## 2 Materials and Methods
### Measures  
**PA.** PA was objectively assessed using the Actigraph GT3X+ accelerometer (Actigraph, Pensacola, Florida, FL, USA). The accelerometer was attached to an elastic, adjustable belt. Participants were instructed to wear the device on the right hip for seven consecutive days during waking hours (except during water-based activities). Actilife v6.11.2 (Firmware 2.2.1, Actigraph, Pensacola, Florida, FL, USA) was used to download accelerometer data. Triaxial accelerometer data were collected in 5 s epochs, and summed as counts per minute (cpm) during data processing. Vector magnitude cut-points for cpm were used to define moderate PA (3208-8564 cpm) and vigorous PA (\(\geqslant\)8565 cpm), which were derived from a study population similar to this study's population [30]. MVPA was calculated as the sum of moderate PA and vigorous PA.  
Because of the slightly older population, non-wear time was defined as episodes of at least 90 min of consecutive zero counts [31], with allowance for up to two consecutive minutes of 1-100 cpm. Non-wear episodes ended when the cpm exceeded 100, or when three or more consecutive minutes accumulated between 1 and 100 cpm [32]. To determine the length of a valid day, the 70/80 rule was used. This rule defines a valid day as having non-missing counts for at least 80% of a measurement day [33]. A measurement day reflects the length of time in which at least 70% of all participants wore  
Figure 2: Flowchart of participant recruitment. the accelerometer device [33], which was 611 min for this study. Calculating 80% of this episode of 611 min yields a valid day of 488.8 min. Only valid data of participants with at least four of these valid days were included for analyses [34]. **PA locations and trips. ** Participants' geographical locations were measured using BT-Q1000 XT GPS-devices (QStarz International Co, Taipei, Taiwan). The GPS-device was attached to the same belt as the accelerometer and wearing instructions were similar to those for wearing an accelerometer. QStarz QTravel software (v1.45, Qstarz International Co., Ltd, Taipei, Taiwan) was used to download GPS-data. GPS- and accelerometer-data were date and time linked using Python software to create combinations of PA intensity and location of PA.  
To gain insight into the locations where adults are actually physically active, GPS-data had to be categorized into various types of activity locations. To do so, all GPS-data were first subdivided into either stop episodes or trips. This identified a first category of activity locations, namely: trips, as being in transit can be considered a \"location\" where PA may take place. Trips are clusters of successive GPS data points of which (1) the average speed was 3 km/h or more; (2) the trip length was 100 m or more; and (3) the minimum duration of a trip was 1 min. \"Trips\" are further referred to as \"transport\". Stop episodes are clusters of successive GPS data points that met the following three criteria: (1) the maximum range of data points was 150 m; (2) the average speed of data points was under 3 km/h; and (3) the minimum duration of a stop episode was 2 min. For each stop episode, the center of gravity was calculated. The coordinates of these centers of gravity were used to map all stop episodes (stops) in ArcMap 10.2.2 (Esri, Redlands, California, CA, USA). To further categorize stops into specific types of locations, ArcMap was used to link data on land use (available from Dutch Statistics, 2010) and buildings (available from Dutch Cadaster, 2014) to these stops. For each stop, we calculated in what type of land use it was located, what types of land use (and in what proportions) occurred within a 25 meter buffer (from the center of gravity), and what functions the three nearest buildings had. Based on this information, stops were further classified into nine different categories.