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Int. J. Environ. Res. Public Health 2017, 14(3), 273; doi:10.3390/ijerph14030273

Optimizing Scoring and Sampling Methods for Assessing Built Neighborhood Environment Quality in Residential Areas

1
National Institutes of Health Undergraduate Scholarship Program, Office of Intramural Training and Education, Office of the Director, National Institutes of Health, Bethesda, MD 20892, USA
2
Department of Global and Community Health, School of Public Health, George Mason University, Fairfax, VA 22030, USA
3
Donald W. Reynolds Cardiovascular Clinical Research Center at the University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
4
Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892, USA
5
Cardiovascular and Pulmonary Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
6
Division of Cardiology, Children’s National Medical Center, Washington, DC 20010, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Derek Clements-Croome
Received: 12 January 2017 / Revised: 27 February 2017 / Accepted: 2 March 2017 / Published: 8 March 2017
(This article belongs to the Section Environmental Health)
View Full-Text   |   Download PDF [940 KB, uploaded 8 March 2017]   |  

Abstract

Optimization of existing measurement tools is necessary to explore links between aspects of the neighborhood built environment and health behaviors or outcomes. We evaluate a scoring method for virtual neighborhood audits utilizing the Active Neighborhood Checklist (the Checklist), a neighborhood audit measure, and assess street segment representativeness in low-income neighborhoods. Eighty-two home neighborhoods of Washington, D.C. Cardiovascular Health/Needs Assessment (NCT01927783) participants were audited using Google Street View imagery and the Checklist (five sections with 89 total questions). Twelve street segments per home address were assessed for (1) Land-Use Type; (2) Public Transportation Availability; (3) Street Characteristics; (4) Environment Quality and (5) Sidewalks/Walking/Biking features. Checklist items were scored 0–2 points/question. A combinations algorithm was developed to assess street segments’ representativeness. Spearman correlations were calculated between built environment quality scores and Walk Score®, a validated neighborhood walkability measure. Street segment quality scores ranged 10–47 (Mean = 29.4 ± 6.9) and overall neighborhood quality scores, 172–475 (Mean = 352.3 ± 63.6). Walk scores® ranged 0–91 (Mean = 46.7 ± 26.3). Street segment combinations’ correlation coefficients ranged 0.75–1.0. Significant positive correlations were found between overall neighborhood quality scores, four of the five Checklist subsection scores, and Walk Scores® (r = 0.62, p < 0.001). This scoring method adequately captures neighborhood features in low-income, residential areas and may aid in delineating impact of specific built environment features on health behaviors and outcomes. View Full-Text
Keywords: virtual audits; Google Street View; Active Neighborhood Checklist; built neighborhood environment; residential neighborhoods; Walk Score®; environment quality; Washington D.C. Cardiovascular Health and Needs Assessment virtual audits; Google Street View; Active Neighborhood Checklist; built neighborhood environment; residential neighborhoods; Walk Score®; environment quality; Washington D.C. Cardiovascular Health and Needs Assessment
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Adu-Brimpong, J.; Coffey, N.; Ayers, C.; Berrigan, D.; Yingling, L.R.; Thomas, S.; Mitchell, V.; Ahuja, C.; Rivers, J.; Hartz, J.; Powell-Wiley, T.M. Optimizing Scoring and Sampling Methods for Assessing Built Neighborhood Environment Quality in Residential Areas. Int. J. Environ. Res. Public Health 2017, 14, 273.

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Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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