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Viewing obesogenic advertising in children's neighbourhoods using Google Street View
Author(s) -
Egli Victoria,
Zinn Caryn,
Mackay Lisa,
Donnellan Niamh,
Villanueva Karen,
Mavoa Suzanne,
Exeter Daniel J.,
Vandevijvere Stefanie,
Smith Melody
Publication year - 2019
Publication title -
geographical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.695
H-Index - 47
eISSN - 1745-5871
pISSN - 1745-5863
DOI - 10.1111/1745-5871.12291
Subject(s) - advertising , geography , neighbourhood (mathematics) , context (archaeology) , centrality , purchasing , unhealthy food , marketing , business , obesity , mathematics , medicine , mathematical analysis , archaeology , combinatorics
The advertising of unhealthy food and beverages forms an important component of obesogenic environments. Such marketing to children is a key health determinant because of its impact on dietary preference and food purchasing behaviour. The location of outdoor advertising is important in exploring obesogenic environments and children's neighbourhoods. The aim of this study is to explore issues involved in the use of Google Street View to examine outdoor food and beverage advertising. The implications for using Google Street View in the context of neighbourhood built environment research and grass‐roots advocacy are discussed. The study was conducted within walkable distances from 19 primary and intermediate schools in Auckland, New Zealand, where “walkable” was defined as limited by 800 m road network boundaries, which are equivalent to school buffer boundaries. Google Street View allows for centrality of data collection, coding, and storage. However, challenges exist with the method because 727 (29.4%) of a total of 2,474 outdoor advertisements that were identified were not able to be categorised because images were unclear, not in English, blocked, or at angles where detail cannot be deciphered. Specific to outdoor advertising for food and beverages, the results presented here show that children are exposed to a significantly greater number of unhealthy advertising than other advertising, P=0.001, eta‐squared statistic (0.45) indicates a large effect size. Overall, the results show promise for the use of Google Street View in the study of obesogenic environments.