J. Prev. Med. 2007;33(4):306–309. doi: 10.1016/j.amepre.2007.06.002. [DOI] [PubMed] [Google Scholar]
  7. Brown B.B., Werner C.M., Tribby C.P., Miller H.J., Smith K.R. Transit use, physical activity, and body mass index changes: objective measures associated with complete street light-rail construction. Am. J. Public Health. 2015;105(7):1468–1474. doi: 10.2105/AJPH.2015.302561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Butler G.P., Orpana H.M., Wiens A.J. By your own two feet: factors associated with active transportation in Canada. Can. J. Public Health. 2007;98(4):259–264. doi: 10.1007/BF03405399. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Chaix B., Kestens Y., Duncan S. Active transportation and public transportation use to achieve physical activity recommendations? A combined GPS, accelerometer, and mobility survey study. Int. J. Behav. Nutr. Phys. Act. 2014;11(1):124. doi: 10.1186/s12966-014-0124-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chen C., Gong H., P. R. Role of the built environment on mode choice decisions: additional evidence on the impact of density. Transportation. 2008;35(3):285–299. [Google Scholar]
  11. CSEP Canadian Physical Activity Guidelines: For Adults 18-64 years. 2012. http://csep.ca/CMFiles/Guidelines/CSEP-InfoSheets-adults-ENG.pdf from.
  12. Dillman D.A., Smyth J., Christian L. Hoboken; NJ, Wiley & Sons: 2008. Internet, Mail, and Mixed-Mode Surveys: The Tailored Design Method. [Google Scholar]
  13. Edwards R.D. Public transit, obesity, and medical costs: assessing the magnitudes. Prev. Med. 2008;46:14–21. doi: 10.1016/j.ypmed.2007.10.004. [DOI] [PubMed] [Google Scholar]
  14. Evans G.W., Wener R.E. Rail commuting duration and passenger stress. Health Psychol. 2006;25:408–412. doi: 10.1037/0278-6133.25.3.408. [DOI] [PubMed] [Google Scholar]
  15. Evans G.W., Wener R.E., Phillips D. The morning rush hour: predictability and commuter stress. Environ. Behav. 2002;34(4):521–530. [Google Scholar]
  16. Feng Z., Boyle P. Do long journeys to work have adverse effects on mental health? Environ. Behav. 2014;46(5):609–625. [Google Scholar]
  17. Frank L.D., Andresen M.A., Schmid T.L. Obesity relationships with community design, physical activity, and time spent in cars. Am. J. Prev. Med. 2004;27(2):87–96. doi: 10.1016/j.amepre.2004.04.011. [DOI] [PubMed] [Google Scholar]
  18. Frank L.D., Saelens B.E., Powell K.E., Chapman J.E. Stepping towards causation: do built environments or neighborhood and travel preferences explain physical activity, driving, and obesity? Soc. Sci. Med. 2007;65(9):1898–1914. doi: 10.1016/j.socscimed.2007.05.053. [DOI] [PubMed] [Google Scholar]
  19. Giles-Corti B., Foster S., Shilton T., Falconer R. The co-benefits for health of investing in active transportation. NSW Publ. Health Bull. 2010;21(5-6):6. doi: 10.1071/NB10027. [DOI] [PubMed] [Google Scholar]
  20. Gordon-Larsen P., Nelson M.C., Beam K. Associations among active transportation, physical activity, and weight status in young adults. Obes. Res. 2005;13(5):868–875. doi: 10.1038/oby.2005.100. [DOI] [PubMed] [Google Scholar]
  21. Handy S.L., Xing Y. Factors correlated with bicycle commuting: a study in six small U.S. cities. Int. J. Sustain. Transp. 2011;5(2):91–110. [Google Scholar]
  22. Hansson E., Mattisson K., Bjork J., Ostergren P.-O., Jakobsson K. Relationship between commuting and health outcomes in a cross-sectional population survey in southern Sweden. BMC Public Health. 2011;11(1):834. doi: 10.1186/1471-2458-11-834. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kam W., Cheung K., Daher N., Sioutas C. Particulate matter (PM) concentrations in underground and ground-level rail systems of the Los Angeles Metro. Atmos. Environ. 2011;45(8):1506–1516. doi: 10.1021/es201195e. [DOI] [PubMed] [Google Scholar]
  24. KEDCO . Kingston Economic Development Corporation; Kingston, ON: 2014. Kingston CMA Major Employers, Expansions and Downsizings and Military Establishments. (Retrieved July 4, 2014, from http://business.kingstoncanada.com/en/communityprofile/employers.asp) [Google Scholar]
  25. Kim S., Ulfarsson G.F. Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips. Transportation. 2008;35(6):723–737. [Google Scholar]
  26. Kingston . Kingston Transit Redevelopment Plan: 2011-2015. 2011. (Kingston, ON, City of Kingston: 84) [Google Scholar]
