Neighborhood Walkability Indicators Using GIS

Objective neighborhood walkability indicators were created via geographic information systems (GIS) using ArcGIS 9.3. GIS data were analyzed using the North American Datum (NAD) 1983 state plane coordinate system for each of the four metropolitan areas. This study includes total retail walking destinations (e.g., clothing stores, pharmacy/drug stores, bookstores) per square kilometer, total service walking destinations (e.g., post offices, banks, credit unions) per square kilometer, total cultural/educational walking destinations (e.g., movie theaters, schools, libraries) per square kilometer, parks per square kilometer, median pedestrian route directness (median of the ratio of distance between one point and another via the street network and straight-line distance between the two points; values closer to 1.00 represent a more direct route or a more connected network), intersection density (the number of street intersections per square kilometer; intersections are defined as street network nodes with three or more associated street segments excluding highways), count of cul de sacs (based on nodes associated with only one street segment), average speed limit (miles per hour), highway density (percentage of area that is highway traveled right of way; class 1 and 2 highways were used), residential density (US census block group occupied housing units per square kilometer were weighted proportionally for the child’s defined neighborhood) and population density (US census block group total population per square kilometer were weighted proportionally for the child’s defined neighborhood). We limited the retail, service and cultural/educational walking destinations to locations with fewer than 250 employees to filter out large businesses (e.g., Costco, Home Depot) as business with greater than 250 employees can take away from the walkability of a neighborhood (e.g., by having large parking lots) [22 ]. Retail, service and cultural/educational walking destinations data come from ESRI Business Analysis InfoUSA Business Locations 2006. ESRI Data and Maps information, from ESRI, has spatial datasets representing several built environment features. InfoUSA (http://infousa.com) is a company that provides listings of private and public businesses (verified yearly by telephone), with 6-digit NAICS codes as well as numbers of employees. Locations of these businesses had been geocoded and were available as a spatial dataset through the ESRI Business Analyst Extension. Data on parks, intersection density, cul de sacs, average speed limit, and highway density come from ESRI Data and Maps 2006; median pedestrian route directness data are derived from ESRI Business Analyst Info USA Business Locations 2006. Residential density and population density data as previously described come from 2000 US Census. This geospatial dataset includes GIS-derived walkability indicators for neighborhoods defined as 400-, 800- and 1600-meter street network buffers. We specifically selected 400- and 800-meters for our small spatial scales because these distances are considered a proximal neighborhood environment for children and adolescents [23 (link),24 (link)], among other populations such as older adults [25 (link)–28 (link)]. The 1600-meter buffer was used because it is approximately 1-mile, which is consistent with the Walk Score algorithm. The street network buffers were created from StreetMap streets excluding highways and ramps using the ArcGIS Network Analyst Extension. The street network buffers consisted of 50-meter buffers around street center lines that extend along the network 400-, 800- and 1600-meters from the geocoded home addresses.