Comparison group

We used a recently developed five-step process to identify two matched comparison sites in Greater Manchester (Fig. 3) [37]. The eight variables used for matching were based on nine systematic reviews of physical activity environmental correlates in adults [38–43] and older adults [44–46]. In brief, the first step involves identifying the most closely matched neighbourhoods to the index intervention neighbourhood, using spatial data at the Lower Layer Super Output Area (LSOA) level (population density, street connectivity, deprivation, neighbourhood greenness). The next four steps involve searching for the most closely matched comparison sites within the potential matched neighbourhoods identified in step one, using variables at the site level (e.g. footpath, benches, lighting). Steps two and three are conducted using Google Street View to narrow down potential matched comparison sites. Steps four and five involve in-person site audits. Additional file 1 provides further details of this matching process.

Overview of the five-step matching process used to identify comparison sites. Numbers in brackets refer to the key variables used for matching. References for the environmental audit tools: Cain et al. [35] and Gidlow et al. [36]. Based on a similar graphic originally published in Benton et al. [37]

The two matched comparison sites were pooled together into one comparison group. The main reason for pooling the comparison sites was to increase statistical power. Also, including multiple comparison sites in the analysis provides increased confidence that any variation in confounding variables across comparison sites is offset, therefore reducing the risk that the intervention effect is confounded by site-specific variables in a single comparison site.

A description of the key characteristics of the intervention and two comparison sites can be found in Table 1. Figure 4 shows the comparison sites at baseline.

Key characteristics of all study sites and LSOAs at baseline

Bromley Cross

(BL2 3EQ)

Leigh West

(WN7 4QP)

^a WalkScore uses a Google search algorithm to calculate a weighted score (1–100) based on the number and accessibility of amenities (such as shops and parks) within a 1-mile radius of a user-entered postcode, whereby closer amenities with the most accessible walking routes are weighted more strongly, used as a measure of ‘access to/ availability of destinations and services’. Higher scores indicate more ‘walkable’ areas

^b Lower Layer Super Output Area (LSOA): census reporting units containing between 1000 and 3000 people

^c Population density: number of persons per hectare; used as a proxy measure of residential density. Higher values indicate areas with higher population density

^d Intersection density: the number of 3-way junctions per 1000mˉ² standardised by LSOA area; used as a measure of street connectivity. Higher values indicate areas with higher street connectivity

^e Index of Multiple Deprivation Score (IMD) [47]: an area deprivation score that combines multiple indicators of deprivation including income, employment, health and crime. Higher values indicate more deprived areas

^f Normalised Difference Vegetation Index (NDVI): a validated normalised scale of healthy vegetation cover; used as a measure for presence of greenery at the neighbourhood-level. Higher values indicate areas with more healthy vegetation cover

Comparison sites at baseline. Photographs taken by Jack Benton in Nov 2017