Walkability Characteristics Research Articles

The Influence of Built Environment on Walkability Using Geographic Information System

The Influence of Built Environment on Walkability Using Geographic Information System The main goal of this study was to analyze the residential environment (built environment), by exploring the relationship between neighborhood walkability characteristics using Geographic Information System (GIS) and level of physical activity (PA). A randomly selected sample of 135 adults from Olomouc, Czech Republic was divided into low and high walkability neighborhoods based on the walkability index (calculated using GIS). The average daily number of steps (using Yamax SW-700 pedometer) between the groups also was measured. Result showed that participants living in the high walkable areas took more steps a day than participant in the low walkable areas. Furthermore, the mean body mass index (BMI) level was inversely correlated with the number of steps on weekdays and during the whole week. On weekend days it was still inversed throughout with the number of steps; taken but the but the relationship was not statistically significant.

Light rail use is more likely on “walkable” blocks: Further support for using micro-level environmental audit measures

The primary purpose of the study was to address the claim that people are more likely to walk to a transit stop if they live on a “walkable” block. An additional purpose was to evaluate the Irvine Minnesota Inventory (IMI) as an environmental audit tool. The IMI was used to measure walkability features of 19 blocks in a revitalizing neighborhood. We hypothesized that residents who walked to a light rail TRAX stop ( n = 22) would live on blocks with higher walkability ratings compared to residents who did not walk to TRAX (nonriders, n = 15), or who walked only after a closer TRAX stop was built (new users, n = 11). A MANCOVA indicated the IMI scales differentiated the blocks; the strongest differences were obtained in subscales that measured the block's diversity, safety from crime and density (marginally significant). Participants' perceptions of their complete walk to the transit stop were consistent with the home block IMI scores, with the continuing riders having more positive views than the other two groups. The results show the ability of the IMI to distinguish among blocks in walkability, and support further use of this audit tool in environmental analyses and active living research. We end with a discussion of conceptual and methodological issues in the use of audit tools and provide recommendations for using these measures for local, immediate interests, as well as for building a broader science of environmental measurement.

Running to the Store? The relationship between neighborhood environments and the risk of obesity

We expand the search for modifiable features of neighborhood environments that alter obesity risk in two ways. First, we examine residents' access to neighborhood retail food options in combination with neighborhood features that facilitate physical activity. Second, we evaluate neighborhood features for both low income and non-low income neighborhoods (bottom quartile of median neighborhood income versus the top three quartiles). Our analyses use data from the Utah Population Database merged with U.S. Census data and Dun & Bradstreet business data for Salt Lake County, Utah. Linear regressions for BMI and logistic regressions for the likelihood of being obese are estimated using various measures of the individual's neighborhood food options and walkability features. As expected, walkability indicators of older neighborhoods and neighborhoods where a higher fraction of the population walks to work is related to a lower BMI/obesity risk, although the strength of the effects varies by neighborhood income. Surprisingly, the walkability indicator of neighborhoods with higher intersection density was linked to higher BMI/obesity risk. The expected inverse relationship between the walkability indicator of population density and BMI/obesity risk is found only in low income neighborhoods. We find a strong association between neighborhood retail food options and BMI/obesity risk with the magnitude of the effects again varying by neighborhood income. For individuals living in non-low income neighborhoods, having one or more convenience stores, full-service restaurants, or fast food restaurants is associated with reduced BMI/obesity risk, compared to having no neighborhood food outlets. The presence of at least one healthy grocery option in low income neighborhoods is also associated with a reduction in BMI/obesity risk relative to no food outlets. Finally, multiple food options within a neighborhood reduce BMI/obesity risk, relative to no food options, for individuals living in either low-income or non-low neighborhoods.

A hierarchy of sociodemographic and environmental correlates of walking and obesity

Objectives Initial studies demonstrate the need for further investigation of how the association of built environment with physical activity and BMI may differ by sociodemographic subgroups. The aim of this study was to use a novel statistical technique to identify possible subgroups. Methods Data from the 2002 Strategies for Metro Atlanta's Regional Transportation and Air Quality (SMARTRAQ) study were analyzed to explore relationships between measures of residential density, street connectivity, land use mix, and sociodemographic characteristics of individuals in predicting walking, overweight and obesity status. Chi-squared Automatic Interaction Detector (CHAID) analyses were used to partition the population into subgroups ( N = 13,065). Results Subgroups, were more likely to walk if they lived in neighborhoods with greater residential density, greater street connectivity and greater land use mix. A similar relationship was seen in men for the outcomes of obesity and overweight. Male residents of more walkable neighborhoods were less likely to be obese or overweight. In contrast, features of walkability were related to higher rates of obesity and overweight in women and non whites. Conclusions These analyses reveal that gender and ethnic subgroups display substantially different weight outcomes across different levels of walkability. In contrast, walking was consistently higher for all groups in the more walkable neighborhoods. This information can contribute to better targeting of interventions, and calls for more detailed investigation of the moderators that affect weight and physical activity across subgroups. This information supports a more efficient use of scarce resources to promote physical activity and healthy body weight.