Associations of local-area walkability with disparities in residents' walking and car use
Introduction
Lack of physical activity is a major health risk and a leading cause of chronic diseases and premature death (Lee et al., 2012). Environmental attributes related to walkability (population density, street connectivity, and availability of utilitarian and recreational destinations), which differ between areas, are associated with residents' overall physical activity and with their walking (Christiansen et al., 2016; Cole et al., 2015; Koohsari et al., 2018; Thielman et al., 2015). A recent study using data from 14 cities worldwide found several built-environment attributes including higher residential density, well-connected streets, better access to public transport, and higher number of parks to be associated with higher levels of adults' physical activity (Sallis et al., 2016).
There are complex patterns in the distribution of physical activity. Disparities in physical activity can contribute to widening socio-economic inequalities in health (Petrovic et al., 2018). Socio-demographic disparities have been documented for self-reported leisure-time physical activity (Blackwell et al., 2014), self-reported walking for transportation (Paul et al., 2015), and accelerometer-measured physical activity (Troiano et al., 2008). However, geographic disparities in physical activity are less understood. There is a need to better understand spatial disparities in physical activity to help develop the place-based interventions that address contextual factors contributing to health problems and inequalities based on understanding of local socioeconomic and environmental characteristics (Smedley and Amaro, 2016).
There are studies examining how physical activity is spatially distributed, but they typically focus on between-area differences in physical activity. For instance, an Australian study found that a measure of walkability (consisting of dwelling density, intersection density, and land use diversity) constructed at a postal-area level accounted for between-area variation in those engaging in walking and moderate-to-vigorous physical activity sufficient for health benefits (Mayne et al., 2017). Similarly, a study conducted in the US showed that a measure of urban sprawl constructed at the level of county (a large administrative unit, which can include an entire metropolitan area) partially explained spatial variations in physical inactivity (Congdon, 2016). Investigating between-area differences in physical activity is an important step to understand its spatial distribution. However, such studies can assume that each unit area is homogeneous in environmental characteristics and activity levels, which is unlikely to be a tenable assumption across large areas, such as counties or cities. Investigating the within-area distribution of physical activity is therefore relevant, since physical activity can vary within an area, and greater within-area disparities may contribute to greater inequalities in health (Petrovic et al., 2018).
A recent study in the US examined within-city disparities of walking steps using the Gini coefficient, and found that cities with higher walkability (measured by Walk Score®) were more likely to have lower disparities in walking (Althoff et al., 2017). Higher city-level walkability was associated not only with higher levels of “mean” walking among residents but also with lower “dispersion” in walking within the city. These findings suggest that improving walkability may contribute to increasing community-level physical activity as well as reducing disparities in physical activity, which may mitigate health inequalities.
In this context, it will be informative to understand to what extent local-area walkability may be associated with within-area disparities in physical activity. Examining such associations at the level of local area, where destinations providing goods and services necessary for everyday life exist, is relevant, as urban design/planning decisions that can affect residents' travel mode choice (e.g., residential density, land use, public open space, sidewalk) are usually made at the local level. In addition to the adverse health consequences of lack of physical activity, there are also detrimental associations of prolonged car use with health outcomes (McCormack and Virk, 2014; Sugiyama et al., 2016). It can be postulated that car use is likely to be more common (less dispersion) in low-walkable areas, while it may be more variable in high-walkable local areas.
We examined the associations of local-area walkability measures with within-area disparities in residents' walking and car use, using household travel survey data collected in a socially and geographically heterogeneous region around an Australian capital city.
Section snippets
Data source
Data were drawn from the 2009 South-East Queensland Travel Survey (SEQTS), a cross-sectional household travel survey administered by the Queensland (Australia) State Government in Brisbane (the state capital city), and the adjacent Sunshine Coast and Gold Coast Statistical Divisions. This region covers a mix of urban, suburban, and regional areas, with a geographic size of 10,946 km2. Its population was approximately 2.9 million in 2009. The SEQTS used a multi-stage random sampling in which
Outcome measures
All members in the selected households on the night before the specified “survey day” were asked to complete a 24-hour travel diary. A short-span activity diary has been found to be more valid and reliable in measuring physical activity and sedentary behavior than conventional self-report questionnaires (van der Ploeg et al., 2010). They reported details of their instances of travel on the survey day, including origin, destination, start time, end time, mode, and purpose. The variables employed
Results
Participants who reported no trip (by any mode) on the survey day were excluded from analysis (n = 4204). In addition, 15 SA2s where none of the participants reported home-based walking were excluded, as the study was designed to examine disparity in walking. After the exclusions, 15,895 participants living in 196 SA2s were retained for analysis. Table 1, Table 2 show the characteristics of participants and SA2s, respectively. The median number of participants in SA2s was 51. The lowest number
Discussion
We examined the associations of disparities in the duration of walking and car use within a local area was explained by walkability-related measures, using household travel survey data collected in Australia. We found the mean disparity in walking duration to be high, due to a large proportion of participants reporting 0 min of walking on the survey day. The disparity in car use was lower, indicating that residents were relatively more homogeneous in the duration of their car use.
Higher
Conclusion
Our study found there was more equity in walking in high-walkable areas. By contrast, low-walkable areas, where people tend to rely on cars for daily travels, showed a greater disparity in walking. Thus, neighborhoods designed to be walkable have the potential to reduce inequities in health-promoting physical activity, while reducing exposure to harmful effects of prolonged car use. Improving walkability of existing neighborhoods is not an easy process. However, planning initiatives such as
Acknowledgments
Koohsari was supported by Postdoctoral Fellowship for Research in Japan from the Japan Society for the Promotion of Science (#17716). Owen was supported by National Health and Medical Research Council (NHMRC) Centre of Research Excellence Grant (#1057608), NHMRC Senior Principal Research Fellowship (#1118225), and the Victorian Government's Operational Infrastructure Support Program.
Conflict of interest statement
None of the authors has any financial interest in walkscore.com.
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