Abstract
BackgroundAdvancements in geographic information systems over the past two decades have increased the specificity by which an individual’s neighborhood environment may be spatially defined for physical activity and health research. This study investigated how different types of street network buffering methods compared in measuring a set of commonly used built environment measures (BEMs) and tested their performance on associations with physical activity outcomes.MethodsAn internationally-developed set of objective BEMs using three different spatial buffering techniques were used to evaluate the relative differences in resulting explanatory power on self-reported physical activity outcomes. BEMs were developed in five countries using ‘sausage,’ ‘detailed-trimmed,’ and ‘detailed,’ network buffers at a distance of 1 km around participant household addresses (n = 5883).ResultsBEM values were significantly different (p < 0.05) for 96% of sausage versus detailed-trimmed buffer comparisons and 89% of sausage versus detailed network buffer comparisons. Results showed that BEM coefficients in physical activity models did not differ significantly across buffering methods, and in most cases BEM associations with physical activity outcomes had the same level of statistical significance across buffer types. However, BEM coefficients differed in significance for 9% of the sausage versus detailed models, which may warrant further investigation.ConclusionsResults of this study inform the selection of spatial buffering methods to estimate physical activity outcomes using an internationally consistent set of BEMs. Using three different network-based buffering methods, the findings indicate significant variation among BEM values, however associations with physical activity outcomes were similar across each buffering technique. The study advances knowledge by presenting consistently assessed relationships between three different network buffer types and utilitarian travel, sedentary behavior, and leisure-oriented physical activity outcomes.
Highlights
Advancements in geographic information systems over the past two decades have increased the specificity by which an individual’s neighborhood environment may be spatially defined for physical activity and health research
The overall purpose of this study is to investigate whether different buffering techniques alter the predictive strength of built environment measure (BEM) on physical activity and sedentary behavior
The combined dataset from these sites consists of 5883 adults from five countries (Brazil, Denmark, New Zealand, United Kingdom, and the United States) Participant recruitment at each study site was stratified by socio-economic status (SES) and transport-related walkability, which have been described in detail in other publications [32]
Summary
Advancements in geographic information systems over the past two decades have increased the specificity by which an individual’s neighborhood environment may be spatially defined for physical activity and health research. Census geography often forces an arbitrary depiction of a behavioural setting or neighbourhood for researchers and the inability to accurately capture how individuals conceptualize their neighborhood. This is known as the ‘modifiable areal unit problem’ (MAUP) and defined as issues of zone and scale arising from arbitrarily defined boundaries used to aggregate continuous spatial features [13, 14]. Mis-specification of the spatial neighborhood definition constitutes a violation of the ecological framework whose premise places the individual in the center of their environment [16]
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