Elsevier

Preventive Medicine

Volume 50, Supplement, January 2010, Pages S74-S79
Preventive Medicine

Neighborhood SES and walkability are related to physical activity behavior in Belgian adults

https://doi.org/10.1016/j.ypmed.2009.07.027Get rights and content

Abstract

Objective

To investigate whether neighborhood walkability (higher residential density, land use mix, street connectivity) is positively associated with physical activity in Belgian adults and whether this association is moderated by neighborhood SES.

Methods

The Belgian Environmental Physical Activity Study (BEPAS) was conducted in Ghent, Belgium. Data were collected between May 2007 and September 2008. Twenty-four neighborhoods were selected, stratified on GIS-based walkability and neighborhood SES. In total, 1200 adults (aged 20–65 years; 50 per neighborhood) completed the International Physical Activity Questionnaire and wore an accelerometer for seven days. After omitting participants with missing accelerometer data, the final sample consisted of 1166 adults.

Results

Living in a high-walkable neighborhood was associated with more accelerometer-based minutes of moderate-to-vigorous physical activity (38.6 vs. 31.8 min/day, p < 0.001), transportational walking and cycling, recreational walking, and less motorized transport (all p < 0.05). Low neighborhood SES was related to more cycling for transport and less motorized transport (all p < 0.05). No interactions between walkability and neighborhood SES were found.

Conclusions

The BEPAS results generally confirmed the findings from Australia and the US showing that, in Europe, walkability is also positively related to physical activity. As neighborhood SES was not a significant moderator, walkability appears beneficial for all economic strata.

Introduction

Ecological models state that physical activity has multiple levels of influence, including demographic, psychosocial, physical environmental, and policy factors. To change people's behavior, it is important to intervene on these multiple levels (Sallis et al., 2008). Previous studies have shown that older, overweight or obese, lower-educated, and female adults are less physically active than their younger, normal weight, higher-educated, and male counterparts (Trost et al., 2002, Sallis and Owen, 1999, Martinez-Gonzalez et al., 1999). Psychosocial correlates, like self-efficacy and social support, also are consistently related to physical activity (De Bourdeaudhuij et al., 2005, Trost et al., 2002).

Recently, an increasing focus on the association between the physical environment and physical activity has occurred (Sallis et al., 2008). In that context, neighborhood “walkability” is an important concept. Key elements of walkability are residential density, land use mix, and connectivity (Saelens et al., 2003). These elements are synergistic, with a higher walkability (greater density, more land use mix, and higher connectivity), being related to more physical activity (Saelens and Handy, 2008). A growing number of US and Australian studies have investigated the relationships between neighborhood walkability and physical activity. Two comprehensive studies are the Neighborhood Quality of Life Study (NQLS) in the US (Frank et al., 2006, Sallis et al., 2009) and the Physical Activity in Localities and Community Environments (PLACE) study in Australia (Owen et al., 2007). Both studies have an identical design and investigated associations between neighborhood SES, walkability, and physical activity in adults. The NQLS showed that high walkability was positively related to walking for transport, leisure-time physical activity, and accelerometer-based moderate-to-vigorous physical activity (MVPA) (Sallis et al., 2009). The PLACE study showed that living in a high-walkable neighborhood was associated with more walking for transport (Owen et al., 2007).

In NQLS and PLACE, neighborhood SES was also studied as a potential moderator of the associations between walkability and physical activity. Regarding these interactions, both studies had different findings. In the PLACE study, physical activity behavior of high-SES neighborhood residents was more strongly associated with walkability than that of low-SES neighborhood residents (Owen et al., 2007). In the NQLS, no such interactions were found (Sallis et al., 2009). Addressing these moderating effects is important for several reasons. First, walkability is a physical environment factor and neighborhood SES a social environment factor with “physical” implications. The social and physical characteristics of low-SES/high-walkable neighborhoods are likely to differ from those of high-SES/high-walkable neighborhoods. If these interactions are not investigated, important underlying mechanisms could be ignored. Second, it is crucially important to reduce known health disparities across socioeconomic groups. Therefore, it is essential to determine whether walkability relates similarly to several health behaviors in low- and high-SES neighborhoods. Third, investigating these interactions is relevant for public health and urban environment policy, and for future environmental and social innovations aiming to increase physical activity.

