Baseline characteristics of the sample were compared for participants living in the greenest 25% (quartile) of neighbourhoods versus the least green 25%, using one-way analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables. The primary outcome, change in physical activity, followed a normal distribution, therefore parametric tests were used. Change in physical activity between baseline and follow-up according to quartile of greenspace exposure in the home neighbourhood was explored using error bar plots and ANOVA. Multivariable regression models were used to explore the association between exposure to greenspace, divided into quartiles, and change in physical activity between baseline and follow-up. The reference category was individuals living in the least green home neighbourhoods (quartile 1). Models were adjusted for physical activity at baseline, age, sex, BMI, SES and marital status. Mediation analysis was conducted to test dog walking as a potential mediator on the causal path between exposure to greenspace and change in physical activity. While the test cannot prove causation, it can indicate whether the data fit with the presumed causal structure (de Vries, van Dillen, Groenewegen, & Spreeuwenberg, 2013), namely that greenspace facilitates dog walking and thereby physical activity. The product of the coefficients method developed by Preacher and Hayes was followed, to calculate total, direct and indirect effects with bootstrapped, bias corrected, standard errors (Preacher & Hayes, 2008). All analyses were conducted using Stata version 13 (Stata Corp, 2013).