Active Transportation in Kingston, Ontario: An Analysis of Mode, Destination, Duration, and Season among Walkers and Cyclists

Abstract

Background: Individuals that engage in active transportation (AT) have healthier weights and fitness levels. Most AT research has focused on work-or school-based destinations. Meanwhile, little is known about the differences between individuals that engage in the most common forms of AT-walking and cycling-and how these AT patterns vary by destination, duration, and season. Methods: We recruited 1400 randomly sampled adults (350 per season) in Kingston, Ontario, Canada to complete a cross-sectional telephone survey. The survey captured the prevalence, destinations, and duration of AT, and we examined the observed differences by mode. Results: The majority (72%) of respondents were AT-users; walking constituted 93% of overall mode share. Cyclists were more likely to be male, younger, and employed than walkers. Walkers tended to access neighborhoodbased destinations, while cyclists were more likely to use AT to get to work. AT duration was comparable by mode, ranging from approximately 8 to 20 minutes. Overall rates of AT were lowest in the winter, but walking rates were reasonably high year-round. Conclusions: Beyond commuting to work and school, policy-makers and planners should consider the breadth of destinations accessed by different modes when aiming to increase physical activity through AT in their communities.

Impact of Seasonality on Physical Activity: A Systematic Review

“…The characteristics of the studies included are detailed in Table 1 and Table 2 . These 26 studies were conducted in 18 different countries with a dominance of the USA with six contributions [ 16 , 20 , 23 , 24 , 27 , 53 ] and Canada with four [ 9 , 31 , 54 , 56 ]. Two studies were developed in countries as Japan [ 13 , 55 ] and Poland [ 17 , 44 ].…”

“…Regarding types of climates, according to the Köppen climate classification, 9 types of climates were represented in the selected articles. Most of the studies were developed in locations with Dfb climate (11 studies) corresponding to a warm-summer humid continental climate [ 23 , 24 , 31 , 32 , 34 , 44 , 45 , 53 , 54 , 56 ], 5 studies in Cfb regions (temperate oceanic climate) [ 15 , 19 , 57 , 59 , 60 ], 4 in Dfc (subartic climate) [ 15 , 45 , 54 , 56 ] and 3 in Cfa (humid subtropical climate) [ 13 , 19 , 55 ]. Just one study corresponds to a Bwh (hot desert climate) [ 5 ], Cfc (subpolar oceanic climate) [ 37 ], Dfa (hot summer humid continental climate) [ 20 ] or Dwa (Monsoon-influenced hot-summer humid continental climate) [ 42 ].…”

“…Recently, the number and relevance of PA promotion interventions have increased such as PA promotion strategy for the WHO European Region 2016–2025 [ 28 ]. It is now well-know that there are factors that modulate participation in PA promotion programs, such as place of residence [ 29 ], accessibility to facilities [ 30 , 31 ], socio-economic characteristics of individuals [ 32 ], lifestyle [ 33 ], aging population [ 34 ], previous pathologies [ 19 , 35 ], beliefs and values [ 36 , 37 ], etc. [ 38 ].…”

Active commuting to school in Finland, the potential for physical activity increase in different seasons

“…2b). The time people are willing to spend on active commuting has been found to be quite fixed (33). Because cycling speed is generally more than twice the speed of walking, a change in active transport mode from cycling to walking can increase the commute time by more than 100%.…”

Longitudinal associations of active commuting with body mass index

“…Much existing research has explored active travel as a composite behaviour, often failing to separate walking and cycling ( Flint et al, 2014 , Laverty et al, 2015 , Lindström, 2008 , Martin et al, 2015 ). It may be important to consider the behaviours separately, because the duration and intensity of each activity can differ ( Ainsworth et al, 2011 , Collins and Mayer, 2015 , Millett et al, 2013 , Panter et al, 2013 ) and they tend to be undertaken by different segments of the population, suggesting that they may be differentially associated with body mass index. Some existing research has also failed to adjust for occupational or recreational activity ( Laverty et al, 2013 , Lindström, 2008 , Martin et al, 2015 ).…”