, 2012) We adjusted our analysis for covariates known to be rela

, 2012). We adjusted our analysis for covariates known to be related to the prevalence of AC (Trost et al., 2002). Participants provided information on their gender, age (grouped as 16–29, 30–39, 40–49, 50–59, ≥ 60 years) and highest find more educational attainment (dichotomised into ‘less than bachelor’s degree’ and ‘bachelor’s degree or higher’) and the distance between their home and workplace (kilometres). We calculated body mass index from self-reported weight and height (kg/m2) and used standard cutpoints to categorise it into ‘normal or underweight’, ‘overweight’,

and ‘obese’ (World Health Organisation, 2000). To control for time spent in other forms of physical activity, we used responses to the validated Recent Physical Activity Questionnaire (RPAQ) (Besson et al., 2010), to compute total time spent in ‘recreational’ and ‘workplace’ physical activity (h/week). Univariable linear regression was used to explore associations between AC and physical and mental wellbeing. We then adjusted for covariates in multivariable models. The final specification of these models was determined using Akaike’s Information

Criterion (AIC) to identify the models that best fit the data. Recognising the potential for weight status to act as a confounder or a mediator of the relationship between active commuting and wellbeing, we present models before and after its inclusion. All analyses were conducted in 2012 using R version 2.13. Of the 1164 participants who completed the questionnaire, 128 were excluded from analysis due to physical disabilities or illnesses that may have prevented them from walking. A further 47 were excluded due to missing data Crenolanib chemical structure in either outcome, exposure, or covariate measures. This resulted in a sample of 989 participants for analysis, of whom most were female (68%), educated to bachelor’s degree level (73.1%) and neither overweight nor obese Histone demethylase (65.1%) (Table 1). Median scores on SF-8 summary variables were

higher than the population averages (50) for both physical (median = 56.0, IQR = 52.8–58.0) and mental (median = 52.5, IQR = 48.2–57.5) wellbeing. AC, educational attainment, and recreational and workplace physical activity were all significantly associated with physical wellbeing in univariable and multivariable analyses (Table 2). There was a clear association between the amount of AC and physical wellbeing, but no such relationship was found for mental wellbeing (adjusted regression coefficients 0.29, 0.27 and 0.68 for 30–149 min/week, 150–224 min/week and ≥ 225 min/week respectively versus < 30 min/week, p = 0.52 for trend). After adjustment for covariates, the strength of the relationship between AC and physical wellbeing was attenuated slightly by the inclusion of weight status in the model. The final model (PCS model 2) suggested that higher physical wellbeing was associated with greater time spent in active commuting (adjusted regression coefficients 0.

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