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.
Original language | English (US) |
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Pages (from-to) | 265-273 |
Number of pages | 9 |
Journal | American Journal of Epidemiology |
Volume | 186 |
Issue number | 3 |
DOIs | |
State | Published - Aug 1 2017 |
Keywords
- Detroit, Michigan
- Google Street View
- data collection
- epidemiologic methods
- social environment
- spatial analysis
- urban health
ASJC Scopus subject areas
- Epidemiology