ABSTRACT The role of the neighbourhood environment in influencing health behaviours continues to be an important topic in public health research and policy. Foot‐based street audits, virtual street audits and secondary data sources are widespread data collection methods used to objectively measure the built environment in environment‐health association studies. We compared these three methods using data collected in a nationally representative epidemiological study in 17 British towns to inform future development of research tools. There was good agreement between foot‐based and virtual audit tools. Foot based audits were superior for fine detail features. Secondary data sources measured very different aspects of the local environment that could be used to derive a range of environmental measures if validated properly. Future built environment research should design studies a priori using multiple approaches and varied data sources in order to best capture features that operate on different health behaviours at varying spatial scales. HighlightsThis study compares multiple data collection methods for measuring built environment features.Virtual street audits are reliable for more objective built environment measures.Street‐based audits are superior for collecting fine detail environmental features.Routine secondary data sources need less resources but must be properly validated.Appropriate methods for health studies vary depending on the research question and resources.
Optimising measurement of health-related characteristics of the built environment: Comparing data collected by foot-based street audits, virtual street audits and routine secondary data sources
T. Pliakas,S. Hawkesworth,R. Silverwood,K. Nanchahal,C. Grundy,B. Armstrong,J. Casas,R. Morris,P. Wilkinson,K. Lock
Published 2016 in Health and Place
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PUBLICATION RECORD
- Publication year
2016
- Venue
Health and Place
- Publication date
2016-11-28
- Fields of study
Medicine, Computer Science, Engineering, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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