Previous studies also showed that neighborhood SES can have a significant direct relationship with physical activity (McNeill et al., 2006, Ross and Mirowsky, 2008). However, findings are at this stage ambiguous, with some studies finding that high-SES neighborhood inhabitants are more physically active (Kavanagh et al., 2005, McNeill et al., 2006) and other studies finding the opposite (van Lenthe et al., 2005, Ross, 2000). Further research is therefore needed to clarify these associations.

However, because large differences in physical environments and physical activity behaviors (especially cycling) exist between Europe and the US or Australia, European studies are needed. Moreover, the physical environment of European cities differs in many ways from other continents and the associations between walkability and physical activity will probably be different when compared, for example, to the US and Australia. Until now, most European physical environmental studies have either used only self-reported physical environmental perceptions (De Bourdeaudhuij et al., 2003, De Bourdeaudhuij et al., 2005, Santos et al., 2008) or included relatively small sample sizes (Van Dyck et al., 2009). For example, in Belgium and Portugal, positive associations between perceived environmental attributes and physical activity were found in a sample of 521 Belgian adults (De Bourdeaudhuij et al., 2003) and a sample of 526 Portuguese and Belgian adults (De Bourdeaudhuij et al., 2005). A Portuguese study of 7330 adults also found positive associations between perceived environment attributes and walking for transport (Santos et al., 2008). Another Belgian study with objective environmental measurements found a positive relationship between walkability and active transportation in 120 adults (Van Dyck et al., 2009). Moreover, no European studies investigated the link between neighborhood SES and walkability, and no common designs are available to enhance cross-national comparisons.

The Belgian Environmental Physical Activity Study (BEPAS) investigated associations between walkability, neighborhood SES, and physical activity among Belgian adults. This is the first large-scale European study with a design identical to NQLS and PLACE. Based on the findings of these studies, we hypothesized that living in a high-walkable neighborhood would be associated with more walking for transport. Moreover, because of inconsistencies between findings from NQLS and PLACE, we investigated whether neighborhood SES moderated the relationship between walkability and physical activity behaviors.

Section snippets

Procedures

The BEPAS was conducted in Ghent (237,000 inhabitants, 156.18 sq km (60.3 sq miles), 1468 inhabitants/km2). Data were collected between May 2007 and September 2008. Research protocols of NQLS and PLACE were modified for the Belgian setting by using Belgian census data (National Institute of Statistics – Belgium, 2008) to define neighborhood SES and using the available Geographic Information Systems (GIS) databases to define walkability. The BEPAS was approved by the Ethics Committee of the

Demographic characteristics and physical activity behavior of the sample

The overall response rate (participants/possible participants found at home) was 58.0% (range 57.5% to 58.7%) across neighborhoods. The final sample consisted of 1166 participants. Demographic characteristics of the sample are shown in Table 2. Compared to data from the National Institute of Statistics - Belgium (2008), the sample was more likely to be highly educated and employed, and participating women were more likely to have a lower BMI.

On average, participants reported a mean of 77.5 (SD = 

Discussion

For the first time in Europe, a large-scale study with a design identical to studies in the US and Australia was undertaken to allow comparison of environment and physical activity results across countries. For self-reported walking for transport and accelerometer-based MVPA, BEPAS results are in line with NQLS (Sallis et al., 2009), and consistent with PLACE on self-reported walking for transport (Owen et al., 2007). However, some new, and potentially European-specific, findings on cycling for

Conclusions

In summary, the BEPAS showed that in Belgium, walkability was related to different physical activity behaviors. The direction of effects and even absolute differences in physical activity across low- and high-walkable neighborhoods were very similar to those found in Australia (Owen et al., 2007) and the US (Sallis et al., 2009). Neighborhood SES did not interact with the relationship between walkability and physical activity, which could have policy implications for the development of

Conflict of interest statement

The authors declare that there are no conflicts of interest.

Acknowledgments

This research was supported by Fund for Scientific Research Flanders (FWO) B/09731/01. Dr. Sallis' contributions were supported by NIH grant HL67350. Dr. Owen's contributions were supported by a Program Grant (#301200) from the National Health and Medical Research Council of Australia, and by a Research Infrastructure Grant from Queensland Health.

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