Relationships of land use mix with walking for transport: do land uses and geographical scale matter?

J Urban Health. 2010 Sep;87(5):782-95. doi: 10.1007/s11524-010-9488-7.

Abstract

Physical activity and public health recommendations now emphasize the creation of activity-friendly neighborhoods. Mixed land use in a neighborhood is important in this regard, as it reflects the availability of destinations to which residents can walk or ride bicycles, and thus is likely to contribute to residents' active lifestyles that in turn will influence their overall health. Relationships between land use mix (LUM) and physical activity have not been apparent in some studies, which may be because geographical scale and the specificity of hypothesized environment-behavior associations are not taken into account. We compared the strength of association of four Geographic Information Systems-derived LUM measures with walking for transport and perceived proximity to destinations. We assessed physical activity behaviors of 2,506 adults in 154 Census Collection Districts (CCDs) in Adelaide, Australia, for which ''original'' LUM measures were calculated, and then refined by either: accounting for the geographic scale of measurement; including only the most-relevant land uses; or, both. The refined (but not the ''original'') LUM measures had significant associations with the frequency of walking for transport (p < 0.05) and area-corrected measures had significant associations with the duration of walking for transport. All LUM measures had significant associations with perceived proximity to destinations, but stronger associations were seen when using the refined measures compared with the original LUM. Identifying the LUM attributes most strongly associated with walking for transport is a priority and can inform environmental and policy initiatives that are needed to promote health-enhancing physical activity.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Censuses
  • Environment Design*
  • Female
  • Geographic Information Systems
  • Health Behavior
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • Motor Activity
  • Residence Characteristics / statistics & numerical data*
  • South Australia
  • Urban Population / statistics & numerical data
  • Walking / statistics & numerical data*