1 Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, 3175 Chemin de la Côte-Sainte-Catherine, Montreal, QC), H3T 1C5, Canada.
2 Faculty of Medicine, Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC), H3T 1J4, Canada.
3 Epidemiology and Biostatistics Unit, INRS Institut Armand-Frappier, 531 Boulevard Des Prairies, Laval, QC), H7V 1B7, Canada.
4 Institut de La Statistique du Québec, 1200 Avenue McGill college 5e ÉtageH3B 4J8, Montreal, QC), Canada.
5 Department of Mathematics, Concordia University and PERFORM Centre, 7200 Rue Sherbrooke Ouest, Montreal, QC), H4B 1R6, Canada.
6 Ingram School of Nursing, McGill University, 680 Rue Sherbrooke Ouest #1800, Montreal, QC), H3A 2M7, Canada.
7 Department of Pediatrics, Université de Montréal, 2900 Boulevard Édouard-Montpetit, Montreal, QC), H3T 1J4, Canada.
8 Département de médecine sociale et préventive, École de santé publique de l'Université de Montréal, 5858 Côte-des-Neiges Rd., Montréal, Canada.
9 Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, 3175 Chemin de la Côte-Sainte-Catherine, Montreal, QC), H3T 1C5, Canada. tracie.barnett@mcgill.ca.
10 Epidemiology and Biostatistics Unit, INRS Institut Armand-Frappier, 531 Boulevard Des Prairies, Laval, QC), H7V 1B7, Canada. tracie.barnett@mcgill.ca.
11 Department of Family Medicine, McGill University, 5858 Côte-des-Neiges Rd., Montreal, QC), H3S 1Z1, Canada. tracie.barnett@mcgill.ca.

Background: The suitability of geospatial services for auditing neighbourhood features relevant to pediatric obesity remains largely unexplored. Our objectives were to (i) establish the measurement properties of a desk-based audit instrument that uses Google Street View ^® to assess street- and neighbourhood-level features relevant to pediatric obesity (QUALITY-NHOOD tool, the test method) and (ii) comment on its capacity to detect changes in the built environment over an 8-year period. In order to do so, we compared this tool with an on-site auditing instrument (the reference method).

Methods: On-site audits of 55 street- and neighbourhood-level features were completed in 2008 in 512 neighbourhoods from the QUALITY cohort study. In 2015, both repeat on-site and desk-based audits were completed in a random sample of 30 of these neighbourhoods.

Results: Agreement between both methods was excellent for almost all street segment items (range 91.9-99.7%), except for road type (81.0%), ads/commercial billboards (81.7%), road-sidewalk buffer zone (76.1%), and road-bicycle path buffer zone (53.3%). It was fair to poor for perceived quality, safety and aesthetics items (range 59.9-87.6%), as well as for general impression items (range 40.0-86.7%). The desk-based method over-detected commercial billboards and road-sidewalk buffer zone, and generally rated neighbourhoods as less safe, requiring more effort to get around, and having less aesthetic appeal. Change detected over the 8-year period was generally similar for both methods, except that the desk-based method appeared to amplify the increase in the number of segments with signs of social disorder.

Conclusions: The QUALITY-NHOOD tool is deemed adequate for evaluating and monitoring changes in pedestrian- and traffic-related features applicable to pediatric populations. Applications for monitoring the obesogenic nature of neighbourhoods appear warranted.