Doing regular moderate-to-vigorous physical activity (MVPA) has several positive short- and long-term effects on health [1–4]. In 2008, approximately 31% of the global adult world population was not active enough to obtain these positive health effects . Being insufficiently active is associated with an increased risk for several chronic diseases, like cardiovascular diseases, type 2 diabetes, obesity and some types of cancers [6–8]. Overall, being insufficiently active is related to premature deaths, resulting in heavy economic costs [6, 8]. No changes in activity levels have been observed, and obesity rates and sedentary activities have increased during the last decade for example in North America and Australia, despite efforts that seek to encourage physical activity (PA) .
It is therefore important to develop insight in the correlates of PA and to develop a comprehensive population-based approach in promoting PA instead of an individual approach, which is the case nowadays [9–13]. Next to personal, cultural, and socio-economical factors, environmental attributes have been identified as important correlates of PA. A bourgeoning number of studies have offered compelling evidence that the physical environment influences people’s propensity to engage in physically active pursuits [13–19]. For example, Humpel et al.  found a positive relationship between accessibility and aesthetic attributes with PA in several reviewed articles. In another review article, Saelens et al. , for their part, identified 14 studies where an association between several neighbourhood attributes (e.g. accessibility, land use mix, access to public transport, and population density) and PA occurred. In a related study, Saelens et al.  concluded that people living in high walkable neighbourhoods in San Diego, California (US) engaged in approximately 52 more minutes of PA during a week compared to their counterparts living in low walkable neighbourhoods. Likewise, Owen et al.  reviewed 18 articles and observed that several environmental attributes (i.e. aesthetics, walking facilities, accessibility, and traffic perceptions) are linked with walking behavior.
However, these environmental attributes can be assessed in either an objective or perceived manner. Objective environmental attributes are measured using detailed georeferenced data by means of geographical information systems (GIS), while perceived attributes stem from self-reports in the form of surveys or questionnaires. Both types of attributes do not necessarily coincide and therefore may relate differently with physical activity behavior. For example, while objective availability of pertinent destinations in a neighborhood may be high, a person’s perceived availability can be low due to the fact that a person may not be aware of all feasible destinations in her/his neighborhood [21, 22]. A decreased environmental awareness may in turn lead to a lower propensity to walk in that neighborhood, although the objective availability of destinations suggests otherwise. People process and store information about their environment according to their own attitudes, motivations, and preferences. These perceptions are not necessarily precise representations of the actual objective environment [23, 24]. Incorporating both objective measures and perceptions of residents in research is important, as the impact of the objective environment on health depends on human perceptions, motivation, and deliberation .
In response to this potential discrepancy between the objective and perceived environment, several studies have scrutinized the concordance between objective and perceived environmental attributes, such as accessibility, walkability, dwelling density, street connectivity, land use mix, and retail density. Cerin et al. , for example, observed moderate to high correspondence between objective and perceived access to services, ease of walking, street connectivity, and walkability, whereas Ball et al.  found only a poor agreement between perceived and objective availability of PA facilities. Additionally, Ball et al.  noticed a greater mismatch between objective and perceived availability of PA facilities for less active people. However, they only examined whether or not certain facilities lie within a buffer zone around respondents’ location of residence (i.e. availability), but did not investigate distances to these facilities (i.e. accessibility). In a similar vein, Gebel et al.  observed a fair overall agreement between objective and perceived measures for dwelling density, intersection density, land use mix, and retail area. They found that less active people are more likely to misperceive the walkability of their neighbourhood. The reason for this is that more active people walk more in their neighbourhood, resulting in a better awareness of the environment [28–30]. Gebel et al.  additionally found that male, higher educated, normal weighted, older people from high walkable neighbourhoods make more correct estimations of environmental attributes.
Instead of examining previously mentioned environmental attributes, this paper studies the agreement between objective and perceived walking times from respondents’ residences to different locations. Only few studies examined the agreement between objective and perceived walking distances/times to date. Jilcott et al.  and Macintyre et al. , for example, observed a fair agreement between objective and perceived walking distances to parks, gyms, and schools, while McCormack et al.  and Lackey & Kaczynski  noticed only a poor agreement for these destinations. Besides general agreement, some studies also studied the degree of underestimation or overestimation. In both Jilcott et al.  and McCormack et al. , it was concluded that on average the perceived walking distance to several destinations is greater than the objective walking distance, presumably because people can be unaware of the existence certain close facilities. An overestimation of walking distance in self-reported data was also identified in many earlier studies [30, 35–37].
The agreement between objective and perceived walking distances/times can depend on several factors, with PA having the strongest influence. Because of greater environmental exposure and concomitant locational awareness, active people not only have a better perception of the previously mentioned attributes such as walkability and connectivity, but they can also make more accurate estimates of walking distances/times [33, 34]. Regarding shops, McCormack et al.  found that less active people overestimate the distance in comparison to their active counterparts. Looking at distances to parks, Lackey & Kaczynski  concluded that people who did at least some park-based PA can more accurately appraise walking distances, since they experience more intimate and slow speed interaction with the places resulting in better distance estimates [20, 22, 28, 29, 38]. However, reasoning also works the other way around: people with a good mental map of the environment might be more likely to be physically active, because they are more familiar with the local environment. However, to date, no literature was found to substantiate this direction of causation. Next to PA, other factors have also been tested. McCormack et al.  observed, for instance, that people from high walkable neighbourhoods in Adelaide (Australia) overestimated distances to several destinations. Also, it has been pointed out that people overestimate short and well-known routes and underestimate long and less-known routes [30, 35, 39, 40]. Considering other socio-demographic variables, Lackey & Kaczynski  concluded that younger, high educated, and normal weighted people have higher odds of achieving a match between objective and perceived proximity to parks in Ontario (Canada).
This study seeks to add to the knowledge base surrounding the above discussion by bringing additional evidence to the fore that sheds new light on the differential effects of objective and perceived access to urban destinations on physical activity.
The first objective is to analyze the agreement between objective and perceived walking times for residents from the city of Ghent. This is done by comparing objective and perceived walking times from one’s residence to different facilities (e.g. bakery, restaurant, and swimming pool etc.). The second objective is to test whether or not this agreement depends on PA, neighbourhood walkability, gender, educational level, body mass index (BMI), and age. It will be determined whether the degree of underestimation or overestimation differs depending on the previously mentioned factors.