The Walkability Index dataset characterizes every Census 2019 block group in the U.S. based on its relative walkability. Walkability depends upon characteristics of the built environment that influence the likelihood of walking being used as a mode of travel. The Walkability Index is based on the EPA's previous data product, the Smart Location Database (SLD). Block group data from the SLD was the only input into the Walkability Index, and consisted of four variables from the SLD weighted in a formula to create the new Walkability Index. This dataset shares the SLD's block group boundary definitions from Census 2019. The methodology describing the process of creating the Walkability Index can be found in the documents located at https://edg.epa.gov/EPADataCommons/public/OA/WalkabilityIndex.zip. You can also learn more about the Smart Location Database at https://www.epa.gov/smartgrowth/smart-location-mapping.

A large body of research has demonstrated that land use and urban form can have a significant effect on transportation outcomes. People who live and/or work in compact neighborhoods with a walkable street grid and easy access to public transit, jobs, stores, and services are more likely to have several transportation options to meet their everyday needs. As a result, they can choose to drive less, which reduces their emissions of greenhouse gases and other pollutants compared to people who live and work in places that are not _location efficient. Walking, biking, and taking public transit can also save people money and improve their health by encouraging physical activity. The Smart Location Database summarizes several demographic, employment, and built environment variables for every census block group (CBG) in the United States. The database includes indicators of the commonly cited “D” variables shown in the transportation research literature to be related to travel behavior. The Ds include residential and employment density, land use diversity, design of the built environment, access to destinations, and distance to transit. SLD variables can be used as inputs to travel demand models, baseline data for scenario planning studies, and combined into composite indicators characterizing the relative location efficiency of CBG within U.S. metropolitan regions. This update features the most recent geographic boundaries (2019 Census Block Groups) and new and expanded sources of data used to calculate variables. Entirely new variables have been added and the methods used to calculate some of the SLD variables have changed. More information on the National Walkability index: https://www.epa.gov/smartgrowth/smart-location-mapping More information on the Smart Location Calculator: https://www.slc.gsa.gov/slc/

The Walkability Index is intended to help address a growing demand for data products and tools that enable users to consistently compare multiple places based on their suitability for walking as a means of travel. It may be of use as source data for transportation or land use sketch planning tools.The Walkability Index dataset characterizes every Census 2010 block group in the U.S. based on its relative walkability. Walkability depends upon characteristics of the built environment that influence the likelihood of walking being used as a mode of travel. The Walkability Index is based on the EPA's previous data product, the Smart Location Database (SLD). Block group data from the SLD was the only input into the Walkability Index and consisted of four variables from the SLD weighted in a formula to create the new Walkability Index. This dataset shares the SLD's block group boundary definitions from Census 2010.

These map layers present the number of National Green Building Standard points awarded for a project site or lot’s relative walkability, and accessibility to jobs via transit or within a 45-minute drive. This map presents information on the following criteria included in the 2020 National Green Building Standard: • Section 405.6(7) - Points for sites located in census block groups with above-average transit access to employment. (See variable D5b in Smart Location Database Technical Documentation and User Guide (2014) for background) • Section 405.6(8) - Points for sites located in census block groups with above-average access to employment within a 45-minute drive (See variable D5a in Smart Location Database Technical Documentation and User Guide (2014) for background on methods) • Section 501.2(4) - Points for lots located in census block groups with above-average neighborhood walkability (See National Walkability Index for background on methods) • Section 11.501.2(3) - Points for lots located in census block groups with above-average neighborhood walkability (See National Walkability Index for background on methods) Using data available through EPA’s Smart Location Database and National Walkability Index, relative walkability and accessibility to jobs via transit or within a 45-minute drive for census block groups were calculated and ranked into quartile groups. The regional comparison was made by considering the score of each individual census block group as a ratio of the average score of the county in which it is located. Those block groups with scores in the highest two quartiles nationally are eligible for NGBS points per the Sections noted above. Details on methodologies and datasets includes in the Smart Location Database and National Walkability Index can be found here: https://www.epa.gov/smartgrowth/smart-location-mapping#SLD

All credit for variables in AHRQ_included_variables.csv is attributed to

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The built environment (BE) has been associated with health outcomes in prior studies. Few have investigated the association between neighborhood walkability, a component of BE, and hypertension. We examined the association between neighborhood walkability and incident hypertension in the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Walkability was measured using Street Smart Walk Score based on participants' residential information at baseline (collected between 2003 and 2007) and was dichotomized as more (score ≥70) and less (score <70) walkable. The primary outcome was incident hypertension defined at the second visit (collected between 2013 and 2017). We derived risk ratios (RR) using modified Poisson regression adjusting for age, race, sex, geographic region, income, alcohol use, smoking, exercise, BMI, dyslipidemia, diabetes, and baseline blood pressure (BP). We further stratified by race, age, and geographic region. Among 6,894 participants, 6.8% lived in more walkable areas and 38% (N = 2,515) had incident hypertension. In adjusted analysis, neighborhood walkability (Walk Score ≥70) was associated with a lower risk of incident hypertension (RR [95%CI]: 0.85[0.74, 0.98], P = 0.02), with similar but non-significant trends in race and age strata. In secondary analyses, living in a more walkable neighborhood was protective against being hypertensive at both study visits (OR [95%CI]: 0.70[0.59, 0.84], P < 0.001). Neighborhood walkability was associated with incident hypertension in the REGARDS cohort, with the relationship consistent across race groups. The results of this study suggest increased neighborhood walkability may be protective for high blood pressure in black and white adults from the general US population.