| Literature DB >> 30008521 |
Katarzyna Iwińska1, Malgorzata Blicharska2, Livia Pierotti3, Marko Tainio4,5, Audrey de Nazelle3.
Abstract
Cycling in urban environments provides many benefits to people. However, planning of cycling infrastructures in large cities faces numerous challenges and requires better understanding of both the factors enabling cycling as well as barriers to it, determined by particular local context. While there is a growing body of research that tackle the bike transport related questions in Western Europe and the USA, there is relatively little research on that in Central Eastern Europe (CEE), in post-communist countries. In this study we used qualitative and quantitative methods to explore urban cyclists and non-cyclists opinions about the cycling, the perceived problems and obstacles, and perception of the on-going changes in bicycle transportation system in Warsaw, Poland. Although many people see potential advantages of cycling, it is mostly perceived as a leisure time activity. Those who do utilitarian cycling are more acutely aware of the benefits, such as rapidity and flexibility of this mean of transport. The main perceived barriers are linked to lack of good cycling infrastructure in the city, the feeling of insecurity linked to the behaviour of drivers, and to maintenance during winter. In conclusion, our research highlights both the opportunities and challenges linked to the development of improved cycle transportation system, suggesting the need for a range of policies, from the infrastructure improvements and comprehensive planning of the whole transportation system, to improving the driving culture that would support feeling of security of the cyclists.Entities:
Keywords: Active transport; Barriers to cycling; Cyclist perception; Infrastructural changes in the city; Urban cycling
Year: 2018 PMID: 30008521 PMCID: PMC6039858 DOI: 10.1016/j.tra.2018.04.014
Source DB: PubMed Journal: Transp Res Part A Policy Pract ISSN: 0965-8564 Impact factor: 5.594
Characteristic of the two samples (random and cyclist) of participants. Data are presented as median unless otherwise stated. VPA = Vigorous Physical Activity; MPA = Medium Physical Activity; SD = Standard deviation; IQR (interquartile range).
| Characteristic | Random sample (N = 561) | Cyclist sample (N = 505) | ||||||
|---|---|---|---|---|---|---|---|---|
| Total | Non-cyclist | Cyclist | p-value | Total | Recreational | Utilitarian | p-value | |
| Female, n (%) | 303 (54%) | 145 (56%) | 158 (52%) | 214 (42%) | 107 (52%) | 107 (36%) | ||
| Male, n (%) | 258 (46%) | 113 (44%) | 145 (48%) | P = 0.381 | 291 (58%) | 100 (48%) | 191 (64%) | P < 0.001 |
| Age mean (SD) | 48 (15.2) | 54 (15.8) | 44 (13.1) | P < 0.001 | 31 (10.3) | 32 (10.6) | 31 (10.1) | P = 0.135 |
| Total duration cycling (minutes per week) | NA | NA | NA | NA | 23 (28) | 16(18) | 28(32) | P < 0.001 |
| Total duration (minutes per week) of VPA | 80 (280) | 90 (180) | 65 (280) | P = 0.527 | 180(280) | 165(180) | 180(280) | P = 0.433 |
| Total duration (minutes per week) of MPA | 100 (300) | 72 (313) | 120 (298) | P < 0.001 | 120(300) | 100(313) | 140(298) | P = 0.126 |
| Walking at least 10 min, n daysMean | 3.5 (2.7) | 2.9 (2.6) | 4.1 (2.7) | P < 0.001 | 4.72 (2.2) | 4.68 (2.2) | 4.75 (2.2) | P = 0.721 |
| BMI mean (SD) | 24.4 (3.8) | 25.1 (4.0) | 23.9 (3.5) | P < 0.001 | 24.4 (4.4) | 24.3 (4.5) | 24.5 (4.3) | P = 0.588 |
| BMI categories, n (%) | P = 0.042 | P = 0.011 | ||||||
| Underweight, n (%) | 13(3%) | 5 (2%) | 8 (3%) | 28 (6%) | 17 (8%) | 11 (4%) | ||
| Normal weight, n (%) | 284 (57%) | 110 (51%) | 174 (61%) | 276 (55%) | 98 (48%) | 178 (60%) | ||
| Overweight, n (%) | 199 (40%) | 100 (47%) | 99 (35%) | 197 (39%) | 88 (43%) | 109 (37%) | ||
Fig. 1Cycling purposes in past 6 months.
Fig. 2Odds ratio for agreeing with perception statements regarding physical and social aspects of cycling and 95% CI for utilitarian vs recreational cyclists in the cyclist sample (figure on the right) and cyclists vs non-cyclist in the random sample (figure on the left). Multivariable logistic regressions are adjusted for age, sex and BMI.