Among participants who reported engaging in some degree of walking activity, we found that the overall number of commercial businesses, the number of likely retail walking destinations, and the percentage of high-volume and low-volume streets in their local neighborhood were associated with the total amount of time these participants spent walking each week. Although these findings were qualitatively similar for the quarter-mile and half-mile radii, the magnitude of the observed associations varied depending on the area at which the built environment characteristic was measured. The relation of commercial establishments to walking time was greatest at the quarter-mile, while the relation of street volume to walking time was most pronounced when measured at the half-mile buffer.
These findings support recent observations of significant associations between physical activity and traffic volume, land-use mix, and proximity of walking destinations (7
). This study extends those findings to the walking behavior of older adults, a group largely neglected in this area of research. We did not observe any association between walking time and intersection density, percentage of sidewalk coverage, or proximity to public transportation. In our subgroup analyses, we found that brisk walking time was associated not only with street volume and number of retail establishments but also with distance to the nearest park or green space. There were no significant associations between walking for leisure and local neighborhood environment.
Notably, we found no association between any of the built environment measures and the odds of walking or not walking. This finding suggests that features of the local built environment were not strongly correlated with whether or not participants engaged in walking, and it enabled us to conjecture that modifications to the built environment may have little benefit in promoting walking behavior among sedentary older adults. Nevertheless, the finding that built environment is associated with increased walking time among reported walkers is important, given that nearly half of older adults report occasional walking at levels below those required to meet minimum activity guidelines (5
Among this population, shifting the average time spent walking toward the levels of physical activity recommended would result in substantial public health benefits. In , we provide adjusted parameter estimates that illustrate the expected change in walking time associated with a standard deviation change in each built environment characteristic. While the changes in walking time associated with individual characteristics are fairly modest, the impact of such changes is best seen within the context of the low levels of activity in this population. For example, a 30-minute increase in walking per week amounts to a nearly 25 percent increase from the mean walking time reported by our sample. Among the participants in this study, this increase would be sufficient to shift nearly 30 percent of those not meeting the Centers for Disease Control and Prevention recommendations for physical activity into compliance with current guidelines.
We found that a greater degree of perceived neighborhood problems was associated with less time spent walking. Perceived neighborhood safety, on the other hand, was not significantly associated with walking time. Previous studies examining the relation between physical activity and perceived safety have produced mixed results (16
). Lastly, neighborhood poverty was positively associated with increased walking time, findings similar to those reported by Ross (31
). The reasons are likely complex but may involve the relation of poverty to land-use mix in urban versus suburban neighborhoods, more reliance on nonautomobile transport in poor communities, and normative walking behaviors in poor neighborhoods.
Only 3.6 percent of the variability in reported walking time among our sample was attributable to differences between the municipally defined neighborhoods that served as the primary sampling units in this study. This finding is compelling in light of the significant associations found between walking and the built environment surrounding participants' residences. It suggests that the variability in built environment characteristics was greater within municipally defined neighborhoods than between them, indicating that local neighborhood is a more appropriate geographic scale for determining the effect of built environment on walking behavior. Currently, there is little agreement on the appropriate scale to best measure built environment in regard to its association with walking behavior, although there appears to be a trend toward utilizing objective measures within “walkable” buffer zones similar in scale to the ones used in this study (10
). Additionally, some built environment characteristics, for example, accessibility of retail and services, were more important at the very local level (quarter-mile radius), while other built environment characteristics, for example, traffic volume, were more important in a larger geographic area (half-mile radius). This finding is consistent with the theory that the appropriate geographic scale differs by built environment characteristics, which further supports the usefulness of characterizing a local neighborhood by using geographic information systems in future studies.
Several limitations of the current study warrant discussion. First, the cluster-randomized design of the original SHAPE trial resulted in small within-neighborhood sample sizes. This limitation reduced our ability to accurately model the variability in walking activity associated with differences in municipally defined neighborhood residence. Nevertheless, given the negligible intergroup variability in walking time calculated in the unconditional means model, we do not think that this variability resulted in misestimation of the associations between local built environment characteristics and walking activity. We do recognize that the necessity of adopting a two-stage modeling approach resulted in relatively small within-group sample sizes for the analyses of walking times, which were further reduced in the subanalyses of walking type. This reduction may have limited our ability to detect significant associations between specific types of walking and built environment characteristics. Second, the city of Portland has an established history of managing urban growth and promoting “pedestrian-friendly” urban planning initiatives, which may limit generalizability of the findings. Similarly, because many characteristics of a pedestrian-friendly built environment are highly correlated, it is difficult to differentiate the effects of individual characteristics.
Third, we lacked data on disease risk or prevalence among our sample; unmeasured confounding by poor health could result in inflated estimates of the association between built environment and walking. However, models were controlled for self-reported health, minimizing concerns about substantial residual confounding. Lastly, this study relied upon self-reported measures of physical activity, which may be subject to self-report or recall bias. Self-report measures continue to be the standard method of assessing physical activity in large studies such as this one, and the scope of this study made the use of objective measures, such as pedometers, impractical.
In summary, this study found that characteristics of the local built environment—street volume and proximity of walking destinations—were independently associated with increases in the level of walking activity among older adults who favor walking. However, we found that the odds of having walked for any length of time during a typical week in the past month were not associated with objective measures of the built environment. These findings suggest that promotion of mixed land-use and pedestrian-friendly neighborhood design could play a significant role in encouraging more vigorous activity among moderately active older adults, although such environmental interventions may have little effect on the behavior of highly sedentary older adults. For older adults who are not already active, approaches to reduce inactivity should focus on physical or psychological concerns, such as chronic medical conditions, declining physical function, history of (in)activity over the life course, and self-efficacy. Future research is needed to clarify the relation between built environment and walking activity among highly sedentary older adults, to confirm the appropriate geographic scale for measurement of neighborhood built environment in studies of older adults, and to examine the effects of environmental interventions on walking behavior over time.