Date of Award


Document Type

Campus Access Thesis

Degree Name

Master of Science (MS)


Exercise and Health Science

First Advisor

Philip J. Troped

Second Advisor

Sarah Camhi

Third Advisor

Ling Shi


Background: Built environment (BE) variables have been associated with bike share use using static spatial analyses; however, dynamic spatial approaches using daily activity spaces may be a more accurate approach to measure these associations. Purpose: To test three GPS-based approaches to generate activity spaces, compare the characteristics of activity spaces, and assess associations between the BE and bike share use. Methods: A sample of 26 bike share members in Boston wore a GPS and accelerometer for seven days. Daily activity spaces were created using three approaches: buffered GPS track, minimum convex hull (MCH) and standard deviation ellipse (SDE1, SDE2, SDE3). ANOVA and Tukey tests were used to compare BE variables across activity spaces. Multilevel modeling was used to examine associations between BE variables and bike share use. Results: Buffer activity spaces showed significantly higher values for four BE variables. In models adjusted for demographics and weather, station density within the buffer activity spaces showed a significant positive association with bike share use (odds ratio (OR) = 3.18). Positive associations were seen for bike network density within buffer (OR=9.61), and MCH (OR=26.86) activity spaces. No significant associations were seen between road density and bike share use. Off-street bike path density was positively associated with bike share use in MCH activity spaces (OR=10.75) and in SDE3 activity spaces (OR=24.86. No significant associations were found between the proportion of roads with bike lanes and bike share use. Conclusion: The buffer activity space method showed significantly higher mean values for four BE density variables. Station density, bike network density, and off-street bike path density showed positive associations with bike share use. Overall, the findings are consistent with prior research on cycling and more specifically bike share use. However, GPS tracking used in this study allowed for dynamic spatial identification of environmental exposures relevant to bike share use. Further research is needed to explore the most appropriate methods to identify activity spaces.


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