One possible explanation for the differing magnitudes

One possible explanation for the differing magnitudes of the correlations (r) for these relationships is as follows: if someone is walking to reach a destination (transportation), it is important that they have access to short routes (connectivity), that the origin and destination be in close proximity (land use), that walking and biking infrastructure is available (traffic safety), and that they have the impression that they can be easily observed by other members of the public (surveillance). Likewise, it may be important to have a park nearby (greenspace) (Sandifer et al., 2015) and atp gamma s facilities (community), particularly if these are the destinations in mind. It was surprising, however, that the predominant type of housing in the neighborhood (density) was not correlated with walking for transportation because low-density neighborhoods may cause longer routes and may result in less people in the streets. Isolated streets are thought to discourage physical activity whether recreational or transportational (Jacobs, 2011). Likewise, it was somewhat unexpected to find that the experience category was not significantly correlated with walking for transportation. We hypothesize that the time of the year that we collected the data might have played a role in shaping these results because during winter, Tucson residents enjoy comfortable weather. Some variables in the experience category, such as access to shade and the presence of trees, might not affect walking during the months we collected data, whereas during the summer months when the daily high temperature is typically above 100°F in Tucson, this category may become more important. Gathering new data during the hot summer months might yield different results for the correlation between the experience category and walking for transportation. With regard to walking for recreation, all of the walkability categories showed significant correlations. It was expected that greenspace and experience would produce the strongest correlations because it has been documented that the greenness of the built environment influence walking for recreation (Hartig et al., 2014), and our results confirmed this expectation. It was also not surprising to find that traffic safety is related to walking for recreation since pedestrian infrastructure is hypothesized as important for lifestyle physical activity (Jacobs, 2011). Likewise, land use showed significant and moderate correlations probably because proximity to shops and restaurant provides interesting sights to pedestrians (Jacobs, 2011; Montgomery, 2013). Even though connectivity, surveillance, and community were significantly correlated with recreational walking, these correlations were weak. It is possible that connectivity was weakly correlated with walking for recreation because a longer route may be enjoyable if the route itself is pleasant. Likewise, surveillance was found to be weakly correlated with this type of walking probably because when the crime rate in the neighborhood is low and neighbors are familiar with one another, people might feel safe walking in their own neighborhoods even if they are not being watched by those inside nearby homes. Similarly, we think that community was significantly but weakly correlated to recreational walking because spaces that allow opportunities for social interaction may be desired but not essential for this type of walking.
Conclusion This study supports the use of the Walkability Model to measure the built environment in relation to physical activity. This model was created by synthesizing the literature from several research domains on design elements that may influence physical activity (Zuniga-Teran, 2015; Zuniga-Teran et al., 2016). The organization of the categories was designed to integrate well with previously developed research tools (Saelens et al., 2003; Cerin et al., 2006; Frank et al., 2009), and the sustainable neighborhood design tool from LEED-ND (USGBC, 2014). The results of this study support our hypothesis that the Walkability Framework can test the strength of relationships between actual physical activity and predicted walkability.