  27. Lachapelle U., Frank L.D. Transit and health: mode of transport, employer-sponsored public transit pass programs, and physical activity. J. Public Health Policy. 2009;30:S73–S94. doi: 10.1057/jphp.2008.52. [DOI] [PubMed] [Google Scholar]
  28. Lachapelle U., Noland R.B. Does the commute mode affect the frequency of walking behavior? The public transit link. Transp. Policy. 2012;21:26–36. [Google Scholar]
  29. Larsen J., El-Geneidy A. Beyond the quarter mile: re-examining travel distances by active transportation. Can. J. Urban Res. 2010;19(1 SUPPL.):70–88. [Google Scholar]
  30. Lawson C.T., Mallia M.E., Franklin C., Fischer B., Hogenkamp D., Ryan M. Case study: university at albany develops a guide to examine commuting behavior and patterns. Sustain. J. Rec. 2012;5(2):107–110. [Google Scholar]
  31. Lindström M. Means of transportation to work and overweight and obesity: a population-based study in southern Sweden. Prev. Med. 2008;46:22–28. doi: 10.1016/j.ypmed.2007.07.012. [DOI] [PubMed] [Google Scholar]
  32. Marzoughi R. Teen travel in the Greater Toronto Area: a descriptive analysis of trends from1986 to 2006 and the policy implications. Transp. Policy. 2011;18:623–630. [Google Scholar]
  33. Olsson L.E., Gärling T., Ettema D., Friman M., Fujii S. Happiness and satisfaction with work commute. Soc. Indic. Res. 2013;111(1):255–263. doi: 10.1007/s11205-012-0003-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Páez A., Whalen K. Enjoyment of commute: a comparison of different transportation modes. Transp. Res. A. 2010;13 [Google Scholar]
  35. Pendola R., Gen S. BMI, auto use, and the urban environment in San Francisco. Health Place. 2007;13:551–556. doi: 10.1016/j.healthplace.2006.02.004. [DOI] [PubMed] [Google Scholar]
  36. PHAC What is Active Transportation? 2010. http://www.phac-aspc.gc.ca/hp-ps/hl-mvs/pa-ap/at-ta-eng.php Retrieved July 21, 2014, from. (February 9, 2010)
  37. Salant P., Dillman D.A. John Wiley & Sons, Inc.; New York: 1994. How to Conduct Your Own Survey. [Google Scholar]
  38. Shannon T., Giles-Corti B., Pikora T., Bulsara M., Shilton T., Bull F. Active commuting in a university setting: assessing commuting habits and potential for modal change. Transp. Policy. 2006;13(3):240–253. [Google Scholar]
  39. Shephard R.J. Is active commuting the answer to population health? Sports Med. 2008;38(9):751–758. doi: 10.2165/00007256-200838090-00004. [DOI] [PubMed] [Google Scholar]
  40. Shoup D. American Planning Association; Chicago, IL: 2011. The High Cost of Free Parking. [Google Scholar]
  41. SPCK&A . Social Planning Council of Kingston & Area; Kingston, ON: 2009. Kingston Community Profile 2009: A Socio-Demographic Analysis of Kingston, Ontario. [Google Scholar]
  42. Statistics Canada . Statistics Canada; Ottawa, ON: 2006. Commuting Patterns and Places of Work of Canadians, 2006 Census. [Google Scholar]
  43. Statistics Canada . Statistics Canada; Ottawa, ON: 2011. Commuting to Work: National Household Survey (NHS), 2011. [Google Scholar]
  44. Statistics Canada . Statistics Canada; Ottawa, ON: 2011. Population and dwelling counts, for census metropolitan areas and census agglomerations, 2011 and 2006 censuses. (Retrieved January 2, 2014, from http://www12.statcan.gc.ca/census-recensement/2011/dp-pd/hlt-fst/pd-pl/Table-Tableau.cfm?LANG=Eng&T=201&SR=1&RPP=150&S=11&O=A) [Google Scholar]
  45. Statistics Canada . Statistics Canada; Ottawa, ON: 2012. Canadian Commuinty Health Survey: Annual Component - 2012 Questionnaire. [Google Scholar]
  46. Statistics Canada . Statistics Canada; Ottawa, ON: 2012. Canadian Survey on Disability. [Google Scholar]
  47. Statistics Canada . Statistics Canada; Ottawa, ON: 2012. Canadian Health Measures Survey - Cycle 3: 2012 to 2013. [Google Scholar]
  48. Turcotte M. Statistics Canada; Ottawa, ON: 2011. Commuting to Work: Results of the 2010 General Social Survey. [Google Scholar]
  49. Wener R.E., Evans G.W. A morning stroll: levels of physical activity in car and mass transit commuting. Environ. Behav. 2007;39(1):62–74. [Google Scholar]
  50. Wener R.E., Evans G.W., Phillips D., Nadler N. Running for the 7:45: the effects of public transit improvements on commuter stress. Transportation. 2003;30(2):203–220. [Google Scholar]

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