, 2013 and Panter et al., 2011). All analyses were conducted in Stata 11.1. Differences in baseline characteristics between participants with and without follow-up data were tested using t tests, χ2 tests or Mann–Whitney U tests. One-way analysis of variance was used to test for differences between change in usual mode(s) and in time spent walking or cycling. Associations between potential predictors and all outcomes were assessed using logistic regression models, initially adjusted for age and sex. Route characteristics were matched to the behaviour of interest; thus walking

models included pleasantness and convenience of routes for walking and convenience of public transport, while cycling models included convenience of routes for cycling. All variables significantly associated at p < 0.25 (in the case of categorical variables, p < 0.25 for heterogeneity Selleckchem MK1775 between groups) ( Hosmer and Lemeshow, 1989) were carried forward into multivariable regression models. No adjustment selleck kinase inhibitor was made for clustering by workplace, as preliminary multilevel models suggested no evidence of this. Relocation can alter the length of a commute or the route taken. As a sensitivity analysis, we identified participants who reported different home

or work postcodes at t1 and t2 corresponding to different locations. Excluding these movers (n = 155) from analysis made no substantial difference

to the direction or size of associations, hence the results presented include these participants. Of the 1164 participants who returned questionnaires at t1, 704 (60.5%) completed questionnaires at t2 and 655 next provided information on commuting at both t1 and t2 and were included in this analysis (Table 2). Those included were more likely to be older (mean age of 43.6 years versus 40.5 years, p = 0.01) and to own their own home (75.1% versus 71.8%, p = 0.01) than those who did not participate at t2. There were no significant differences in gender, educational qualifications, weight status, car ownership or time spent walking or cycling at baseline. Changes in time spent walking and cycling were symmetrically distributed. Many participants had change values of 0 min/week, reflecting either: (i) no walking (or cycling) at t1 and t2 or (ii) exactly the same number of trips and average duration of walking (or cycling) per trip at t1 and t2. Mean change values were relatively small (walking: + 3.0 min/week, s.d. = 66.7, p = 0.24; cycling: − 5.3 min/week, s.d. = 74.7, p = 0.07). Those who reported more time walking or cycling on the journey to work at t1 tended to report less at t2 ( Fig. 1).