br Methods br Results The analyses indicate how microscale

Methods
Results The analyses indicate how microscale pedestrian environment features varied by block group median income and race/ethnicity (Table 2). In all three regions, the findings revealed that tsa trichostatin certain microscale pedestrian features were less favorable (i.e., lower quality or absent) in lower-income neighborhoods and other features were less favorable in higher-income neighborhoods. Similarly, some microscale pedestrian features were less favorable in neighborhoods with a higher proportion of racial/ethnic minorities and other features were less favorable in neighborhoods with fewer racial/ethnic minorities. In Table 2, meanings of positive and negative values vary depending on the nature of the microscale feature (i.e., positive or negative relationship with physical activity) and the independent variable of interest (income or race/ethnicity). To assist interpretation of Table 2, disparities are identified by bold and underlined font; equitable differences appear in bold font, without underlining. Considerable variation existed between regions as to the type of microscale pedestrian features that had disparities, whether the disparities were found mostly in residential or mixed-use neighborhoods, the mix of disparities and “equitable differences”, and whether the disparities were defined by neighborhood income level or racial/ethnic composition (Table 3). Across all three regions, 12 microscale pedestrian features were significantly worse in low-income neighborhoods, and 12 microscale pedestrian features were worse in high-income neighborhoods. Neighborhoods with a higher proportion of racial/ethnic minorities had 7 significantly worse microscale pedestrian features, as compared to 11 features that were worse in neighborhoods with fewer racial/ethnic minorities. Disparities in microscale pedestrian features occurred more frequently in residential-only routes (11 significant findings) as compared to mixed-use routes (8 significant findings), but variation existed between regions. The Seattle region had more disparities in residential as compared to mixed-use routes, whereas the San Diego and Baltimore regions had an equal number of disparities in residential-only and mixed-use routes (Table 3). Results also included 11 significant interactions between income and racial/ethnic composition in relation to microscale pedestrian features (Table 2; Figs. 1–11).
Discussion This study provides evidence that unfavorable microscale pedestrian features occur in neighborhoods of all income levels and racial/ethnic compositions, but the type of adverse features and locations (residential versus mixed-use neighborhoods) varies greatly between cities. Previous studies of microscale environments have been limited to a single city (Neckerman et al., 2009; Yu, 2014; Zhu & Lee, 2008), or have combined data from multiple cities across the US (Gibbs et al., 2012). Our current approach, which included a comprehensive assessment of microscale pedestrian features, allowed us to examine the generalizability of findings regarding disparities in microscale features. Our results show that relationships between neighborhood income and race/ethnicity, and microscale features, vary widely across different regions in the US. Local streetscape audits are necessary for policy makers to determine how to best allocate resources to address disparities in local environments. Local audits can provide policy makers and urban designers with important information regarding how to build walkable environments and encourage higher levels of physical activity across all SES levels. Despite the region-specific findings, a few generalizable results emerged. Across all three regions, esthetic/social features were consistently worse in low-income and high racial/ethnic minority neighborhoods as compared to high-income or mostly White neighborhoods. In San Diego and Seattle regions, neighborhoods with a high proportion of racial/ethnic minorities had fewer positive esthetic features such as art, fountains, sculptures, and landscaping. Low-income neighborhoods in all three regions had more negative esthetics and social elements (e.g., graffiti, broken windows, litter, drug paraphernalia, poorly maintained buildings) as compared to higher income neighborhoods. Seattle and Baltimore regions also had fewer trees in low-income neighborhoods. These findings are consistent with previous studies showing that disadvantaged neighborhoods have fewer trees (Landry & Chakraborty, 2009), landmarked buildings, and decorative architecture; and more noise, litter, and signs of disrepair (Neckerman et al., 2009). Indicators of social and physical disorder like graffiti have been linked to residents’ evaluation of higher crime risk and fear of crime (LaGrange, Ferraro, & Supancic, 1992), and residents who feel unsafe may walk less in their neighborhoods (Mason, Kearns, & Livingston, 2013). Additional research is needed to examine relationships between microscale pedestrian environments, fear of crime, objective crime rates, and physical activity in neighborhoods with different income and racial/ethnic composition. We would expect interventions aimed at improving neighborhood esthetics and social elements to increase physical activity, and such interventions should be evaluated. Given concerns that neighborhood improvements would invite gentrification and displacement of current residents (Smith & Williams, 2013), we recommend a process that involves city planners, community groups, and health agencies in developing community revitalization efforts designed to benefit current residents.