Street Audits to Measure Neighborhood Disorder: Virtual or in-Person?

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Citation

Mooney, Stephen J.; Bader, Michael D. M.; Lovasi, Gina S.; Teitler, Julien O.; Koenen, Karestan C.; Aiello, Allison E.; Galea, Sandro; Goldmann, Emily S.; Sheehan, Daniel M.; & Rundle, Andrew G. (2017). Street Audits to Measure Neighborhood Disorder: Virtual or in-Person?. American Journal of Epidemiology, 186(3), 265-273. PMCID: PMC5860155

Abstract

Neighborhood conditions may influence a broad range of health indicators, including obesity, injury, and psychopathology. In particular, neighborhood physical disorder-a measure of urban deterioration-is thought to encourage crime and high-risk behaviors, leading to poor mental and physical health. In studies to assess neighborhood physical disorder, investigators typically rely on time-consuming and expensive in-person systematic neighborhood audits. We compared 2 audit-based measures of neighborhood physical disorder in the city of Detroit, Michigan: One used Google Street View imagery from 2009 and the other used an in-person survey conducted in 2008. Each measure used spatial interpolation to estimate disorder at unobserved locations. In total, the virtual audit required approximately 3% of the time required by the in-person audit. However, the final physical disorder measures were significantly positively correlated at census block centroids (r = 0.52), identified the same regions as highly disordered, and displayed comparable leave-one-out cross-validation accuracy. The measures resulted in very similar convergent validity characteristics (correlation coefficients within 0.03 of each other). The virtual audit-based physical disorder measure could substitute for the in-person one with little to no loss of precision. Virtual audits appear to be a viable and much less expensive alternative to in-person audits for assessing neighborhood conditions.

URL

http://dx.doi.org/10.1093/aje/kwx004

Reference Type

Journal Article

Year Published

2017

Journal Title

American Journal of Epidemiology

Author(s)

Mooney, Stephen J.
Bader, Michael D. M.
Lovasi, Gina S.
Teitler, Julien O.
Koenen, Karestan C.
Aiello, Allison E.
Galea, Sandro
Goldmann, Emily S.
Sheehan, Daniel M.
Rundle, Andrew G.

PMCID

PMC5860155

ORCiD

Aiello - 0000-0001-7029-2537